ANN_CNN_RNN.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#How you are calculation the loss in cost ---> loss function  e.g. mean-squared_error\n",
    "#what are you doing to reduce the error or gain more loss ---> optimizers e.g. sgd\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.718281828459045"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import math\n",
    "import numpy as np\n",
    "import scipy as sc\n",
    "import pandas as pd\n",
    "math.e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22026.465794806703"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "math.pow(math.e,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 3, 4, 5, 6, 7, 8, 9])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.arange(1,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10.])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.linspace(1,10,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5640"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.random.seed(100)\n",
    "np.random.randint(10033)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sns\n"
     ]
    }
   ],
   "source": [
    "str=\"sonus\"\n",
    "print str[::-2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    2\n",
       "b    3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(data=[2,3],index=['a','b'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.DataFrame(np.random.randn(5,4),['A','B','C','D','E'],['X','Y','Z','Z+'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A   -0.415847\n",
       "B    1.525180\n",
       "C   -0.886748\n",
       "D    0.959657\n",
       "E    0.373661\n",
       "Name: Z+, dtype: float64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Z+']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[34mArtificial_Neural_Networks\u001b[m\u001b[m Untitled.ipynb\r\n"
     ]
    }
   ],
   "source": [
    "!ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "!cd Artificial_Neural_Networks/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[34mArtificial_Neural_Networks\u001b[m\u001b[m Untitled.ipynb\r\n"
     ]
    }
   ],
   "source": [
    "!ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('Artificial_Neural_Networks/Churn_Modelling.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RowNumber</th>\n",
       "      <th>CustomerId</th>\n",
       "      <th>Surname</th>\n",
       "      <th>CreditScore</th>\n",
       "      <th>Geography</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tenure</th>\n",
       "      <th>Balance</th>\n",
       "      <th>NumOfProducts</th>\n",
       "      <th>HasCrCard</th>\n",
       "      <th>IsActiveMember</th>\n",
       "      <th>EstimatedSalary</th>\n",
       "      <th>Exited</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>15634602</td>\n",
       "      <td>Hargrave</td>\n",
       "      <td>619</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>42</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>101348.88</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>15647311</td>\n",
       "      <td>Hill</td>\n",
       "      <td>608</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>83807.86</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>112542.58</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>15619304</td>\n",
       "      <td>Onio</td>\n",
       "      <td>502</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>42</td>\n",
       "      <td>8</td>\n",
       "      <td>159660.80</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113931.57</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>15701354</td>\n",
       "      <td>Boni</td>\n",
       "      <td>699</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>93826.63</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>15737888</td>\n",
       "      <td>Mitchell</td>\n",
       "      <td>850</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>125510.82</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>79084.10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   RowNumber  CustomerId   Surname  CreditScore Geography  Gender  Age  \\\n",
       "0          1    15634602  Hargrave          619    France  Female   42   \n",
       "1          2    15647311      Hill          608     Spain  Female   41   \n",
       "2          3    15619304      Onio          502    France  Female   42   \n",
       "3          4    15701354      Boni          699    France  Female   39   \n",
       "4          5    15737888  Mitchell          850     Spain  Female   43   \n",
       "\n",
       "   Tenure    Balance  NumOfProducts  HasCrCard  IsActiveMember  \\\n",
       "0       2       0.00              1          1               1   \n",
       "1       1   83807.86              1          0               1   \n",
       "2       8  159660.80              3          1               0   \n",
       "3       1       0.00              2          0               0   \n",
       "4       2  125510.82              1          1               1   \n",
       "\n",
       "   EstimatedSalary  Exited  \n",
       "0        101348.88       1  \n",
       "1        112542.58       0  \n",
       "2        113931.57       1  \n",
       "3         93826.63       0  \n",
       "4         79084.10       0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cross_validation import train_test_split\n",
    "X = df.iloc[:,3:13].values\n",
    "Y = df.iloc[:,13].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, Y_train, Y_test = train_test_split(X,Y, test_size=0.25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "82500"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder, OneHotEncoder\n",
    "labelEncoder_X1 = LabelEncoder()\n",
    "labelEncoder_X2 = LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[619 0 0 ... 1 1 101348.88]\n",
      " [608 2 0 ... 0 1 112542.58]\n",
      " [502 0 0 ... 1 0 113931.57]\n",
      " ...\n",
      " [709 0 0 ... 0 1 42085.58]\n",
      " [772 1 1 ... 1 0 92888.52]\n",
      " [792 0 0 ... 1 0 38190.78]]\n"
     ]
    }
   ],
   "source": [
    "X[:,1] = labelEncoder_X1.fit_transform(X[:,1])\n",
    "X[:,2] = labelEncoder_X2.fit_transform(X[:,2])\n",
    "print X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1.0000000e+00 0.0000000e+00 0.0000000e+00 ... 1.0000000e+00\n",
      "  1.0000000e+00 1.0134888e+05]\n",
      " [0.0000000e+00 0.0000000e+00 1.0000000e+00 ... 0.0000000e+00\n",
      "  1.0000000e+00 1.1254258e+05]\n",
      " [1.0000000e+00 0.0000000e+00 0.0000000e+00 ... 1.0000000e+00\n",
      "  0.0000000e+00 1.1393157e+05]\n",
      " ...\n",
      " [1.0000000e+00 0.0000000e+00 0.0000000e+00 ... 0.0000000e+00\n",
      "  1.0000000e+00 4.2085580e+04]\n",
      " [0.0000000e+00 1.0000000e+00 0.0000000e+00 ... 1.0000000e+00\n",
      "  0.0000000e+00 9.2888520e+04]\n",
      " [1.0000000e+00 0.0000000e+00 0.0000000e+00 ... 1.0000000e+00\n",
      "  0.0000000e+00 3.8190780e+04]]\n"
     ]
    }
   ],
   "source": [
    "onehotencoder = OneHotEncoder(categorical_features=[1])\n",
    "X = onehotencoder.fit_transform(X).toarray()\n",
    "print X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.0000000e+00 0.0000000e+00 6.1900000e+02 ... 1.0000000e+00\n",
      "  1.0000000e+00 1.0134888e+05]\n",
      " [0.0000000e+00 1.0000000e+00 6.0800000e+02 ... 0.0000000e+00\n",
      "  1.0000000e+00 1.1254258e+05]\n",
      " [0.0000000e+00 0.0000000e+00 5.0200000e+02 ... 1.0000000e+00\n",
      "  0.0000000e+00 1.1393157e+05]\n",
      " ...\n",
      " [0.0000000e+00 0.0000000e+00 7.0900000e+02 ... 0.0000000e+00\n",
      "  1.0000000e+00 4.2085580e+04]\n",
      " [1.0000000e+00 0.0000000e+00 7.7200000e+02 ... 1.0000000e+00\n",
      "  0.0000000e+00 9.2888520e+04]\n",
      " [0.0000000e+00 0.0000000e+00 7.9200000e+02 ... 1.0000000e+00\n",
      "  0.0000000e+00 3.8190780e+04]]\n"
     ]
    }
   ],
   "source": [
    "X = X[:,1:]\n",
    "print X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10000, 11)\n"
     ]
    }
   ],
   "source": [
    "print X.shape\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "standardScalar = StandardScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "could not convert string to float: Male",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-19-1bbeca253725>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mX_train\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstandardScalar\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mX_test\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstandardScalar\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/lib/python2.7/site-packages/sklearn/base.pyc\u001b[0m in \u001b[0;36mfit_transform\u001b[0;34m(self, X, y, **fit_params)\u001b[0m\n\u001b[1;32m    515\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0my\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    516\u001b[0m             \u001b[0;31m# fit method of arity 1 (unsupervised transformation)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 517\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mfit_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtransform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    518\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    519\u001b[0m             \u001b[0;31m# fit method of arity 2 (supervised transformation)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/lib/python2.7/site-packages/sklearn/preprocessing/data.pyc\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y)\u001b[0m\n\u001b[1;32m    588\u001b[0m         \u001b[0;31m# Reset internal state before fitting\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    589\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 590\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpartial_fit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    591\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    592\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mpartial_fit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/lib/python2.7/site-packages/sklearn/preprocessing/data.pyc\u001b[0m in \u001b[0;36mpartial_fit\u001b[0;34m(self, X, y)\u001b[0m\n\u001b[1;32m    610\u001b[0m         \"\"\"\n\u001b[1;32m    611\u001b[0m         X = check_array(X, accept_sparse=('csr', 'csc'), copy=self.copy,\n\u001b[0;32m--> 612\u001b[0;31m                         warn_on_dtype=True, estimator=self, dtype=FLOAT_DTYPES)\n\u001b[0m\u001b[1;32m    613\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    614\u001b[0m         \u001b[0;31m# Even in the case of `with_mean=False`, we update the mean anyway\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/lib/python2.7/site-packages/sklearn/utils/validation.pyc\u001b[0m in \u001b[0;36mcheck_array\u001b[0;34m(array, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)\u001b[0m\n\u001b[1;32m    431\u001b[0m                                       force_all_finite)\n\u001b[1;32m    432\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 433\u001b[0;31m         \u001b[0marray\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    434\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    435\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mensure_2d\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: could not convert string to float: Male"
     ]
    }
   ],
   "source": [
    "X_train = standardScalar.fit_transform(X_train)\n",
    "X_test = standardScalar.fit_transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[693, 'Spain', 'Female', ..., 1, 1, 26589.56],\n",
       "       [718, 'Germany', 'Female', ..., 1, 1, 190746.38],\n",
       "       [637, 'France', 'Female', ..., 0, 0, 175072.47],\n",
       "       ...,\n",
       "       [600, 'Germany', 'Female', ..., 1, 1, 96051.1],\n",
       "       [531, 'Spain', 'Male', ..., 0, 0, 99503.19],\n",
       "       [576, 'France', 'Female', ..., 0, 0, 148477.57]], dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, Activation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier = Sequential()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier.add(Dense(6,activation='relu',kernel_initializer='uniform',input_dim=11))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier.add(Dense(6,activation='relu',kernel_initializer='uniform'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier.add(Dense(1,activation='sigmoid',kernel_initializer='uniform'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "82500"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "7500/7500 [==============================] - 1s 158us/step - loss: 0.4867 - acc: 0.7927\n",
      "Epoch 2/10\n",
      "7500/7500 [==============================] - 1s 118us/step - loss: 0.4291 - acc: 0.7953\n",
      "Epoch 3/10\n",
      "7500/7500 [==============================] - 1s 119us/step - loss: 0.4212 - acc: 0.8251\n",
      "Epoch 4/10\n",
      "7500/7500 [==============================] - 1s 120us/step - loss: 0.4157 - acc: 0.8305\n",
      "Epoch 5/10\n",
      "7500/7500 [==============================] - 1s 120us/step - loss: 0.4125 - acc: 0.8321\n",
      "Epoch 6/10\n",
      "7500/7500 [==============================] - 1s 120us/step - loss: 0.4101 - acc: 0.8301\n",
      "Epoch 7/10\n",
      "7500/7500 [==============================] - 1s 121us/step - loss: 0.4084 - acc: 0.8319\n",
      "Epoch 8/10\n",
      "7500/7500 [==============================] - 1s 119us/step - loss: 0.4063 - acc: 0.8325\n",
      "Epoch 9/10\n",
      "7500/7500 [==============================] - 1s 121us/step - loss: 0.4052 - acc: 0.8328\n",
      "Epoch 10/10\n",
      "7500/7500 [==============================] - 1s 122us/step - loss: 0.4042 - acc: 0.8331\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x119ed8bd0>"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classifier.fit(X_train,Y_train,batch_size=10,epochs=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred=classifier.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = (y_pred>=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [],
   "source": [
    "cm= confusion_matrix(Y_test,y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1951,   67],\n",
       "       [ 316,  166]])"
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'France'"
      ]
     },
     "execution_count": 238,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test=[600,'France','Male',40,3,60000,2,1,1,50000]\n",
    "test[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {},
   "outputs": [],
   "source": [
    "test[1]=labelEncoder_X1.transform([test[1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[600, array([0]), 'Male', 40, 3, 60000, 2, 1, 1, 50000]"
      ]
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [],
   "source": [
    "test[2]=labelEncoder_X2.transform([test[2]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[600, array([0]), array([1]), 40, 3, 60000, 2, 1, 1, 50000]"
      ]
     },
     "execution_count": 242,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {},
   "outputs": [],
   "source": [
    "test=onehotencoder.transform([test]).toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.e+00, 0.e+00, 0.e+00, 6.e+02, 1.e+00, 4.e+01, 3.e+00, 6.e+04,\n",
       "        2.e+00, 1.e+00, 1.e+00, 5.e+04]])"
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {},
   "outputs": [],
   "source": [
    "test = [round(x,2) for x in test[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1.0, 0.0, 0.0, 600.0, 1.0, 40.0, 3.0, 60000.0, 2.0, 1.0, 1.0, 50000.0]"
      ]
     },
     "execution_count": 246,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {},
   "outputs": [],
   "source": [
    "test = test[1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.0, 0.0, 600.0, 1.0, 40.0, 3.0, 60000.0, 2.0, 1.0, 1.0, 50000.0]"
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [],
   "source": [
    "test = standardScalar.transform([test])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(11,)"
      ]
     },
     "execution_count": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test[0].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred1 = classifier.predict(np.array(test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred1 = (y_pred1 >= 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[False]])"
      ]
     },
     "execution_count": 260,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.wrappers.scikit_learn import KerasClassifier\n",
    "def build_classifier(optimizer):\n",
    "    classifier = Sequential()\n",
    "    classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu', input_dim = 11))\n",
    "    classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu'))\n",
    "    classifier.add(Dense(units = 1, kernel_initializer = 'uniform', activation = 'sigmoid'))\n",
    "    classifier.compile(optimizer = optimizer, loss = 'binary_crossentropy', metrics = ['accuracy'])\n",
    "    return classifier\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier = KerasClassifier(build_fn=build_classifier)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "metadata": {},
   "outputs": [],
   "source": [
    "parameters = {'batch_size': [10, 20],\n",
    "              'epochs': [50, 100],\n",
    "              'optimizer': ['adam', 'rmsprop']}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "metadata": {},
   "outputs": [],
   "source": [
    "grid_search = GridSearchCV(estimator = classifier,\n",
    "                           param_grid = parameters,\n",
    "                           scoring = 'accuracy',\n",
    "                           cv = 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "6750/6750 [==============================] - 1s 173us/step - loss: 0.5004 - acc: 0.7905\n",
      "Epoch 2/50\n",
      "6750/6750 [==============================] - 1s 133us/step - loss: 0.4371 - acc: 0.7910 0s - loss: 0.4407 - acc: 0\n",
      "Epoch 3/50\n",
      "6750/6750 [==============================] - 1s 132us/step - loss: 0.4315 - acc: 0.7910\n",
      "Epoch 4/50\n",
      "6750/6750 [==============================] - 1s 129us/step - loss: 0.4273 - acc: 0.8086\n",
      "Epoch 5/50\n",
      "6750/6750 [==============================] - 1s 130us/step - loss: 0.4251 - acc: 0.8210 0s - loss: 0.4307 - a\n",
      "Epoch 6/50\n",
      "6750/6750 [==============================] - 1s 133us/step - loss: 0.4231 - acc: 0.8259\n",
      "Epoch 7/50\n",
      "6750/6750 [==============================] - 1s 132us/step - loss: 0.4216 - acc: 0.8277\n",
      "Epoch 8/50\n",
      "6750/6750 [==============================] - 1s 131us/step - loss: 0.4204 - acc: 0.8270\n",
      "Epoch 9/50\n",
      "6750/6750 [==============================] - 1s 130us/step - loss: 0.4192 - acc: 0.8295\n",
      "Epoch 10/50\n",
      "6750/6750 [==============================] - 1s 134us/step - loss: 0.4186 - acc: 0.8286\n",
      "Epoch 11/50\n",
      "6750/6750 [==============================] - 1s 135us/step - loss: 0.4176 - acc: 0.8308\n",
      "Epoch 12/50\n",
      "6750/6750 [==============================] - 1s 136us/step - loss: 0.4170 - acc: 0.8301\n",
      "Epoch 13/50\n",
      "6750/6750 [==============================] - 1s 137us/step - loss: 0.4164 - acc: 0.8310\n",
      "Epoch 14/50\n",
      "6750/6750 [==============================] - 1s 134us/step - loss: 0.4158 - acc: 0.8313\n",
      "Epoch 15/50\n",
      "6750/6750 [==============================] - 1s 132us/step - loss: 0.4150 - acc: 0.8313\n",
      "Epoch 16/50\n",
      "6750/6750 [==============================] - 1s 136us/step - loss: 0.4146 - acc: 0.8295\n",
      "Epoch 17/50\n",
      "6750/6750 [==============================] - 1s 134us/step - loss: 0.4146 - acc: 0.8314\n",
      "Epoch 18/50\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6750/6750 [==============================] - 1s 132us/step - loss: 0.4153 - acc: 0.8304 0s - loss: 0.4153 - acc: 0.83\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "6750/6750 [==============================] - 1s 160us/step - loss: 0.4056 - acc: 0.8324\n",
      "Epoch 47/50\n",
      "6750/6750 [==============================] - 1s 153us/step - loss: 0.4056 - acc: 0.8320 0s - loss: 0.4030 - acc: \n",
      "Epoch 48/50\n",
      "6750/6750 [==============================] - 1s 154us/step - loss: 0.4057 - acc: 0.8319\n",
      "Epoch 49/50\n",
      "6750/6750 [==============================] - 1s 153us/step - loss: 0.4051 - acc: 0.8321 0s - loss: 0.3992 -\n",
      "Epoch 50/50\n",
      "6750/6750 [==============================] - 1s 152us/step - loss: 0.4054 - acc: 0.8314\n",
      "Epoch 1/50\n",
      "6750/6750 [==============================] - 2s 222us/step - loss: 0.4955 - acc: 0.7944\n",
      "Epoch 2/50\n",
      "6750/6750 [==============================] - 1s 156us/step - loss: 0.4363 - acc: 0.7947\n",
      "Epoch 3/50\n",
      "6750/6750 [==============================] - 1s 148us/step - loss: 0.4314 - acc: 0.7947\n",
      "Epoch 4/50\n",
      "6750/6750 [==============================] - 1s 153us/step - loss: 0.4257 - acc: 0.8119\n",
      "Epoch 5/50\n",
      "6750/6750 [==============================] - 1s 154us/step - loss: 0.4194 - acc: 0.8231\n",
      "Epoch 6/50\n",
      "6750/6750 [==============================] - 1s 149us/step - loss: 0.4150 - acc: 0.8283\n",
      "Epoch 7/50\n",
      "6750/6750 [==============================] - 1s 148us/step - loss: 0.4121 - acc: 0.8305\n",
      "Epoch 8/50\n",
      "6750/6750 [==============================] - 1s 154us/step - loss: 0.4096 - acc: 0.8316\n",
      "Epoch 9/50\n",
      "6750/6750 [==============================] - 1s 158us/step - loss: 0.4073 - acc: 0.8317\n",
      "Epoch 10/50\n",
      "6750/6750 [==============================] - 1s 155us/step - loss: 0.4068 - acc: 0.8339\n",
      "Epoch 11/50\n",
      "6750/6750 [==============================] - 1s 154us/step - loss: 0.4054 - acc: 0.8321\n",
      "Epoch 12/50\n",
      "6750/6750 [==============================] - 1s 153us/step - loss: 0.4047 - acc: 0.8321\n",
      "Epoch 13/50\n",
      "6750/6750 [==============================] - 1s 153us/step - loss: 0.4037 - acc: 0.8345\n",
      "Epoch 14/50\n",
      "6750/6750 [==============================] - 1s 156us/step - loss: 0.4031 - acc: 0.8344\n",
      "Epoch 15/50\n",
      "6750/6750 [==============================] - 1s 155us/step - loss: 0.4026 - acc: 0.8316\n",
      "Epoch 16/50\n",
      "6750/6750 [==============================] - 1s 158us/step - loss: 0.4021 - acc: 0.8348\n",
      "Epoch 17/50\n",
      "4600/6750 [===================>..........] - ETA: 0s - loss: 0.4056 - acc: 0.8365"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-303-296b7bf4cd19>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mgrid_search\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/sklearn/model_selection/_search.pyc\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y, groups, **fit_params)\u001b[0m\n\u001b[1;32m    637\u001b[0m                                   error_score=self.error_score)\n\u001b[1;32m    638\u001b[0m           for parameters, (train, test) in product(candidate_params,\n\u001b[0;32m--> 639\u001b[0;31m                                                    cv.split(X, y, groups)))\n\u001b[0m\u001b[1;32m    640\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    641\u001b[0m         \u001b[0;31m# if one choose to see train score, \"out\" will contain train score info\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.pyc\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m    777\u001b[0m             \u001b[0;31m# was dispatched. In particular this covers the edge\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    778\u001b[0m             \u001b[0;31m# case of Parallel used with an exhausted iterator.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 779\u001b[0;31m             \u001b[0;32mwhile\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdispatch_one_batch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0miterator\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    780\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_iterating\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    781\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.pyc\u001b[0m in \u001b[0;36mdispatch_one_batch\u001b[0;34m(self, iterator)\u001b[0m\n\u001b[1;32m    623\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    624\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 625\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dispatch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtasks\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    626\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    627\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.pyc\u001b[0m in \u001b[0;36m_dispatch\u001b[0;34m(self, batch)\u001b[0m\n\u001b[1;32m    586\u001b[0m         \u001b[0mdispatch_timestamp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    587\u001b[0m         \u001b[0mcb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBatchCompletionCallBack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdispatch_timestamp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatch\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 588\u001b[0;31m         \u001b[0mjob\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_backend\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_async\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatch\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcallback\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    589\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jobs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjob\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    590\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/sklearn/externals/joblib/_parallel_backends.pyc\u001b[0m in \u001b[0;36mapply_async\u001b[0;34m(self, func, callback)\u001b[0m\n\u001b[1;32m    109\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mapply_async\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcallback\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    110\u001b[0m         \u001b[0;34m\"\"\"Schedule a func to be run\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 111\u001b[0;31m         \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mImmediateResult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    112\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcallback\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    113\u001b[0m             \u001b[0mcallback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/sklearn/externals/joblib/_parallel_backends.pyc\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, batch)\u001b[0m\n\u001b[1;32m    330\u001b[0m         \u001b[0;31m# Don't delay the application, to avoid keeping the input\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    331\u001b[0m         \u001b[0;31m# arguments in memory\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 332\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbatch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    333\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    334\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.pyc\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    129\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    130\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__call__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 131\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    132\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    133\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__len__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/sklearn/model_selection/_validation.pyc\u001b[0m in \u001b[0;36m_fit_and_score\u001b[0;34m(estimator, X, y, scorer, train, test, verbose, parameters, fit_params, return_train_score, return_parameters, return_n_test_samples, return_times, error_score)\u001b[0m\n\u001b[1;32m    456\u001b[0m             \u001b[0mestimator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mfit_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    457\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 458\u001b[0;31m             \u001b[0mestimator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mfit_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    459\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    460\u001b[0m     \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/keras/wrappers/scikit_learn.pyc\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, x, y, sample_weight, **kwargs)\u001b[0m\n\u001b[1;32m    207\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0msample_weight\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    208\u001b[0m             \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'sample_weight'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msample_weight\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 209\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mKerasClassifier\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    210\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    211\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/keras/wrappers/scikit_learn.pyc\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, x, y, **kwargs)\u001b[0m\n\u001b[1;32m    149\u001b[0m         \u001b[0mfit_args\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    150\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 151\u001b[0;31m         \u001b[0mhistory\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mfit_args\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    152\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    153\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mhistory\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/keras/engine/training.pyc\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, **kwargs)\u001b[0m\n\u001b[1;32m   1040\u001b[0m                                         \u001b[0minitial_epoch\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minitial_epoch\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1041\u001b[0m                                         \u001b[0msteps_per_epoch\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msteps_per_epoch\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1042\u001b[0;31m                                         validation_steps=validation_steps)\n\u001b[0m\u001b[1;32m   1043\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1044\u001b[0m     def evaluate(self, x=None, y=None,\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/keras/engine/training_arrays.pyc\u001b[0m in \u001b[0;36mfit_loop\u001b[0;34m(model, f, ins, out_labels, batch_size, epochs, verbose, callbacks, val_f, val_ins, shuffle, callback_metrics, initial_epoch, steps_per_epoch, validation_steps)\u001b[0m\n\u001b[1;32m    193\u001b[0m                 \u001b[0mbatch_logs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'batch'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbatch_index\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    194\u001b[0m                 \u001b[0mbatch_logs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'size'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatch_ids\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 195\u001b[0;31m                 \u001b[0mcallbacks\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_batch_begin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatch_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbatch_logs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    196\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mindices_for_conversion_to_dense\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    197\u001b[0m                     \u001b[0mins_batch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mins_batch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtoarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/keras/callbacks.pyc\u001b[0m in \u001b[0;36mon_batch_begin\u001b[0;34m(self, batch, logs)\u001b[0m\n\u001b[1;32m     87\u001b[0m         \u001b[0mt_before_callbacks\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     88\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mcallback\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcallbacks\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 89\u001b[0;31m             \u001b[0mcallback\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_batch_begin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatch\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlogs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     90\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_delta_ts_batch_begin\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mt_before_callbacks\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     91\u001b[0m         \u001b[0mdelta_t_median\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmedian\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_delta_ts_batch_begin\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "grid_search.fit(X_train,Y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'GridSearchCV' object has no attribute 'best_params_'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-305-b1068600e498>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mgrid_search\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbest_params_\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m: 'GridSearchCV' object has no attribute 'best_params_'"
     ]
    }
   ],
   "source": [
    "grid_search.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.applications.vgg16 import VGG16\n",
    "vgg16=VGG16()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "input_1 (InputLayer)         (None, 224, 224, 3)       0         \n",
      "_________________________________________________________________\n",
      "block1_conv1 (Conv2D)        (None, 224, 224, 64)      1792      \n",
      "_________________________________________________________________\n",
      "block1_conv2 (Conv2D)        (None, 224, 224, 64)      36928     \n",
      "_________________________________________________________________\n",
      "block1_pool (MaxPooling2D)   (None, 112, 112, 64)      0         \n",
      "_________________________________________________________________\n",
      "block2_conv1 (Conv2D)        (None, 112, 112, 128)     73856     \n",
      "_________________________________________________________________\n",
      "block2_conv2 (Conv2D)        (None, 112, 112, 128)     147584    \n",
      "_________________________________________________________________\n",
      "block2_pool (MaxPooling2D)   (None, 56, 56, 128)       0         \n",
      "_________________________________________________________________\n",
      "block3_conv1 (Conv2D)        (None, 56, 56, 256)       295168    \n",
      "_________________________________________________________________\n",
      "block3_conv2 (Conv2D)        (None, 56, 56, 256)       590080    \n",
      "_________________________________________________________________\n",
      "block3_conv3 (Conv2D)        (None, 56, 56, 256)       590080    \n",
      "_________________________________________________________________\n",
      "block3_pool (MaxPooling2D)   (None, 28, 28, 256)       0         \n",
      "_________________________________________________________________\n",
      "block4_conv1 (Conv2D)        (None, 28, 28, 512)       1180160   \n",
      "_________________________________________________________________\n",
      "block4_conv2 (Conv2D)        (None, 28, 28, 512)       2359808   \n",
      "_________________________________________________________________\n",
      "block4_conv3 (Conv2D)        (None, 28, 28, 512)       2359808   \n",
      "_________________________________________________________________\n",
      "block4_pool (MaxPooling2D)   (None, 14, 14, 512)       0         \n",
      "_________________________________________________________________\n",
      "block5_conv1 (Conv2D)        (None, 14, 14, 512)       2359808   \n",
      "_________________________________________________________________\n",
      "block5_conv2 (Conv2D)        (None, 14, 14, 512)       2359808   \n",
      "_________________________________________________________________\n",
      "block5_conv3 (Conv2D)        (None, 14, 14, 512)       2359808   \n",
      "_________________________________________________________________\n",
      "block5_pool (MaxPooling2D)   (None, 7, 7, 512)         0         \n",
      "_________________________________________________________________\n",
      "flatten (Flatten)            (None, 25088)             0         \n",
      "_________________________________________________________________\n",
      "fc1 (Dense)                  (None, 4096)              102764544 \n",
      "_________________________________________________________________\n",
      "fc2 (Dense)                  (None, 4096)              16781312  \n",
      "_________________________________________________________________\n",
      "predictions (Dense)          (None, 1000)              4097000   \n",
      "=================================================================\n",
      "Total params: 138,357,544\n",
      "Trainable params: 138,357,544\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "vgg16.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from keras.models import Sequential\n",
    "from keras.layers import Conv2D, Dense, Activation, MaxPool2D, Flatten"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier = Sequential()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier.add(Conv2D(32,(1,1),input_shape=(64,64,3),activation='relu'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_2 (Conv2D)            (None, 64, 64, 32)        128       \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 64, 64, 128)       4224      \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 64, 64, 1)         129       \n",
      "=================================================================\n",
      "Total params: 4,481\n",
      "Trainable params: 4,481\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "classifier.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier.add(MaxPool2D(pool_size=(2,2)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier.add(Flatten())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier.add(Dense(128,activation='relu'))\n",
    "classifier.add(Dense(1,activation='sigmoid'))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 422,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier.compile(optimizer='adam',loss='binary_crossentropy',metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 396,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.preprocessing.image import ImageDataGenerator\n",
    "train_datagen=ImageDataGenerator(rescale=1./255,shear_range=0.2,zoom_range=0.2,horizontal_flip=True)\n",
    "test_datagen=ImageDataGenerator(rescale=1./255)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 397,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 8000 images belonging to 2 classes.\n"
     ]
    }
   ],
   "source": [
    "train_generator=train_datagen.flow_from_directory(\n",
    "    'Convolutional_Neural_Networks/dataset/training_set',\n",
    "    target_size=(64,64),batch_size=32,class_mode='binary')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 398,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 2000 images belonging to 2 classes.\n"
     ]
    }
   ],
   "source": [
    "test_generator=test_datagen.flow_from_directory('Convolutional_Neural_Networks/dataset/test_set',target_size=(64,64),batch_size=32,class_mode='binary')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 399,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "100/100 [==============================] - 35s 347ms/step - loss: 0.7761 - acc: 0.5413 - val_loss: 0.6583 - val_acc: 0.6362\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x11c986410>"
      ]
     },
     "execution_count": 399,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classifier.fit_generator(train_generator,steps_per_epoch=100,epochs=1,validation_data=test_generator,validation_steps=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 404,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.preprocessing.image import load_img, img_to_array\n",
    "img=load_img('Convolutional_Neural_Networks/dataset/single_prediction/cat_or_dog_1.jpg',target_size=(64,64))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 408,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.preprocessing.image import load_img, img_to_array\n",
    "img=load_img('Convolutional_Neural_Networks/dataset/single_prediction/cat_or_dog_2.jpg',target_size=(64,64))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 409,
   "metadata": {},
   "outputs": [],
   "source": [
    "img=img_to_array(img)\n",
    "img=np.expand_dims(img,axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 410,
   "metadata": {},
   "outputs": [],
   "source": [
    "res=classifier.predict(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 413,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0\n"
     ]
    }
   ],
   "source": [
    "print round(res,4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 414,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([[[[ 0.12242493,  0.02543759,  0.10789277,  0.04730863,\n",
       "            0.06091548, -0.13916117, -0.07549855,  0.12604631,\n",
       "           -0.03242766,  0.07647866, -0.08613928,  0.11667246,\n",
       "           -0.02770501,  0.0648014 , -0.00152566,  0.00039287,\n",
       "            0.07723846,  0.03019977,  0.00672807,  0.11152345,\n",
       "           -0.00640651,  0.07845575, -0.01760415, -0.04748692,\n",
       "            0.10321265,  0.04933825,  0.04206071,  0.13130994,\n",
       "            0.0323403 ,  0.02221284,  0.04926774,  0.07285043],\n",
       "          [-0.12052996, -0.03829017,  0.01903471,  0.04956289,\n",
       "           -0.09551302,  0.05170377, -0.08512532, -0.06195225,\n",
       "            0.05561343, -0.09504143,  0.10613877, -0.01472836,\n",
       "           -0.0460622 , -0.07538506, -0.02442078, -0.07205718,\n",
       "           -0.09265807, -0.12190943,  0.11013773, -0.13894774,\n",
       "           -0.0648367 ,  0.06494527,  0.13613372,  0.11787897,\n",
       "            0.09562885,  0.02925572, -0.12224244, -0.08866128,\n",
       "           -0.12939319, -0.06205553, -0.11041415,  0.03661109],\n",
       "          [-0.02259055, -0.14218673,  0.0492503 , -0.14170744,\n",
       "            0.02290279,  0.0373064 ,  0.02206061,  0.11422821,\n",
       "           -0.09457409,  0.09965829,  0.01941815, -0.04528996,\n",
       "           -0.00966979, -0.14653178, -0.03923264,  0.02214566,\n",
       "           -0.07609697, -0.01746396,  0.08908904,  0.0205892 ,\n",
       "            0.05355939,  0.13653506, -0.11282238,  0.01132086,\n",
       "            0.07313821, -0.0841459 , -0.08651869,  0.14389516,\n",
       "            0.03999379, -0.12973079, -0.09775242, -0.04267137]],\n",
       " \n",
       "         [[-0.05602351,  0.01600306,  0.11492804, -0.0446982 ,\n",
       "           -0.05316982, -0.05924363, -0.08365818, -0.04716127,\n",
       "            0.04388339, -0.11183266, -0.0550794 , -0.07894717,\n",
       "           -0.13325156, -0.00420516, -0.12333802, -0.00691422,\n",
       "            0.0529347 , -0.01656156,  0.04162846,  0.05514961,\n",
       "           -0.08435041, -0.06272035,  0.00559527,  0.09595916,\n",
       "           -0.10153972, -0.14023916,  0.01248014, -0.10900766,\n",
       "            0.05216865,  0.04773006,  0.0012158 ,  0.07722858],\n",
       "          [-0.06853352, -0.02369901, -0.1294369 , -0.06747724,\n",
       "            0.01935231,  0.12451219, -0.11834222,  0.09638669,\n",
       "           -0.09386498,  0.05285212,  0.04864425, -0.05112684,\n",
       "            0.1205241 , -0.00921546, -0.00469323, -0.10367015,\n",
       "            0.02933647, -0.04073636,  0.10258213, -0.07673442,\n",
       "            0.0356049 ,  0.07755947, -0.04034949, -0.14574094,\n",
       "            0.11134673, -0.04453312, -0.03747361, -0.08493178,\n",
       "            0.08044524,  0.03659777, -0.02061717,  0.08759959],\n",
       "          [-0.10061821, -0.00461599,  0.08778275, -0.05903227,\n",
       "            0.00689311,  0.06800272,  0.04234186, -0.09787958,\n",
       "           -0.13972935, -0.12839754,  0.03871692, -0.04324391,\n",
       "            0.03250483,  0.10374651, -0.09321724,  0.0132846 ,\n",
       "           -0.02270609,  0.02581809, -0.03930339,  0.03607452,\n",
       "            0.09964539,  0.08852978, -0.07641519, -0.01342378,\n",
       "           -0.02357651, -0.11427051, -0.04222773,  0.04494457,\n",
       "            0.02903215, -0.07003713,  0.12049147, -0.11133879]],\n",
       " \n",
       "         [[-0.04601054,  0.13019945, -0.05099646,  0.0016175 ,\n",
       "            0.09750941,  0.03013171, -0.07989177,  0.12269065,\n",
       "           -0.06316663, -0.10341145,  0.10601757, -0.05212025,\n",
       "           -0.0293675 , -0.11349374, -0.06662652, -0.01411013,\n",
       "           -0.03108906,  0.03993749,  0.09897622, -0.02678364,\n",
       "           -0.10631876, -0.0148148 , -0.06069136, -0.14465109,\n",
       "           -0.1163827 , -0.0159802 , -0.01833148,  0.12232611,\n",
       "           -0.09672172,  0.0363611 ,  0.01844222,  0.1152517 ],\n",
       "          [-0.11546154, -0.05097293,  0.03429441, -0.09600522,\n",
       "            0.00701927,  0.05567303, -0.14596923,  0.03885235,\n",
       "           -0.00203737,  0.10816236,  0.02415197, -0.05134533,\n",
       "           -0.00383042, -0.13137749, -0.03029211,  0.09909   ,\n",
       "            0.08234417, -0.09556638, -0.05362432,  0.12649682,\n",
       "            0.06650472, -0.00983012,  0.07639381, -0.14151627,\n",
       "           -0.09671675,  0.12435442, -0.04420533, -0.06981441,\n",
       "           -0.02746879, -0.03584062,  0.05513559, -0.06267344],\n",
       "          [ 0.03594356,  0.11038096,  0.106157  ,  0.02874565,\n",
       "           -0.11987108, -0.12102178, -0.06919864, -0.08130609,\n",
       "            0.09880671, -0.10005026, -0.07488558,  0.06584968,\n",
       "           -0.05709887, -0.11803806,  0.10828302, -0.05848422,\n",
       "            0.08425731, -0.08609693,  0.02410876, -0.1219264 ,\n",
       "           -0.1335773 ,  0.10101743,  0.12012896,  0.09816854,\n",
       "           -0.03396127, -0.12835322, -0.06717575,  0.13208632,\n",
       "           -0.0964096 ,  0.07032953, -0.05484118, -0.13883226]]],\n",
       " \n",
       " \n",
       "        [[[-0.12718537, -0.13780686,  0.0749983 ,  0.02934791,\n",
       "            0.10568649, -0.04704894,  0.07918715,  0.03059453,\n",
       "            0.0546273 ,  0.09799252, -0.00859413, -0.01320916,\n",
       "           -0.08733497,  0.01525528,  0.09644978,  0.01311872,\n",
       "           -0.11762945, -0.01587993, -0.01517955,  0.08244479,\n",
       "            0.01485807,  0.05435404, -0.02649951, -0.07414031,\n",
       "           -0.02856277,  0.02334085, -0.01704393, -0.10769723,\n",
       "           -0.05563585,  0.06493033, -0.141889  ,  0.11010728],\n",
       "          [-0.06191146,  0.01496525,  0.04809741,  0.0209067 ,\n",
       "           -0.02833044,  0.04676648, -0.07823369, -0.08000463,\n",
       "           -0.11110232,  0.00440608,  0.0169148 ,  0.02614705,\n",
       "            0.00628649,  0.09730626, -0.04939353,  0.03712135,\n",
       "            0.04772622, -0.10658186,  0.00782679,  0.02110425,\n",
       "            0.06335697,  0.13571124, -0.01095122,  0.09786475,\n",
       "           -0.06366602, -0.02883387, -0.12297622, -0.12818947,\n",
       "           -0.03395179,  0.0889415 ,  0.00243549, -0.13726789],\n",
       "          [ 0.04382786,  0.06777662, -0.10689944,  0.09904516,\n",
       "            0.00083203, -0.05656857,  0.02029318, -0.10610364,\n",
       "            0.08680903,  0.10530432, -0.0231213 , -0.00073406,\n",
       "           -0.0488175 , -0.10119002, -0.04402514, -0.04883071,\n",
       "            0.13185075, -0.11822172, -0.08750049, -0.05692528,\n",
       "           -0.10512235, -0.09456272, -0.0538574 ,  0.09191875,\n",
       "            0.05668327,  0.00614844, -0.06636471,  0.0509629 ,\n",
       "           -0.05583895, -0.04990561, -0.01632138, -0.03215703]],\n",
       " \n",
       "         [[ 0.09073243,  0.07443386, -0.13966845, -0.14376873,\n",
       "           -0.10851914,  0.03830367,  0.01289275, -0.07956576,\n",
       "           -0.14730737, -0.05938898, -0.03920196, -0.11138166,\n",
       "            0.12300596,  0.07815113, -0.01555037, -0.11095386,\n",
       "           -0.0967107 ,  0.05289419,  0.01047826, -0.11800921,\n",
       "            0.00333704, -0.07723399,  0.07406383, -0.01396427,\n",
       "            0.03958746,  0.04655747,  0.00809763, -0.03660998,\n",
       "           -0.00078192, -0.03865278, -0.01448821, -0.1401922 ],\n",
       "          [ 0.00846331,  0.07995918,  0.10626061,  0.08187355,\n",
       "            0.00160431,  0.11228163, -0.06381429,  0.05003374,\n",
       "            0.03679626,  0.12877113,  0.07098325,  0.13673861,\n",
       "           -0.10351576,  0.05343536,  0.05482243, -0.06268515,\n",
       "           -0.09978557,  0.08717299,  0.06706478,  0.05313873,\n",
       "            0.08932458, -0.08175289,  0.07026144,  0.0518771 ,\n",
       "           -0.11893812,  0.01954058, -0.11980634, -0.10058326,\n",
       "            0.11361277, -0.01992079, -0.07461368,  0.04721918],\n",
       "          [ 0.07237422, -0.08496482,  0.08202332,  0.01791179,\n",
       "           -0.09641732, -0.06620123, -0.02259812,  0.01808685,\n",
       "           -0.03943804, -0.10437243,  0.06038523, -0.0262554 ,\n",
       "           -0.09406371,  0.05888761, -0.01588661, -0.09906565,\n",
       "            0.11476388, -0.12142827, -0.023546  , -0.0956321 ,\n",
       "            0.12388022, -0.09938649, -0.0827466 ,  0.1228333 ,\n",
       "           -0.030771  , -0.01692272,  0.04067235, -0.06275644,\n",
       "            0.1202254 , -0.11493134,  0.12741505, -0.06311534]],\n",
       " \n",
       "         [[ 0.0457533 , -0.10666842, -0.07125542,  0.04702459,\n",
       "            0.093633  ,  0.00848373,  0.05690914,  0.00665742,\n",
       "           -0.12187648, -0.05934158, -0.04144419, -0.01795502,\n",
       "            0.07458083,  0.04536152, -0.0884802 , -0.1083898 ,\n",
       "            0.04790098, -0.08009419, -0.07339054,  0.02720218,\n",
       "           -0.03314983, -0.0706129 ,  0.07638641,  0.05396273,\n",
       "            0.09225547, -0.05406892,  0.10556569, -0.10872598,\n",
       "            0.12204797, -0.12389348, -0.12019166,  0.05641786],\n",
       "          [ 0.06378081,  0.03654318,  0.07197233,  0.0151837 ,\n",
       "           -0.01893745,  0.04551398, -0.06491259, -0.08457759,\n",
       "            0.05432509,  0.01244725,  0.08625157,  0.09618791,\n",
       "            0.01893738,  0.11013445,  0.03833934,  0.12572938,\n",
       "           -0.11872428, -0.01205139,  0.11181714,  0.06520361,\n",
       "            0.04481226, -0.07582127, -0.03295463,  0.01175747,\n",
       "           -0.04380225,  0.05067291, -0.07195362, -0.03615708,\n",
       "           -0.05995291,  0.00613471,  0.01076152, -0.05705648],\n",
       "          [ 0.0629067 , -0.00748867,  0.0665364 ,  0.09213107,\n",
       "           -0.12451653, -0.09580797,  0.05823229,  0.01554727,\n",
       "            0.10284836, -0.00939397,  0.04142168, -0.04114084,\n",
       "            0.12907065,  0.0567763 , -0.00243736, -0.14819588,\n",
       "            0.09303351, -0.07165411,  0.0263225 ,  0.03336893,\n",
       "           -0.1153933 , -0.13699558, -0.06256349,  0.0544978 ,\n",
       "           -0.08655845, -0.12683044,  0.09840527,  0.00658421,\n",
       "           -0.11332951,  0.04287936, -0.04414457,  0.11997209]]],\n",
       " \n",
       " \n",
       "        [[[-0.08758167, -0.07066784,  0.11657935, -0.00660576,\n",
       "            0.06822265,  0.03956261,  0.04541803, -0.0850824 ,\n",
       "            0.07338364,  0.04526844,  0.09925415, -0.09527153,\n",
       "           -0.07425733,  0.00594128,  0.08597875,  0.0569342 ,\n",
       "           -0.11825632,  0.11636137,  0.12334502, -0.00659837,\n",
       "            0.08483946, -0.11076445,  0.03486542, -0.02290385,\n",
       "            0.0322262 ,  0.03727824, -0.01977582,  0.08729373,\n",
       "           -0.01489307,  0.04504549, -0.06437688,  0.1182909 ],\n",
       "          [ 0.12105634,  0.05976044, -0.15122543, -0.0177571 ,\n",
       "            0.05432504, -0.03116818, -0.06662132,  0.13679315,\n",
       "            0.02132717, -0.11380531,  0.11639735,  0.00396211,\n",
       "           -0.12095115,  0.09158434,  0.1013263 , -0.01839156,\n",
       "           -0.11935202,  0.09393314,  0.06535245, -0.13078503,\n",
       "            0.05304199,  0.02944748,  0.09862925, -0.03895532,\n",
       "            0.12934381, -0.11378101,  0.09803994,  0.04670748,\n",
       "            0.11514579,  0.08506513, -0.07229245,  0.0171183 ],\n",
       "          [ 0.09054028, -0.01754452,  0.0190359 , -0.0992895 ,\n",
       "            0.1161583 ,  0.07339164, -0.10596613,  0.04649504,\n",
       "           -0.08912082, -0.03106704, -0.1272472 , -0.06456018,\n",
       "            0.11158769,  0.07015453,  0.07760218,  0.04502164,\n",
       "           -0.02963213,  0.04701733,  0.07846539,  0.01262185,\n",
       "            0.07677549, -0.12190184, -0.10376671,  0.11544214,\n",
       "           -0.10234834,  0.01453106,  0.02848332,  0.09561924,\n",
       "            0.056401  , -0.04740759, -0.09428951, -0.08463456]],\n",
       " \n",
       "         [[ 0.06853805,  0.13259012,  0.11360252, -0.03174807,\n",
       "           -0.02963374, -0.07936037,  0.01144048, -0.11428598,\n",
       "            0.04198376, -0.11605137, -0.02509113,  0.05123278,\n",
       "            0.04420222, -0.09860146, -0.02537809,  0.00977309,\n",
       "            0.03951516, -0.01689206,  0.00624182,  0.0615941 ,\n",
       "           -0.05867986,  0.02718821, -0.06166014,  0.11814255,\n",
       "           -0.02152297, -0.07141481,  0.14066629, -0.06328596,\n",
       "            0.09611335, -0.09979439,  0.11585828, -0.05098842],\n",
       "          [-0.01496307, -0.04848777, -0.13277286,  0.11708108,\n",
       "            0.01072675, -0.09749584, -0.00945079,  0.08416642,\n",
       "            0.04777304, -0.02224392, -0.04538681, -0.08883943,\n",
       "            0.05069078,  0.0717105 ,  0.07827822,  0.00548099,\n",
       "           -0.03450245,  0.10351436, -0.02428078,  0.05507486,\n",
       "           -0.06912231, -0.1152943 ,  0.01574702,  0.03989726,\n",
       "           -0.02936255, -0.03021795,  0.01257167,  0.08370931,\n",
       "           -0.07126864, -0.09128205,  0.13521959,  0.00167881],\n",
       "          [-0.09417648, -0.08207082,  0.07273612,  0.11724242,\n",
       "           -0.07257188,  0.06295948, -0.04215245, -0.06776458,\n",
       "            0.04077031,  0.03483254, -0.09694988, -0.11327133,\n",
       "           -0.01606873,  0.09002361, -0.11304012,  0.11059988,\n",
       "           -0.06999831,  0.02281621, -0.00018075, -0.1046199 ,\n",
       "            0.06339765,  0.07657101, -0.05750113,  0.09729151,\n",
       "           -0.05325686, -0.06967092,  0.10997936, -0.0628223 ,\n",
       "            0.12638126, -0.04086636,  0.03342725, -0.08566991]],\n",
       " \n",
       "         [[-0.14115034, -0.12115763,  0.03535567,  0.00267795,\n",
       "           -0.09936348, -0.03015243, -0.06538192,  0.12851973,\n",
       "            0.03533272, -0.14665172, -0.00564628,  0.09736542,\n",
       "           -0.04574452, -0.09113604,  0.04443678,  0.07214452,\n",
       "           -0.08909325,  0.09106538, -0.10519451,  0.00716676,\n",
       "           -0.12756996, -0.06602815,  0.04095528,  0.10526107,\n",
       "            0.03727106,  0.06845541, -0.01191388,  0.0944517 ,\n",
       "            0.07204998, -0.09604195, -0.06264785, -0.00208158],\n",
       "          [-0.00085715,  0.07723663, -0.11184297, -0.0011715 ,\n",
       "           -0.00314007, -0.0733243 , -0.0680858 , -0.12825   ,\n",
       "           -0.09575635,  0.0198923 ,  0.0608469 ,  0.11340579,\n",
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       "        [-0.04719552],\n",
       "        [-0.05255469],\n",
       "        [ 0.09900819],\n",
       "        [-0.04763248],\n",
       "        [-0.04795617],\n",
       "        [ 0.0038053 ],\n",
       "        [-0.08091898],\n",
       "        [-0.20571554],\n",
       "        [ 0.10389253],\n",
       "        [-0.16253583],\n",
       "        [ 0.12629856],\n",
       "        [-0.16292818],\n",
       "        [ 0.14657503],\n",
       "        [ 0.04870061],\n",
       "        [ 0.13153881],\n",
       "        [-0.1394889 ],\n",
       "        [ 0.0916727 ],\n",
       "        [-0.04141597],\n",
       "        [ 0.19531976]], dtype=float32),\n",
       " array([-0.00232022], dtype=float32)]"
      ]
     },
     "execution_count": 414,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classifier.get_weights()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 423,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([[[[-1.33701682e-01, -2.23046765e-02,  1.03748202e-01,\n",
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       " \n",
       " \n",
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       "            1.86602622e-02,  8.75114799e-02]],\n",
       " \n",
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       " \n",
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       " \n",
       " \n",
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       " \n",
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       " \n",
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       "        [-0.1311644 ],\n",
       "        [ 0.20115837],\n",
       "        [ 0.16926178],\n",
       "        [ 0.15642315],\n",
       "        [ 0.06799805],\n",
       "        [-0.11683448],\n",
       "        [-0.05328296],\n",
       "        [-0.15958177],\n",
       "        [ 0.04531559],\n",
       "        [-0.21150675],\n",
       "        [ 0.11918515],\n",
       "        [ 0.08623004],\n",
       "        [ 0.03159137],\n",
       "        [-0.20664142],\n",
       "        [ 0.09983999],\n",
       "        [ 0.03637213],\n",
       "        [-0.10762464],\n",
       "        [ 0.07458916],\n",
       "        [-0.10869455],\n",
       "        [-0.07398248],\n",
       "        [ 0.10333684],\n",
       "        [ 0.1977956 ],\n",
       "        [-0.14015558],\n",
       "        [ 0.2128655 ],\n",
       "        [-0.14139396],\n",
       "        [-0.09606273],\n",
       "        [ 0.13940656],\n",
       "        [ 0.01145376],\n",
       "        [ 0.08130759],\n",
       "        [ 0.15627801],\n",
       "        [-0.11147286],\n",
       "        [ 0.11980078],\n",
       "        [-0.1415986 ],\n",
       "        [-0.0396166 ],\n",
       "        [ 0.03451642],\n",
       "        [-0.11400214],\n",
       "        [ 0.21089292],\n",
       "        [-0.17041558],\n",
       "        [ 0.17135951],\n",
       "        [-0.01263691],\n",
       "        [ 0.11606506],\n",
       "        [-0.21261822],\n",
       "        [-0.01973264],\n",
       "        [ 0.18182692],\n",
       "        [-0.17311645],\n",
       "        [ 0.03446528],\n",
       "        [ 0.03106244],\n",
       "        [-0.01721621],\n",
       "        [ 0.0523456 ],\n",
       "        [-0.19077614],\n",
       "        [ 0.06427205],\n",
       "        [-0.1853651 ],\n",
       "        [-0.10611951],\n",
       "        [ 0.2125166 ],\n",
       "        [ 0.00313751],\n",
       "        [ 0.08960739],\n",
       "        [ 0.13379449],\n",
       "        [ 0.1607576 ],\n",
       "        [-0.12474129],\n",
       "        [ 0.04454738],\n",
       "        [-0.05285726],\n",
       "        [-0.08322488],\n",
       "        [ 0.1840818 ],\n",
       "        [-0.14793426],\n",
       "        [-0.03905614],\n",
       "        [-0.11407752],\n",
       "        [-0.09912702],\n",
       "        [-0.08309916],\n",
       "        [-0.13053325],\n",
       "        [ 0.05220312],\n",
       "        [-0.17726043],\n",
       "        [-0.02361767],\n",
       "        [ 0.09552097],\n",
       "        [ 0.0188797 ],\n",
       "        [-0.11181726],\n",
       "        [ 0.12380636],\n",
       "        [-0.14457506],\n",
       "        [-0.100563  ],\n",
       "        [ 0.18222108],\n",
       "        [ 0.02304029],\n",
       "        [ 0.18439573],\n",
       "        [-0.11523974],\n",
       "        [-0.17787261],\n",
       "        [ 0.00027236],\n",
       "        [-0.13693887],\n",
       "        [ 0.1890463 ],\n",
       "        [-0.07439351],\n",
       "        [ 0.09984919],\n",
       "        [-0.18099718],\n",
       "        [-0.11833005],\n",
       "        [-0.10108706],\n",
       "        [ 0.02500053],\n",
       "        [-0.04419234],\n",
       "        [ 0.06524974],\n",
       "        [ 0.19439268],\n",
       "        [ 0.07453543],\n",
       "        [ 0.11379898],\n",
       "        [-0.17763445],\n",
       "        [-0.10711425],\n",
       "        [ 0.15326786],\n",
       "        [-0.13971657],\n",
       "        [-0.10285123],\n",
       "        [-0.19084005],\n",
       "        [-0.18548459],\n",
       "        [-0.20998065],\n",
       "        [-0.06113726],\n",
       "        [-0.12663093],\n",
       "        [-0.08440123],\n",
       "        [ 0.00804111],\n",
       "        [ 0.02776983],\n",
       "        [-0.04857892],\n",
       "        [ 0.0790869 ],\n",
       "        [-0.1347866 ],\n",
       "        [-0.07955363],\n",
       "        [ 0.08369961],\n",
       "        [-0.10468472],\n",
       "        [-0.04336388],\n",
       "        [-0.08487844],\n",
       "        [ 0.09085926],\n",
       "        [ 0.14162904],\n",
       "        [ 0.14842844],\n",
       "        [ 0.18853408],\n",
       "        [-0.18993081],\n",
       "        [ 0.12904024]], dtype=float32),\n",
       " array([0.], dtype=float32)]"
      ]
     },
     "execution_count": 423,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classifier.get_weights()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 556,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv(\"Recurrent_Neural_Networks/Google_Stock_Price_Train.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 557,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/3/2012</td>\n",
       "      <td>325.25</td>\n",
       "      <td>332.83</td>\n",
       "      <td>324.97</td>\n",
       "      <td>663.59</td>\n",
       "      <td>7,380,500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/4/2012</td>\n",
       "      <td>331.27</td>\n",
       "      <td>333.87</td>\n",
       "      <td>329.08</td>\n",
       "      <td>666.45</td>\n",
       "      <td>5,749,400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/5/2012</td>\n",
       "      <td>329.83</td>\n",
       "      <td>330.75</td>\n",
       "      <td>326.89</td>\n",
       "      <td>657.21</td>\n",
       "      <td>6,590,300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/6/2012</td>\n",
       "      <td>328.34</td>\n",
       "      <td>328.77</td>\n",
       "      <td>323.68</td>\n",
       "      <td>648.24</td>\n",
       "      <td>5,405,900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/9/2012</td>\n",
       "      <td>322.04</td>\n",
       "      <td>322.29</td>\n",
       "      <td>309.46</td>\n",
       "      <td>620.76</td>\n",
       "      <td>11,688,800</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Date    Open    High     Low   Close      Volume\n",
       "0  1/3/2012  325.25  332.83  324.97  663.59   7,380,500\n",
       "1  1/4/2012  331.27  333.87  329.08  666.45   5,749,400\n",
       "2  1/5/2012  329.83  330.75  326.89  657.21   6,590,300\n",
       "3  1/6/2012  328.34  328.77  323.68  648.24   5,405,900\n",
       "4  1/9/2012  322.04  322.29  309.46  620.76  11,688,800"
      ]
     },
     "execution_count": 557,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 457,
   "metadata": {},
   "outputs": [],
   "source": [
    "training_dataset = df.iloc[:,1:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 458,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[325.25]\n",
      " [331.27]\n",
      " [329.83]\n",
      " ...\n",
      " [793.7 ]\n",
      " [783.33]\n",
      " [782.75]]\n"
     ]
    }
   ],
   "source": [
    "print training_dataset.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 459,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler\n",
    "sc= MinMaxScaler(feature_range=(0,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 460,
   "metadata": {},
   "outputs": [],
   "source": [
    "training_dataset_scaled=sc.fit_transform(training_dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 461,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train=[]\n",
    "Y_train=[]\n",
    "for i in range(60,1258):\n",
    "    X_train.append(training_dataset_scaled[i-60:i,0])\n",
    "    Y_train.append(training_dataset_scaled[i,0])\n",
    "X_train =np.array(X_train)\n",
    "Y_train  = np.array(Y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 462,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.09701243 0.09433366 0.09156187 0.07984225 0.0643277  0.0585423\n",
      " 0.06568569 0.06109085 0.06639259 0.0614257  0.07474514 0.02797827\n",
      " 0.02379269 0.02409033 0.0159238  0.01078949 0.00967334 0.01642607\n",
      " 0.02100231 0.02280676 0.02273235 0.02810849 0.03212665 0.0433812\n",
      " 0.04475779 0.04790163 0.0440695  0.04648783 0.04745517 0.04873875\n",
      " 0.03936305 0.04137213 0.04034898 0.04784582 0.04325099 0.04356723\n",
      " 0.04286033 0.04602277 0.05398467 0.05738894 0.05714711 0.05569611\n",
      " 0.04421832 0.04514845 0.04605997 0.04412531 0.03675869 0.04486941\n",
      " 0.05065481 0.05214302 0.05612397 0.05818885 0.06540665 0.06882953\n",
      " 0.07243843 0.07993526 0.07846566 0.08034452 0.08497656 0.08627874]\n",
      "0.08627874097775134\n"
     ]
    }
   ],
   "source": [
    "print X_train[1]\n",
    "print Y_train [0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 463,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = np.reshape(X_train, (X_train.shape[0],X_train.shape[1],1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 464,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1198, 60, 1)\n"
     ]
    }
   ],
   "source": [
    "print X_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 465,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.layers import LSTM,Dropout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 466,
   "metadata": {},
   "outputs": [],
   "source": [
    "regressor = Sequential()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 467,
   "metadata": {},
   "outputs": [],
   "source": [
    "regressor.add(LSTM(units=50, return_sequences=True, input_shape=(X_train.shape[1],1)))\n",
    "regressor.add(Dropout(0.2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 452,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "lstm_1 (LSTM)                (None, 60, 50)            10400     \n",
      "_________________________________________________________________\n",
      "dropout_1 (Dropout)          (None, 60, 50)            0         \n",
      "_________________________________________________________________\n",
      "lstm_2 (LSTM)                (None, 60, 50)            20200     \n",
      "_________________________________________________________________\n",
      "dropout_2 (Dropout)          (None, 60, 50)            0         \n",
      "_________________________________________________________________\n",
      "lstm_3 (LSTM)                (None, 60, 50)            20200     \n",
      "_________________________________________________________________\n",
      "dropout_3 (Dropout)          (None, 60, 50)            0         \n",
      "_________________________________________________________________\n",
      "lstm_4 (LSTM)                (None, 50)                20200     \n",
      "_________________________________________________________________\n",
      "dropout_4 (Dropout)          (None, 50)                0         \n",
      "_________________________________________________________________\n",
      "dense_50 (Dense)             (None, 1)                 51        \n",
      "=================================================================\n",
      "Total params: 71,051\n",
      "Trainable params: 71,051\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print regressor.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 468,
   "metadata": {},
   "outputs": [],
   "source": [
    "regressor.add(LSTM(units=50, return_sequences=True))\n",
    "regressor.add(Dropout(0.2))\n",
    "\n",
    "regressor.add(LSTM(units=50, return_sequences=True))\n",
    "regressor.add(Dropout(0.2))\n",
    "\n",
    "regressor.add(LSTM(units=50))\n",
    "regressor.add(Dropout(0.2))\n",
    "\n",
    "regressor.add(Dense(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 469,
   "metadata": {},
   "outputs": [],
   "source": [
    "regressor.compile(optimizer='adam',loss='mean_squared_error')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 470,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "1198/1198 [==============================] - 10s 8ms/step - loss: 0.0505\n",
      "Epoch 2/10\n",
      "1198/1198 [==============================] - 8s 6ms/step - loss: 0.0067\n",
      "Epoch 3/10\n",
      "1198/1198 [==============================] - 8s 7ms/step - loss: 0.0051\n",
      "Epoch 4/10\n",
      "1198/1198 [==============================] - 9s 7ms/step - loss: 0.0048\n",
      "Epoch 5/10\n",
      "1198/1198 [==============================] - 9s 7ms/step - loss: 0.0047\n",
      "Epoch 6/10\n",
      "1198/1198 [==============================] - 8s 7ms/step - loss: 0.0044\n",
      "Epoch 7/10\n",
      "1198/1198 [==============================] - 8s 7ms/step - loss: 0.0046\n",
      "Epoch 8/10\n",
      "1198/1198 [==============================] - 8s 7ms/step - loss: 0.0042\n",
      "Epoch 9/10\n",
      "1198/1198 [==============================] - 8s 6ms/step - loss: 0.0043\n",
      "Epoch 10/10\n",
      "1198/1198 [==============================] - 7s 6ms/step - loss: 0.0043\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x13fdd6ad0>"
      ]
     },
     "execution_count": 470,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regressor.fit(X_train,Y_train,epochs=10,batch_size=32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 558,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1=pd.read_csv('Recurrent_Neural_Networks/Google_Stock_Price_Test.csv')\n",
    "real_stock_price = df1.iloc[:,1:2].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 559,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset_total=pd.concat((df['Open'],df1['Open']),axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 560,
   "metadata": {},
   "outputs": [],
   "source": [
    "inputs = dataset_total[len(dataset_total)-len(df1)-60:].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 562,
   "metadata": {},
   "outputs": [],
   "source": [
    "inputs = inputs.reshape(-1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 522,
   "metadata": {},
   "outputs": [],
   "source": [
    "inputs = inputs.reshape(-1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 563,
   "metadata": {},
   "outputs": [],
   "source": [
    "inputs= sc.transform(inputs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 564,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test=[]\n",
    "Y_test=[]\n",
    "for i in range(60,80):\n",
    "    X_test.append(inputs[i-60:i,0])\n",
    "    Y_test.append(inputs[i,0])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 565,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test =np.array(X_test)\n",
    "Y_test  = np.array(Y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 566,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test = np.reshape(X_test, (X_test.shape[0],X_test.shape[1],1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 567,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(20, 60, 1)\n"
     ]
    }
   ],
   "source": [
    "print X_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 568,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_price = regressor.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 569,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_price_org = sc.inverse_transform(pred_price)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 570,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[780.27136],\n",
       "       [781.1757 ],\n",
       "       [781.763  ],\n",
       "       [782.07916],\n",
       "       [782.21387],\n",
       "       [782.3022 ],\n",
       "       [782.4719 ],\n",
       "       [782.80145],\n",
       "       [783.3323 ],\n",
       "       [784.0703 ],\n",
       "       [784.9929 ],\n",
       "       [786.0538 ],\n",
       "       [787.1951 ],\n",
       "       [788.3668 ],\n",
       "       [789.5277 ],\n",
       "       [790.7036 ],\n",
       "       [791.9598 ],\n",
       "       [793.3826 ],\n",
       "       [795.0195 ],\n",
       "       [796.7976 ]], dtype=float32)"
      ]
     },
     "execution_count": 570,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_price_org"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 573,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.51750586],\n",
       "       [-0.51747281],\n",
       "       [-0.5174807 ],\n",
       "       [-0.51744893],\n",
       "       [-0.51741038],\n",
       "       [-0.51740533],\n",
       "       [-0.51741522],\n",
       "       [-0.51740782],\n",
       "       [-0.51740664],\n",
       "       [-0.51740803],\n",
       "       [-0.51741242],\n",
       "       [-0.51741481],\n",
       "       [-0.51740861],\n",
       "       [-0.51740744],\n",
       "       [-0.51735536],\n",
       "       [-0.51733003],\n",
       "       [-0.51730168],\n",
       "       [-0.51731241],\n",
       "       [-0.51738179],\n",
       "       [-0.51744339]])"
      ]
     },
     "execution_count": 573,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sc.transform(Y_test.reshape(20,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 539,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 572,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(real_stock_price, color = 'red', label = 'Real Google Stock Price')\n",
    "plt.plot(pred_price_org, color = 'blue', label = 'Predicted Google Stock Price')\n",
    "plt.title('Google Stock Price Prediction')\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Google Stock Price')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 552,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Date    Open    High     Low   Close     Volume\n",
      "0    1/3/2017  778.81  789.63  775.80  786.14  1,657,300\n",
      "1    1/4/2017  788.36  791.34  783.16  786.90  1,073,000\n",
      "2    1/5/2017  786.08  794.48  785.02  794.02  1,335,200\n",
      "3    1/6/2017  795.26  807.90  792.20  806.15  1,640,200\n",
      "4    1/9/2017  806.40  809.97  802.83  806.65  1,272,400\n",
      "5   1/10/2017  807.86  809.13  803.51  804.79  1,176,800\n",
      "6   1/11/2017  805.00  808.15  801.37  807.91  1,065,900\n",
      "7   1/12/2017  807.14  807.39  799.17  806.36  1,353,100\n",
      "8   1/13/2017  807.48  811.22  806.69  807.88  1,099,200\n",
      "9   1/17/2017  807.08  807.14  800.37  804.61  1,362,100\n",
      "10  1/18/2017  805.81  806.21  800.99  806.07  1,294,400\n",
      "11  1/19/2017  805.12  809.48  801.80  802.17    919,300\n",
      "12  1/20/2017  806.91  806.91  801.69  805.02  1,670,000\n",
      "13  1/23/2017  807.25  820.87  803.74  819.31  1,963,600\n",
      "14  1/24/2017  822.30  825.90  817.82  823.87  1,474,000\n",
      "15  1/25/2017  829.62  835.77  825.06  835.67  1,494,500\n",
      "16  1/26/2017  837.81  838.00  827.01  832.15  2,973,900\n",
      "17  1/27/2017  834.71  841.95  820.44  823.31  2,965,800\n",
      "18  1/30/2017  814.66  815.84  799.80  802.32  3,246,600\n",
      "19  1/31/2017  796.86  801.25  790.52  796.79  2,160,600\n"
     ]
    }
   ],
   "source": [
    "print df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 574,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'{\"class_name\": \"Sequential\", \"keras_version\": \"2.2.0\", \"config\": [{\"class_name\": \"LSTM\", \"config\": {\"recurrent_activation\": \"hard_sigmoid\", \"dtype\": \"float32\", \"trainable\": true, \"recurrent_initializer\": {\"class_name\": \"Orthogonal\", \"config\": {\"seed\": null, \"gain\": 1.0}}, \"use_bias\": true, \"bias_regularizer\": null, \"return_state\": false, \"unroll\": false, \"activation\": \"tanh\", \"bias_initializer\": {\"class_name\": \"Zeros\", \"config\": {}}, \"units\": 50, \"batch_input_shape\": [null, 60, 1], \"activity_regularizer\": null, \"recurrent_dropout\": 0.0, \"kernel_initializer\": {\"class_name\": \"VarianceScaling\", \"config\": {\"distribution\": \"uniform\", \"scale\": 1.0, \"seed\": null, \"mode\": \"fan_avg\"}}, \"kernel_constraint\": null, \"dropout\": 0.0, \"stateful\": false, \"unit_forget_bias\": true, \"recurrent_regularizer\": null, \"name\": \"lstm_5\", \"bias_constraint\": null, \"go_backwards\": false, \"implementation\": 1, \"kernel_regularizer\": null, \"return_sequences\": true, \"recurrent_constraint\": null}}, {\"class_name\": \"Dropout\", \"config\": {\"rate\": 0.2, \"noise_shape\": null, \"trainable\": true, \"seed\": null, \"name\": \"dropout_5\"}}, {\"class_name\": \"LSTM\", \"config\": {\"recurrent_activation\": \"hard_sigmoid\", \"trainable\": true, \"recurrent_initializer\": {\"class_name\": \"Orthogonal\", \"config\": {\"seed\": null, \"gain\": 1.0}}, \"use_bias\": true, \"bias_regularizer\": null, \"return_state\": false, \"unroll\": false, \"activation\": \"tanh\", \"bias_initializer\": {\"class_name\": \"Zeros\", \"config\": {}}, \"units\": 50, \"unit_forget_bias\": true, \"activity_regularizer\": null, \"recurrent_dropout\": 0.0, \"kernel_initializer\": {\"class_name\": \"VarianceScaling\", \"config\": {\"distribution\": \"uniform\", \"scale\": 1.0, \"seed\": null, \"mode\": \"fan_avg\"}}, \"kernel_constraint\": null, \"dropout\": 0.0, \"stateful\": false, \"recurrent_regularizer\": null, \"name\": \"lstm_6\", \"bias_constraint\": null, \"go_backwards\": false, \"implementation\": 1, \"kernel_regularizer\": null, \"return_sequences\": true, \"recurrent_constraint\": null}}, {\"class_name\": \"Dropout\", \"config\": {\"rate\": 0.2, \"noise_shape\": null, \"trainable\": true, \"seed\": null, \"name\": \"dropout_6\"}}, {\"class_name\": \"LSTM\", \"config\": {\"recurrent_activation\": \"hard_sigmoid\", \"trainable\": true, \"recurrent_initializer\": {\"class_name\": \"Orthogonal\", \"config\": {\"seed\": null, \"gain\": 1.0}}, \"use_bias\": true, \"bias_regularizer\": null, \"return_state\": false, \"unroll\": false, \"activation\": \"tanh\", \"bias_initializer\": {\"class_name\": \"Zeros\", \"config\": {}}, \"units\": 50, \"unit_forget_bias\": true, \"activity_regularizer\": null, \"recurrent_dropout\": 0.0, \"kernel_initializer\": {\"class_name\": \"VarianceScaling\", \"config\": {\"distribution\": \"uniform\", \"scale\": 1.0, \"seed\": null, \"mode\": \"fan_avg\"}}, \"kernel_constraint\": null, \"dropout\": 0.0, \"stateful\": false, \"recurrent_regularizer\": null, \"name\": \"lstm_7\", \"bias_constraint\": null, \"go_backwards\": false, \"implementation\": 1, \"kernel_regularizer\": null, \"return_sequences\": true, \"recurrent_constraint\": null}}, {\"class_name\": \"Dropout\", \"config\": {\"rate\": 0.2, \"noise_shape\": null, \"trainable\": true, \"seed\": null, \"name\": \"dropout_7\"}}, {\"class_name\": \"LSTM\", \"config\": {\"recurrent_activation\": \"hard_sigmoid\", \"trainable\": true, \"recurrent_initializer\": {\"class_name\": \"Orthogonal\", \"config\": {\"seed\": null, \"gain\": 1.0}}, \"use_bias\": true, \"bias_regularizer\": null, \"return_state\": false, \"unroll\": false, \"activation\": \"tanh\", \"bias_initializer\": {\"class_name\": \"Zeros\", \"config\": {}}, \"units\": 50, \"unit_forget_bias\": true, \"activity_regularizer\": null, \"recurrent_dropout\": 0.0, \"kernel_initializer\": {\"class_name\": \"VarianceScaling\", \"config\": {\"distribution\": \"uniform\", \"scale\": 1.0, \"seed\": null, \"mode\": \"fan_avg\"}}, \"kernel_constraint\": null, \"dropout\": 0.0, \"stateful\": false, \"recurrent_regularizer\": null, \"name\": \"lstm_8\", \"bias_constraint\": null, \"go_backwards\": false, \"implementation\": 1, \"kernel_regularizer\": null, \"return_sequences\": false, \"recurrent_constraint\": null}}, {\"class_name\": \"Dropout\", \"config\": {\"rate\": 0.2, \"noise_shape\": null, \"trainable\": true, \"seed\": null, \"name\": \"dropout_8\"}}, {\"class_name\": \"Dense\", \"config\": {\"kernel_initializer\": {\"class_name\": \"VarianceScaling\", \"config\": {\"distribution\": \"uniform\", \"scale\": 1.0, \"seed\": null, \"mode\": \"fan_avg\"}}, \"name\": \"dense_51\", \"kernel_constraint\": null, \"bias_regularizer\": null, \"bias_constraint\": null, \"activation\": \"linear\", \"trainable\": true, \"kernel_regularizer\": null, \"bias_initializer\": {\"class_name\": \"Zeros\", \"config\": {}}, \"units\": 1, \"use_bias\": true, \"activity_regularizer\": null}}], \"backend\": \"tensorflow\"}'"
      ]
     },
     "execution_count": 574,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regressor.to_json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 580,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solving environment: failed\n",
      "\n",
      "PackagesNotFoundError: The following packages are not available from current channels:\n",
      "\n",
      "  - pycaffe\n",
      "\n",
      "Current channels:\n",
      "\n",
      "  - https://repo.anaconda.com/pkgs/main/osx-64\n",
      "  - https://repo.anaconda.com/pkgs/main/noarch\n",
      "  - https://repo.anaconda.com/pkgs/free/osx-64\n",
      "  - https://repo.anaconda.com/pkgs/free/noarch\n",
      "  - https://repo.anaconda.com/pkgs/r/osx-64\n",
      "  - https://repo.anaconda.com/pkgs/r/noarch\n",
      "  - https://repo.anaconda.com/pkgs/pro/osx-64\n",
      "  - https://repo.anaconda.com/pkgs/pro/noarch\n",
      "\n",
      "To search for alternate channels that may provide the conda package you're\n",
      "looking for, navigate to\n",
      "\n",
      "    https://anaconda.org\n",
      "\n",
      "and use the search bar at the top of the page.\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!conda install pycaffe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 582,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting py-caffe\n",
      "\u001b[31m  Could not find a version that satisfies the requirement py-caffe (from versions: )\u001b[0m\n",
      "\u001b[31mNo matching distribution found for py-caffe\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install py-caffe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 593,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting nltk\n",
      "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/50/09/3b1755d528ad9156ee7243d52aa5cd2b809ef053a0f31b53d92853dd653a/nltk-3.3.0.zip (1.4MB)\n",
      "\u001b[K    100% |████████████████████████████████| 1.4MB 707kB/s ta 0:00:011\n",
      "\u001b[?25hRequirement already satisfied: six in /anaconda2/envs/Keras/lib/python2.7/site-packages (from nltk) (1.11.0)\n",
      "Building wheels for collected packages: nltk\n",
      "  Running setup.py bdist_wheel for nltk ... \u001b[?25ldone\n",
      "\u001b[?25h  Stored in directory: /Users/sks000y/Library/Caches/pip/wheels/d1/ab/40/3bceea46922767e42986aef7606a600538ca80de6062dc266c\n",
      "Successfully built nltk\n",
      "Installing collected packages: nltk\n",
      "Successfully installed nltk-3.3\n"
     ]
    }
   ],
   "source": [
    "!pip install nltk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 590,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pattern.en as en\n",
    "base_form = en.lemma('potatoe') # base_form == \"eat\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 591,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'potatoe'"
      ]
     },
     "execution_count": 591,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "base_form"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 597,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.stem.snowball import SnowballStemmer\n",
    "stemmer = SnowballStemmer(\"porter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 598,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "u'babi'"
      ]
     },
     "execution_count": 598,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stemmer.stem('baby')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.applications import VGG16\n",
    "vgg16=VGG16(weights='imagenet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[array([[[[ 4.29470569e-01,  1.17273867e-01,  3.40129584e-02, ...,\n",
      "          -1.32241577e-01, -5.33475243e-02,  7.57738389e-03],\n",
      "         [ 5.50379455e-01,  2.08774377e-02,  9.88311544e-02, ...,\n",
      "          -8.48205537e-02, -5.11389151e-02,  3.74943428e-02],\n",
      "         [ 4.80015397e-01, -1.72696680e-01,  3.75577137e-02, ...,\n",
      "          -1.27135560e-01, -5.02991639e-02,  3.48965675e-02]],\n",
      "\n",
      "        [[ 3.73466998e-01,  1.62062630e-01,  1.70863140e-03, ...,\n",
      "          -1.48207128e-01, -2.35300660e-01, -6.30356818e-02],\n",
      "         [ 4.40074533e-01,  4.73412387e-02,  5.13819456e-02, ...,\n",
      "          -9.88498852e-02, -2.96195745e-01, -7.04357103e-02],\n",
      "         [ 4.08547401e-01, -1.70375049e-01, -4.96297423e-03, ...,\n",
      "          -1.22360572e-01, -2.76450396e-01, -3.90796512e-02]],\n",
      "\n",
      "        [[-6.13601133e-02,  1.35693997e-01, -1.15694344e-01, ...,\n",
      "          -1.40158370e-01, -3.77666801e-01, -3.00509870e-01],\n",
      "         [-8.13870355e-02,  4.18543853e-02, -1.01763301e-01, ...,\n",
      "          -9.43124294e-02, -5.05662560e-01, -3.83694321e-01],\n",
      "         [-6.51455522e-02, -1.54351532e-01, -1.38038069e-01, ...,\n",
      "          -1.29404560e-01, -4.62243795e-01, -3.23985279e-01]]],\n",
      "\n",
      "\n",
      "       [[[ 2.74769872e-01,  1.48350164e-01,  1.61559835e-01, ...,\n",
      "          -1.14316158e-01,  3.65494519e-01,  3.39938998e-01],\n",
      "         [ 3.45739067e-01,  3.10493708e-02,  2.40750551e-01, ...,\n",
      "          -6.93419054e-02,  4.37116861e-01,  4.13171440e-01],\n",
      "         [ 3.10477257e-01, -1.87601492e-01,  1.66595340e-01, ...,\n",
      "          -9.88388434e-02,  4.04058546e-01,  3.92561197e-01]],\n",
      "\n",
      "        [[ 3.86807770e-02,  2.02298447e-01,  1.56414255e-01, ...,\n",
      "          -5.20089604e-02,  2.57149011e-01,  3.71682674e-01],\n",
      "         [ 4.06322069e-02,  6.58102185e-02,  2.20311403e-01, ...,\n",
      "          -3.78979952e-03,  2.69412428e-01,  4.09505904e-01],\n",
      "         [ 5.02023660e-02, -1.77571565e-01,  1.51188180e-01, ...,\n",
      "          -1.40649760e-02,  2.59300828e-01,  4.23764467e-01]],\n",
      "\n",
      "        [[-3.67223352e-01,  1.61688417e-01, -8.99365395e-02, ...,\n",
      "          -1.45945460e-01, -2.71823555e-01, -2.39718184e-01],\n",
      "         [-4.53501314e-01,  4.62574959e-02, -6.67438358e-02, ...,\n",
      "          -1.03502415e-01, -3.45792353e-01, -2.92486250e-01],\n",
      "         [-4.03383434e-01, -1.74399972e-01, -1.09849639e-01, ...,\n",
      "          -1.25688612e-01, -3.14026326e-01, -2.32839763e-01]]],\n",
      "\n",
      "\n",
      "       [[[-5.74681684e-02,  1.29344285e-01,  1.29030216e-02, ...,\n",
      "          -1.41449392e-01,  2.41099641e-01,  4.55602147e-02],\n",
      "         [-5.86349145e-02,  3.16787697e-02,  7.59588331e-02, ...,\n",
      "          -1.05017252e-01,  3.39550197e-01,  9.86374393e-02],\n",
      "         [-5.08716851e-02, -1.66002661e-01,  1.56279504e-02, ...,\n",
      "          -1.49742723e-01,  3.06801915e-01,  8.82701725e-02]],\n",
      "\n",
      "        [[-2.62249678e-01,  1.71572417e-01,  5.44555223e-05, ...,\n",
      "          -1.22728683e-01,  2.44687453e-01,  5.32913655e-02],\n",
      "         [-3.30669671e-01,  5.47101051e-02,  4.86797579e-02, ...,\n",
      "          -8.29023942e-02,  2.95466095e-01,  7.44469985e-02],\n",
      "         [-2.85227507e-01, -1.66666731e-01, -7.96697661e-03, ...,\n",
      "          -1.09780088e-01,  2.79203743e-01,  9.46525261e-02]],\n",
      "\n",
      "        [[-3.50096762e-01,  1.38710454e-01, -1.25339806e-01, ...,\n",
      "          -1.53092295e-01, -1.39917329e-01, -2.65075237e-01],\n",
      "         [-4.85030204e-01,  4.23195846e-02, -1.12076312e-01, ...,\n",
      "          -1.18306056e-01, -1.67058021e-01, -3.22241962e-01],\n",
      "         [-4.18516338e-01, -1.57048807e-01, -1.49133086e-01, ...,\n",
      "          -1.56839803e-01, -1.42874300e-01, -2.69694626e-01]]]],\n",
      "      dtype=float32), array([ 0.73429835,  0.09340367,  0.06775674,  0.8862966 ,  0.25994542,\n",
      "        0.66426694, -0.01582893,  0.3249065 ,  0.68600726,  0.06247932,\n",
      "        0.58156496,  0.2361475 ,  0.69694996,  0.19451167,  0.4858922 ,\n",
      "        0.44571847,  0.5113422 ,  0.208576  ,  0.57557714,  0.33199573,\n",
      "        0.4997983 ,  0.7117759 ,  0.30284074,  0.7082712 ,  0.04548979,\n",
      "        0.7446502 ,  0.29845494,  0.48211655,  0.81658626,  0.62603897,\n",
      "        0.3768093 ,  2.064037  ,  0.77311045,  0.3459577 ,  0.6130958 ,\n",
      "        0.65459156,  0.39045632,  0.50869167,  0.2625384 ,  0.23669638,\n",
      "        0.07971057,  1.1179353 ,  0.26129362,  0.8697589 ,  0.21543622,\n",
      "        0.78007823,  0.37015367,  0.47993386,  0.4313978 ,  0.5084194 ,\n",
      "        0.23049663,  0.7636527 ,  0.35419866,  0.45794216,  0.4662595 ,\n",
      "        0.09850298,  0.3803252 ,  0.66880196,  0.4015123 ,  0.90510356,\n",
      "        0.43166816,  1.302014  ,  0.5306885 ,  0.48993504], dtype=float32), array([[[[ 1.66219279e-01,  1.42701820e-01, -4.02113283e-03, ...,\n",
      "           6.18828237e-02, -1.74057148e-02, -3.00644431e-02],\n",
      "         [ 9.46945231e-03,  3.87477316e-03,  5.08365929e-02, ...,\n",
      "          -2.77981739e-02,  1.71373668e-03,  6.82722731e-03],\n",
      "         [ 6.32681847e-02,  2.12877709e-02, -1.63465310e-02, ...,\n",
      "           8.80054955e-04,  6.68104272e-03, -1.41139806e-03],\n",
      "         ...,\n",
      "         [ 3.47490981e-03,  8.47019628e-02, -4.07223180e-02, ...,\n",
      "          -1.13523193e-02, -7.48998486e-03,  3.19077494e-03],\n",
      "         [ 5.97234145e-02,  4.97663505e-02, -3.23118735e-03, ...,\n",
      "           1.43114366e-02,  3.03175431e-02, -4.23925705e-02],\n",
      "         [ 1.33459672e-01,  4.95484173e-02, -1.78808011e-02, ...,\n",
      "           2.25385167e-02,  3.02020740e-02, -2.17075031e-02]],\n",
      "\n",
      "        [[ 2.12007999e-01,  2.10127644e-02, -1.47626130e-02, ...,\n",
      "           2.29580477e-02,  1.23102348e-02, -3.08422819e-02],\n",
      "         [-2.62175221e-03,  7.42094172e-03,  6.74030930e-02, ...,\n",
      "          -3.06594316e-02,  1.80578313e-03,  4.27369215e-03],\n",
      "         [ 2.27197763e-02, -1.07841045e-02, -1.31095545e-02, ...,\n",
      "          -1.15751950e-02,  4.18359675e-02, -1.92268589e-03],\n",
      "         ...,\n",
      "         [-2.70304317e-03,  7.41161704e-02, -3.32262330e-02, ...,\n",
      "          -1.10277236e-02,  1.39831286e-02,  5.34419343e-03],\n",
      "         [-3.20506282e-02, -2.40584910e-02, -4.52397857e-03, ...,\n",
      "          -6.04042644e-03,  2.01962605e-01, -5.04491515e-02],\n",
      "         [ 1.68114193e-02, -2.33167298e-02, -1.40886130e-02, ...,\n",
      "          -7.79278344e-03,  1.28428593e-01, -2.58184522e-02]],\n",
      "\n",
      "        [[-5.91698708e-03, -2.26223674e-02,  4.88128467e-03, ...,\n",
      "           4.13784146e-04, -4.84175496e-02,  1.63675251e-03],\n",
      "         [-3.93767562e-03,  9.07397643e-03,  5.36517277e-02, ...,\n",
      "          -2.56106984e-02, -4.17886395e-03,  2.47476017e-03],\n",
      "         [-3.07008922e-02, -1.09781921e-02, -3.69096454e-03, ...,\n",
      "          -1.19221993e-02, -1.39777903e-02,  8.52933805e-03],\n",
      "         ...,\n",
      "         [ 5.83332591e-03,  2.96198055e-02, -3.56571227e-02, ...,\n",
      "          -1.01153394e-02,  5.06090466e-03, -2.86859111e-03],\n",
      "         [-7.80934095e-02, -1.95693132e-02,  2.14814320e-02, ...,\n",
      "           7.42452731e-03,  5.41617945e-02, -2.35790759e-02],\n",
      "         [-7.82641992e-02, -2.47034207e-02,  1.36250593e-02, ...,\n",
      "          -7.53259566e-03, -2.59861015e-02,  4.52143652e-03]]],\n",
      "\n",
      "\n",
      "       [[[ 1.99202523e-01,  5.03257252e-02, -1.93236247e-02, ...,\n",
      "           1.62308700e-02, -1.15369558e-02,  1.55777042e-03],\n",
      "         [-1.38656620e-03,  4.52297740e-03,  6.65066689e-02, ...,\n",
      "          -3.00004911e-02,  1.71904117e-04, -1.11898372e-03],\n",
      "         [ 2.14257818e-02,  1.79782789e-03, -1.76792312e-02, ...,\n",
      "          -6.09106943e-03, -3.21686491e-02, -1.07312342e-03],\n",
      "         ...,\n",
      "         [-1.47800148e-02,  7.77616128e-02, -2.67065037e-02, ...,\n",
      "          -8.10234528e-03, -1.15585206e-02, -5.30505227e-03],\n",
      "         [-1.39283072e-02,  1.69547591e-02, -1.20282415e-02, ...,\n",
      "           1.25513040e-02, -8.44068080e-02, -4.48253192e-02],\n",
      "         [ 2.55671684e-02,  7.02229328e-03, -2.82986648e-02, ...,\n",
      "           1.17048556e-02, -7.34802186e-02, -2.06979234e-02]],\n",
      "\n",
      "        [[-2.59410664e-02, -4.97468375e-02, -2.42083799e-02, ...,\n",
      "          -2.39597876e-02,  2.09030695e-02,  1.69499479e-02],\n",
      "         [-4.78290301e-03,  1.04173329e-02,  8.31823424e-02, ...,\n",
      "          -3.18786576e-02,  3.48328054e-03, -3.56311840e-03],\n",
      "         [-3.81173752e-02, -1.85197107e-02, -1.43900532e-02, ...,\n",
      "          -1.41960718e-02,  3.14613059e-02,  4.11967095e-03],\n",
      "         ...,\n",
      "         [-1.79932006e-02,  7.17700496e-02, -1.99375115e-02, ...,\n",
      "          -6.12784317e-03,  1.66521706e-02, -7.48346280e-03],\n",
      "         [-8.91536921e-02, -4.69055325e-02, -1.37380632e-02, ...,\n",
      "          -8.06835108e-03,  6.04359731e-02, -4.47445139e-02],\n",
      "         [-1.00021079e-01, -3.55393849e-02, -2.46136412e-02, ...,\n",
      "          -7.50665693e-03,  9.11064222e-02, -1.06519591e-02]],\n",
      "\n",
      "        [[-9.84916389e-02, -5.77464141e-02, -4.49889433e-03, ...,\n",
      "          -2.21592579e-02, -9.32130869e-03,  5.57853021e-02],\n",
      "         [ 4.70533501e-03,  1.18583711e-02,  6.85855076e-02, ...,\n",
      "          -2.62385849e-02, -2.82203127e-03, -4.67023626e-03],\n",
      "         [-2.28894763e-02, -7.75412470e-03, -9.86886956e-03, ...,\n",
      "          -1.22523597e-02,  4.30414118e-02,  1.28994938e-02],\n",
      "         ...,\n",
      "         [ 2.93275771e-05,  1.62800644e-02, -2.53228396e-02, ...,\n",
      "          -8.11440870e-03,  9.42004658e-03, -1.69352964e-02],\n",
      "         [-4.56118677e-03, -3.88334878e-02, -8.15101550e-04, ...,\n",
      "          -7.37672672e-05,  2.05828294e-01, -1.84731018e-02],\n",
      "         [-3.79626676e-02, -1.82646457e-02, -7.20302528e-03, ...,\n",
      "          -1.28044421e-03,  1.40015617e-01,  1.13147246e-02]]],\n",
      "\n",
      "\n",
      "       [[[-1.11585744e-02, -4.15539136e-03, -6.83113467e-03, ...,\n",
      "           3.17358202e-03, -6.52846992e-02,  8.59456360e-02],\n",
      "         [-6.14583818e-03,  4.85422462e-03,  5.14627509e-02, ...,\n",
      "          -2.23777443e-02, -1.03412592e-03, -8.19014851e-03],\n",
      "         [-1.00106997e-02, -1.59974187e-03, -1.14092128e-02, ...,\n",
      "          -3.87838250e-03, -3.99293639e-02,  1.13589503e-02],\n",
      "         ...,\n",
      "         [-1.68860350e-02,  5.18255346e-02, -2.66014934e-02, ...,\n",
      "          -1.99763244e-03,  4.35560057e-03, -4.49330434e-02],\n",
      "         [-1.34146223e-02,  6.32185815e-03, -7.33473897e-03, ...,\n",
      "           4.59014578e-03, -2.98611149e-02,  3.69221941e-02],\n",
      "         [-2.88858525e-02, -4.22423892e-03, -1.42897591e-02, ...,\n",
      "           1.11823296e-02, -7.52132908e-02,  1.67242344e-02]],\n",
      "\n",
      "        [[-1.02114283e-01, -5.26558608e-02, -1.00238100e-02, ...,\n",
      "          -1.37801170e-02, -4.94753271e-02,  1.25953421e-01],\n",
      "         [ 2.65349774e-03,  1.04075735e-02,  6.73149154e-02, ...,\n",
      "          -2.37589777e-02,  6.13968645e-04, -9.96601582e-03],\n",
      "         [-1.50703192e-02, -1.28871305e-02, -8.77845287e-03, ...,\n",
      "          -1.01640215e-02, -4.76290248e-02,  1.36717530e-02],\n",
      "         ...,\n",
      "         [-5.43789240e-03,  3.35888155e-02, -2.11151708e-02, ...,\n",
      "          -3.83130647e-03, -1.02301398e-02, -5.32924160e-02],\n",
      "         [-2.21891310e-02, -4.92077954e-02, -1.38867581e-02, ...,\n",
      "          -1.28568839e-02, -9.37007815e-02,  5.59309907e-02],\n",
      "         [-2.61166841e-02, -3.50148268e-02, -1.47816772e-02, ...,\n",
      "          -2.86548026e-03, -1.01101905e-01,  1.94419883e-02]],\n",
      "\n",
      "        [[ 2.73401570e-02, -3.54428887e-02,  1.18577422e-03, ...,\n",
      "           5.02943760e-04,  4.51298095e-02,  1.23520821e-01],\n",
      "         [ 9.48381796e-03,  1.12858564e-02,  5.32916747e-02, ...,\n",
      "          -1.81195941e-02, -1.31687860e-03, -1.01092532e-02],\n",
      "         [ 3.73495184e-02, -7.93821830e-03, -5.94039401e-03, ...,\n",
      "          -7.96878152e-03,  1.53274648e-02,  9.63651482e-03],\n",
      "         ...,\n",
      "         [-2.60413792e-02, -2.53635142e-02, -2.81382054e-02, ...,\n",
      "          -6.63971901e-03, -7.26283342e-03, -5.57855107e-02],\n",
      "         [ 2.67488584e-02, -4.73727398e-02, -3.06198676e-03, ...,\n",
      "          -4.82000969e-03,  4.08617556e-02,  6.99444860e-02],\n",
      "         [ 7.98859298e-02, -2.87372041e-02,  6.38093508e-04, ...,\n",
      "           9.73386108e-04,  4.21557203e-02,  1.60824433e-02]]]],\n",
      "      dtype=float32), array([-0.30912212,  0.36397225,  0.13737613,  0.07717966,  0.9052184 ,\n",
      "        0.08885256,  0.10789118, -0.23106739, -0.6318097 ,  0.18161367,\n",
      "       -0.33391494,  0.1961724 ,  0.43838617,  0.1938708 ,  0.10894354,\n",
      "        0.10315038, -1.0271513 ,  0.05252688,  0.13118458,  0.22851577,\n",
      "       -0.71377224,  0.2154155 , -0.6981962 ,  0.04061132,  0.13955347,\n",
      "        0.28767544,  0.35358745,  0.3937295 ,  0.43452853, -0.48259264,\n",
      "        0.02631121,  0.09220165,  0.05196398,  0.550705  ,  0.32368094,\n",
      "        0.07263482, -0.17745508,  0.3761972 ,  0.39344102,  0.17673127,\n",
      "       -0.15784228,  0.26051855,  0.08342359,  0.08603705, -0.09131282,\n",
      "        0.22932515,  0.2998315 ,  0.13511261, -0.3835829 ,  0.10912544,\n",
      "       -0.53432876,  0.4741787 , -0.0740848 ,  0.30046257,  0.12590808,\n",
      "        0.16480374,  0.2403943 ,  0.23401979, -0.19334187,  0.01663565,\n",
      "        0.27144948,  0.03385786,  0.06076292, -0.5825159 ], dtype=float32), array([[[[-8.90296325e-03,  3.78169715e-02,  1.39756575e-02, ...,\n",
      "          -6.35457635e-02,  2.83470433e-02, -5.54975234e-02],\n",
      "         [-5.66543266e-03, -1.05560187e-03, -2.29203496e-02, ...,\n",
      "          -1.30956469e-03,  2.52478309e-02, -2.95403805e-02],\n",
      "         [-7.85139855e-03, -4.38382570e-03, -1.29586197e-02, ...,\n",
      "           1.22073088e-02,  4.46309976e-04, -2.49174051e-02],\n",
      "         ...,\n",
      "         [-5.82487276e-03,  3.78986611e-03, -1.48562957e-02, ...,\n",
      "           1.27910008e-03,  1.27594778e-02, -1.33825615e-02],\n",
      "         [-1.54342148e-02,  5.62145375e-03,  3.05225104e-02, ...,\n",
      "           1.61413271e-02, -4.20058556e-02, -3.35679092e-02],\n",
      "         [-4.21814434e-03,  2.95577031e-02,  2.57514068e-03, ...,\n",
      "          -2.59456299e-02, -1.35917868e-03, -5.85189313e-02]],\n",
      "\n",
      "        [[-1.03394873e-02,  3.75955850e-02,  6.87777717e-03, ...,\n",
      "          -5.84545359e-02,  3.90824042e-02,  3.70086096e-02],\n",
      "         [ 4.86768410e-03,  4.54719039e-03, -1.62224416e-02, ...,\n",
      "          -2.55017504e-02,  1.88396666e-02, -6.24489179e-03],\n",
      "         [-5.31206699e-03, -1.19874987e-03, -1.11892410e-02, ...,\n",
      "           1.98805016e-02, -1.90202110e-02, -3.79090838e-04],\n",
      "         ...,\n",
      "         [-6.00387994e-03,  7.28632743e-03, -1.53944585e-02, ...,\n",
      "          -5.26854116e-03,  1.68532860e-02,  3.76290455e-03],\n",
      "         [-1.78998355e-02,  1.46924695e-02,  9.51688085e-03, ...,\n",
      "           1.07260697e-01,  2.80233864e-02, -1.89538375e-02],\n",
      "         [-3.70884268e-03,  3.08528487e-02, -5.70769282e-03, ...,\n",
      "          -3.34496573e-02, -4.65932442e-03,  1.17018344e-02]],\n",
      "\n",
      "        [[-1.01951612e-02,  1.21747078e-02,  1.11724688e-02, ...,\n",
      "           2.69737188e-02, -2.22921986e-02,  6.45900667e-02],\n",
      "         [ 1.22869862e-02,  6.45142654e-03, -3.07416776e-03, ...,\n",
      "          -1.61525756e-02, -2.23605409e-02,  1.09485257e-02],\n",
      "         [-7.09734391e-03, -5.40411752e-03, -9.43870191e-03, ...,\n",
      "          -1.52021297e-03, -2.17991360e-02, -3.77143058e-03],\n",
      "         ...,\n",
      "         [-5.21149486e-03,  1.03359867e-03, -7.52882753e-03, ...,\n",
      "          -1.92244481e-02, -6.39424520e-03,  3.69722745e-03],\n",
      "         [-1.53886806e-02, -1.34543087e-02,  5.72274020e-03, ...,\n",
      "           5.47401682e-02, -6.08180426e-02, -2.23444626e-02],\n",
      "         [-3.45917395e-03,  2.13373415e-02, -2.14421172e-02, ...,\n",
      "          -6.91150427e-02, -1.54741071e-02,  4.44306619e-02]]],\n",
      "\n",
      "\n",
      "       [[[-1.23298699e-02, -1.91225596e-02,  1.29218930e-02, ...,\n",
      "           4.33554836e-02,  1.26128104e-02, -5.96396960e-02],\n",
      "         [-1.31860480e-03, -9.51261446e-03, -1.85527243e-02, ...,\n",
      "           2.88356710e-02,  2.38556787e-02, -4.06758748e-02],\n",
      "         [-4.25214088e-03, -6.78345608e-03, -1.38743157e-02, ...,\n",
      "           2.22070217e-02,  1.34524666e-02, -2.03017425e-02],\n",
      "         ...,\n",
      "         [-7.83586409e-03, -2.57805572e-03, -1.08931847e-02, ...,\n",
      "           1.92594435e-02,  1.59353893e-02, -1.89792961e-02],\n",
      "         [-1.94495711e-02, -3.60343307e-02,  6.04022592e-02, ...,\n",
      "          -2.22710613e-02, -5.43530397e-02, -4.17403802e-02],\n",
      "         [-4.36492451e-03, -1.08945146e-02, -3.35957273e-03, ...,\n",
      "           1.72520187e-02, -1.28518986e-02, -4.72729132e-02]],\n",
      "\n",
      "        [[-1.45433825e-02, -3.68030928e-02,  3.51226889e-02, ...,\n",
      "           5.09550609e-03, -8.08145478e-02,  1.02682762e-01],\n",
      "         [ 7.81208277e-03, -1.63471382e-02, -8.99212994e-03, ...,\n",
      "          -3.65188569e-02, -8.37247167e-03, -7.34759448e-03],\n",
      "         [-1.76124368e-03, -4.82094986e-03, -1.33856600e-02, ...,\n",
      "           1.97411682e-02, -6.24130992e-03,  2.11908761e-03],\n",
      "         ...,\n",
      "         [-8.09418783e-03, -5.44183236e-03, -9.95591376e-03, ...,\n",
      "           1.03512814e-03, -1.01502263e-03,  9.89024434e-03],\n",
      "         [-2.14152560e-02, -1.22487647e-02,  4.47364189e-02, ...,\n",
      "           1.18361183e-01, -1.86819024e-02,  5.11289574e-02],\n",
      "         [-3.61343310e-03, -1.55030079e-02, -1.55327516e-02, ...,\n",
      "           2.49069761e-02, -6.95429044e-03,  1.30494153e-02]],\n",
      "\n",
      "        [[-1.17718522e-02, -2.43640933e-02,  2.16566566e-02, ...,\n",
      "           1.52593330e-01, -1.00578181e-02,  8.74510705e-02],\n",
      "         [ 1.56845041e-02, -1.70876738e-02, -1.32727087e-03, ...,\n",
      "           3.55747603e-02, -4.06013057e-02,  2.82184500e-02],\n",
      "         [-3.66246584e-03, -9.08438675e-03, -8.76258500e-03, ...,\n",
      "          -7.32058019e-04, -1.63256414e-02,  8.90959927e-04],\n",
      "         ...,\n",
      "         [-6.92374213e-03, -1.25479233e-02, -7.42880348e-03, ...,\n",
      "           3.50585720e-03, -2.07631718e-02,  1.39397075e-02],\n",
      "         [-1.86536163e-02, -9.74296406e-03, -1.49605959e-03, ...,\n",
      "          -1.41743785e-02, -1.41348932e-02,  5.55095226e-02],\n",
      "         [-1.87194371e-03, -7.81994499e-03, -1.14830295e-02, ...,\n",
      "          -5.49505465e-02, -8.39654077e-03,  3.37504521e-02]]],\n",
      "\n",
      "\n",
      "       [[[-7.51168234e-03, -1.57704763e-02,  4.40593623e-03, ...,\n",
      "           8.08628425e-02,  1.54139521e-02, -3.71525325e-02],\n",
      "         [ 3.67319165e-03, -4.84256167e-03, -9.42679588e-03, ...,\n",
      "           1.78013276e-02,  1.10012209e-02, -3.05487644e-02],\n",
      "         [-5.12040500e-03, -2.92832567e-03, -1.70742609e-02, ...,\n",
      "          -1.19602494e-03,  2.55921856e-02, -2.38123816e-02],\n",
      "         ...,\n",
      "         [-6.98121730e-03, -5.92697598e-03, -4.53395769e-03, ...,\n",
      "           1.43473689e-02,  1.32299559e-02, -1.86933577e-02],\n",
      "         [-1.64366160e-02, -2.88906470e-02,  5.16189029e-03, ...,\n",
      "           6.27482450e-03,  3.09459344e-02, -3.86791453e-02],\n",
      "         [ 7.87568372e-03,  3.53289805e-02, -8.80536530e-03, ...,\n",
      "           1.03661101e-02,  1.50152808e-02, -2.25142129e-02]],\n",
      "\n",
      "        [[-8.03535990e-03, -6.21744758e-03,  3.11630405e-02, ...,\n",
      "           1.99134022e-01, -6.17154641e-03,  1.39599340e-02],\n",
      "         [ 1.37082441e-02, -4.04076884e-03, -9.80419107e-03, ...,\n",
      "           5.20565063e-02,  6.79946598e-03, -1.67599937e-04],\n",
      "         [-2.68182647e-03,  9.37074132e-04, -1.77672971e-02, ...,\n",
      "           7.02630170e-03,  1.19604953e-02, -2.38061114e-03],\n",
      "         ...,\n",
      "         [-6.67789765e-03, -8.06673337e-03, -4.78939526e-03, ...,\n",
      "           2.99814232e-02,  3.63594829e-03,  6.42562099e-03],\n",
      "         [-2.00417619e-02, -5.05231880e-02,  2.04375144e-02, ...,\n",
      "          -9.16022658e-02, -2.39189416e-02,  5.67581393e-02],\n",
      "         [ 9.37450770e-03,  4.14647050e-02, -1.89982001e-02, ...,\n",
      "           9.74066462e-03,  2.91863047e-02, -2.41922438e-02]],\n",
      "\n",
      "        [[-7.34003959e-03,  7.00018462e-03,  1.78023316e-02, ...,\n",
      "           4.10795175e-02,  1.60309300e-02, -6.50887610e-03],\n",
      "         [ 1.98623370e-02, -4.18649800e-03, -1.23496391e-02, ...,\n",
      "          -1.08256517e-03, -6.54376950e-03,  1.12769182e-03],\n",
      "         [-4.14572377e-03, -3.37855937e-03, -1.22076506e-02, ...,\n",
      "          -1.23778330e-02,  1.39588572e-03, -7.97146652e-03],\n",
      "         ...,\n",
      "         [-5.31869614e-03, -1.09051373e-02, -5.76505670e-03, ...,\n",
      "          -1.08993258e-02, -4.60993918e-03, -3.81152914e-03],\n",
      "         [-1.69911478e-02, -3.15449387e-02,  8.09636060e-03, ...,\n",
      "          -1.06819831e-02, -2.92898342e-02,  7.60448575e-02],\n",
      "         [ 9.20531712e-03,  3.90281789e-02, -1.15968632e-02, ...,\n",
      "          -2.66397055e-02,  2.04669069e-02, -8.92718323e-03]]]],\n",
      "      dtype=float32), array([-4.5777660e-02,  6.4407811e-02, -3.1368658e-02,  8.6917542e-02,\n",
      "        1.2785070e-01,  2.4616894e-01,  1.6408961e-01,  2.3979376e-01,\n",
      "        2.2164847e-01,  1.4246197e-01,  3.3131771e-02,  1.4955571e-01,\n",
      "        1.1550413e-02, -1.8516029e-04,  2.7014315e-01,  2.4461022e-01,\n",
      "        2.7350754e-01,  2.7142024e-01,  2.7011135e-01,  2.7027962e-01,\n",
      "        2.2164130e-01,  1.8953906e-01,  3.9793090e-03,  6.1518628e-02,\n",
      "        3.6547425e-01,  2.1779412e-01,  1.4007972e-01,  2.2691796e-02,\n",
      "       -1.4714201e-02,  6.5621443e-02,  3.1406230e-01, -7.7050015e-02,\n",
      "        1.0462435e-01,  2.0993298e-01, -7.4100301e-02, -8.5880190e-02,\n",
      "        1.3652268e-01,  2.3663981e-01,  3.0105148e-02, -3.6816043e-03,\n",
      "        7.6591093e-03,  3.0664349e-01,  1.3023020e-01,  4.1607008e-03,\n",
      "        2.7055809e-01,  2.5207508e-01,  2.8904697e-01,  1.2730265e-01,\n",
      "        2.8076398e-01, -4.4764560e-02, -4.2357225e-02,  6.2559925e-02,\n",
      "        1.0018661e-01, -9.9623539e-02,  1.0176195e-01,  2.3699294e-01,\n",
      "        7.8422479e-02,  1.2831993e-01,  1.1392979e-01, -1.3174531e-02,\n",
      "       -1.0383477e-01,  2.2861110e-01,  9.1953836e-02,  6.5147914e-02,\n",
      "        1.9676815e-01,  7.1536556e-02,  2.6198325e-01, -6.4189523e-02,\n",
      "        4.9607549e-02, -6.1662562e-02,  1.3248019e-01,  9.0231813e-02,\n",
      "        1.0324936e-01,  2.2680637e-01, -3.3503436e-02, -1.7922063e-01,\n",
      "        2.0180932e-01,  5.2303892e-02,  1.7740984e-01,  2.1679863e-01,\n",
      "        1.2819616e-01,  1.6143866e-01,  1.6376132e-01,  3.5884404e-01,\n",
      "       -5.2223109e-02,  2.1117201e-01,  1.4626507e-01,  1.0392818e-01,\n",
      "        2.3689806e-01, -1.7589157e-02,  1.4187863e-01, -1.5676373e-01,\n",
      "        5.5077035e-02,  1.7919958e-01,  1.9530067e-01,  4.9757544e-02,\n",
      "        1.4647865e-01,  1.5057972e-01,  4.9321059e-02,  2.2425601e-01,\n",
      "        2.8004406e-02,  4.6344060e-02,  5.4642409e-02,  3.2176018e-01,\n",
      "       -2.3094574e-02,  5.1442902e-03,  2.2401743e-02,  1.9448744e-01,\n",
      "       -9.5472252e-03,  2.5650701e-01,  1.3772449e-01,  2.8766793e-01,\n",
      "       -9.4692776e-04, -8.9352727e-03,  7.2267972e-02,  1.9602686e-02,\n",
      "        2.5652054e-01, -3.6785334e-02,  3.2890160e-02,  2.6736060e-01,\n",
      "       -1.0560317e-01,  3.7151142e-03,  2.8068131e-01, -8.9383557e-02,\n",
      "        6.6791281e-02,  3.1667921e-01,  9.5985740e-02,  1.3152032e-01],\n",
      "      dtype=float32), array([[[[-2.30123661e-03, -5.89181297e-03,  3.96523578e-03, ...,\n",
      "           8.69934738e-04,  4.31257114e-03,  2.39815353e-03],\n",
      "         [ 6.93455897e-03,  1.77669781e-03,  1.87194608e-02, ...,\n",
      "          -3.17397565e-02, -4.21442185e-03, -1.76308881e-02],\n",
      "         [-1.27900802e-02, -6.50780788e-03, -4.10286430e-03, ...,\n",
      "           2.31482647e-03, -4.67822663e-02, -3.75668402e-03],\n",
      "         ...,\n",
      "         [-4.75286070e-04, -2.96283532e-02,  3.03538516e-02, ...,\n",
      "           1.51648500e-03, -2.71695852e-02, -1.84430566e-03],\n",
      "         [ 1.41743217e-02, -3.64480889e-04, -2.33754283e-03, ...,\n",
      "          -2.28237733e-02, -1.60014853e-02,  2.46631019e-02],\n",
      "         [ 1.18608214e-02, -2.77200472e-02, -2.48606838e-02, ...,\n",
      "           4.10957001e-02,  5.57063818e-02, -2.19316985e-02]],\n",
      "\n",
      "        [[-1.38294604e-03, -5.54690696e-03, -1.06138433e-03, ...,\n",
      "           1.82250992e-03, -3.59015947e-04,  9.99924168e-03],\n",
      "         [ 6.75601466e-03,  1.10390119e-03,  2.18637586e-02, ...,\n",
      "          -3.56409214e-02, -2.45026941e-03, -6.04407070e-03],\n",
      "         [-1.35804852e-02, -8.60609580e-03,  1.28111104e-02, ...,\n",
      "          -1.01041503e-03, -3.83789763e-02,  1.18479142e-02],\n",
      "         ...,\n",
      "         [-3.61973490e-03,  4.19556797e-02,  5.89246452e-02, ...,\n",
      "           3.10248807e-02, -1.03577944e-02, -2.23138258e-02],\n",
      "         [ 1.48718422e-02,  1.86822154e-02, -3.46057713e-02, ...,\n",
      "          -2.32062247e-02, -1.91165209e-02,  8.65985733e-03],\n",
      "         [-5.93924429e-03,  1.08361673e-02,  2.81376876e-02, ...,\n",
      "           1.17414417e-02,  8.40279087e-02, -6.45612031e-02]],\n",
      "\n",
      "        [[-9.91582056e-04,  4.55033936e-04, -9.36682150e-03, ...,\n",
      "           3.41384741e-03, -5.51316887e-03,  1.24911871e-02],\n",
      "         [ 1.07221371e-02, -3.19505017e-03,  2.47716717e-02, ...,\n",
      "          -1.63276494e-02,  8.99969228e-03, -3.90315428e-03],\n",
      "         [ 4.23295191e-03,  1.27883134e-02,  1.17508639e-02, ...,\n",
      "          -1.22649251e-02,  2.91934842e-03,  1.42700337e-02],\n",
      "         ...,\n",
      "         [ 2.98261386e-03,  4.09221351e-02,  2.68427730e-02, ...,\n",
      "           9.12894122e-03,  2.94868927e-02, -3.27900308e-03],\n",
      "         [ 8.43982119e-03, -1.85558088e-02,  1.26812793e-02, ...,\n",
      "          -9.75666288e-03,  6.52654376e-03, -5.94963925e-03],\n",
      "         [-3.94721312e-04,  6.81950822e-02,  8.70230980e-03, ...,\n",
      "           1.19850151e-02,  9.72716659e-02, -2.87150545e-03]]],\n",
      "\n",
      "\n",
      "       [[[-6.72967779e-03, -6.32101856e-03,  1.24791730e-03, ...,\n",
      "          -5.51869674e-03,  5.54611022e-03,  2.74169119e-03],\n",
      "         [-1.90283672e-03,  2.39737774e-03,  7.45097920e-03, ...,\n",
      "          -6.27250373e-02, -1.16790943e-02,  1.36177419e-02],\n",
      "         [-2.43349690e-02, -9.58706811e-03,  5.12539688e-03, ...,\n",
      "           2.03479634e-04, -5.18149063e-02, -1.06236124e-02],\n",
      "         ...,\n",
      "         [-8.23690323e-04, -4.52437773e-02,  4.49064933e-02, ...,\n",
      "          -1.48973670e-02, -3.74213159e-02, -2.50751078e-02],\n",
      "         [ 1.20533947e-02, -4.14178381e-03, -2.23253462e-02, ...,\n",
      "          -8.56044441e-02, -2.15003770e-02,  5.37014790e-02],\n",
      "         [ 1.72066651e-02, -2.44826339e-02, -1.10037383e-02, ...,\n",
      "           4.80076745e-02,  3.21536772e-02, -2.96083037e-02]],\n",
      "\n",
      "        [[-4.56147827e-03, -4.65280237e-03, -8.31684005e-03, ...,\n",
      "          -5.54831931e-03,  1.18862418e-03,  9.64665227e-03],\n",
      "         [ 2.62077316e-03,  5.77449473e-03,  1.19720455e-02, ...,\n",
      "          -6.83966503e-02,  1.35026115e-03,  5.91752259e-03],\n",
      "         [-2.97386330e-02, -3.90352937e-03,  1.28964186e-02, ...,\n",
      "           6.27378060e-04, -4.46732230e-02,  1.30419582e-02],\n",
      "         ...,\n",
      "         [-2.97931256e-03,  7.04262778e-02,  4.67705168e-02, ...,\n",
      "          -2.63439678e-02, -2.75591165e-02, -3.54478620e-02],\n",
      "         [ 9.99665074e-03,  1.62281040e-02,  8.01674929e-03, ...,\n",
      "          -7.52160326e-02, -1.95330698e-02,  7.38804974e-03],\n",
      "         [ 9.53063485e-04,  5.06784841e-02,  2.04059742e-02, ...,\n",
      "           4.51842928e-03,  4.47761454e-02, -7.42928088e-02]],\n",
      "\n",
      "        [[-2.81608710e-03, -3.68988403e-04, -9.52884182e-03, ...,\n",
      "          -1.62106077e-03, -4.23267297e-03,  1.35960653e-02],\n",
      "         [ 7.26349046e-03,  3.17442766e-03,  2.06175316e-02, ...,\n",
      "          -3.99732366e-02,  2.22933367e-02, -7.41374539e-03],\n",
      "         [-1.37994336e-02,  2.29467135e-02, -6.29038131e-03, ...,\n",
      "          -5.79428207e-03, -1.50836250e-02,  1.31318215e-02],\n",
      "         ...,\n",
      "         [ 2.00410513e-03,  3.91520634e-02, -3.18683162e-02, ...,\n",
      "          -3.54397879e-03, -8.54784995e-03,  1.36236998e-03],\n",
      "         [ 5.49011305e-03, -1.51369004e-02,  2.77213678e-02, ...,\n",
      "          -2.81145964e-02,  9.72870039e-04, -6.28185738e-03],\n",
      "         [ 7.10674515e-03,  8.02865252e-02,  6.19208254e-03, ...,\n",
      "           1.03570186e-02,  7.63423666e-02, -7.15952739e-03]]],\n",
      "\n",
      "\n",
      "       [[[-1.08065400e-02, -7.45501043e-03, -5.10151871e-03, ...,\n",
      "          -4.49332688e-03,  7.89736584e-03, -3.35464210e-05],\n",
      "         [-6.12053089e-03, -1.79325249e-02, -1.11700445e-02, ...,\n",
      "          -4.62095961e-02, -4.28734301e-03,  2.02734675e-03],\n",
      "         [-2.64673289e-02, -1.31910611e-02,  1.76633168e-02, ...,\n",
      "          -6.08402630e-03, -3.14402916e-02, -1.81844179e-02],\n",
      "         ...,\n",
      "         [ 1.37444083e-02, -2.84396205e-02,  1.88047513e-02, ...,\n",
      "          -1.93887874e-02, -3.75849679e-02, -2.45505963e-02],\n",
      "         [ 7.21093081e-03, -1.23673957e-02, -5.60066104e-03, ...,\n",
      "          -4.09601741e-02, -1.16450675e-02,  3.63268666e-02],\n",
      "         [ 1.34990485e-02, -1.55054999e-03,  5.54364361e-03, ...,\n",
      "           3.92058305e-02,  2.16900297e-02, -1.13665536e-02]],\n",
      "\n",
      "        [[-8.32169224e-03, -6.18967554e-03, -1.13438964e-02, ...,\n",
      "          -3.40542640e-03,  3.85991205e-03,  7.26305228e-03],\n",
      "         [-2.55200220e-03, -1.41635584e-02, -3.80055211e-03, ...,\n",
      "          -5.45916855e-02,  2.17752811e-03, -5.23553835e-03],\n",
      "         [-3.21345851e-02, -2.83276942e-03, -2.20403913e-03, ...,\n",
      "          -1.67740230e-02, -3.22663859e-02,  2.23135133e-03],\n",
      "         ...,\n",
      "         [ 3.27714277e-03,  8.55310634e-02, -2.84323972e-02, ...,\n",
      "           2.72681676e-02, -3.39798741e-02, -1.60314962e-02],\n",
      "         [ 3.99958156e-03,  1.23148263e-02,  3.01949140e-02, ...,\n",
      "          -5.21975756e-02, -1.14355180e-02, -7.70385157e-07],\n",
      "         [-1.03606293e-02,  7.14352727e-02,  1.61257926e-02, ...,\n",
      "          -1.47721104e-04,  9.00403503e-03, -3.94313596e-02]],\n",
      "\n",
      "        [[-5.75947622e-03,  4.07667161e-04, -5.18753566e-03, ...,\n",
      "           8.14088504e-04, -4.34151705e-04,  1.14657767e-02],\n",
      "         [ 4.41048900e-03, -3.57159856e-03,  3.01857502e-03, ...,\n",
      "          -3.98184508e-02,  1.49278138e-02, -8.20163079e-03],\n",
      "         [-2.44483184e-02,  2.32945569e-02, -2.34904625e-02, ...,\n",
      "          -1.79554094e-02, -3.21781076e-02,  1.07798241e-02],\n",
      "         ...,\n",
      "         [ 5.12963720e-03,  2.35215593e-02, -3.53378877e-02, ...,\n",
      "           3.48278917e-02, -2.01826524e-02,  2.35197158e-03],\n",
      "         [ 3.45730968e-03, -1.26461498e-02,  1.03930170e-02, ...,\n",
      "          -3.20292413e-02, -6.37839548e-04, -7.48459855e-03],\n",
      "         [ 3.67492763e-03,  6.75461590e-02,  9.46969260e-03, ...,\n",
      "           4.72220499e-03,  4.39464301e-02,  6.21765293e-03]]]],\n",
      "      dtype=float32), array([-0.06418542, -0.11568324, -0.13206749,  0.0608536 ,  0.2689488 ,\n",
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      "        0.1316739 , -0.01181007, -0.27968737, -0.01710657,  0.14509922,\n",
      "       -0.2100034 ,  0.09921633, -0.01273028, -0.10428324,  0.11836739,\n",
      "       -0.21125603, -0.22762309,  0.44482312,  0.04079875, -0.30996218,\n",
      "       -0.03813913, -0.2617242 ,  0.04896495,  0.14684829, -0.09759409,\n",
      "       -0.16100882, -0.08115347,  0.2567695 ,  0.09040406,  0.03538936,\n",
      "        0.23496653, -0.59533477,  0.280156  ,  0.02269722,  0.15407647,\n",
      "        0.10761564,  0.15549968, -0.27726585,  0.14555272, -0.07341251,\n",
      "        0.0086478 , -0.08294716,  0.16158143, -0.17374775, -0.00751741,\n",
      "       -0.2599541 ,  0.0932769 ,  0.35911047, -0.09218857,  0.08189061,\n",
      "       -0.24053718, -0.12922512, -0.01862046, -0.11662732, -0.11673097,\n",
      "       -0.1816601 ,  0.16486758, -0.04786587, -0.04397993,  0.14281501,\n",
      "        0.26927033,  0.3568714 ,  0.03537106, -0.17966093,  0.04918984,\n",
      "        0.63375777, -0.20748404, -0.06041681,  0.12094544, -0.08843092,\n",
      "       -0.30141872,  0.28632042,  0.10882995,  0.14509913, -0.04585594,\n",
      "       -0.08846492,  0.13556598,  0.16782367,  0.07018866, -0.10737082,\n",
      "        0.44746682, -0.08115204, -0.04683498,  0.18236732, -0.01913908,\n",
      "       -0.0207867 ,  0.37967235,  0.07472062, -0.09300313,  0.3070309 ,\n",
      "        0.01550341,  0.15720516, -0.18576111,  0.07595339, -0.28695267,\n",
      "        0.20711343, -0.22942008,  0.17479539,  0.2029741 , -0.44217134,\n",
      "        0.04695964, -0.14719886, -0.02473967,  0.14871362,  0.00526441,\n",
      "        0.00490166, -0.17585608, -0.00920897, -0.25866592, -0.01254782,\n",
      "        0.04957367,  0.173761  , -0.01913427, -0.1067858 ,  0.01878852,\n",
      "       -0.08317517,  0.06669547,  0.01067064,  0.37834755,  0.11717828,\n",
      "        0.20528455,  0.2403423 ,  0.27507326], dtype=float32), array([[[[ 2.48631509e-03,  3.29096033e-03, -3.13071609e-02, ...,\n",
      "           4.71851649e-03,  6.10046380e-04,  1.08059337e-02],\n",
      "         [ 1.36040282e-02,  3.80906137e-03, -3.50438058e-02, ...,\n",
      "           8.50365497e-03,  4.99894470e-03,  2.45373725e-04],\n",
      "         [-1.02960337e-02,  1.11045251e-02, -1.05560301e-02, ...,\n",
      "           1.18119251e-02,  4.14630165e-03,  1.04994141e-02],\n",
      "         ...,\n",
      "         [ 2.14050314e-03,  2.17348989e-03, -4.09283377e-02, ...,\n",
      "          -8.34189355e-03,  2.35738587e-02, -1.85471829e-02],\n",
      "         [ 1.61261633e-02,  8.04742594e-05, -3.95269990e-02, ...,\n",
      "          -3.94453527e-03,  8.42030905e-03, -6.98040065e-04],\n",
      "         [-3.51465750e-03,  1.08316056e-02, -2.23830044e-02, ...,\n",
      "           1.92155335e-02,  4.21972945e-03, -1.55707300e-02]],\n",
      "\n",
      "        [[ 6.11093594e-03,  5.44822821e-03,  1.57541838e-02, ...,\n",
      "           5.60781872e-03,  1.93978904e-03,  1.49202365e-02],\n",
      "         [-3.13426033e-02,  1.45718846e-02,  1.18744513e-02, ...,\n",
      "           1.21863568e-02,  1.49443159e-02,  2.60730181e-03],\n",
      "         [-2.32275911e-02,  2.08911151e-02,  1.11537259e-02, ...,\n",
      "           2.36150771e-02,  1.06090466e-02,  4.31246823e-03],\n",
      "         ...,\n",
      "         [ 2.83093913e-03,  5.63543057e-03,  1.72611587e-02, ...,\n",
      "          -2.76210159e-03,  3.27554196e-02, -1.73731633e-02],\n",
      "         [ 4.87203449e-02,  1.24137765e-02,  3.64911221e-02, ...,\n",
      "           9.30428132e-03,  5.34809241e-03,  6.80550281e-03],\n",
      "         [-2.03473382e-02,  1.38210657e-03, -2.35674269e-02, ...,\n",
      "           3.24176252e-02,  2.19412390e-02, -3.02630980e-02]],\n",
      "\n",
      "        [[ 1.05408970e-02,  7.44795799e-03, -3.36561389e-02, ...,\n",
      "           2.62853602e-04, -6.13683043e-03,  1.33312661e-02],\n",
      "         [-3.32584940e-02,  1.55691411e-02, -2.89147953e-04, ...,\n",
      "          -3.60562908e-03,  1.49507467e-02,  7.65243312e-03],\n",
      "         [ 3.94205609e-03,  1.48937441e-02, -1.59246754e-02, ...,\n",
      "           1.39236227e-02,  3.22588254e-03,  6.02472946e-03],\n",
      "         ...,\n",
      "         [ 9.61219659e-04, -2.27980153e-03, -4.54332307e-02, ...,\n",
      "          -8.10870901e-03,  3.84118455e-03, -1.65238492e-02],\n",
      "         [ 2.77294349e-02,  1.70650017e-02,  2.01114286e-02, ...,\n",
      "           8.16452038e-03,  4.37149359e-03,  8.13044887e-03],\n",
      "         [-1.77335721e-02,  1.02985008e-02, -3.90648767e-02, ...,\n",
      "           2.65211053e-02,  1.88891459e-02, -1.68677885e-02]]],\n",
      "\n",
      "\n",
      "       [[[ 4.49297950e-03, -3.98075627e-03,  1.72210410e-02, ...,\n",
      "           8.42886325e-03, -1.04969469e-04,  5.74578904e-03],\n",
      "         [-4.00591874e-03, -2.41769738e-02, -1.10928714e-02, ...,\n",
      "          -1.52679645e-02,  6.81134174e-03, -3.05488333e-03],\n",
      "         [-1.56376939e-02, -5.00010047e-03,  4.81709233e-03, ...,\n",
      "           5.51846065e-03,  4.62341262e-03,  5.28823584e-03],\n",
      "         ...,\n",
      "         [ 3.78267164e-03, -7.20065041e-03,  2.24571675e-02, ...,\n",
      "           1.21734152e-02,  1.66180804e-02, -2.85227131e-02],\n",
      "         [ 3.54970875e-03, -7.91174546e-03,  6.50567329e-03, ...,\n",
      "           5.75853884e-03, -5.25432348e-04, -3.29109584e-03],\n",
      "         [ 2.42216233e-03, -1.42111657e-02,  3.40532698e-02, ...,\n",
      "          -8.09886493e-03,  6.40509045e-03, -2.32355390e-02]],\n",
      "\n",
      "        [[ 6.58771209e-03, -3.84311262e-03,  6.62338808e-02, ...,\n",
      "           5.46263764e-03,  2.69173388e-03,  9.38945077e-03],\n",
      "         [-5.54355457e-02, -2.00809669e-02,  3.39177996e-02, ...,\n",
      "          -2.65794396e-02,  7.77757354e-03,  1.45330857e-02],\n",
      "         [-5.56085445e-03, -1.38856005e-02,  3.95981222e-02, ...,\n",
      "          -7.25830847e-04,  4.43886919e-03,  2.62149167e-03],\n",
      "         ...,\n",
      "         [ 2.70528113e-03, -5.45389997e-03,  8.94473717e-02, ...,\n",
      "           2.45114118e-02,  5.10585234e-02, -3.43545228e-02],\n",
      "         [ 5.07756323e-02,  1.51661120e-03,  8.18592831e-02, ...,\n",
      "           2.16385573e-02,  1.26126707e-02,  1.81507389e-03],\n",
      "         [-2.27336828e-02, -3.00953630e-02,  3.85253243e-02, ...,\n",
      "          -9.51036997e-03,  8.18072818e-03, -3.70927304e-02]],\n",
      "\n",
      "        [[ 5.95341111e-03,  8.94323515e-04,  1.05835460e-02, ...,\n",
      "           4.89834580e-04,  5.24436589e-04,  9.38476902e-03],\n",
      "         [-4.07811590e-02,  4.78578452e-03,  1.44789219e-02, ...,\n",
      "          -5.62724238e-03, -4.85808152e-04,  1.29066659e-02],\n",
      "         [ 1.34129170e-02, -1.18021872e-02,  4.19147732e-03, ...,\n",
      "          -8.13282002e-03, -4.46207495e-03,  8.42996407e-03],\n",
      "         ...,\n",
      "         [ 1.52341533e-03, -6.47965074e-03,  1.00679537e-02, ...,\n",
      "           1.56302936e-02,  3.72295864e-02, -3.21733207e-02],\n",
      "         [ 3.96381617e-02,  1.58769619e-02,  3.92291285e-02, ...,\n",
      "           1.72687024e-02,  2.41979603e-02,  5.91078307e-03],\n",
      "         [-1.79783162e-02, -2.94427648e-02,  1.28269298e-02, ...,\n",
      "          -1.60066597e-02, -5.16920770e-03, -2.00248957e-02]]],\n",
      "\n",
      "\n",
      "       [[[ 4.85232845e-03, -2.46043317e-03, -9.62745398e-03, ...,\n",
      "           1.07441526e-02, -2.84585054e-03, -1.90984423e-03],\n",
      "         [-1.19528649e-02, -1.80358142e-02, -3.36395353e-02, ...,\n",
      "          -1.47682996e-02,  1.02861486e-02, -3.36993136e-03],\n",
      "         [ 4.98365518e-03, -1.66885350e-02, -1.20581677e-02, ...,\n",
      "          -1.59126818e-02,  1.31858326e-02,  2.94562749e-04],\n",
      "         ...,\n",
      "         [-5.69525547e-03, -1.74089391e-02, -3.64525653e-02, ...,\n",
      "           7.06359418e-03, -1.58607736e-02, -2.61105206e-02],\n",
      "         [-3.87686165e-03, -2.40983404e-02, -5.60978092e-02, ...,\n",
      "          -1.22877983e-02, -3.04629817e-03, -1.03539054e-03],\n",
      "         [ 1.35685736e-02, -2.09947508e-02, -1.52395582e-02, ...,\n",
      "          -2.87993886e-02,  1.74087044e-02, -1.86969731e-02]],\n",
      "\n",
      "        [[ 1.45290594e-03, -6.42601680e-03,  1.14819771e-02, ...,\n",
      "           1.17859095e-02,  8.51634599e-04, -2.82667065e-03],\n",
      "         [-2.43061744e-02, -1.82640739e-02,  1.50347399e-02, ...,\n",
      "          -2.63812207e-02,  2.30616182e-02,  4.71212249e-03],\n",
      "         [ 1.60123650e-02, -1.25727728e-02,  1.22705530e-02, ...,\n",
      "          -1.90321188e-02,  1.43274162e-02, -9.16460936e-04],\n",
      "         ...,\n",
      "         [ 2.31739320e-03, -1.62090212e-02,  1.71782896e-02, ...,\n",
      "           1.23864021e-02,  7.53226131e-03, -2.98976954e-02],\n",
      "         [ 1.98312830e-02, -1.12192128e-02,  1.70756541e-02, ...,\n",
      "          -1.62761565e-02, -2.72694766e-03, -1.83170743e-03],\n",
      "         [-3.89542966e-03, -3.53942066e-02, -1.64013300e-02, ...,\n",
      "          -4.73240092e-02,  1.97671168e-02, -2.87492648e-02]],\n",
      "\n",
      "        [[ 1.00636412e-03, -5.19909943e-03, -3.75667326e-02, ...,\n",
      "           7.44984252e-03,  4.31809276e-05, -3.22302600e-04],\n",
      "         [-1.04536200e-02, -9.70086199e-04,  1.94423497e-02, ...,\n",
      "          -1.29293650e-04,  9.82195791e-03, -1.07756234e-03],\n",
      "         [ 5.58500132e-03, -1.86028529e-03, -8.09577946e-03, ...,\n",
      "          -6.18272461e-03,  1.71643522e-04,  7.06695300e-03],\n",
      "         ...,\n",
      "         [-3.72283580e-03, -1.86357144e-02, -4.54351157e-02, ...,\n",
      "           1.30783571e-02,  3.22722102e-04, -3.35289426e-02],\n",
      "         [ 1.59978885e-02,  8.11644178e-03, -1.23626338e-02, ...,\n",
      "           2.87816068e-03,  2.04773736e-03, -6.40190148e-04],\n",
      "         [-4.09534993e-03, -3.75131555e-02, -3.33721489e-02, ...,\n",
      "          -4.82492335e-02,  3.41874664e-03, -1.31510263e-02]]]],\n",
      "      dtype=float32), array([-7.43588656e-02, -7.82142300e-03,  1.99858069e-01,  5.86250983e-02,\n",
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      "       -9.05257389e-02, -1.03295766e-01, -3.65283228e-02, -5.99550568e-02,\n",
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      "       -8.14075861e-03, -3.03441286e-02, -2.73723528e-03,  1.04369465e-02,\n",
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      "       -2.94738077e-02,  9.18932706e-02, -3.09058055e-02,  2.83562243e-02,\n",
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      "       -2.41919458e-02, -6.04458451e-02,  5.60694151e-02,  3.48671922e-03,\n",
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      "       -9.42966118e-02, -9.68727842e-03, -1.33719174e-02,  1.70798182e-01,\n",
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      "       -6.21608971e-03,  3.39489020e-02, -1.58346687e-02,  6.97900355e-02,\n",
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      "       -4.93083969e-02, -9.13676899e-03,  7.50048086e-02,  1.19404271e-01,\n",
      "        4.21564467e-02, -3.56978104e-02,  6.22963049e-02, -5.56988753e-02,\n",
      "       -8.98351986e-03,  4.67670858e-02,  1.15553811e-01,  1.54885754e-03,\n",
      "       -6.53147623e-02, -2.76188087e-03, -2.88737379e-02,  3.49496126e-01,\n",
      "        1.32759318e-01,  7.41247907e-02,  9.06468648e-03,  8.58006533e-04,\n",
      "        2.35754419e-02, -3.43079567e-02,  5.42532057e-02,  3.14495265e-02,\n",
      "        3.93943256e-03,  6.62599280e-02,  8.03745165e-02, -2.91163549e-02,\n",
      "       -1.98691040e-02,  5.25035225e-02, -4.46449406e-02, -2.78639924e-02],\n",
      "      dtype=float32), array([[[[-1.03266295e-02, -2.57659331e-03,  2.39167653e-04, ...,\n",
      "          -1.18998659e-03, -9.75547917e-03, -2.47324049e-03],\n",
      "         [-9.87034664e-03, -1.88852882e-03,  2.75667437e-04, ...,\n",
      "          -9.98693518e-03, -5.98258805e-03,  4.40906314e-03],\n",
      "         [ 1.61835626e-02, -9.38057806e-03, -6.73405966e-03, ...,\n",
      "          -2.42401171e-03,  1.09589035e-02,  1.39167206e-02],\n",
      "         ...,\n",
      "         [-1.40176648e-02, -3.08811688e-03,  3.41502228e-03, ...,\n",
      "           5.33248903e-03, -1.70355793e-02, -1.36359241e-02],\n",
      "         [ 1.74193655e-03, -9.95234400e-03, -4.35903465e-04, ...,\n",
      "          -2.41840957e-03, -1.68555733e-02,  1.05463974e-02],\n",
      "         [-4.77309758e-03, -6.66776532e-03,  5.07126655e-03, ...,\n",
      "          -1.20526762e-03,  3.55557725e-03,  1.17330160e-03]],\n",
      "\n",
      "        [[-6.64285664e-03, -3.47881275e-03,  2.39190087e-03, ...,\n",
      "          -7.53906369e-03, -5.72045427e-03, -9.24838521e-03],\n",
      "         [-2.97287968e-03,  3.34521150e-03, -3.18630366e-03, ...,\n",
      "          -1.15623679e-02, -7.90791214e-03,  5.92658529e-03],\n",
      "         [ 2.53777411e-02,  2.53286422e-03,  2.17707790e-02, ...,\n",
      "           2.15302818e-02,  1.67279467e-02,  2.45583057e-02],\n",
      "         ...,\n",
      "         [-7.73527799e-03,  6.76160492e-03, -1.16094667e-03, ...,\n",
      "           4.41490719e-03, -1.44865643e-02, -1.29020950e-02],\n",
      "         [ 1.03217484e-02, -7.36614782e-03, -5.86766237e-03, ...,\n",
      "          -4.04950976e-03, -1.98591519e-02,  1.01560345e-02],\n",
      "         [-1.55079812e-02,  1.91596281e-02,  2.70862889e-04, ...,\n",
      "          -6.27748622e-03,  4.34006471e-03,  1.73485430e-04]],\n",
      "\n",
      "        [[ 4.12674667e-03, -4.57745697e-03,  6.64306013e-03, ...,\n",
      "          -2.34278967e-03, -9.18853935e-03, -1.25898141e-03],\n",
      "         [-3.07818851e-03,  7.09499512e-03, -1.60038937e-03, ...,\n",
      "          -6.78885821e-03, -1.09325945e-02,  7.65817193e-03],\n",
      "         [ 2.55893916e-02, -1.47064438e-03,  9.20196623e-03, ...,\n",
      "          -5.94317727e-03,  2.50070821e-03,  6.69544796e-03],\n",
      "         ...,\n",
      "         [-9.56582557e-03,  7.91247934e-03, -5.33100963e-03, ...,\n",
      "           4.76566935e-03, -1.49843339e-02, -6.69805566e-03],\n",
      "         [ 1.19609423e-02, -3.48291663e-03,  1.67369528e-03, ...,\n",
      "           8.51548160e-04, -1.82969198e-02,  8.18597153e-03],\n",
      "         [-1.66008994e-02,  1.42412046e-02, -3.94398719e-03, ...,\n",
      "          -3.43332323e-03,  2.92040431e-03,  3.60240089e-03]]],\n",
      "\n",
      "\n",
      "       [[[-1.50715457e-02,  3.58128431e-03,  1.96502986e-03, ...,\n",
      "           1.93002622e-03,  1.64739266e-02, -1.30437613e-02],\n",
      "         [-1.05031207e-02, -1.34232629e-03,  8.39629397e-03, ...,\n",
      "          -6.13174262e-03, -7.77114695e-03, -7.34500634e-03],\n",
      "         [ 1.59280524e-02, -4.93563304e-04,  2.06456911e-02, ...,\n",
      "           3.44217420e-02,  2.81744432e-02,  4.31641713e-02],\n",
      "         ...,\n",
      "         [-2.63509643e-03, -1.55394357e-02,  1.79553684e-02, ...,\n",
      "           5.62341791e-03,  7.54640112e-03, -1.32122431e-02],\n",
      "         [-8.40738416e-03, -1.08226598e-03, -8.15254636e-03, ...,\n",
      "           7.50581920e-03, -2.10973900e-02,  4.46510874e-03],\n",
      "         [ 3.56538873e-03, -1.49670860e-03,  3.90027976e-03, ...,\n",
      "           2.24968046e-03, -1.23405561e-03, -5.28686540e-03]],\n",
      "\n",
      "        [[-1.69400852e-02,  2.77157854e-02, -1.96665525e-03, ...,\n",
      "          -1.36413379e-02,  1.78107675e-02, -1.66987181e-02],\n",
      "         [-7.62252975e-03,  2.68657506e-03,  5.14760846e-03, ...,\n",
      "          -1.13447458e-02, -9.81413107e-03, -6.15228107e-03],\n",
      "         [ 2.45921463e-02,  1.22981239e-02,  4.96367253e-02, ...,\n",
      "           5.45314848e-02,  3.91974635e-02,  5.24803512e-02],\n",
      "         ...,\n",
      "         [ 4.61020367e-03, -1.76493190e-02,  1.43087450e-02, ...,\n",
      "           5.83570963e-03,  8.79333634e-03, -1.14443125e-02],\n",
      "         [ 6.86999364e-03, -9.89954080e-03, -1.38055198e-02, ...,\n",
      "           3.88898421e-03, -2.33089775e-02,  5.92778437e-03],\n",
      "         [-1.12817856e-02,  2.83943769e-02,  8.38675944e-04, ...,\n",
      "          -4.76626121e-03, -4.87527344e-03, -6.83464762e-03]],\n",
      "\n",
      "        [[-6.74894638e-03,  4.08497546e-03,  1.99278723e-03, ...,\n",
      "          -1.32070435e-02,  6.80110930e-03, -1.38106188e-02],\n",
      "         [-5.74127119e-03,  3.86035186e-03, -2.07123021e-03, ...,\n",
      "          -1.55830057e-02, -9.33692232e-03, -3.36189335e-03],\n",
      "         [ 2.10623369e-02,  6.44711405e-03,  3.90940160e-02, ...,\n",
      "           2.81947572e-02,  2.81029381e-02,  2.58975681e-02],\n",
      "         ...,\n",
      "         [ 2.77161086e-03, -9.33946855e-03, -3.96435941e-03, ...,\n",
      "           3.31284921e-03,  4.68998821e-03, -8.24241433e-03],\n",
      "         [ 9.93933622e-03, -1.26227587e-02, -5.30784763e-03, ...,\n",
      "           3.16704577e-03, -2.50813738e-02,  6.99498504e-03],\n",
      "         [-1.09259533e-02,  2.50802208e-02, -4.98637464e-03, ...,\n",
      "          -5.42974379e-03, -2.79875263e-03, -1.12388714e-03]]],\n",
      "\n",
      "\n",
      "       [[[-1.05695715e-02, -6.65004551e-03,  1.14270793e-02, ...,\n",
      "           1.13982856e-02,  2.48910710e-02, -2.01158524e-02],\n",
      "         [ 3.46275163e-03,  5.79921063e-03, -1.63540186e-03, ...,\n",
      "          -6.75595738e-03, -5.29716769e-03, -1.25067402e-02],\n",
      "         [-4.70241671e-03, -3.87823209e-03,  2.08221911e-03, ...,\n",
      "           3.55734415e-02,  1.33386767e-02,  4.47410196e-02],\n",
      "         ...,\n",
      "         [ 1.49224093e-02, -1.12200771e-02,  1.46477595e-02, ...,\n",
      "           7.56622152e-03,  3.02859787e-02, -3.93884303e-03],\n",
      "         [-5.07909758e-03,  1.31783877e-02, -1.02952961e-02, ...,\n",
      "           7.72063248e-03, -2.13399660e-02,  2.11469270e-03],\n",
      "         [ 1.11438399e-02, -1.19275544e-02,  3.20557575e-03, ...,\n",
      "           3.00401030e-03, -1.19526843e-02, -8.13317019e-03]],\n",
      "\n",
      "        [[-1.70508623e-02,  8.58010631e-03, -1.14486006e-03, ...,\n",
      "          -5.15660597e-03,  1.45966867e-02, -2.28679758e-02],\n",
      "         [-3.17657227e-03,  5.48885623e-03, -6.66785199e-05, ...,\n",
      "          -9.54495370e-03, -5.38741006e-03, -1.21885082e-02],\n",
      "         [ 1.06314057e-02,  3.72430380e-03,  2.05148254e-02, ...,\n",
      "           4.78186421e-02,  2.96977889e-02,  5.15434667e-02],\n",
      "         ...,\n",
      "         [ 3.04241665e-02, -1.32622952e-02,  8.83379206e-03, ...,\n",
      "           1.04780542e-03,  2.52286401e-02, -4.45278827e-03],\n",
      "         [-1.25949143e-03,  3.22387321e-03, -2.05024239e-02, ...,\n",
      "           5.14487643e-03, -2.70085242e-02,  2.27415795e-03],\n",
      "         [ 3.74635536e-04,  1.97586371e-03, -2.43942440e-03, ...,\n",
      "          -5.21882903e-03, -1.60979982e-02, -1.23087317e-02]],\n",
      "\n",
      "        [[-1.17229745e-02, -4.97850310e-03, -1.49952564e-02, ...,\n",
      "          -2.01662164e-02, -6.41265698e-03, -1.63828563e-02],\n",
      "         [-4.89720202e-04,  3.05005093e-03, -2.13698624e-03, ...,\n",
      "          -1.25116957e-02, -7.37623428e-04, -9.91498586e-03],\n",
      "         [ 3.77920503e-03,  4.25475789e-03,  4.48718248e-03, ...,\n",
      "           1.36323832e-02,  2.40158159e-02,  2.37192456e-02],\n",
      "         ...,\n",
      "         [ 2.55739931e-02, -8.89623910e-03, -4.37693624e-03, ...,\n",
      "          -1.07840088e-03,  1.47468811e-02, -7.86467455e-03],\n",
      "         [-2.09070556e-03, -6.24532858e-03, -2.55214944e-02, ...,\n",
      "          -1.60773040e-03, -2.46536992e-02,  2.47029914e-03],\n",
      "         [-9.88541869e-04,  3.25043732e-03, -7.95861613e-03, ...,\n",
      "          -6.07489794e-03, -1.01532796e-02, -7.52132060e-03]]]],\n",
      "      dtype=float32), array([ 1.96750183e-02, -1.37529126e-03,  9.24313217e-02,  1.27414614e-01,\n",
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      "       -8.83346796e-03,  7.88244158e-02,  9.81942266e-02,  1.63116872e-01],\n",
      "      dtype=float32), array([[[[ 2.49182852e-03, -8.25067237e-03, -1.34461222e-03, ...,\n",
      "           8.61167070e-03, -3.73780821e-03,  6.45499909e-04],\n",
      "         [-4.42567188e-03, -1.88350787e-05, -1.74789131e-02, ...,\n",
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      "         [-1.45422723e-02,  6.53489307e-03,  4.29056808e-02, ...,\n",
      "           2.32872367e-03, -8.22560862e-03, -1.34951407e-02],\n",
      "         ...,\n",
      "         [ 8.14430788e-03,  4.64800792e-03,  1.78648401e-02, ...,\n",
      "           1.30022259e-03, -1.02303829e-02, -8.59441701e-03],\n",
      "         [-1.25717523e-03, -4.16684226e-04, -5.34598716e-03, ...,\n",
      "          -1.43156825e-02, -5.26516093e-03, -1.92927010e-03],\n",
      "         [ 7.58334296e-03,  3.03687761e-04,  1.76798610e-03, ...,\n",
      "          -6.30416349e-03,  5.41360758e-04, -2.08757468e-03]],\n",
      "\n",
      "        [[ 5.62601024e-04, -1.57458056e-02, -1.89978105e-03, ...,\n",
      "           3.74664553e-03, -7.80931325e-04,  7.86909834e-03],\n",
      "         [-9.07994434e-03, -1.88095204e-03, -1.08374842e-02, ...,\n",
      "           3.25201056e-03, -8.60407297e-03, -1.06352521e-02],\n",
      "         [-1.02429595e-02,  8.97591282e-03,  2.03796718e-02, ...,\n",
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      "         ...,\n",
      "         [ 2.76015643e-02,  3.51342745e-02,  1.60577446e-02, ...,\n",
      "          -3.92214302e-03, -3.94038716e-03, -1.28798457e-02],\n",
      "         [-9.14710574e-03,  7.83217512e-03, -1.45204505e-03, ...,\n",
      "          -2.50025140e-03,  4.37620515e-03, -2.92862463e-03],\n",
      "         [ 1.53262382e-02,  3.19609744e-03, -3.10626184e-03, ...,\n",
      "          -1.26120343e-03,  1.93217583e-03, -4.34497744e-03]],\n",
      "\n",
      "        [[ 1.19078634e-02,  1.22632412e-02,  1.10837901e-02, ...,\n",
      "          -7.12652551e-03, -4.51076403e-03, -1.80176343e-04],\n",
      "         [ 1.09123939e-04, -2.57430226e-03,  5.92016324e-04, ...,\n",
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      "         [-3.65449372e-03, -5.48841013e-03,  2.82002846e-03, ...,\n",
      "          -9.52219777e-03,  1.63100380e-03, -9.41131264e-03],\n",
      "         ...,\n",
      "         [ 2.27532778e-02,  2.56275944e-02,  1.38883954e-02, ...,\n",
      "          -3.09439981e-03,  8.96250270e-03, -1.08324187e-02],\n",
      "         [-1.14783114e-02, -4.79689304e-04, -5.75645873e-03, ...,\n",
      "           5.71634853e-03,  1.44765461e-02, -3.67933162e-03],\n",
      "         [ 1.40898814e-02, -3.01762018e-03, -1.16279358e-02, ...,\n",
      "          -3.89153371e-03,  4.75310662e-04, -1.12566911e-02]]],\n",
      "\n",
      "\n",
      "       [[[-9.41542629e-03, -9.80154704e-03, -3.69167840e-03, ...,\n",
      "           8.45058262e-03, -1.11409568e-03,  1.57259796e-02],\n",
      "         [-2.05228683e-02,  3.40567291e-04, -1.74381770e-02, ...,\n",
      "          -1.73003264e-02, -4.24027769e-03, -1.03721013e-02],\n",
      "         [-8.17882922e-03,  4.71192319e-03,  5.10138553e-03, ...,\n",
      "           2.30808929e-03, -3.67084774e-03, -6.74672890e-03],\n",
      "         ...,\n",
      "         [ 8.09922162e-03, -6.36649085e-03,  7.09572807e-03, ...,\n",
      "           1.55610824e-02, -4.00183955e-03,  8.52918660e-04],\n",
      "         [ 9.46240834e-06, -4.80348710e-03,  6.38567237e-03, ...,\n",
      "          -1.66918933e-02,  7.42614502e-03, -5.22509357e-03],\n",
      "         [ 6.23346865e-03, -8.45635124e-03,  1.28625380e-02, ...,\n",
      "           7.55864847e-03,  3.60822654e-03,  1.02037117e-02]],\n",
      "\n",
      "        [[-9.66143794e-03, -1.66031346e-02, -3.75456340e-03, ...,\n",
      "           3.77679267e-03,  8.85611749e-04,  3.90423387e-02],\n",
      "         [-2.29902640e-02, -5.48137818e-04,  6.26104232e-03, ...,\n",
      "           3.09622195e-03, -1.12797739e-02, -2.21406780e-02],\n",
      "         [-7.34363217e-03,  9.97547805e-03, -1.59962792e-02, ...,\n",
      "          -2.01132614e-02,  4.04101564e-03, -1.30811296e-02],\n",
      "         ...,\n",
      "         [ 2.91116592e-02,  2.56295223e-02, -5.18021779e-03, ...,\n",
      "           1.64482743e-02,  9.89971100e-04, -5.71119506e-03],\n",
      "         [-3.59656615e-03,  3.92737426e-03,  1.15985656e-02, ...,\n",
      "          -4.35973983e-03,  1.28727686e-02, -3.06857913e-03],\n",
      "         [ 1.48936510e-02, -2.79081590e-03,  1.20031787e-02, ...,\n",
      "           1.37832770e-02,  1.05134724e-02,  2.34108530e-02]],\n",
      "\n",
      "        [[ 4.74231754e-04,  3.63741280e-03,  2.15365533e-02, ...,\n",
      "          -1.89999817e-03, -5.15478104e-03,  1.31619368e-02],\n",
      "         [-9.18400660e-03,  1.93454546e-03,  1.09110810e-02, ...,\n",
      "           9.14575998e-03, -8.21557175e-03, -8.30788538e-03],\n",
      "         [-1.69444911e-03, -4.36456734e-03, -2.26653703e-02, ...,\n",
      "          -1.38805434e-02,  1.06112342e-02, -1.10037765e-02],\n",
      "         ...,\n",
      "         [ 2.16357969e-02,  1.74818505e-02, -4.67658462e-03, ...,\n",
      "          -9.58664925e-04,  1.37514127e-02, -7.61160767e-03],\n",
      "         [-1.90485851e-03, -4.57544671e-03,  5.04404213e-03, ...,\n",
      "           7.49490084e-03,  2.18671728e-02, -5.64512424e-03],\n",
      "         [ 1.06539074e-02, -6.43269531e-03, -5.04566648e-04, ...,\n",
      "           8.10153224e-03,  1.10825021e-02,  1.70141142e-02]]],\n",
      "\n",
      "\n",
      "       [[[-4.50136606e-03, -6.02411199e-03,  3.11873481e-03, ...,\n",
      "          -5.44655835e-04,  2.41484423e-03,  2.56585758e-02],\n",
      "         [-1.60623565e-02,  2.61958572e-03, -4.11093468e-03, ...,\n",
      "          -1.52113223e-02, -2.44396157e-03, -9.40611679e-03],\n",
      "         [ 1.03867343e-02,  9.93811246e-03, -6.63214130e-03, ...,\n",
      "           4.57423186e-04, -1.41171238e-03,  1.74400141e-03],\n",
      "         ...,\n",
      "         [-3.64836096e-03, -3.09328665e-03, -1.06807053e-02, ...,\n",
      "           1.12805534e-02, -2.41819987e-04,  9.97136254e-03],\n",
      "         [ 2.19470632e-04, -1.80030242e-03,  4.31476161e-03, ...,\n",
      "          -1.55662363e-02,  1.01363128e-02, -5.82250673e-03],\n",
      "         [-1.94603333e-03, -1.33034596e-02,  1.00488653e-02, ...,\n",
      "           1.57581102e-02,  6.38718856e-03,  9.57524404e-03]],\n",
      "\n",
      "        [[-1.47843594e-03, -1.02676339e-02,  1.72790524e-03, ...,\n",
      "          -7.44713098e-03,  7.77076697e-03,  6.32125139e-02],\n",
      "         [-1.55830020e-02, -9.06818022e-04,  1.38317700e-02, ...,\n",
      "           1.86586718e-03, -1.31476419e-02, -2.01811269e-02],\n",
      "         [ 4.06060950e-04,  1.30023547e-02, -2.33655237e-02, ...,\n",
      "          -2.13477034e-02,  1.25812916e-02, -6.86774962e-03],\n",
      "         ...,\n",
      "         [ 8.52249004e-03,  2.30366867e-02, -2.14423127e-02, ...,\n",
      "           2.31715962e-02,  7.81933870e-03,  9.37404856e-03],\n",
      "         [ 3.03807063e-03,  3.03328532e-04,  1.46860117e-02, ...,\n",
      "          -4.26525855e-03,  1.57574061e-02, -4.55228426e-03],\n",
      "         [-1.30841765e-03, -5.18516358e-03,  4.14379733e-03, ...,\n",
      "           2.45135967e-02,  1.46029377e-02,  2.09346768e-02]],\n",
      "\n",
      "        [[ 1.05792219e-02,  7.71222962e-03,  1.60458777e-02, ...,\n",
      "          -1.14335474e-02,  1.80619667e-04,  3.85264903e-02],\n",
      "         [-3.40054696e-03,  3.24828108e-03, -2.46915198e-03, ...,\n",
      "           1.20599633e-02, -8.42132140e-03, -9.39693395e-03],\n",
      "         [-6.27992442e-03,  5.48810531e-05, -3.39485556e-02, ...,\n",
      "          -1.67110953e-02,  2.01697182e-02, -9.91834793e-03],\n",
      "         ...,\n",
      "         [ 6.44019945e-03,  1.73932556e-02, -1.23419259e-02, ...,\n",
      "           4.06535063e-03,  1.56269483e-02,  4.64981329e-03],\n",
      "         [ 4.31994861e-03, -6.28653821e-03,  1.34719890e-02, ...,\n",
      "           1.59082916e-02,  2.07160246e-02, -4.53479309e-03],\n",
      "         [-8.85906070e-03, -5.81115717e-03, -5.50442899e-04, ...,\n",
      "           1.17796622e-02,  1.62397400e-02,  2.18943544e-02]]]],\n",
      "      dtype=float32), array([ 3.54152434e-02,  1.07918017e-01, -1.80004574e-02,  4.33173068e-02,\n",
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      "      dtype=float32), array([[[[-1.24538150e-02,  8.40655994e-03, -5.28845051e-03, ...,\n",
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      "         ...,\n",
      "         [ 1.37888230e-02, -6.58180192e-03,  9.65370331e-03, ...,\n",
      "           7.17610447e-03,  3.45725450e-03,  5.33173978e-03],\n",
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      "         [-8.53933115e-03,  1.43394794e-03, -2.91879033e-03, ...,\n",
      "           3.77660524e-03,  2.05454584e-02, -1.35868033e-02]],\n",
      "\n",
      "        [[-1.20176468e-02,  1.51250837e-03,  3.43130133e-03, ...,\n",
      "          -1.57830697e-02, -2.39501009e-03,  2.93573504e-03],\n",
      "         [ 1.07167801e-02, -1.72885903e-03, -1.83217339e-02, ...,\n",
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      "         [-2.78812763e-03,  1.09002152e-02,  7.31469830e-03, ...,\n",
      "           1.32350891e-03,  5.71234105e-03, -2.06499193e-02],\n",
      "         ...,\n",
      "         [ 5.34640905e-03, -7.61074666e-03, -2.95266091e-05, ...,\n",
      "           1.06462219e-03,  7.16414442e-03,  5.50952321e-03],\n",
      "         [-1.97489071e-03, -5.18740201e-03, -3.50479130e-03, ...,\n",
      "          -7.65207084e-03,  6.48583705e-03,  7.29372769e-05],\n",
      "         [-8.13952927e-03, -1.72344397e-03, -1.71952751e-02, ...,\n",
      "           6.51383121e-03,  2.62788888e-02, -7.40201725e-03]],\n",
      "\n",
      "        [[-1.13097280e-02, -2.71398202e-03,  5.21831634e-03, ...,\n",
      "           3.75532242e-03, -4.37350944e-03, -1.71778537e-03],\n",
      "         [ 9.51003470e-03,  2.10385933e-03, -6.23627566e-03, ...,\n",
      "           9.84872226e-04, -1.22357579e-02, -5.77230006e-03],\n",
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      "          -1.15952350e-03,  7.16441032e-03, -6.74266228e-03],\n",
      "         ...,\n",
      "         [ 3.84493452e-03,  6.50770171e-03, -3.08423012e-04, ...,\n",
      "           7.76557205e-03,  4.50123427e-03,  2.94768345e-03],\n",
      "         [-5.20469574e-03,  2.53336993e-03, -2.00857781e-03, ...,\n",
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      "         [-4.31006867e-03, -4.26639896e-03, -1.50389588e-02, ...,\n",
      "          -6.62087603e-03,  1.03521571e-02,  2.33515655e-03]]],\n",
      "\n",
      "\n",
      "       [[[-1.66037567e-02,  2.41671409e-02, -1.76821016e-02, ...,\n",
      "          -8.38128850e-03, -3.02293082e-03,  3.58365453e-03],\n",
      "         [ 9.80825536e-03,  1.05249183e-02, -4.66881320e-02, ...,\n",
      "          -7.78164901e-03, -3.83233977e-03,  2.94483802e-03],\n",
      "         [ 1.34947952e-02, -1.25661753e-02,  1.29038952e-02, ...,\n",
      "           1.43833098e-03, -5.72983874e-03, -1.78362131e-02],\n",
      "         ...,\n",
      "         [ 9.57040023e-03,  1.17314365e-02,  1.55258663e-02, ...,\n",
      "           2.69203974e-05,  2.30762083e-03,  7.98452704e-04],\n",
      "         [-2.26363889e-03, -2.44599045e-03,  5.42335818e-03, ...,\n",
      "          -7.61786243e-04,  7.27130566e-03,  2.00658664e-02],\n",
      "         [-6.25453144e-03,  8.70768726e-03,  5.96766314e-03, ...,\n",
      "           2.25311015e-02,  1.17731886e-02, -8.07471387e-03]],\n",
      "\n",
      "        [[-2.05247719e-02,  9.02097579e-03, -1.39437476e-03, ...,\n",
      "          -1.84835698e-02,  1.36483200e-02,  1.48000638e-03],\n",
      "         [ 8.35212879e-03, -3.76963033e-03, -2.36531124e-02, ...,\n",
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      "         [ 1.35796964e-02, -1.72847509e-02,  9.88537073e-03, ...,\n",
      "           7.85652269e-03,  1.02855563e-02, -2.21692659e-02],\n",
      "         ...,\n",
      "         [ 4.50371159e-03,  7.92721228e-04,  8.28000717e-03, ...,\n",
      "          -1.25710340e-03,  2.60498724e-03,  6.89739687e-03],\n",
      "         [-4.07085335e-03, -4.51655919e-03, -2.78022187e-03, ...,\n",
      "           1.75143685e-03,  7.57344998e-03,  1.27716700e-03],\n",
      "         [-4.38698288e-03,  1.11662695e-04, -1.52793936e-02, ...,\n",
      "           3.82050462e-02,  3.65496846e-03, -6.30834652e-03]],\n",
      "\n",
      "        [[-1.67291705e-02, -7.51205778e-04,  8.62288661e-03, ...,\n",
      "          -4.92068566e-03,  2.60210619e-03, -8.31924565e-03],\n",
      "         [ 7.60383205e-03, -2.44896696e-03, -9.95151792e-03, ...,\n",
      "           2.84005492e-03,  1.40986012e-04, -7.82902353e-03],\n",
      "         [ 2.45916261e-03, -6.49120752e-03, -8.32979660e-03, ...,\n",
      "           7.72433681e-03,  1.30170006e-02, -1.23488028e-02],\n",
      "         ...,\n",
      "         [ 1.33765105e-03,  7.21688429e-03,  1.26626331e-03, ...,\n",
      "           3.94847291e-03,  5.32880379e-03, -2.07663863e-03],\n",
      "         [-2.70236470e-03,  1.28381781e-03, -6.93748286e-03, ...,\n",
      "           8.98882467e-03,  1.46908136e-02, -4.21756599e-03],\n",
      "         [-2.33115349e-03, -6.12587482e-03, -2.12312099e-02, ...,\n",
      "           9.15342360e-04,  3.17362952e-04,  1.23123394e-03]]],\n",
      "\n",
      "\n",
      "       [[[-1.45651354e-02,  9.64931585e-03, -1.16087059e-02, ...,\n",
      "           2.59297341e-03, -8.05760548e-03,  2.21103709e-03],\n",
      "         [ 6.19267486e-03,  8.93716048e-03, -4.51339036e-02, ...,\n",
      "          -6.12378679e-03, -4.00708383e-03,  6.47111796e-03],\n",
      "         [ 1.43068740e-02, -2.66728899e-03,  3.41038289e-03, ...,\n",
      "           3.44638783e-03, -8.62873974e-04, -1.33675877e-02],\n",
      "         ...,\n",
      "         [ 1.29059236e-02,  9.14617069e-03,  8.28087237e-03, ...,\n",
      "          -4.39318595e-03, -8.14242568e-03, -2.26692040e-03],\n",
      "         [-1.31062279e-03, -5.64920157e-03,  6.37932634e-03, ...,\n",
      "           6.66187890e-03,  4.44209296e-03,  4.41963132e-03],\n",
      "         [-6.42832462e-03,  4.18221578e-03,  7.65334209e-03, ...,\n",
      "           1.20814089e-02, -6.66856999e-03,  3.25094647e-04]],\n",
      "\n",
      "        [[-1.66320223e-02,  4.54504183e-03, -6.67143054e-03, ...,\n",
      "           2.28197756e-03, -6.31665680e-05, -4.71796095e-03],\n",
      "         [ 2.97540380e-03, -6.40762178e-03, -2.85963546e-02, ...,\n",
      "          -2.35724798e-03,  4.74322308e-03,  4.67349339e-04],\n",
      "         [ 2.36185007e-02, -1.89911220e-02,  4.60000196e-03, ...,\n",
      "           1.08400211e-02, -9.18388832e-03, -2.74709109e-02],\n",
      "         ...,\n",
      "         [ 8.74977279e-03,  1.61244010e-03,  3.06530995e-03, ...,\n",
      "           4.53018304e-03, -7.39837857e-03,  4.47823061e-03],\n",
      "         [-1.20457367e-03, -2.87331175e-03, -5.18758828e-03, ...,\n",
      "           1.17142722e-02,  7.62202404e-03, -5.77956159e-03],\n",
      "         [-4.07704106e-03,  5.63840521e-03, -1.10617159e-02, ...,\n",
      "           2.38051061e-02, -1.34268589e-02, -2.97562080e-03]],\n",
      "\n",
      "        [[-8.99161492e-03,  5.84716024e-03,  5.29400352e-03, ...,\n",
      "           3.04830913e-03, -1.18276821e-02, -8.41523055e-03],\n",
      "         [ 3.12718400e-03, -5.05524641e-03, -1.94435567e-02, ...,\n",
      "           3.33701703e-03,  1.45587865e-02, -4.61388379e-03],\n",
      "         [ 1.11383200e-02, -2.28672028e-02,  2.00467315e-04, ...,\n",
      "          -3.49199137e-04, -8.52558948e-03, -1.46135921e-02],\n",
      "         ...,\n",
      "         [ 4.12542978e-03,  1.88087288e-03, -2.15299334e-03, ...,\n",
      "           3.59076308e-03, -1.91574858e-03, -3.53228627e-03],\n",
      "         [-2.84922371e-05,  9.47301451e-04, -8.46835505e-03, ...,\n",
      "           1.27441790e-02,  1.32457484e-02, -2.80284905e-03],\n",
      "         [-6.17068168e-03, -5.06139966e-03, -1.87711921e-02, ...,\n",
      "          -2.79223267e-03, -1.10712685e-02,  4.57540294e-03]]]],\n",
      "      dtype=float32), array([ 0.01348567,  0.00756114,  0.06701895,  0.04177905,  0.00131124,\n",
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      "       -0.0481341 , -0.00103277,  0.05884005,  0.01856414,  0.0359413 ,\n",
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      "       -0.00413027,  0.0101658 ], dtype=float32), array([[[[ 7.11654220e-03,  7.00819055e-06,  9.24700499e-03, ...,\n",
      "           4.03929735e-03,  8.05561524e-03, -3.74245713e-03],\n",
      "         [ 1.12781115e-03,  1.61532906e-03, -9.08267568e-04, ...,\n",
      "          -7.93790072e-03, -4.59095975e-03, -8.13464867e-04],\n",
      "         [-4.63789236e-03, -1.18727237e-02,  6.58529717e-03, ...,\n",
      "           7.42091658e-03, -6.53812988e-03, -2.42086244e-03],\n",
      "         ...,\n",
      "         [ 1.28063676e-03,  1.49819313e-03,  7.28668272e-03, ...,\n",
      "          -5.99841867e-03, -2.01151473e-03, -1.18386478e-03],\n",
      "         [-4.89709014e-03, -6.26946846e-03, -5.09714335e-03, ...,\n",
      "           1.26905064e-03,  1.07506765e-02, -2.44210777e-03],\n",
      "         [ 2.12570513e-03, -3.61318327e-03, -7.26481713e-03, ...,\n",
      "           3.64817417e-04,  1.50787262e-02,  4.10703570e-03]],\n",
      "\n",
      "        [[ 6.64269971e-03, -6.01840531e-03,  9.42177977e-03, ...,\n",
      "           4.53453884e-03,  4.71206789e-04,  3.50896595e-03],\n",
      "         [-1.24128824e-02,  1.62265194e-03,  2.18410187e-05, ...,\n",
      "          -9.26828291e-03, -1.32720219e-02,  7.84974638e-03],\n",
      "         [-2.27750093e-03, -1.37851508e-02,  6.04773080e-03, ...,\n",
      "           5.82123734e-03, -4.03309939e-03, -3.08526703e-03],\n",
      "         ...,\n",
      "         [ 9.42836609e-03, -7.80543603e-04,  1.71435010e-02, ...,\n",
      "          -7.94082507e-03, -7.73798907e-04,  3.02146119e-03],\n",
      "         [-3.22291674e-03, -2.85354297e-04, -2.08436535e-03, ...,\n",
      "          -4.60813055e-03, -5.56954136e-03,  6.86109858e-03],\n",
      "         [ 9.59297060e-04,  7.38721387e-03, -8.91729910e-03, ...,\n",
      "          -1.65850704e-03,  7.24582188e-03,  6.19835919e-03]],\n",
      "\n",
      "        [[ 2.34439736e-03, -9.28215683e-03, -3.19302635e-04, ...,\n",
      "           8.40835925e-03,  4.12485213e-04,  3.09582963e-03],\n",
      "         [-1.55776711e-02, -1.08954648e-03, -4.28956561e-03, ...,\n",
      "          -1.46012632e-02, -1.17095094e-03, -1.09702547e-03],\n",
      "         [-7.46384822e-03, -6.07428560e-03,  1.01981256e-02, ...,\n",
      "          -3.00147524e-03,  6.63558196e-04, -6.11750875e-03],\n",
      "         ...,\n",
      "         [ 4.24216688e-03,  4.56949836e-03,  8.23827088e-03, ...,\n",
      "          -5.40188514e-03, -8.07413179e-03,  1.09999124e-02],\n",
      "         [-7.86238699e-04,  1.90356933e-03,  1.71771063e-03, ...,\n",
      "          -2.16562231e-03, -1.10405972e-02,  9.30893887e-03],\n",
      "         [ 6.02629362e-03,  1.86428446e-02, -1.34665128e-02, ...,\n",
      "          -8.40879139e-03,  7.48337386e-03, -4.10805363e-03]]],\n",
      "\n",
      "\n",
      "       [[[ 5.44611085e-03, -9.18421778e-04,  9.77920461e-03, ...,\n",
      "          -1.19165263e-04, -3.40916682e-03, -6.98734634e-03],\n",
      "         [ 2.51410692e-03,  4.60237265e-03, -2.46173400e-03, ...,\n",
      "          -5.48852608e-03, -7.09898863e-03,  5.42021822e-03],\n",
      "         [-9.05828271e-03, -1.00242114e-02,  2.94465595e-03, ...,\n",
      "           9.01548378e-03,  6.37277029e-04, -2.18915544e-03],\n",
      "         ...,\n",
      "         [-3.00789997e-03, -9.66227599e-05,  1.85708259e-03, ...,\n",
      "          -2.42409506e-03,  2.34206222e-04, -3.27465497e-03],\n",
      "         [-5.01462910e-03, -3.50114633e-03, -6.08791783e-03, ...,\n",
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      "         [-8.52283556e-03, -1.07422760e-02, -2.84677697e-03, ...,\n",
      "           6.36414066e-03,  1.55793177e-02,  2.62972061e-03]],\n",
      "\n",
      "        [[ 6.34042593e-03, -5.55177638e-03,  1.12122018e-02, ...,\n",
      "           3.84862011e-04, -7.39399204e-03, -2.59233406e-03],\n",
      "         [ 1.83797081e-03,  4.37067216e-03, -2.16640974e-03, ...,\n",
      "          -9.72099602e-03, -4.33123438e-03,  6.84785657e-03],\n",
      "         [-2.52128625e-03, -9.25008021e-03,  5.38919820e-03, ...,\n",
      "           6.01652497e-03,  7.39997532e-03, -3.47864232e-03],\n",
      "         ...,\n",
      "         [ 6.54197996e-03, -1.80534972e-03,  6.87478622e-03, ...,\n",
      "          -2.96625658e-03,  7.19870348e-03, -3.49612092e-03],\n",
      "         [-1.20014576e-02, -9.55184049e-04,  3.21550784e-03, ...,\n",
      "          -6.86675077e-03,  3.81029584e-03, -1.35953142e-03],\n",
      "         [-1.33076878e-02, -5.95784932e-03,  2.00847466e-03, ...,\n",
      "           3.71311558e-03, -4.85057989e-03,  6.59804884e-03]],\n",
      "\n",
      "        [[ 2.90424004e-03, -9.89661831e-03,  1.91741413e-03, ...,\n",
      "           5.65523747e-03, -6.10089628e-03, -2.42118305e-03],\n",
      "         [-3.49682709e-03,  1.72886357e-04, -5.87909436e-03, ...,\n",
      "          -1.28070693e-02,  4.43585636e-03,  6.80614915e-03],\n",
      "         [-1.09087434e-02, -7.73155596e-03,  1.13571603e-02, ...,\n",
      "          -1.85778399e-03,  4.53320518e-03, -6.28825603e-03],\n",
      "         ...,\n",
      "         [ 4.70118131e-03,  1.73194357e-03,  2.63497210e-03, ...,\n",
      "           2.44574575e-03, -1.33330061e-03, -3.43957436e-06],\n",
      "         [-8.93086009e-03,  3.52435117e-03,  3.11156409e-03, ...,\n",
      "          -6.06179424e-03, -1.80058610e-02,  1.25560276e-02],\n",
      "         [-1.18324636e-02,  8.83054268e-03,  3.15376674e-03, ...,\n",
      "          -1.96965900e-03, -5.68017829e-03,  7.08003854e-03]]],\n",
      "\n",
      "\n",
      "       [[[ 8.75416305e-03, -4.36640298e-03,  4.88167582e-03, ...,\n",
      "           8.39018787e-04, -5.99739561e-03, -1.24212792e-02],\n",
      "         [ 4.01801849e-03,  3.51571711e-04,  3.97934671e-03, ...,\n",
      "           1.03333630e-02, -1.19119482e-02,  1.45259704e-02],\n",
      "         [-1.23062739e-02, -7.49821402e-03, -1.16881379e-03, ...,\n",
      "           1.00372350e-02,  3.78591637e-03, -3.27527802e-03],\n",
      "         ...,\n",
      "         [ 3.92382033e-04, -5.11869090e-03, -5.72134461e-03, ...,\n",
      "          -5.19906683e-03,  2.44495110e-03, -2.64277123e-03],\n",
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      "         [ 2.48351321e-03, -4.45801299e-03, -1.41727342e-03, ...,\n",
      "           1.14606246e-02,  2.31800862e-02,  1.90563314e-03]],\n",
      "\n",
      "        [[ 9.47191007e-03, -3.94198066e-03,  3.83984810e-03, ...,\n",
      "           2.04855483e-03, -3.98352416e-03, -9.07041319e-03],\n",
      "         [ 4.09901841e-03, -5.52556419e-04,  9.95470490e-03, ...,\n",
      "           6.61444664e-03,  1.68336404e-03,  5.98631799e-03],\n",
      "         [-5.33673773e-03, -3.10067786e-03, -2.68109678e-03, ...,\n",
      "           6.30002609e-03,  9.23030172e-03, -1.12451822e-03],\n",
      "         ...,\n",
      "         [ 3.42691923e-03, -3.57319019e-03, -3.67652508e-03, ...,\n",
      "          -2.96659744e-03,  2.97217467e-03, -5.51824691e-03],\n",
      "         [-6.08776370e-03, -3.16021242e-03, -3.34903644e-03, ...,\n",
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      "         [-6.22821553e-03, -5.55740483e-03,  1.33099854e-02, ...,\n",
      "           1.53019335e-02, -1.71303935e-03,  3.84857692e-03]],\n",
      "\n",
      "        [[ 6.73177093e-03, -7.76051125e-03, -1.60716416e-03, ...,\n",
      "           3.37521662e-03, -3.43736820e-03, -7.08474452e-03],\n",
      "         [-1.92464353e-03, -1.43057271e-03,  1.68074947e-03, ...,\n",
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      "          -2.28520279e-04,  2.16215150e-04, -1.52036909e-03],\n",
      "         ...,\n",
      "         [ 4.53559542e-03, -1.34184927e-04, -9.41309205e-04, ...,\n",
      "           1.11481512e-03, -4.47113672e-03, -4.62406827e-03],\n",
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      "         [-8.02905019e-03,  7.79318798e-04,  2.27084830e-02, ...,\n",
      "           1.30782668e-02,  1.38504582e-03,  7.73181953e-03]]]],\n",
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      "        5.62454313e-02,  1.43612195e-02,  6.42168671e-02,  4.83797006e-02,\n",
      "        1.25911102e-01,  1.25651538e-01,  7.45308250e-02, -1.71924084e-02],\n",
      "      dtype=float32), array([[[[-4.13556537e-03,  7.47195398e-03, -3.50115891e-03, ...,\n",
      "           4.89854301e-06, -2.53839465e-03, -5.25326468e-03],\n",
      "         [-9.53834411e-03,  1.41056092e-03, -1.65442061e-02, ...,\n",
      "          -1.52774970e-03,  1.11036829e-03, -1.79786165e-03],\n",
      "         [-3.51967965e-03,  8.38233996e-03,  1.37014373e-03, ...,\n",
      "          -2.04362301e-03, -3.33098392e-03, -3.59164621e-03],\n",
      "         ...,\n",
      "         [-4.51420387e-03, -9.90713015e-03, -7.90119357e-03, ...,\n",
      "          -2.74181948e-04,  8.04592157e-04, -9.21490043e-03],\n",
      "         [ 4.13362030e-03,  1.64503278e-03, -1.24853069e-03, ...,\n",
      "          -4.80085961e-04,  1.43603736e-03, -2.37931171e-03],\n",
      "         [-9.46063921e-03, -3.02881887e-03, -3.93793161e-04, ...,\n",
      "          -8.37404653e-03, -8.49721371e-04,  2.19010212e-03]],\n",
      "\n",
      "        [[-4.10446478e-03, -1.54824147e-03, -5.41875651e-03, ...,\n",
      "          -2.24129972e-03, -2.28596875e-03, -3.34858289e-03],\n",
      "         [-4.84787673e-03,  2.47201161e-03, -1.29879676e-02, ...,\n",
      "           8.18996597e-03, -4.54588607e-03,  9.62644164e-03],\n",
      "         [-3.10205529e-03,  3.47901974e-03,  2.52036308e-03, ...,\n",
      "          -5.83003787e-03,  1.09997432e-04, -3.84454383e-03],\n",
      "         ...,\n",
      "         [-7.76591944e-03, -1.44146327e-02, -7.61551922e-03, ...,\n",
      "          -3.92687973e-03, -6.16982626e-03, -5.35330735e-03],\n",
      "         [ 1.01468374e-03,  1.67173836e-02, -6.25725277e-03, ...,\n",
      "          -2.52300198e-03, -4.94909706e-03, -9.14588978e-04],\n",
      "         [-7.97870383e-03, -4.20195796e-03,  1.45270012e-03, ...,\n",
      "          -1.22739337e-02, -2.10561347e-03,  5.49114076e-03]],\n",
      "\n",
      "        [[-2.88630649e-03,  2.41750688e-03,  1.50172273e-03, ...,\n",
      "          -1.28930504e-03, -4.96551802e-04,  2.69375363e-04],\n",
      "         [ 3.95747193e-05, -1.94887386e-03, -7.08143180e-03, ...,\n",
      "           1.00128017e-02, -4.74765385e-03,  1.33702094e-02],\n",
      "         [ 4.38523851e-03,  2.79099098e-03, -4.09206329e-03, ...,\n",
      "          -2.73540127e-03, -3.12048779e-03, -2.88168900e-03],\n",
      "         ...,\n",
      "         [-4.95913485e-03, -1.23296445e-02, -5.42156352e-03, ...,\n",
      "          -2.32423958e-03, -8.56377464e-03, -7.15223281e-03],\n",
      "         [-6.16921112e-03,  1.57617237e-02, -4.47978219e-03, ...,\n",
      "          -2.25248467e-03, -9.93228331e-03, -6.10898901e-03],\n",
      "         [-4.50641429e-03, -5.51745854e-03, -2.20075878e-03, ...,\n",
      "          -1.30875418e-02, -3.93497292e-03,  6.03448506e-03]]],\n",
      "\n",
      "\n",
      "       [[[-4.41893004e-03,  1.37486542e-02, -8.45907908e-03, ...,\n",
      "          -2.21222895e-03, -2.15952285e-03,  1.23409089e-02],\n",
      "         [-6.33585500e-03, -4.42368211e-03, -3.91021417e-03, ...,\n",
      "          -9.76585504e-03,  1.04509713e-02, -1.36236623e-02],\n",
      "         [-4.40114317e-03,  7.94552453e-03,  2.42980407e-03, ...,\n",
      "          -5.41694043e-03,  8.71099706e-04, -9.86627582e-03],\n",
      "         ...,\n",
      "         [-1.34519069e-02, -1.00430250e-02,  1.51449756e-04, ...,\n",
      "           1.60089054e-04,  3.75668914e-03, -9.09452140e-03],\n",
      "         [ 2.45954143e-03,  5.74873528e-03, -4.06519882e-03, ...,\n",
      "           4.02215123e-03,  7.62883713e-03,  5.94564248e-03],\n",
      "         [-9.32596903e-03, -1.13636081e-03, -6.24895329e-03, ...,\n",
      "          -1.08463904e-02,  1.40982226e-03, -7.70578452e-04]],\n",
      "\n",
      "        [[-5.51303476e-03,  5.81868412e-03, -1.07901720e-02, ...,\n",
      "          -3.43920151e-03, -7.63218326e-04,  1.36730876e-02],\n",
      "         [-1.67119992e-03, -3.32675921e-03,  7.43533950e-03, ...,\n",
      "          -3.50478198e-03,  6.62456639e-03, -4.99307271e-03],\n",
      "         [-5.86137315e-03,  6.13010547e-04,  8.30108393e-03, ...,\n",
      "          -9.87416040e-03,  5.06723206e-03, -7.71902688e-03],\n",
      "         ...,\n",
      "         [-1.29670175e-02, -1.55268898e-02, -8.49602278e-04, ...,\n",
      "           6.30461425e-03,  5.32882579e-04, -6.07468095e-03],\n",
      "         [-1.12099759e-03,  2.91328244e-02, -4.23871959e-03, ...,\n",
      "           2.93749222e-03,  3.47164372e-04,  8.26061238e-03],\n",
      "         [-5.98738715e-03, -9.14713892e-04, -3.92263103e-03, ...,\n",
      "          -1.36881256e-02, -8.12742568e-04,  7.36264093e-03]],\n",
      "\n",
      "        [[-3.41959228e-03,  4.66367882e-03,  3.37764691e-03, ...,\n",
      "          -2.56140856e-03, -1.21631820e-04,  1.15059484e-02],\n",
      "         [ 2.40420690e-04, -3.77301918e-03,  6.58437563e-03, ...,\n",
      "           9.60138626e-03,  2.05660984e-03,  9.79973841e-03],\n",
      "         [ 1.32909336e-04,  1.90253675e-04,  6.17130077e-04, ...,\n",
      "          -8.72793701e-03, -1.45053165e-03, -3.49612208e-03],\n",
      "         ...,\n",
      "         [-9.77272261e-03, -1.07788146e-02, -9.54640738e-04, ...,\n",
      "           6.30754652e-03, -2.78572715e-03, -5.98356128e-03],\n",
      "         [-1.03954598e-02,  2.61091348e-02, -5.07673249e-03, ...,\n",
      "          -2.80671171e-03, -5.53699769e-03, -2.10620486e-03],\n",
      "         [-3.11570894e-03, -3.08538810e-03, -3.10157356e-03, ...,\n",
      "          -1.59878880e-02, -3.33151151e-03,  1.18652089e-02]]],\n",
      "\n",
      "\n",
      "       [[[-4.26715612e-03,  8.63417238e-03,  1.76529714e-03, ...,\n",
      "          -2.84227985e-03, -1.75439665e-04,  2.90537663e-02],\n",
      "         [-6.29396923e-03, -1.76275475e-03, -6.42163330e-04, ...,\n",
      "          -1.01052411e-02,  3.43423686e-03, -1.41305421e-02],\n",
      "         [-3.68094444e-03,  6.39184844e-03,  7.07066664e-03, ...,\n",
      "          -2.24087667e-03,  8.55041016e-03, -8.31523445e-03],\n",
      "         ...,\n",
      "         [-1.18850870e-02, -7.78572122e-03, -4.24755132e-03, ...,\n",
      "          -1.43992031e-04,  2.01374627e-04, -2.33163615e-03],\n",
      "         [ 2.30761128e-03, -9.47567285e-04, -1.79581740e-03, ...,\n",
      "          -4.05802298e-03,  5.83436852e-03,  1.24853859e-02],\n",
      "         [-7.39294710e-03,  6.41175592e-03, -1.01529667e-02, ...,\n",
      "          -1.17332852e-02,  1.69780722e-03,  1.15358143e-03]],\n",
      "\n",
      "        [[-4.61219344e-03, -3.59420269e-03, -8.21814407e-04, ...,\n",
      "          -4.81084595e-03, -4.44865436e-04,  3.18669118e-02],\n",
      "         [-1.15395896e-03, -5.12891915e-03,  9.74675361e-03, ...,\n",
      "          -7.82980397e-03,  7.25134509e-03, -6.98588043e-03],\n",
      "         [-5.98424906e-03,  1.12204099e-04,  9.43994615e-03, ...,\n",
      "          -4.51271143e-03,  8.94110464e-03, -8.36270489e-03],\n",
      "         ...,\n",
      "         [-1.31882168e-02, -9.57226939e-03, -6.37137098e-03, ...,\n",
      "           1.04999328e-02, -1.76120212e-03, -3.13745732e-05],\n",
      "         [ 1.22509198e-03,  1.17349727e-02, -2.26895651e-03, ...,\n",
      "          -6.69820094e-03,  4.28338209e-03,  1.29151903e-02],\n",
      "         [-2.21199635e-03,  1.19306184e-02, -3.41698364e-03, ...,\n",
      "          -1.32360598e-02, -4.97587898e-04,  1.26575744e-02]],\n",
      "\n",
      "        [[-3.64933652e-03, -4.82958928e-03,  9.14632156e-03, ...,\n",
      "          -4.02110023e-03, -1.57763090e-04,  1.70223936e-02],\n",
      "         [ 6.29810616e-04, -2.43360968e-03,  6.34040590e-03, ...,\n",
      "           3.36989964e-04,  6.95535308e-03,  1.70514290e-03],\n",
      "         [-3.24976468e-03,  2.30040471e-03,  4.15086048e-03, ...,\n",
      "          -4.70836135e-03, -1.04901823e-03, -6.13272097e-03],\n",
      "         ...,\n",
      "         [-1.13391438e-02, -4.96303104e-03, -2.09907000e-03, ...,\n",
      "           9.20415949e-03, -3.33326217e-03, -1.52914249e-03],\n",
      "         [-3.99327371e-03,  1.23460982e-02, -3.62788007e-04, ...,\n",
      "          -9.96733084e-03, -2.58089555e-03,  4.87980247e-03],\n",
      "         [-1.03235664e-03,  1.21477433e-03,  4.89632657e-04, ...,\n",
      "          -1.49842957e-02, -3.02216387e-03,  1.48773128e-02]]]],\n",
      "      dtype=float32), array([ 3.75776812e-02,  2.33153161e-02,  4.87732068e-02, -1.31543912e-02,\n",
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      "       -6.31701499e-02,  4.49785119e-04,  1.11907467e-01,  3.42719327e-03,\n",
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      "       -9.37856138e-02,  4.62724715e-02,  3.18735167e-02, -1.16503248e-02,\n",
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      "       -7.91937932e-02,  7.22831637e-02, -1.29031166e-01,  5.37225716e-02],\n",
      "      dtype=float32), array([[[[-6.0689339e-04,  1.4231558e-03,  7.3316055e-03, ...,\n",
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      "         [-4.8605306e-03,  4.9075234e-04, -1.2511463e-03, ...,\n",
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      "         [ 2.0234480e-03, -5.8380342e-03, -2.3825851e-03, ...,\n",
      "           1.3192679e-03, -8.6920448e-03, -8.2156417e-04],\n",
      "         [ 7.9414165e-03, -8.0086980e-03,  7.7348115e-04, ...,\n",
      "           9.1014095e-03,  6.8836473e-04, -9.8630879e-03],\n",
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      "          -1.8046533e-03, -7.7111748e-05,  3.5778836e-03]],\n",
      "\n",
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      "          -8.1634670e-03, -8.1500728e-03, -5.8323247e-03],\n",
      "         [-1.2195857e-03, -5.4482273e-03, -8.4939813e-03, ...,\n",
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      "         ...,\n",
      "         [-6.8472535e-04, -2.8301261e-03,  1.2871494e-03, ...,\n",
      "           1.8639782e-02, -1.4961872e-02, -1.3423259e-03],\n",
      "         [-1.5397326e-02, -1.0199412e-03,  1.0786263e-02, ...,\n",
      "           1.0112063e-02, -6.9852192e-03, -6.4757215e-03],\n",
      "         [ 1.0720392e-02, -3.2282835e-03, -1.0194050e-04, ...,\n",
      "          -4.7621364e-03,  1.0120733e-02,  5.2126674e-03]],\n",
      "\n",
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      "          -2.5150599e-03, -3.5095667e-03, -5.6064618e-03],\n",
      "         [ 1.0596886e-02, -1.0044489e-02,  1.8063044e-03, ...,\n",
      "          -2.9223200e-03,  8.0995419e-04, -2.0323446e-02],\n",
      "         [-1.7607687e-03,  2.3017763e-03, -1.5706603e-03, ...,\n",
      "          -1.1904801e-02, -5.6624818e-03, -2.7024033e-03],\n",
      "         ...,\n",
      "         [-8.9463210e-03, -7.5343349e-03,  7.4039923e-04, ...,\n",
      "           1.2268053e-02, -1.3198548e-02, -3.2026084e-05],\n",
      "         [-3.9164912e-02, -7.5820535e-03,  1.3907746e-03, ...,\n",
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      "         [ 6.8326667e-03, -2.0392942e-03,  4.8815343e-03, ...,\n",
      "          -2.2594277e-03,  1.3842926e-03,  7.3076310e-03]]],\n",
      "\n",
      "\n",
      "       [[[ 4.3825014e-03, -8.4557459e-03,  6.0976552e-05, ...,\n",
      "          -1.5721424e-03, -6.2847957e-03, -6.0747643e-03],\n",
      "         [-1.9328265e-02,  4.7232583e-03,  5.4184967e-03, ...,\n",
      "          -7.3021773e-04,  5.4419693e-03, -1.3912930e-02],\n",
      "         [ 5.5229296e-03,  4.6481588e-03, -7.7780159e-03, ...,\n",
      "           2.7554642e-04, -1.3050669e-02, -3.9565605e-03],\n",
      "         ...,\n",
      "         [ 3.2179512e-04, -3.4885360e-03, -1.0874616e-02, ...,\n",
      "           8.2677584e-03, -1.1178210e-02,  7.5714481e-03],\n",
      "         [ 4.0616496e-03, -7.2419085e-03, -1.3705336e-03, ...,\n",
      "           1.0747767e-02, -7.4744545e-04, -1.1671883e-02],\n",
      "         [ 1.2030830e-03,  7.4582128e-04,  3.5220869e-03, ...,\n",
      "          -1.7955588e-04,  2.9120417e-03,  6.2693246e-03]],\n",
      "\n",
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      "          -8.2665663e-03, -1.9626400e-02, -7.4289762e-03],\n",
      "         [-6.0759084e-03, -9.6884841e-04,  6.0364590e-03, ...,\n",
      "          -9.3692346e-03,  4.3691956e-03, -1.3639066e-02],\n",
      "         [-9.0519208e-03,  9.6781654e-03,  8.6934352e-03, ...,\n",
      "           9.1049206e-03, -9.7425170e-03, -7.6264590e-03],\n",
      "         ...,\n",
      "         [-3.8311486e-03,  7.1369117e-04, -1.1714270e-02, ...,\n",
      "           1.6859323e-02, -1.6344676e-02,  1.2910481e-02],\n",
      "         [ 9.2128823e-03, -1.5336460e-03,  5.2924841e-03, ...,\n",
      "           3.0931132e-03, -9.8296702e-03, -5.3623371e-04],\n",
      "         [ 3.9525158e-03,  9.3688892e-04,  3.7328359e-03, ...,\n",
      "          -5.5979183e-03,  1.0980255e-02,  1.2100901e-02]],\n",
      "\n",
      "        [[-1.7740640e-03, -1.1662573e-02,  1.6112716e-03, ...,\n",
      "           1.2962105e-04, -1.1654774e-02, -5.4892940e-03],\n",
      "         [ 1.5333769e-02, -6.9049154e-03,  9.9986177e-03, ...,\n",
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      "         [-1.9262903e-04,  2.8037187e-03, -1.7493139e-03, ...,\n",
      "           2.6137648e-02, -9.3979454e-03, -4.5618960e-03],\n",
      "         ...,\n",
      "         [-6.4418763e-03, -2.7641824e-03, -8.7552797e-03, ...,\n",
      "           1.0848792e-02, -1.2664125e-02,  1.1188427e-02],\n",
      "         [-1.4976529e-02, -8.0800392e-03,  1.1753010e-03, ...,\n",
      "          -1.4212406e-02, -1.4587110e-02, -5.5110687e-04],\n",
      "         [ 4.9651507e-03,  1.9658136e-03,  4.4132387e-03, ...,\n",
      "          -3.2392361e-03,  3.2961257e-03,  1.0079567e-02]]],\n",
      "\n",
      "\n",
      "       [[[-1.0813643e-02, -1.2109953e-03,  4.0739947e-03, ...,\n",
      "          -3.7609618e-03, -8.4045194e-03, -4.1101421e-03],\n",
      "         [-1.6155045e-02,  3.3042664e-04,  2.8314698e-03, ...,\n",
      "           3.8799408e-03,  1.0882318e-02, -1.2172839e-02],\n",
      "         [ 1.3959367e-02,  4.1269679e-03, -5.6302696e-03, ...,\n",
      "           8.7758545e-03, -3.2438899e-03, -3.4345812e-03],\n",
      "         ...,\n",
      "         [ 9.1708098e-03, -6.2859273e-03, -1.2609004e-02, ...,\n",
      "           1.6977531e-03, -9.6289860e-03,  5.1916544e-05],\n",
      "         [-9.7496519e-03, -2.1479633e-03, -1.9520836e-02, ...,\n",
      "          -9.5207070e-04,  6.3222921e-03, -1.7897552e-02],\n",
      "         [ 3.9352821e-03,  4.7744825e-03,  2.0808049e-03, ...,\n",
      "           9.7545320e-03, -1.2982457e-02,  4.6863281e-03]],\n",
      "\n",
      "        [[-6.3140173e-03, -2.0006283e-03, -4.0322897e-04, ...,\n",
      "           7.0220581e-03, -1.3161357e-02, -7.2546205e-03],\n",
      "         [-7.1486277e-03,  7.5339980e-04,  1.3867128e-03, ...,\n",
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      "         [-1.4313880e-03,  7.5597558e-03, -2.7771997e-03, ...,\n",
      "           3.3415109e-02, -3.9894031e-03, -6.9557610e-03],\n",
      "         ...,\n",
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      "          -6.8885856e-04, -1.6479922e-02, -1.7523849e-04],\n",
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      "          -5.6522340e-03, -8.0006220e-04, -1.0039192e-02],\n",
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      "          -5.3754007e-04, -1.7849701e-02,  5.1220311e-03]],\n",
      "\n",
      "        [[ 6.7127135e-04, -3.2391129e-03,  7.8760099e-04, ...,\n",
      "           7.2297198e-03, -5.2612908e-03, -4.2801294e-03],\n",
      "         [ 5.4616379e-03, -1.8265145e-03,  8.0440696e-03, ...,\n",
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      "         [ 4.7172702e-04,  6.6203335e-03, -5.3720833e-03, ...,\n",
      "           4.0812425e-02, -3.6152611e-03, -5.1507959e-03],\n",
      "         ...,\n",
      "         [-1.1449282e-03, -6.4645633e-03, -1.2517356e-02, ...,\n",
      "          -6.6413991e-03, -1.0809171e-02, -2.6953095e-03],\n",
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      "          -1.0663199e-02, -5.6493361e-03, -4.9214857e-03],\n",
      "         [ 4.3073772e-03,  3.5157984e-03,  4.7004086e-04, ...,\n",
      "          -2.4001813e-04, -1.6719183e-02,  4.8483759e-03]]]],\n",
      "      dtype=float32), array([ 9.72232521e-02, -7.32301399e-02,  1.51504159e-01,  1.07368380e-01,\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "           3.34846694e-03,  1.33423917e-02,  4.46979143e-03]]],\n",
      "\n",
      "\n",
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      "         [-6.78315479e-03,  7.97655899e-03,  1.22533282e-02, ...,\n",
      "           1.35311754e-02,  1.13436170e-02,  1.00916745e-02],\n",
      "         ...,\n",
      "         [-5.42715983e-03,  6.82500936e-03,  2.06867745e-03, ...,\n",
      "           1.15423445e-02,  1.35911524e-03, -5.60511416e-03],\n",
      "         [ 4.61982097e-03,  8.86386912e-03, -5.09008206e-03, ...,\n",
      "           2.30618101e-03, -2.10025930e-03, -1.28205456e-02],\n",
      "         [-1.71301316e-03, -1.08229686e-02, -6.23088004e-03, ...,\n",
      "          -9.36139748e-03,  4.23580030e-04,  6.02343772e-03]],\n",
      "\n",
      "        [[-7.84571003e-03, -7.72077264e-03, -4.10368491e-04, ...,\n",
      "          -4.64761769e-03,  4.84151114e-03, -8.10108799e-03],\n",
      "         [ 7.03802519e-03, -6.14652690e-03, -3.35389609e-03, ...,\n",
      "          -7.66926736e-04, -4.10724850e-03,  3.30237439e-03],\n",
      "         [-1.26976296e-02,  4.06949688e-03,  1.57761611e-02, ...,\n",
      "           2.05063750e-03,  1.35973999e-02,  2.45495401e-02],\n",
      "         ...,\n",
      "         [-4.94020339e-03, -6.04472240e-04,  3.70768807e-03, ...,\n",
      "           5.28301718e-03,  5.77830663e-03, -5.73270582e-03],\n",
      "         [ 6.47951430e-03,  5.04286960e-03, -5.76301245e-03, ...,\n",
      "          -3.84971802e-03, -1.53160375e-02, -1.36713414e-02],\n",
      "         [-6.13218453e-03, -7.85352290e-03, -2.66636047e-03, ...,\n",
      "          -2.86623905e-03,  8.13857932e-03,  3.23665445e-03]],\n",
      "\n",
      "        [[-1.03016887e-02, -7.32906163e-03, -1.26632303e-02, ...,\n",
      "          -1.51485833e-03, -4.73790773e-04, -1.50191726e-03],\n",
      "         [ 2.47099600e-03, -3.58005147e-03, -8.92815471e-04, ...,\n",
      "           2.19221620e-04, -5.89206407e-04,  1.02671504e-03],\n",
      "         [-7.04030367e-03,  2.31858669e-03,  1.17366202e-02, ...,\n",
      "          -1.00303544e-02,  9.60416254e-03,  3.07981335e-02],\n",
      "         ...,\n",
      "         [ 1.02732638e-02, -4.61639231e-03, -3.90697533e-04, ...,\n",
      "           5.76351210e-03,  5.99978026e-03, -6.46614050e-03],\n",
      "         [ 1.79310958e-03, -1.10877156e-02, -4.39016009e-03, ...,\n",
      "          -3.89495096e-03, -1.43652763e-02, -1.33516490e-02],\n",
      "         [-4.76273848e-03,  9.76819452e-03, -6.88574556e-03, ...,\n",
      "           7.87178893e-03,  2.10002940e-02,  2.46465113e-03]]]],\n",
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      "      dtype=float32), array([[[[ 4.07882966e-04,  4.82621184e-03, -9.11695044e-03, ...,\n",
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      "\n",
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      "         [-9.60117579e-03,  5.01031429e-03, -1.13053191e-02, ...,\n",
      "           8.86707660e-03,  6.21224102e-03,  2.48882570e-03],\n",
      "         [-1.13499342e-02, -4.72285505e-03, -8.57903156e-03, ...,\n",
      "          -3.04920389e-03,  9.67197306e-03,  1.90250184e-02],\n",
      "         ...,\n",
      "         [-4.48127137e-03,  5.53716440e-03,  4.68912302e-03, ...,\n",
      "          -4.91005788e-03,  6.40070112e-03, -8.28019064e-03],\n",
      "         [-6.00830279e-03, -7.51605199e-04,  8.29616503e-04, ...,\n",
      "           2.07461347e-03,  3.22994636e-03, -1.69727230e-03],\n",
      "         [-2.81035155e-03,  1.36994272e-02, -2.04460253e-03, ...,\n",
      "          -5.17683988e-03, -9.04289633e-03, -1.79657899e-03]],\n",
      "\n",
      "        [[ 3.09069827e-03, -7.85107608e-04, -1.12262042e-02, ...,\n",
      "           1.38624888e-02, -1.50248851e-03, -2.83075101e-03],\n",
      "         [-1.78263709e-02, -4.06336552e-03, -1.11764381e-02, ...,\n",
      "           1.76884588e-02, -1.14172359e-03,  1.50952139e-03],\n",
      "         [-1.26420632e-02, -1.19902752e-03, -1.03873471e-02, ...,\n",
      "          -1.54873531e-03,  3.21487361e-03,  1.84067711e-02],\n",
      "         ...,\n",
      "         [ 4.99952445e-03,  8.96072667e-03,  2.35912274e-03, ...,\n",
      "          -6.95799524e-03,  9.11425054e-03, -1.76598097e-03],\n",
      "         [-3.11188446e-03, -4.81695170e-03,  2.14671413e-03, ...,\n",
      "           8.69878661e-03,  4.66441829e-03,  3.96351190e-03],\n",
      "         [-1.56560540e-03,  1.01758400e-02, -1.81451999e-03, ...,\n",
      "          -7.93038029e-03, -7.92690739e-03,  9.85421613e-03]]],\n",
      "\n",
      "\n",
      "       [[[ 2.21009902e-03,  5.53841889e-03, -1.51329748e-02, ...,\n",
      "           1.92244705e-02, -2.94085429e-03, -2.05214042e-03],\n",
      "         [ 4.31180233e-03, -4.67703957e-03, -9.83539224e-03, ...,\n",
      "          -1.16664264e-03, -7.47026131e-03,  8.98758229e-03],\n",
      "         [-1.00150378e-02, -3.31197702e-03, -4.38165246e-03, ...,\n",
      "           1.28704909e-04,  6.90069282e-05,  5.32614533e-03],\n",
      "         ...,\n",
      "         [-1.65325180e-02,  5.79520175e-03, -1.08136714e-03, ...,\n",
      "          -3.87264206e-03,  3.87065555e-03, -8.52444116e-03],\n",
      "         [-1.10835498e-02,  6.04208373e-03,  6.12878706e-03, ...,\n",
      "          -4.66409931e-03, -1.65367487e-03, -4.93706390e-03],\n",
      "         [-5.82469627e-03,  2.77068373e-03,  2.59765168e-03, ...,\n",
      "          -9.57501866e-03, -3.32338479e-03,  3.07677989e-03]],\n",
      "\n",
      "        [[ 3.59932799e-03,  1.19693214e-02, -1.60994809e-02, ...,\n",
      "           1.80910621e-02,  3.29896147e-06, -6.10836258e-04],\n",
      "         [-7.41903298e-03, -5.61146066e-03, -1.38216335e-02, ...,\n",
      "           2.96197180e-03,  2.69207382e-03,  7.01817824e-03],\n",
      "         [-8.48251395e-03,  9.95878596e-04,  6.25522574e-04, ...,\n",
      "          -3.68017773e-03,  1.27349654e-02,  4.87677474e-03],\n",
      "         ...,\n",
      "         [-8.20725970e-03,  1.95525214e-03,  2.69707199e-03, ...,\n",
      "          -4.49266564e-03,  6.45229314e-03, -1.28380703e-02],\n",
      "         [-5.50353806e-03,  1.61080994e-03,  1.39699667e-03, ...,\n",
      "          -2.52319360e-03, -4.11227718e-03, -5.21757640e-03],\n",
      "         [-2.69698747e-03,  2.70054420e-03,  3.79564380e-03, ...,\n",
      "          -7.66708190e-03, -9.20492224e-03, -4.52092383e-03]],\n",
      "\n",
      "        [[ 2.48262100e-03,  6.13112841e-03, -1.47995697e-02, ...,\n",
      "           1.69335436e-02,  1.16662926e-03,  1.17623655e-03],\n",
      "         [-1.69411730e-02, -8.71018134e-03, -1.29530905e-02, ...,\n",
      "           1.87354535e-03, -6.88433880e-04, -1.68701622e-03],\n",
      "         [-6.59902534e-03,  3.46401357e-03, -3.11806914e-03, ...,\n",
      "          -4.05590283e-03,  7.37769250e-03,  5.51742781e-03],\n",
      "         ...,\n",
      "         [ 9.51702707e-04,  1.64372730e-03,  1.49127271e-03, ...,\n",
      "          -7.65326899e-03,  1.19846454e-02, -9.10102390e-03],\n",
      "         [ 2.88849953e-03, -5.35335718e-03, -3.08376068e-04, ...,\n",
      "           3.87483276e-04, -4.36716061e-03, -2.73425644e-03],\n",
      "         [-1.54271268e-03,  4.30263951e-03, -4.31923472e-05, ...,\n",
      "          -5.21167647e-03, -8.79874174e-03, -2.11346560e-04]]],\n",
      "\n",
      "\n",
      "       [[[-2.93453527e-03,  4.62880917e-03, -9.69677325e-03, ...,\n",
      "           1.48544796e-02,  3.87839018e-03,  1.85810984e-03],\n",
      "         [ 5.63784037e-03, -6.04889123e-03, -5.59245935e-03, ...,\n",
      "          -4.98529337e-03, -1.92062720e-03,  4.07473044e-03],\n",
      "         [-4.84194839e-03,  2.70295335e-04, -3.02166585e-03, ...,\n",
      "          -1.49492722e-03, -1.31164724e-02,  2.69274553e-03],\n",
      "         ...,\n",
      "         [-1.79702230e-02, -3.29879066e-03, -6.12194091e-03, ...,\n",
      "          -7.89267663e-03, -1.74841529e-03, -2.64002383e-03],\n",
      "         [-1.11466460e-02,  5.13884844e-03,  1.51880039e-02, ...,\n",
      "          -4.87166690e-03,  2.45198980e-03, -3.42866592e-03],\n",
      "         [-6.12380216e-03,  8.87359586e-03, -3.45014478e-03, ...,\n",
      "          -1.09723555e-02,  2.66773975e-03, -4.79325093e-03]],\n",
      "\n",
      "        [[-6.14633691e-03,  1.40388934e-02, -9.19489283e-03, ...,\n",
      "           1.60656814e-02,  8.88941437e-03,  6.56510517e-03],\n",
      "         [-5.72578516e-03, -3.33702704e-03, -8.64025764e-03, ...,\n",
      "           1.98416272e-03,  7.86264334e-03,  2.50778953e-03],\n",
      "         [-3.77366156e-03,  9.24240507e-04,  7.29091058e-04, ...,\n",
      "          -4.96890210e-03,  3.85057204e-03, -7.15580711e-04],\n",
      "         ...,\n",
      "         [-1.22111076e-02, -2.42003356e-03, -4.81141545e-03, ...,\n",
      "          -4.22020489e-03, -1.01946108e-02, -5.80721162e-03],\n",
      "         [-9.04400460e-03,  1.94370467e-03,  7.34009594e-03, ...,\n",
      "          -5.14973374e-03,  3.66879918e-04, -5.37241250e-03],\n",
      "         [-3.53684562e-04,  1.53788179e-02, -8.76262202e-04, ...,\n",
      "          -7.13666994e-03, -4.27656015e-03, -1.42133404e-02]],\n",
      "\n",
      "        [[-6.67408668e-03,  9.11168288e-03, -9.18486901e-03, ...,\n",
      "           1.21346870e-02,  8.51947255e-03,  7.15135690e-03],\n",
      "         [-1.64910071e-02, -2.04550894e-03, -7.30760070e-03, ...,\n",
      "          -2.89353775e-03,  1.16095145e-03, -6.60440046e-03],\n",
      "         [-7.68517129e-05,  4.32093628e-03, -6.93119306e-04, ...,\n",
      "          -3.48316878e-03, -1.47545757e-03, -2.85687298e-03],\n",
      "         ...,\n",
      "         [-4.66702832e-03, -1.39780261e-03,  3.67210196e-05, ...,\n",
      "          -4.95146902e-04,  7.23151665e-04, -6.29519764e-03],\n",
      "         [ 3.63699184e-03, -4.63909749e-03,  5.31478412e-03, ...,\n",
      "          -1.50180201e-03, -7.48660788e-03, -1.94359326e-03],\n",
      "         [-1.03440508e-03,  1.57131702e-02, -1.98940560e-03, ...,\n",
      "          -5.38550608e-04, -5.37431426e-03, -9.20103770e-03]]]],\n",
      "      dtype=float32), array([ 1.88378572e-01, -5.00367463e-01,  5.42223394e-01,  2.46460959e-01,\n",
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      "       -4.80620004e-02,  1.38647243e-01, -3.01776342e-02,  1.83977813e-01,\n",
      "       -1.18016593e-01,  3.89179081e-01,  6.13915585e-02,  1.58884943e-01,\n",
      "        5.89057468e-02,  5.19612193e-01,  1.23953849e-01,  5.55581629e-01,\n",
      "        5.01390219e-01, -3.79978642e-02, -1.41257286e-01,  7.03621209e-02,\n",
      "       -1.73130766e-01,  3.50397527e-01, -1.34628639e-01, -2.30107084e-02,\n",
      "        5.94515465e-02,  3.11439663e-01,  4.39245671e-01, -8.34068432e-02,\n",
      "        8.05468298e-03,  8.24325830e-02, -6.42216429e-02,  1.73451111e-01,\n",
      "        9.77575108e-02, -9.48499516e-02,  6.00330293e-01, -2.85697937e-01,\n",
      "        6.63027644e-01,  2.28900835e-01, -5.50854504e-02,  1.96810931e-01,\n",
      "        1.31078482e-01,  1.16677739e-01,  2.73458511e-01, -1.60894319e-01,\n",
      "        1.54009443e-02,  1.65677398e-01,  4.01737362e-01,  1.94677606e-01,\n",
      "       -3.40434372e-01,  4.65704620e-01, -2.72638332e-02,  9.78857726e-02,\n",
      "        3.00865740e-01,  8.31336603e-02,  6.52762055e-02,  1.93404332e-01,\n",
      "        4.39618938e-02,  1.97853178e-01,  6.20303333e-01, -2.47850232e-02,\n",
      "        3.16133723e-02,  4.27223206e-01, -1.78643763e-01,  2.27603521e-02,\n",
      "        1.01879463e-01, -1.77166402e-01, -9.12419409e-02,  6.85135424e-02,\n",
      "        2.09163412e-01,  2.12687582e-01,  2.60186791e-01, -1.92657262e-02,\n",
      "        1.86271384e-01,  8.68155286e-02, -1.64935917e-01, -6.73513263e-02,\n",
      "        3.51010323e-01,  7.94189423e-02,  3.47567499e-01, -3.27353388e-01,\n",
      "        2.28438899e-01,  1.91672705e-02,  4.34933186e-01,  2.34846137e-02,\n",
      "        5.02053857e-01,  2.87198114e+00,  3.45609011e-03, -3.42143588e-02,\n",
      "        3.52340311e-01,  4.58314866e-01, -1.96509138e-01, -1.23567872e-01,\n",
      "        1.77132830e-01,  6.33585453e-02, -2.15546321e-03,  3.33019942e-01,\n",
      "       -5.46362288e-02,  1.94658935e-01,  2.31957555e-01, -1.94247887e-01,\n",
      "        7.14528114e-02,  4.19912785e-02,  3.27715337e-01, -1.10557206e-01,\n",
      "       -1.07955880e-01,  1.31638125e-01,  2.46899307e-01,  7.21076829e-03,\n",
      "        2.77655154e-01, -1.57194927e-01,  6.24649376e-02, -1.32860814e-03,\n",
      "       -1.57012362e-02,  2.07436994e-01, -9.61607322e-03, -4.07151505e-02,\n",
      "        3.30549240e-01, -5.71658760e-02,  5.70487320e-01, -1.03581101e-01,\n",
      "       -1.79280698e-01,  3.29045117e-01,  5.74648529e-02, -8.48884210e-02,\n",
      "        1.71312660e-01, -5.71665429e-02,  3.82779270e-01,  2.49197200e-01,\n",
      "       -1.67588264e-01, -5.42712435e-02,  4.65058923e-01, -3.14851582e-01,\n",
      "        3.38773549e-01, -1.19772919e-01,  7.56180510e-02,  2.71076292e-01,\n",
      "        1.29012525e-01,  1.41996786e-01,  3.30376983e-01,  2.09672466e-01,\n",
      "        2.74694502e-01,  1.87327504e-01,  2.14084148e-01,  1.21977694e-01,\n",
      "        5.93084395e-01,  2.13688929e-02,  8.09027970e-01,  3.09404194e-01,\n",
      "        3.44152540e-01,  1.66218415e-01,  1.36155128e-01,  2.33373582e-01,\n",
      "        8.00405815e-03,  1.03328384e-01,  6.38187110e-01, -2.65396535e-02],\n",
      "      dtype=float32), array([[ 1.9745843e-05,  3.5308721e-04, -1.8327669e-03, ...,\n",
      "         3.9865216e-05, -2.8762815e-03,  3.3547997e-03],\n",
      "       [-5.3512463e-03, -1.5712962e-03, -3.3635952e-04, ...,\n",
      "         1.8792559e-03,  1.2153931e-04,  4.3403511e-03],\n",
      "       [ 6.6062581e-04,  1.3003269e-03, -1.2985406e-03, ...,\n",
      "         1.8807432e-03,  1.2526809e-03,  1.7083823e-04],\n",
      "       ...,\n",
      "       [-7.4534374e-04,  3.0306131e-03,  1.1758753e-03, ...,\n",
      "        -1.1366602e-03, -2.6967376e-03, -4.3831998e-03],\n",
      "       [ 1.1018270e-05, -6.4710301e-04, -3.5804727e-03, ...,\n",
      "        -8.2136394e-06,  4.2700255e-03, -1.0924845e-03],\n",
      "       [ 6.6752714e-04,  1.8266561e-03,  1.1025965e-03, ...,\n",
      "        -1.7052686e-03,  1.8931089e-03, -5.1029213e-03]], dtype=float32), array([-0.18869764,  0.12655699, -0.29960382, ..., -0.18377073,\n",
      "        0.17445327, -0.16718599], dtype=float32), array([[ 3.9014784e-03, -1.8080651e-03,  1.3615922e-03, ...,\n",
      "         1.0518912e-03, -5.8323862e-03,  1.5549988e-03],\n",
      "       [ 5.3532249e-03, -2.3153909e-03, -3.6157474e-03, ...,\n",
      "        -8.4152538e-04, -1.5586627e-03,  5.2202651e-03],\n",
      "       [-3.1340534e-03, -8.6071879e-05,  2.8132410e-03, ...,\n",
      "         2.3308401e-03,  4.5287302e-03, -6.2349276e-03],\n",
      "       ...,\n",
      "       [-4.2402726e-03, -4.1440636e-04, -7.8919629e-04, ...,\n",
      "         6.7993044e-03,  3.3782453e-03,  2.1300779e-03],\n",
      "       [ 2.7873128e-04,  9.5619177e-03, -6.2027783e-04, ...,\n",
      "        -2.1619676e-03,  5.9084590e-03,  1.7662607e-03],\n",
      "       [ 4.9691816e-04,  1.6384347e-03, -9.9276251e-04, ...,\n",
      "        -4.4977027e-05, -3.5091984e-04,  5.0349059e-03]], dtype=float32), array([0.647107  , 0.48036072, 0.5855111 , ..., 0.5024527 , 0.41782504,\n",
      "       0.66609925], dtype=float32), array([[ 0.00598402,  0.01706047, -0.0047221 , ..., -0.01066629,\n",
      "        -0.01532426,  0.03909317],\n",
      "       [-0.02089795,  0.02904208,  0.01328237, ..., -0.03435417,\n",
      "         0.03425778,  0.04883012],\n",
      "       [ 0.00432274, -0.03068626, -0.03465997, ..., -0.0080341 ,\n",
      "         0.0333431 , -0.03589739],\n",
      "       ...,\n",
      "       [-0.03692014,  0.03585469,  0.0204751 , ..., -0.01732253,\n",
      "         0.04010402, -0.04228922],\n",
      "       [ 0.00231082,  0.0426367 ,  0.04354849, ...,  0.03791017,\n",
      "         0.03722108, -0.03467615],\n",
      "       [-0.03160965, -0.04544796, -0.0379716 , ..., -0.01421608,\n",
      "        -0.04557591,  0.02805731]], dtype=float32), array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
      "       0.], dtype=float32)]\n"
     ]
    }
   ],
   "source": [
    "from keras.models import Model\n",
    "x1=Dense(256,activation='softmax',kernel_initializer='uniform')(vgg16.layers[-2].output)\n",
    "model=Model(inputs=vgg16.input,outputs=x1)\n",
    "#print model.get_weights()\n",
    "#    print \"same weight\"\n",
    "#else:\n",
    "#    print \"different weights,bro\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[array([[[[ 4.29470569e-01,  1.17273867e-01,  3.40129584e-02, ...,\n",
      "          -1.32241577e-01, -5.33475243e-02,  7.57738389e-03],\n",
      "         [ 5.50379455e-01,  2.08774377e-02,  9.88311544e-02, ...,\n",
      "          -8.48205537e-02, -5.11389151e-02,  3.74943428e-02],\n",
      "         [ 4.80015397e-01, -1.72696680e-01,  3.75577137e-02, ...,\n",
      "          -1.27135560e-01, -5.02991639e-02,  3.48965675e-02]],\n",
      "\n",
      "        [[ 3.73466998e-01,  1.62062630e-01,  1.70863140e-03, ...,\n",
      "          -1.48207128e-01, -2.35300660e-01, -6.30356818e-02],\n",
      "         [ 4.40074533e-01,  4.73412387e-02,  5.13819456e-02, ...,\n",
      "          -9.88498852e-02, -2.96195745e-01, -7.04357103e-02],\n",
      "         [ 4.08547401e-01, -1.70375049e-01, -4.96297423e-03, ...,\n",
      "          -1.22360572e-01, -2.76450396e-01, -3.90796512e-02]],\n",
      "\n",
      "        [[-6.13601133e-02,  1.35693997e-01, -1.15694344e-01, ...,\n",
      "          -1.40158370e-01, -3.77666801e-01, -3.00509870e-01],\n",
      "         [-8.13870355e-02,  4.18543853e-02, -1.01763301e-01, ...,\n",
      "          -9.43124294e-02, -5.05662560e-01, -3.83694321e-01],\n",
      "         [-6.51455522e-02, -1.54351532e-01, -1.38038069e-01, ...,\n",
      "          -1.29404560e-01, -4.62243795e-01, -3.23985279e-01]]],\n",
      "\n",
      "\n",
      "       [[[ 2.74769872e-01,  1.48350164e-01,  1.61559835e-01, ...,\n",
      "          -1.14316158e-01,  3.65494519e-01,  3.39938998e-01],\n",
      "         [ 3.45739067e-01,  3.10493708e-02,  2.40750551e-01, ...,\n",
      "          -6.93419054e-02,  4.37116861e-01,  4.13171440e-01],\n",
      "         [ 3.10477257e-01, -1.87601492e-01,  1.66595340e-01, ...,\n",
      "          -9.88388434e-02,  4.04058546e-01,  3.92561197e-01]],\n",
      "\n",
      "        [[ 3.86807770e-02,  2.02298447e-01,  1.56414255e-01, ...,\n",
      "          -5.20089604e-02,  2.57149011e-01,  3.71682674e-01],\n",
      "         [ 4.06322069e-02,  6.58102185e-02,  2.20311403e-01, ...,\n",
      "          -3.78979952e-03,  2.69412428e-01,  4.09505904e-01],\n",
      "         [ 5.02023660e-02, -1.77571565e-01,  1.51188180e-01, ...,\n",
      "          -1.40649760e-02,  2.59300828e-01,  4.23764467e-01]],\n",
      "\n",
      "        [[-3.67223352e-01,  1.61688417e-01, -8.99365395e-02, ...,\n",
      "          -1.45945460e-01, -2.71823555e-01, -2.39718184e-01],\n",
      "         [-4.53501314e-01,  4.62574959e-02, -6.67438358e-02, ...,\n",
      "          -1.03502415e-01, -3.45792353e-01, -2.92486250e-01],\n",
      "         [-4.03383434e-01, -1.74399972e-01, -1.09849639e-01, ...,\n",
      "          -1.25688612e-01, -3.14026326e-01, -2.32839763e-01]]],\n",
      "\n",
      "\n",
      "       [[[-5.74681684e-02,  1.29344285e-01,  1.29030216e-02, ...,\n",
      "          -1.41449392e-01,  2.41099641e-01,  4.55602147e-02],\n",
      "         [-5.86349145e-02,  3.16787697e-02,  7.59588331e-02, ...,\n",
      "          -1.05017252e-01,  3.39550197e-01,  9.86374393e-02],\n",
      "         [-5.08716851e-02, -1.66002661e-01,  1.56279504e-02, ...,\n",
      "          -1.49742723e-01,  3.06801915e-01,  8.82701725e-02]],\n",
      "\n",
      "        [[-2.62249678e-01,  1.71572417e-01,  5.44555223e-05, ...,\n",
      "          -1.22728683e-01,  2.44687453e-01,  5.32913655e-02],\n",
      "         [-3.30669671e-01,  5.47101051e-02,  4.86797579e-02, ...,\n",
      "          -8.29023942e-02,  2.95466095e-01,  7.44469985e-02],\n",
      "         [-2.85227507e-01, -1.66666731e-01, -7.96697661e-03, ...,\n",
      "          -1.09780088e-01,  2.79203743e-01,  9.46525261e-02]],\n",
      "\n",
      "        [[-3.50096762e-01,  1.38710454e-01, -1.25339806e-01, ...,\n",
      "          -1.53092295e-01, -1.39917329e-01, -2.65075237e-01],\n",
      "         [-4.85030204e-01,  4.23195846e-02, -1.12076312e-01, ...,\n",
      "          -1.18306056e-01, -1.67058021e-01, -3.22241962e-01],\n",
      "         [-4.18516338e-01, -1.57048807e-01, -1.49133086e-01, ...,\n",
      "          -1.56839803e-01, -1.42874300e-01, -2.69694626e-01]]]],\n",
      "      dtype=float32), array([ 0.73429835,  0.09340367,  0.06775674,  0.8862966 ,  0.25994542,\n",
      "        0.66426694, -0.01582893,  0.3249065 ,  0.68600726,  0.06247932,\n",
      "        0.58156496,  0.2361475 ,  0.69694996,  0.19451167,  0.4858922 ,\n",
      "        0.44571847,  0.5113422 ,  0.208576  ,  0.57557714,  0.33199573,\n",
      "        0.4997983 ,  0.7117759 ,  0.30284074,  0.7082712 ,  0.04548979,\n",
      "        0.7446502 ,  0.29845494,  0.48211655,  0.81658626,  0.62603897,\n",
      "        0.3768093 ,  2.064037  ,  0.77311045,  0.3459577 ,  0.6130958 ,\n",
      "        0.65459156,  0.39045632,  0.50869167,  0.2625384 ,  0.23669638,\n",
      "        0.07971057,  1.1179353 ,  0.26129362,  0.8697589 ,  0.21543622,\n",
      "        0.78007823,  0.37015367,  0.47993386,  0.4313978 ,  0.5084194 ,\n",
      "        0.23049663,  0.7636527 ,  0.35419866,  0.45794216,  0.4662595 ,\n",
      "        0.09850298,  0.3803252 ,  0.66880196,  0.4015123 ,  0.90510356,\n",
      "        0.43166816,  1.302014  ,  0.5306885 ,  0.48993504], dtype=float32), array([[[[ 1.66219279e-01,  1.42701820e-01, -4.02113283e-03, ...,\n",
      "           6.18828237e-02, -1.74057148e-02, -3.00644431e-02],\n",
      "         [ 9.46945231e-03,  3.87477316e-03,  5.08365929e-02, ...,\n",
      "          -2.77981739e-02,  1.71373668e-03,  6.82722731e-03],\n",
      "         [ 6.32681847e-02,  2.12877709e-02, -1.63465310e-02, ...,\n",
      "           8.80054955e-04,  6.68104272e-03, -1.41139806e-03],\n",
      "         ...,\n",
      "         [ 3.47490981e-03,  8.47019628e-02, -4.07223180e-02, ...,\n",
      "          -1.13523193e-02, -7.48998486e-03,  3.19077494e-03],\n",
      "         [ 5.97234145e-02,  4.97663505e-02, -3.23118735e-03, ...,\n",
      "           1.43114366e-02,  3.03175431e-02, -4.23925705e-02],\n",
      "         [ 1.33459672e-01,  4.95484173e-02, -1.78808011e-02, ...,\n",
      "           2.25385167e-02,  3.02020740e-02, -2.17075031e-02]],\n",
      "\n",
      "        [[ 2.12007999e-01,  2.10127644e-02, -1.47626130e-02, ...,\n",
      "           2.29580477e-02,  1.23102348e-02, -3.08422819e-02],\n",
      "         [-2.62175221e-03,  7.42094172e-03,  6.74030930e-02, ...,\n",
      "          -3.06594316e-02,  1.80578313e-03,  4.27369215e-03],\n",
      "         [ 2.27197763e-02, -1.07841045e-02, -1.31095545e-02, ...,\n",
      "          -1.15751950e-02,  4.18359675e-02, -1.92268589e-03],\n",
      "         ...,\n",
      "         [-2.70304317e-03,  7.41161704e-02, -3.32262330e-02, ...,\n",
      "          -1.10277236e-02,  1.39831286e-02,  5.34419343e-03],\n",
      "         [-3.20506282e-02, -2.40584910e-02, -4.52397857e-03, ...,\n",
      "          -6.04042644e-03,  2.01962605e-01, -5.04491515e-02],\n",
      "         [ 1.68114193e-02, -2.33167298e-02, -1.40886130e-02, ...,\n",
      "          -7.79278344e-03,  1.28428593e-01, -2.58184522e-02]],\n",
      "\n",
      "        [[-5.91698708e-03, -2.26223674e-02,  4.88128467e-03, ...,\n",
      "           4.13784146e-04, -4.84175496e-02,  1.63675251e-03],\n",
      "         [-3.93767562e-03,  9.07397643e-03,  5.36517277e-02, ...,\n",
      "          -2.56106984e-02, -4.17886395e-03,  2.47476017e-03],\n",
      "         [-3.07008922e-02, -1.09781921e-02, -3.69096454e-03, ...,\n",
      "          -1.19221993e-02, -1.39777903e-02,  8.52933805e-03],\n",
      "         ...,\n",
      "         [ 5.83332591e-03,  2.96198055e-02, -3.56571227e-02, ...,\n",
      "          -1.01153394e-02,  5.06090466e-03, -2.86859111e-03],\n",
      "         [-7.80934095e-02, -1.95693132e-02,  2.14814320e-02, ...,\n",
      "           7.42452731e-03,  5.41617945e-02, -2.35790759e-02],\n",
      "         [-7.82641992e-02, -2.47034207e-02,  1.36250593e-02, ...,\n",
      "          -7.53259566e-03, -2.59861015e-02,  4.52143652e-03]]],\n",
      "\n",
      "\n",
      "       [[[ 1.99202523e-01,  5.03257252e-02, -1.93236247e-02, ...,\n",
      "           1.62308700e-02, -1.15369558e-02,  1.55777042e-03],\n",
      "         [-1.38656620e-03,  4.52297740e-03,  6.65066689e-02, ...,\n",
      "          -3.00004911e-02,  1.71904117e-04, -1.11898372e-03],\n",
      "         [ 2.14257818e-02,  1.79782789e-03, -1.76792312e-02, ...,\n",
      "          -6.09106943e-03, -3.21686491e-02, -1.07312342e-03],\n",
      "         ...,\n",
      "         [-1.47800148e-02,  7.77616128e-02, -2.67065037e-02, ...,\n",
      "          -8.10234528e-03, -1.15585206e-02, -5.30505227e-03],\n",
      "         [-1.39283072e-02,  1.69547591e-02, -1.20282415e-02, ...,\n",
      "           1.25513040e-02, -8.44068080e-02, -4.48253192e-02],\n",
      "         [ 2.55671684e-02,  7.02229328e-03, -2.82986648e-02, ...,\n",
      "           1.17048556e-02, -7.34802186e-02, -2.06979234e-02]],\n",
      "\n",
      "        [[-2.59410664e-02, -4.97468375e-02, -2.42083799e-02, ...,\n",
      "          -2.39597876e-02,  2.09030695e-02,  1.69499479e-02],\n",
      "         [-4.78290301e-03,  1.04173329e-02,  8.31823424e-02, ...,\n",
      "          -3.18786576e-02,  3.48328054e-03, -3.56311840e-03],\n",
      "         [-3.81173752e-02, -1.85197107e-02, -1.43900532e-02, ...,\n",
      "          -1.41960718e-02,  3.14613059e-02,  4.11967095e-03],\n",
      "         ...,\n",
      "         [-1.79932006e-02,  7.17700496e-02, -1.99375115e-02, ...,\n",
      "          -6.12784317e-03,  1.66521706e-02, -7.48346280e-03],\n",
      "         [-8.91536921e-02, -4.69055325e-02, -1.37380632e-02, ...,\n",
      "          -8.06835108e-03,  6.04359731e-02, -4.47445139e-02],\n",
      "         [-1.00021079e-01, -3.55393849e-02, -2.46136412e-02, ...,\n",
      "          -7.50665693e-03,  9.11064222e-02, -1.06519591e-02]],\n",
      "\n",
      "        [[-9.84916389e-02, -5.77464141e-02, -4.49889433e-03, ...,\n",
      "          -2.21592579e-02, -9.32130869e-03,  5.57853021e-02],\n",
      "         [ 4.70533501e-03,  1.18583711e-02,  6.85855076e-02, ...,\n",
      "          -2.62385849e-02, -2.82203127e-03, -4.67023626e-03],\n",
      "         [-2.28894763e-02, -7.75412470e-03, -9.86886956e-03, ...,\n",
      "          -1.22523597e-02,  4.30414118e-02,  1.28994938e-02],\n",
      "         ...,\n",
      "         [ 2.93275771e-05,  1.62800644e-02, -2.53228396e-02, ...,\n",
      "          -8.11440870e-03,  9.42004658e-03, -1.69352964e-02],\n",
      "         [-4.56118677e-03, -3.88334878e-02, -8.15101550e-04, ...,\n",
      "          -7.37672672e-05,  2.05828294e-01, -1.84731018e-02],\n",
      "         [-3.79626676e-02, -1.82646457e-02, -7.20302528e-03, ...,\n",
      "          -1.28044421e-03,  1.40015617e-01,  1.13147246e-02]]],\n",
      "\n",
      "\n",
      "       [[[-1.11585744e-02, -4.15539136e-03, -6.83113467e-03, ...,\n",
      "           3.17358202e-03, -6.52846992e-02,  8.59456360e-02],\n",
      "         [-6.14583818e-03,  4.85422462e-03,  5.14627509e-02, ...,\n",
      "          -2.23777443e-02, -1.03412592e-03, -8.19014851e-03],\n",
      "         [-1.00106997e-02, -1.59974187e-03, -1.14092128e-02, ...,\n",
      "          -3.87838250e-03, -3.99293639e-02,  1.13589503e-02],\n",
      "         ...,\n",
      "         [-1.68860350e-02,  5.18255346e-02, -2.66014934e-02, ...,\n",
      "          -1.99763244e-03,  4.35560057e-03, -4.49330434e-02],\n",
      "         [-1.34146223e-02,  6.32185815e-03, -7.33473897e-03, ...,\n",
      "           4.59014578e-03, -2.98611149e-02,  3.69221941e-02],\n",
      "         [-2.88858525e-02, -4.22423892e-03, -1.42897591e-02, ...,\n",
      "           1.11823296e-02, -7.52132908e-02,  1.67242344e-02]],\n",
      "\n",
      "        [[-1.02114283e-01, -5.26558608e-02, -1.00238100e-02, ...,\n",
      "          -1.37801170e-02, -4.94753271e-02,  1.25953421e-01],\n",
      "         [ 2.65349774e-03,  1.04075735e-02,  6.73149154e-02, ...,\n",
      "          -2.37589777e-02,  6.13968645e-04, -9.96601582e-03],\n",
      "         [-1.50703192e-02, -1.28871305e-02, -8.77845287e-03, ...,\n",
      "          -1.01640215e-02, -4.76290248e-02,  1.36717530e-02],\n",
      "         ...,\n",
      "         [-5.43789240e-03,  3.35888155e-02, -2.11151708e-02, ...,\n",
      "          -3.83130647e-03, -1.02301398e-02, -5.32924160e-02],\n",
      "         [-2.21891310e-02, -4.92077954e-02, -1.38867581e-02, ...,\n",
      "          -1.28568839e-02, -9.37007815e-02,  5.59309907e-02],\n",
      "         [-2.61166841e-02, -3.50148268e-02, -1.47816772e-02, ...,\n",
      "          -2.86548026e-03, -1.01101905e-01,  1.94419883e-02]],\n",
      "\n",
      "        [[ 2.73401570e-02, -3.54428887e-02,  1.18577422e-03, ...,\n",
      "           5.02943760e-04,  4.51298095e-02,  1.23520821e-01],\n",
      "         [ 9.48381796e-03,  1.12858564e-02,  5.32916747e-02, ...,\n",
      "          -1.81195941e-02, -1.31687860e-03, -1.01092532e-02],\n",
      "         [ 3.73495184e-02, -7.93821830e-03, -5.94039401e-03, ...,\n",
      "          -7.96878152e-03,  1.53274648e-02,  9.63651482e-03],\n",
      "         ...,\n",
      "         [-2.60413792e-02, -2.53635142e-02, -2.81382054e-02, ...,\n",
      "          -6.63971901e-03, -7.26283342e-03, -5.57855107e-02],\n",
      "         [ 2.67488584e-02, -4.73727398e-02, -3.06198676e-03, ...,\n",
      "          -4.82000969e-03,  4.08617556e-02,  6.99444860e-02],\n",
      "         [ 7.98859298e-02, -2.87372041e-02,  6.38093508e-04, ...,\n",
      "           9.73386108e-04,  4.21557203e-02,  1.60824433e-02]]]],\n",
      "      dtype=float32), array([-0.30912212,  0.36397225,  0.13737613,  0.07717966,  0.9052184 ,\n",
      "        0.08885256,  0.10789118, -0.23106739, -0.6318097 ,  0.18161367,\n",
      "       -0.33391494,  0.1961724 ,  0.43838617,  0.1938708 ,  0.10894354,\n",
      "        0.10315038, -1.0271513 ,  0.05252688,  0.13118458,  0.22851577,\n",
      "       -0.71377224,  0.2154155 , -0.6981962 ,  0.04061132,  0.13955347,\n",
      "        0.28767544,  0.35358745,  0.3937295 ,  0.43452853, -0.48259264,\n",
      "        0.02631121,  0.09220165,  0.05196398,  0.550705  ,  0.32368094,\n",
      "        0.07263482, -0.17745508,  0.3761972 ,  0.39344102,  0.17673127,\n",
      "       -0.15784228,  0.26051855,  0.08342359,  0.08603705, -0.09131282,\n",
      "        0.22932515,  0.2998315 ,  0.13511261, -0.3835829 ,  0.10912544,\n",
      "       -0.53432876,  0.4741787 , -0.0740848 ,  0.30046257,  0.12590808,\n",
      "        0.16480374,  0.2403943 ,  0.23401979, -0.19334187,  0.01663565,\n",
      "        0.27144948,  0.03385786,  0.06076292, -0.5825159 ], dtype=float32), array([[[[-8.90296325e-03,  3.78169715e-02,  1.39756575e-02, ...,\n",
      "          -6.35457635e-02,  2.83470433e-02, -5.54975234e-02],\n",
      "         [-5.66543266e-03, -1.05560187e-03, -2.29203496e-02, ...,\n",
      "          -1.30956469e-03,  2.52478309e-02, -2.95403805e-02],\n",
      "         [-7.85139855e-03, -4.38382570e-03, -1.29586197e-02, ...,\n",
      "           1.22073088e-02,  4.46309976e-04, -2.49174051e-02],\n",
      "         ...,\n",
      "         [-5.82487276e-03,  3.78986611e-03, -1.48562957e-02, ...,\n",
      "           1.27910008e-03,  1.27594778e-02, -1.33825615e-02],\n",
      "         [-1.54342148e-02,  5.62145375e-03,  3.05225104e-02, ...,\n",
      "           1.61413271e-02, -4.20058556e-02, -3.35679092e-02],\n",
      "         [-4.21814434e-03,  2.95577031e-02,  2.57514068e-03, ...,\n",
      "          -2.59456299e-02, -1.35917868e-03, -5.85189313e-02]],\n",
      "\n",
      "        [[-1.03394873e-02,  3.75955850e-02,  6.87777717e-03, ...,\n",
      "          -5.84545359e-02,  3.90824042e-02,  3.70086096e-02],\n",
      "         [ 4.86768410e-03,  4.54719039e-03, -1.62224416e-02, ...,\n",
      "          -2.55017504e-02,  1.88396666e-02, -6.24489179e-03],\n",
      "         [-5.31206699e-03, -1.19874987e-03, -1.11892410e-02, ...,\n",
      "           1.98805016e-02, -1.90202110e-02, -3.79090838e-04],\n",
      "         ...,\n",
      "         [-6.00387994e-03,  7.28632743e-03, -1.53944585e-02, ...,\n",
      "          -5.26854116e-03,  1.68532860e-02,  3.76290455e-03],\n",
      "         [-1.78998355e-02,  1.46924695e-02,  9.51688085e-03, ...,\n",
      "           1.07260697e-01,  2.80233864e-02, -1.89538375e-02],\n",
      "         [-3.70884268e-03,  3.08528487e-02, -5.70769282e-03, ...,\n",
      "          -3.34496573e-02, -4.65932442e-03,  1.17018344e-02]],\n",
      "\n",
      "        [[-1.01951612e-02,  1.21747078e-02,  1.11724688e-02, ...,\n",
      "           2.69737188e-02, -2.22921986e-02,  6.45900667e-02],\n",
      "         [ 1.22869862e-02,  6.45142654e-03, -3.07416776e-03, ...,\n",
      "          -1.61525756e-02, -2.23605409e-02,  1.09485257e-02],\n",
      "         [-7.09734391e-03, -5.40411752e-03, -9.43870191e-03, ...,\n",
      "          -1.52021297e-03, -2.17991360e-02, -3.77143058e-03],\n",
      "         ...,\n",
      "         [-5.21149486e-03,  1.03359867e-03, -7.52882753e-03, ...,\n",
      "          -1.92244481e-02, -6.39424520e-03,  3.69722745e-03],\n",
      "         [-1.53886806e-02, -1.34543087e-02,  5.72274020e-03, ...,\n",
      "           5.47401682e-02, -6.08180426e-02, -2.23444626e-02],\n",
      "         [-3.45917395e-03,  2.13373415e-02, -2.14421172e-02, ...,\n",
      "          -6.91150427e-02, -1.54741071e-02,  4.44306619e-02]]],\n",
      "\n",
      "\n",
      "       [[[-1.23298699e-02, -1.91225596e-02,  1.29218930e-02, ...,\n",
      "           4.33554836e-02,  1.26128104e-02, -5.96396960e-02],\n",
      "         [-1.31860480e-03, -9.51261446e-03, -1.85527243e-02, ...,\n",
      "           2.88356710e-02,  2.38556787e-02, -4.06758748e-02],\n",
      "         [-4.25214088e-03, -6.78345608e-03, -1.38743157e-02, ...,\n",
      "           2.22070217e-02,  1.34524666e-02, -2.03017425e-02],\n",
      "         ...,\n",
      "         [-7.83586409e-03, -2.57805572e-03, -1.08931847e-02, ...,\n",
      "           1.92594435e-02,  1.59353893e-02, -1.89792961e-02],\n",
      "         [-1.94495711e-02, -3.60343307e-02,  6.04022592e-02, ...,\n",
      "          -2.22710613e-02, -5.43530397e-02, -4.17403802e-02],\n",
      "         [-4.36492451e-03, -1.08945146e-02, -3.35957273e-03, ...,\n",
      "           1.72520187e-02, -1.28518986e-02, -4.72729132e-02]],\n",
      "\n",
      "        [[-1.45433825e-02, -3.68030928e-02,  3.51226889e-02, ...,\n",
      "           5.09550609e-03, -8.08145478e-02,  1.02682762e-01],\n",
      "         [ 7.81208277e-03, -1.63471382e-02, -8.99212994e-03, ...,\n",
      "          -3.65188569e-02, -8.37247167e-03, -7.34759448e-03],\n",
      "         [-1.76124368e-03, -4.82094986e-03, -1.33856600e-02, ...,\n",
      "           1.97411682e-02, -6.24130992e-03,  2.11908761e-03],\n",
      "         ...,\n",
      "         [-8.09418783e-03, -5.44183236e-03, -9.95591376e-03, ...,\n",
      "           1.03512814e-03, -1.01502263e-03,  9.89024434e-03],\n",
      "         [-2.14152560e-02, -1.22487647e-02,  4.47364189e-02, ...,\n",
      "           1.18361183e-01, -1.86819024e-02,  5.11289574e-02],\n",
      "         [-3.61343310e-03, -1.55030079e-02, -1.55327516e-02, ...,\n",
      "           2.49069761e-02, -6.95429044e-03,  1.30494153e-02]],\n",
      "\n",
      "        [[-1.17718522e-02, -2.43640933e-02,  2.16566566e-02, ...,\n",
      "           1.52593330e-01, -1.00578181e-02,  8.74510705e-02],\n",
      "         [ 1.56845041e-02, -1.70876738e-02, -1.32727087e-03, ...,\n",
      "           3.55747603e-02, -4.06013057e-02,  2.82184500e-02],\n",
      "         [-3.66246584e-03, -9.08438675e-03, -8.76258500e-03, ...,\n",
      "          -7.32058019e-04, -1.63256414e-02,  8.90959927e-04],\n",
      "         ...,\n",
      "         [-6.92374213e-03, -1.25479233e-02, -7.42880348e-03, ...,\n",
      "           3.50585720e-03, -2.07631718e-02,  1.39397075e-02],\n",
      "         [-1.86536163e-02, -9.74296406e-03, -1.49605959e-03, ...,\n",
      "          -1.41743785e-02, -1.41348932e-02,  5.55095226e-02],\n",
      "         [-1.87194371e-03, -7.81994499e-03, -1.14830295e-02, ...,\n",
      "          -5.49505465e-02, -8.39654077e-03,  3.37504521e-02]]],\n",
      "\n",
      "\n",
      "       [[[-7.51168234e-03, -1.57704763e-02,  4.40593623e-03, ...,\n",
      "           8.08628425e-02,  1.54139521e-02, -3.71525325e-02],\n",
      "         [ 3.67319165e-03, -4.84256167e-03, -9.42679588e-03, ...,\n",
      "           1.78013276e-02,  1.10012209e-02, -3.05487644e-02],\n",
      "         [-5.12040500e-03, -2.92832567e-03, -1.70742609e-02, ...,\n",
      "          -1.19602494e-03,  2.55921856e-02, -2.38123816e-02],\n",
      "         ...,\n",
      "         [-6.98121730e-03, -5.92697598e-03, -4.53395769e-03, ...,\n",
      "           1.43473689e-02,  1.32299559e-02, -1.86933577e-02],\n",
      "         [-1.64366160e-02, -2.88906470e-02,  5.16189029e-03, ...,\n",
      "           6.27482450e-03,  3.09459344e-02, -3.86791453e-02],\n",
      "         [ 7.87568372e-03,  3.53289805e-02, -8.80536530e-03, ...,\n",
      "           1.03661101e-02,  1.50152808e-02, -2.25142129e-02]],\n",
      "\n",
      "        [[-8.03535990e-03, -6.21744758e-03,  3.11630405e-02, ...,\n",
      "           1.99134022e-01, -6.17154641e-03,  1.39599340e-02],\n",
      "         [ 1.37082441e-02, -4.04076884e-03, -9.80419107e-03, ...,\n",
      "           5.20565063e-02,  6.79946598e-03, -1.67599937e-04],\n",
      "         [-2.68182647e-03,  9.37074132e-04, -1.77672971e-02, ...,\n",
      "           7.02630170e-03,  1.19604953e-02, -2.38061114e-03],\n",
      "         ...,\n",
      "         [-6.67789765e-03, -8.06673337e-03, -4.78939526e-03, ...,\n",
      "           2.99814232e-02,  3.63594829e-03,  6.42562099e-03],\n",
      "         [-2.00417619e-02, -5.05231880e-02,  2.04375144e-02, ...,\n",
      "          -9.16022658e-02, -2.39189416e-02,  5.67581393e-02],\n",
      "         [ 9.37450770e-03,  4.14647050e-02, -1.89982001e-02, ...,\n",
      "           9.74066462e-03,  2.91863047e-02, -2.41922438e-02]],\n",
      "\n",
      "        [[-7.34003959e-03,  7.00018462e-03,  1.78023316e-02, ...,\n",
      "           4.10795175e-02,  1.60309300e-02, -6.50887610e-03],\n",
      "         [ 1.98623370e-02, -4.18649800e-03, -1.23496391e-02, ...,\n",
      "          -1.08256517e-03, -6.54376950e-03,  1.12769182e-03],\n",
      "         [-4.14572377e-03, -3.37855937e-03, -1.22076506e-02, ...,\n",
      "          -1.23778330e-02,  1.39588572e-03, -7.97146652e-03],\n",
      "         ...,\n",
      "         [-5.31869614e-03, -1.09051373e-02, -5.76505670e-03, ...,\n",
      "          -1.08993258e-02, -4.60993918e-03, -3.81152914e-03],\n",
      "         [-1.69911478e-02, -3.15449387e-02,  8.09636060e-03, ...,\n",
      "          -1.06819831e-02, -2.92898342e-02,  7.60448575e-02],\n",
      "         [ 9.20531712e-03,  3.90281789e-02, -1.15968632e-02, ...,\n",
      "          -2.66397055e-02,  2.04669069e-02, -8.92718323e-03]]]],\n",
      "      dtype=float32), array([-4.5777660e-02,  6.4407811e-02, -3.1368658e-02,  8.6917542e-02,\n",
      "        1.2785070e-01,  2.4616894e-01,  1.6408961e-01,  2.3979376e-01,\n",
      "        2.2164847e-01,  1.4246197e-01,  3.3131771e-02,  1.4955571e-01,\n",
      "        1.1550413e-02, -1.8516029e-04,  2.7014315e-01,  2.4461022e-01,\n",
      "        2.7350754e-01,  2.7142024e-01,  2.7011135e-01,  2.7027962e-01,\n",
      "        2.2164130e-01,  1.8953906e-01,  3.9793090e-03,  6.1518628e-02,\n",
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      "       -1.4714201e-02,  6.5621443e-02,  3.1406230e-01, -7.7050015e-02,\n",
      "        1.0462435e-01,  2.0993298e-01, -7.4100301e-02, -8.5880190e-02,\n",
      "        1.3652268e-01,  2.3663981e-01,  3.0105148e-02, -3.6816043e-03,\n",
      "        7.6591093e-03,  3.0664349e-01,  1.3023020e-01,  4.1607008e-03,\n",
      "        2.7055809e-01,  2.5207508e-01,  2.8904697e-01,  1.2730265e-01,\n",
      "        2.8076398e-01, -4.4764560e-02, -4.2357225e-02,  6.2559925e-02,\n",
      "        1.0018661e-01, -9.9623539e-02,  1.0176195e-01,  2.3699294e-01,\n",
      "        7.8422479e-02,  1.2831993e-01,  1.1392979e-01, -1.3174531e-02,\n",
      "       -1.0383477e-01,  2.2861110e-01,  9.1953836e-02,  6.5147914e-02,\n",
      "        1.9676815e-01,  7.1536556e-02,  2.6198325e-01, -6.4189523e-02,\n",
      "        4.9607549e-02, -6.1662562e-02,  1.3248019e-01,  9.0231813e-02,\n",
      "        1.0324936e-01,  2.2680637e-01, -3.3503436e-02, -1.7922063e-01,\n",
      "        2.0180932e-01,  5.2303892e-02,  1.7740984e-01,  2.1679863e-01,\n",
      "        1.2819616e-01,  1.6143866e-01,  1.6376132e-01,  3.5884404e-01,\n",
      "       -5.2223109e-02,  2.1117201e-01,  1.4626507e-01,  1.0392818e-01,\n",
      "        2.3689806e-01, -1.7589157e-02,  1.4187863e-01, -1.5676373e-01,\n",
      "        5.5077035e-02,  1.7919958e-01,  1.9530067e-01,  4.9757544e-02,\n",
      "        1.4647865e-01,  1.5057972e-01,  4.9321059e-02,  2.2425601e-01,\n",
      "        2.8004406e-02,  4.6344060e-02,  5.4642409e-02,  3.2176018e-01,\n",
      "       -2.3094574e-02,  5.1442902e-03,  2.2401743e-02,  1.9448744e-01,\n",
      "       -9.5472252e-03,  2.5650701e-01,  1.3772449e-01,  2.8766793e-01,\n",
      "       -9.4692776e-04, -8.9352727e-03,  7.2267972e-02,  1.9602686e-02,\n",
      "        2.5652054e-01, -3.6785334e-02,  3.2890160e-02,  2.6736060e-01,\n",
      "       -1.0560317e-01,  3.7151142e-03,  2.8068131e-01, -8.9383557e-02,\n",
      "        6.6791281e-02,  3.1667921e-01,  9.5985740e-02,  1.3152032e-01],\n",
      "      dtype=float32), array([[[[-2.30123661e-03, -5.89181297e-03,  3.96523578e-03, ...,\n",
      "           8.69934738e-04,  4.31257114e-03,  2.39815353e-03],\n",
      "         [ 6.93455897e-03,  1.77669781e-03,  1.87194608e-02, ...,\n",
      "          -3.17397565e-02, -4.21442185e-03, -1.76308881e-02],\n",
      "         [-1.27900802e-02, -6.50780788e-03, -4.10286430e-03, ...,\n",
      "           2.31482647e-03, -4.67822663e-02, -3.75668402e-03],\n",
      "         ...,\n",
      "         [-4.75286070e-04, -2.96283532e-02,  3.03538516e-02, ...,\n",
      "           1.51648500e-03, -2.71695852e-02, -1.84430566e-03],\n",
      "         [ 1.41743217e-02, -3.64480889e-04, -2.33754283e-03, ...,\n",
      "          -2.28237733e-02, -1.60014853e-02,  2.46631019e-02],\n",
      "         [ 1.18608214e-02, -2.77200472e-02, -2.48606838e-02, ...,\n",
      "           4.10957001e-02,  5.57063818e-02, -2.19316985e-02]],\n",
      "\n",
      "        [[-1.38294604e-03, -5.54690696e-03, -1.06138433e-03, ...,\n",
      "           1.82250992e-03, -3.59015947e-04,  9.99924168e-03],\n",
      "         [ 6.75601466e-03,  1.10390119e-03,  2.18637586e-02, ...,\n",
      "          -3.56409214e-02, -2.45026941e-03, -6.04407070e-03],\n",
      "         [-1.35804852e-02, -8.60609580e-03,  1.28111104e-02, ...,\n",
      "          -1.01041503e-03, -3.83789763e-02,  1.18479142e-02],\n",
      "         ...,\n",
      "         [-3.61973490e-03,  4.19556797e-02,  5.89246452e-02, ...,\n",
      "           3.10248807e-02, -1.03577944e-02, -2.23138258e-02],\n",
      "         [ 1.48718422e-02,  1.86822154e-02, -3.46057713e-02, ...,\n",
      "          -2.32062247e-02, -1.91165209e-02,  8.65985733e-03],\n",
      "         [-5.93924429e-03,  1.08361673e-02,  2.81376876e-02, ...,\n",
      "           1.17414417e-02,  8.40279087e-02, -6.45612031e-02]],\n",
      "\n",
      "        [[-9.91582056e-04,  4.55033936e-04, -9.36682150e-03, ...,\n",
      "           3.41384741e-03, -5.51316887e-03,  1.24911871e-02],\n",
      "         [ 1.07221371e-02, -3.19505017e-03,  2.47716717e-02, ...,\n",
      "          -1.63276494e-02,  8.99969228e-03, -3.90315428e-03],\n",
      "         [ 4.23295191e-03,  1.27883134e-02,  1.17508639e-02, ...,\n",
      "          -1.22649251e-02,  2.91934842e-03,  1.42700337e-02],\n",
      "         ...,\n",
      "         [ 2.98261386e-03,  4.09221351e-02,  2.68427730e-02, ...,\n",
      "           9.12894122e-03,  2.94868927e-02, -3.27900308e-03],\n",
      "         [ 8.43982119e-03, -1.85558088e-02,  1.26812793e-02, ...,\n",
      "          -9.75666288e-03,  6.52654376e-03, -5.94963925e-03],\n",
      "         [-3.94721312e-04,  6.81950822e-02,  8.70230980e-03, ...,\n",
      "           1.19850151e-02,  9.72716659e-02, -2.87150545e-03]]],\n",
      "\n",
      "\n",
      "       [[[-6.72967779e-03, -6.32101856e-03,  1.24791730e-03, ...,\n",
      "          -5.51869674e-03,  5.54611022e-03,  2.74169119e-03],\n",
      "         [-1.90283672e-03,  2.39737774e-03,  7.45097920e-03, ...,\n",
      "          -6.27250373e-02, -1.16790943e-02,  1.36177419e-02],\n",
      "         [-2.43349690e-02, -9.58706811e-03,  5.12539688e-03, ...,\n",
      "           2.03479634e-04, -5.18149063e-02, -1.06236124e-02],\n",
      "         ...,\n",
      "         [-8.23690323e-04, -4.52437773e-02,  4.49064933e-02, ...,\n",
      "          -1.48973670e-02, -3.74213159e-02, -2.50751078e-02],\n",
      "         [ 1.20533947e-02, -4.14178381e-03, -2.23253462e-02, ...,\n",
      "          -8.56044441e-02, -2.15003770e-02,  5.37014790e-02],\n",
      "         [ 1.72066651e-02, -2.44826339e-02, -1.10037383e-02, ...,\n",
      "           4.80076745e-02,  3.21536772e-02, -2.96083037e-02]],\n",
      "\n",
      "        [[-4.56147827e-03, -4.65280237e-03, -8.31684005e-03, ...,\n",
      "          -5.54831931e-03,  1.18862418e-03,  9.64665227e-03],\n",
      "         [ 2.62077316e-03,  5.77449473e-03,  1.19720455e-02, ...,\n",
      "          -6.83966503e-02,  1.35026115e-03,  5.91752259e-03],\n",
      "         [-2.97386330e-02, -3.90352937e-03,  1.28964186e-02, ...,\n",
      "           6.27378060e-04, -4.46732230e-02,  1.30419582e-02],\n",
      "         ...,\n",
      "         [-2.97931256e-03,  7.04262778e-02,  4.67705168e-02, ...,\n",
      "          -2.63439678e-02, -2.75591165e-02, -3.54478620e-02],\n",
      "         [ 9.99665074e-03,  1.62281040e-02,  8.01674929e-03, ...,\n",
      "          -7.52160326e-02, -1.95330698e-02,  7.38804974e-03],\n",
      "         [ 9.53063485e-04,  5.06784841e-02,  2.04059742e-02, ...,\n",
      "           4.51842928e-03,  4.47761454e-02, -7.42928088e-02]],\n",
      "\n",
      "        [[-2.81608710e-03, -3.68988403e-04, -9.52884182e-03, ...,\n",
      "          -1.62106077e-03, -4.23267297e-03,  1.35960653e-02],\n",
      "         [ 7.26349046e-03,  3.17442766e-03,  2.06175316e-02, ...,\n",
      "          -3.99732366e-02,  2.22933367e-02, -7.41374539e-03],\n",
      "         [-1.37994336e-02,  2.29467135e-02, -6.29038131e-03, ...,\n",
      "          -5.79428207e-03, -1.50836250e-02,  1.31318215e-02],\n",
      "         ...,\n",
      "         [ 2.00410513e-03,  3.91520634e-02, -3.18683162e-02, ...,\n",
      "          -3.54397879e-03, -8.54784995e-03,  1.36236998e-03],\n",
      "         [ 5.49011305e-03, -1.51369004e-02,  2.77213678e-02, ...,\n",
      "          -2.81145964e-02,  9.72870039e-04, -6.28185738e-03],\n",
      "         [ 7.10674515e-03,  8.02865252e-02,  6.19208254e-03, ...,\n",
      "           1.03570186e-02,  7.63423666e-02, -7.15952739e-03]]],\n",
      "\n",
      "\n",
      "       [[[-1.08065400e-02, -7.45501043e-03, -5.10151871e-03, ...,\n",
      "          -4.49332688e-03,  7.89736584e-03, -3.35464210e-05],\n",
      "         [-6.12053089e-03, -1.79325249e-02, -1.11700445e-02, ...,\n",
      "          -4.62095961e-02, -4.28734301e-03,  2.02734675e-03],\n",
      "         [-2.64673289e-02, -1.31910611e-02,  1.76633168e-02, ...,\n",
      "          -6.08402630e-03, -3.14402916e-02, -1.81844179e-02],\n",
      "         ...,\n",
      "         [ 1.37444083e-02, -2.84396205e-02,  1.88047513e-02, ...,\n",
      "          -1.93887874e-02, -3.75849679e-02, -2.45505963e-02],\n",
      "         [ 7.21093081e-03, -1.23673957e-02, -5.60066104e-03, ...,\n",
      "          -4.09601741e-02, -1.16450675e-02,  3.63268666e-02],\n",
      "         [ 1.34990485e-02, -1.55054999e-03,  5.54364361e-03, ...,\n",
      "           3.92058305e-02,  2.16900297e-02, -1.13665536e-02]],\n",
      "\n",
      "        [[-8.32169224e-03, -6.18967554e-03, -1.13438964e-02, ...,\n",
      "          -3.40542640e-03,  3.85991205e-03,  7.26305228e-03],\n",
      "         [-2.55200220e-03, -1.41635584e-02, -3.80055211e-03, ...,\n",
      "          -5.45916855e-02,  2.17752811e-03, -5.23553835e-03],\n",
      "         [-3.21345851e-02, -2.83276942e-03, -2.20403913e-03, ...,\n",
      "          -1.67740230e-02, -3.22663859e-02,  2.23135133e-03],\n",
      "         ...,\n",
      "         [ 3.27714277e-03,  8.55310634e-02, -2.84323972e-02, ...,\n",
      "           2.72681676e-02, -3.39798741e-02, -1.60314962e-02],\n",
      "         [ 3.99958156e-03,  1.23148263e-02,  3.01949140e-02, ...,\n",
      "          -5.21975756e-02, -1.14355180e-02, -7.70385157e-07],\n",
      "         [-1.03606293e-02,  7.14352727e-02,  1.61257926e-02, ...,\n",
      "          -1.47721104e-04,  9.00403503e-03, -3.94313596e-02]],\n",
      "\n",
      "        [[-5.75947622e-03,  4.07667161e-04, -5.18753566e-03, ...,\n",
      "           8.14088504e-04, -4.34151705e-04,  1.14657767e-02],\n",
      "         [ 4.41048900e-03, -3.57159856e-03,  3.01857502e-03, ...,\n",
      "          -3.98184508e-02,  1.49278138e-02, -8.20163079e-03],\n",
      "         [-2.44483184e-02,  2.32945569e-02, -2.34904625e-02, ...,\n",
      "          -1.79554094e-02, -3.21781076e-02,  1.07798241e-02],\n",
      "         ...,\n",
      "         [ 5.12963720e-03,  2.35215593e-02, -3.53378877e-02, ...,\n",
      "           3.48278917e-02, -2.01826524e-02,  2.35197158e-03],\n",
      "         [ 3.45730968e-03, -1.26461498e-02,  1.03930170e-02, ...,\n",
      "          -3.20292413e-02, -6.37839548e-04, -7.48459855e-03],\n",
      "         [ 3.67492763e-03,  6.75461590e-02,  9.46969260e-03, ...,\n",
      "           4.72220499e-03,  4.39464301e-02,  6.21765293e-03]]]],\n",
      "      dtype=float32), array([-0.06418542, -0.11568324, -0.13206749,  0.0608536 ,  0.2689488 ,\n",
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      "       -0.2100034 ,  0.09921633, -0.01273028, -0.10428324,  0.11836739,\n",
      "       -0.21125603, -0.22762309,  0.44482312,  0.04079875, -0.30996218,\n",
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      "       -0.16100882, -0.08115347,  0.2567695 ,  0.09040406,  0.03538936,\n",
      "        0.23496653, -0.59533477,  0.280156  ,  0.02269722,  0.15407647,\n",
      "        0.10761564,  0.15549968, -0.27726585,  0.14555272, -0.07341251,\n",
      "        0.0086478 , -0.08294716,  0.16158143, -0.17374775, -0.00751741,\n",
      "       -0.2599541 ,  0.0932769 ,  0.35911047, -0.09218857,  0.08189061,\n",
      "       -0.24053718, -0.12922512, -0.01862046, -0.11662732, -0.11673097,\n",
      "       -0.1816601 ,  0.16486758, -0.04786587, -0.04397993,  0.14281501,\n",
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      "       -0.30141872,  0.28632042,  0.10882995,  0.14509913, -0.04585594,\n",
      "       -0.08846492,  0.13556598,  0.16782367,  0.07018866, -0.10737082,\n",
      "        0.44746682, -0.08115204, -0.04683498,  0.18236732, -0.01913908,\n",
      "       -0.0207867 ,  0.37967235,  0.07472062, -0.09300313,  0.3070309 ,\n",
      "        0.01550341,  0.15720516, -0.18576111,  0.07595339, -0.28695267,\n",
      "        0.20711343, -0.22942008,  0.17479539,  0.2029741 , -0.44217134,\n",
      "        0.04695964, -0.14719886, -0.02473967,  0.14871362,  0.00526441,\n",
      "        0.00490166, -0.17585608, -0.00920897, -0.25866592, -0.01254782,\n",
      "        0.04957367,  0.173761  , -0.01913427, -0.1067858 ,  0.01878852,\n",
      "       -0.08317517,  0.06669547,  0.01067064,  0.37834755,  0.11717828,\n",
      "        0.20528455,  0.2403423 ,  0.27507326], dtype=float32), array([[[[ 2.48631509e-03,  3.29096033e-03, -3.13071609e-02, ...,\n",
      "           4.71851649e-03,  6.10046380e-04,  1.08059337e-02],\n",
      "         [ 1.36040282e-02,  3.80906137e-03, -3.50438058e-02, ...,\n",
      "           8.50365497e-03,  4.99894470e-03,  2.45373725e-04],\n",
      "         [-1.02960337e-02,  1.11045251e-02, -1.05560301e-02, ...,\n",
      "           1.18119251e-02,  4.14630165e-03,  1.04994141e-02],\n",
      "         ...,\n",
      "         [ 2.14050314e-03,  2.17348989e-03, -4.09283377e-02, ...,\n",
      "          -8.34189355e-03,  2.35738587e-02, -1.85471829e-02],\n",
      "         [ 1.61261633e-02,  8.04742594e-05, -3.95269990e-02, ...,\n",
      "          -3.94453527e-03,  8.42030905e-03, -6.98040065e-04],\n",
      "         [-3.51465750e-03,  1.08316056e-02, -2.23830044e-02, ...,\n",
      "           1.92155335e-02,  4.21972945e-03, -1.55707300e-02]],\n",
      "\n",
      "        [[ 6.11093594e-03,  5.44822821e-03,  1.57541838e-02, ...,\n",
      "           5.60781872e-03,  1.93978904e-03,  1.49202365e-02],\n",
      "         [-3.13426033e-02,  1.45718846e-02,  1.18744513e-02, ...,\n",
      "           1.21863568e-02,  1.49443159e-02,  2.60730181e-03],\n",
      "         [-2.32275911e-02,  2.08911151e-02,  1.11537259e-02, ...,\n",
      "           2.36150771e-02,  1.06090466e-02,  4.31246823e-03],\n",
      "         ...,\n",
      "         [ 2.83093913e-03,  5.63543057e-03,  1.72611587e-02, ...,\n",
      "          -2.76210159e-03,  3.27554196e-02, -1.73731633e-02],\n",
      "         [ 4.87203449e-02,  1.24137765e-02,  3.64911221e-02, ...,\n",
      "           9.30428132e-03,  5.34809241e-03,  6.80550281e-03],\n",
      "         [-2.03473382e-02,  1.38210657e-03, -2.35674269e-02, ...,\n",
      "           3.24176252e-02,  2.19412390e-02, -3.02630980e-02]],\n",
      "\n",
      "        [[ 1.05408970e-02,  7.44795799e-03, -3.36561389e-02, ...,\n",
      "           2.62853602e-04, -6.13683043e-03,  1.33312661e-02],\n",
      "         [-3.32584940e-02,  1.55691411e-02, -2.89147953e-04, ...,\n",
      "          -3.60562908e-03,  1.49507467e-02,  7.65243312e-03],\n",
      "         [ 3.94205609e-03,  1.48937441e-02, -1.59246754e-02, ...,\n",
      "           1.39236227e-02,  3.22588254e-03,  6.02472946e-03],\n",
      "         ...,\n",
      "         [ 9.61219659e-04, -2.27980153e-03, -4.54332307e-02, ...,\n",
      "          -8.10870901e-03,  3.84118455e-03, -1.65238492e-02],\n",
      "         [ 2.77294349e-02,  1.70650017e-02,  2.01114286e-02, ...,\n",
      "           8.16452038e-03,  4.37149359e-03,  8.13044887e-03],\n",
      "         [-1.77335721e-02,  1.02985008e-02, -3.90648767e-02, ...,\n",
      "           2.65211053e-02,  1.88891459e-02, -1.68677885e-02]]],\n",
      "\n",
      "\n",
      "       [[[ 4.49297950e-03, -3.98075627e-03,  1.72210410e-02, ...,\n",
      "           8.42886325e-03, -1.04969469e-04,  5.74578904e-03],\n",
      "         [-4.00591874e-03, -2.41769738e-02, -1.10928714e-02, ...,\n",
      "          -1.52679645e-02,  6.81134174e-03, -3.05488333e-03],\n",
      "         [-1.56376939e-02, -5.00010047e-03,  4.81709233e-03, ...,\n",
      "           5.51846065e-03,  4.62341262e-03,  5.28823584e-03],\n",
      "         ...,\n",
      "         [ 3.78267164e-03, -7.20065041e-03,  2.24571675e-02, ...,\n",
      "           1.21734152e-02,  1.66180804e-02, -2.85227131e-02],\n",
      "         [ 3.54970875e-03, -7.91174546e-03,  6.50567329e-03, ...,\n",
      "           5.75853884e-03, -5.25432348e-04, -3.29109584e-03],\n",
      "         [ 2.42216233e-03, -1.42111657e-02,  3.40532698e-02, ...,\n",
      "          -8.09886493e-03,  6.40509045e-03, -2.32355390e-02]],\n",
      "\n",
      "        [[ 6.58771209e-03, -3.84311262e-03,  6.62338808e-02, ...,\n",
      "           5.46263764e-03,  2.69173388e-03,  9.38945077e-03],\n",
      "         [-5.54355457e-02, -2.00809669e-02,  3.39177996e-02, ...,\n",
      "          -2.65794396e-02,  7.77757354e-03,  1.45330857e-02],\n",
      "         [-5.56085445e-03, -1.38856005e-02,  3.95981222e-02, ...,\n",
      "          -7.25830847e-04,  4.43886919e-03,  2.62149167e-03],\n",
      "         ...,\n",
      "         [ 2.70528113e-03, -5.45389997e-03,  8.94473717e-02, ...,\n",
      "           2.45114118e-02,  5.10585234e-02, -3.43545228e-02],\n",
      "         [ 5.07756323e-02,  1.51661120e-03,  8.18592831e-02, ...,\n",
      "           2.16385573e-02,  1.26126707e-02,  1.81507389e-03],\n",
      "         [-2.27336828e-02, -3.00953630e-02,  3.85253243e-02, ...,\n",
      "          -9.51036997e-03,  8.18072818e-03, -3.70927304e-02]],\n",
      "\n",
      "        [[ 5.95341111e-03,  8.94323515e-04,  1.05835460e-02, ...,\n",
      "           4.89834580e-04,  5.24436589e-04,  9.38476902e-03],\n",
      "         [-4.07811590e-02,  4.78578452e-03,  1.44789219e-02, ...,\n",
      "          -5.62724238e-03, -4.85808152e-04,  1.29066659e-02],\n",
      "         [ 1.34129170e-02, -1.18021872e-02,  4.19147732e-03, ...,\n",
      "          -8.13282002e-03, -4.46207495e-03,  8.42996407e-03],\n",
      "         ...,\n",
      "         [ 1.52341533e-03, -6.47965074e-03,  1.00679537e-02, ...,\n",
      "           1.56302936e-02,  3.72295864e-02, -3.21733207e-02],\n",
      "         [ 3.96381617e-02,  1.58769619e-02,  3.92291285e-02, ...,\n",
      "           1.72687024e-02,  2.41979603e-02,  5.91078307e-03],\n",
      "         [-1.79783162e-02, -2.94427648e-02,  1.28269298e-02, ...,\n",
      "          -1.60066597e-02, -5.16920770e-03, -2.00248957e-02]]],\n",
      "\n",
      "\n",
      "       [[[ 4.85232845e-03, -2.46043317e-03, -9.62745398e-03, ...,\n",
      "           1.07441526e-02, -2.84585054e-03, -1.90984423e-03],\n",
      "         [-1.19528649e-02, -1.80358142e-02, -3.36395353e-02, ...,\n",
      "          -1.47682996e-02,  1.02861486e-02, -3.36993136e-03],\n",
      "         [ 4.98365518e-03, -1.66885350e-02, -1.20581677e-02, ...,\n",
      "          -1.59126818e-02,  1.31858326e-02,  2.94562749e-04],\n",
      "         ...,\n",
      "         [-5.69525547e-03, -1.74089391e-02, -3.64525653e-02, ...,\n",
      "           7.06359418e-03, -1.58607736e-02, -2.61105206e-02],\n",
      "         [-3.87686165e-03, -2.40983404e-02, -5.60978092e-02, ...,\n",
      "          -1.22877983e-02, -3.04629817e-03, -1.03539054e-03],\n",
      "         [ 1.35685736e-02, -2.09947508e-02, -1.52395582e-02, ...,\n",
      "          -2.87993886e-02,  1.74087044e-02, -1.86969731e-02]],\n",
      "\n",
      "        [[ 1.45290594e-03, -6.42601680e-03,  1.14819771e-02, ...,\n",
      "           1.17859095e-02,  8.51634599e-04, -2.82667065e-03],\n",
      "         [-2.43061744e-02, -1.82640739e-02,  1.50347399e-02, ...,\n",
      "          -2.63812207e-02,  2.30616182e-02,  4.71212249e-03],\n",
      "         [ 1.60123650e-02, -1.25727728e-02,  1.22705530e-02, ...,\n",
      "          -1.90321188e-02,  1.43274162e-02, -9.16460936e-04],\n",
      "         ...,\n",
      "         [ 2.31739320e-03, -1.62090212e-02,  1.71782896e-02, ...,\n",
      "           1.23864021e-02,  7.53226131e-03, -2.98976954e-02],\n",
      "         [ 1.98312830e-02, -1.12192128e-02,  1.70756541e-02, ...,\n",
      "          -1.62761565e-02, -2.72694766e-03, -1.83170743e-03],\n",
      "         [-3.89542966e-03, -3.53942066e-02, -1.64013300e-02, ...,\n",
      "          -4.73240092e-02,  1.97671168e-02, -2.87492648e-02]],\n",
      "\n",
      "        [[ 1.00636412e-03, -5.19909943e-03, -3.75667326e-02, ...,\n",
      "           7.44984252e-03,  4.31809276e-05, -3.22302600e-04],\n",
      "         [-1.04536200e-02, -9.70086199e-04,  1.94423497e-02, ...,\n",
      "          -1.29293650e-04,  9.82195791e-03, -1.07756234e-03],\n",
      "         [ 5.58500132e-03, -1.86028529e-03, -8.09577946e-03, ...,\n",
      "          -6.18272461e-03,  1.71643522e-04,  7.06695300e-03],\n",
      "         ...,\n",
      "         [-3.72283580e-03, -1.86357144e-02, -4.54351157e-02, ...,\n",
      "           1.30783571e-02,  3.22722102e-04, -3.35289426e-02],\n",
      "         [ 1.59978885e-02,  8.11644178e-03, -1.23626338e-02, ...,\n",
      "           2.87816068e-03,  2.04773736e-03, -6.40190148e-04],\n",
      "         [-4.09534993e-03, -3.75131555e-02, -3.33721489e-02, ...,\n",
      "          -4.82492335e-02,  3.41874664e-03, -1.31510263e-02]]]],\n",
      "      dtype=float32), array([-7.43588656e-02, -7.82142300e-03,  1.99858069e-01,  5.86250983e-02,\n",
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      "       -9.05257389e-02, -1.03295766e-01, -3.65283228e-02, -5.99550568e-02,\n",
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      "       -1.55145142e-04, -2.77894381e-02, -5.92041761e-02,  7.75184184e-02,\n",
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      "       -8.14075861e-03, -3.03441286e-02, -2.73723528e-03,  1.04369465e-02,\n",
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      "       -2.94738077e-02,  9.18932706e-02, -3.09058055e-02,  2.83562243e-02,\n",
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      "       -2.41919458e-02, -6.04458451e-02,  5.60694151e-02,  3.48671922e-03,\n",
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      "       -9.42966118e-02, -9.68727842e-03, -1.33719174e-02,  1.70798182e-01,\n",
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      "       -6.21608971e-03,  3.39489020e-02, -1.58346687e-02,  6.97900355e-02,\n",
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      "       -4.93083969e-02, -9.13676899e-03,  7.50048086e-02,  1.19404271e-01,\n",
      "        4.21564467e-02, -3.56978104e-02,  6.22963049e-02, -5.56988753e-02,\n",
      "       -8.98351986e-03,  4.67670858e-02,  1.15553811e-01,  1.54885754e-03,\n",
      "       -6.53147623e-02, -2.76188087e-03, -2.88737379e-02,  3.49496126e-01,\n",
      "        1.32759318e-01,  7.41247907e-02,  9.06468648e-03,  8.58006533e-04,\n",
      "        2.35754419e-02, -3.43079567e-02,  5.42532057e-02,  3.14495265e-02,\n",
      "        3.93943256e-03,  6.62599280e-02,  8.03745165e-02, -2.91163549e-02,\n",
      "       -1.98691040e-02,  5.25035225e-02, -4.46449406e-02, -2.78639924e-02],\n",
      "      dtype=float32), array([[[[-1.03266295e-02, -2.57659331e-03,  2.39167653e-04, ...,\n",
      "          -1.18998659e-03, -9.75547917e-03, -2.47324049e-03],\n",
      "         [-9.87034664e-03, -1.88852882e-03,  2.75667437e-04, ...,\n",
      "          -9.98693518e-03, -5.98258805e-03,  4.40906314e-03],\n",
      "         [ 1.61835626e-02, -9.38057806e-03, -6.73405966e-03, ...,\n",
      "          -2.42401171e-03,  1.09589035e-02,  1.39167206e-02],\n",
      "         ...,\n",
      "         [-1.40176648e-02, -3.08811688e-03,  3.41502228e-03, ...,\n",
      "           5.33248903e-03, -1.70355793e-02, -1.36359241e-02],\n",
      "         [ 1.74193655e-03, -9.95234400e-03, -4.35903465e-04, ...,\n",
      "          -2.41840957e-03, -1.68555733e-02,  1.05463974e-02],\n",
      "         [-4.77309758e-03, -6.66776532e-03,  5.07126655e-03, ...,\n",
      "          -1.20526762e-03,  3.55557725e-03,  1.17330160e-03]],\n",
      "\n",
      "        [[-6.64285664e-03, -3.47881275e-03,  2.39190087e-03, ...,\n",
      "          -7.53906369e-03, -5.72045427e-03, -9.24838521e-03],\n",
      "         [-2.97287968e-03,  3.34521150e-03, -3.18630366e-03, ...,\n",
      "          -1.15623679e-02, -7.90791214e-03,  5.92658529e-03],\n",
      "         [ 2.53777411e-02,  2.53286422e-03,  2.17707790e-02, ...,\n",
      "           2.15302818e-02,  1.67279467e-02,  2.45583057e-02],\n",
      "         ...,\n",
      "         [-7.73527799e-03,  6.76160492e-03, -1.16094667e-03, ...,\n",
      "           4.41490719e-03, -1.44865643e-02, -1.29020950e-02],\n",
      "         [ 1.03217484e-02, -7.36614782e-03, -5.86766237e-03, ...,\n",
      "          -4.04950976e-03, -1.98591519e-02,  1.01560345e-02],\n",
      "         [-1.55079812e-02,  1.91596281e-02,  2.70862889e-04, ...,\n",
      "          -6.27748622e-03,  4.34006471e-03,  1.73485430e-04]],\n",
      "\n",
      "        [[ 4.12674667e-03, -4.57745697e-03,  6.64306013e-03, ...,\n",
      "          -2.34278967e-03, -9.18853935e-03, -1.25898141e-03],\n",
      "         [-3.07818851e-03,  7.09499512e-03, -1.60038937e-03, ...,\n",
      "          -6.78885821e-03, -1.09325945e-02,  7.65817193e-03],\n",
      "         [ 2.55893916e-02, -1.47064438e-03,  9.20196623e-03, ...,\n",
      "          -5.94317727e-03,  2.50070821e-03,  6.69544796e-03],\n",
      "         ...,\n",
      "         [-9.56582557e-03,  7.91247934e-03, -5.33100963e-03, ...,\n",
      "           4.76566935e-03, -1.49843339e-02, -6.69805566e-03],\n",
      "         [ 1.19609423e-02, -3.48291663e-03,  1.67369528e-03, ...,\n",
      "           8.51548160e-04, -1.82969198e-02,  8.18597153e-03],\n",
      "         [-1.66008994e-02,  1.42412046e-02, -3.94398719e-03, ...,\n",
      "          -3.43332323e-03,  2.92040431e-03,  3.60240089e-03]]],\n",
      "\n",
      "\n",
      "       [[[-1.50715457e-02,  3.58128431e-03,  1.96502986e-03, ...,\n",
      "           1.93002622e-03,  1.64739266e-02, -1.30437613e-02],\n",
      "         [-1.05031207e-02, -1.34232629e-03,  8.39629397e-03, ...,\n",
      "          -6.13174262e-03, -7.77114695e-03, -7.34500634e-03],\n",
      "         [ 1.59280524e-02, -4.93563304e-04,  2.06456911e-02, ...,\n",
      "           3.44217420e-02,  2.81744432e-02,  4.31641713e-02],\n",
      "         ...,\n",
      "         [-2.63509643e-03, -1.55394357e-02,  1.79553684e-02, ...,\n",
      "           5.62341791e-03,  7.54640112e-03, -1.32122431e-02],\n",
      "         [-8.40738416e-03, -1.08226598e-03, -8.15254636e-03, ...,\n",
      "           7.50581920e-03, -2.10973900e-02,  4.46510874e-03],\n",
      "         [ 3.56538873e-03, -1.49670860e-03,  3.90027976e-03, ...,\n",
      "           2.24968046e-03, -1.23405561e-03, -5.28686540e-03]],\n",
      "\n",
      "        [[-1.69400852e-02,  2.77157854e-02, -1.96665525e-03, ...,\n",
      "          -1.36413379e-02,  1.78107675e-02, -1.66987181e-02],\n",
      "         [-7.62252975e-03,  2.68657506e-03,  5.14760846e-03, ...,\n",
      "          -1.13447458e-02, -9.81413107e-03, -6.15228107e-03],\n",
      "         [ 2.45921463e-02,  1.22981239e-02,  4.96367253e-02, ...,\n",
      "           5.45314848e-02,  3.91974635e-02,  5.24803512e-02],\n",
      "         ...,\n",
      "         [ 4.61020367e-03, -1.76493190e-02,  1.43087450e-02, ...,\n",
      "           5.83570963e-03,  8.79333634e-03, -1.14443125e-02],\n",
      "         [ 6.86999364e-03, -9.89954080e-03, -1.38055198e-02, ...,\n",
      "           3.88898421e-03, -2.33089775e-02,  5.92778437e-03],\n",
      "         [-1.12817856e-02,  2.83943769e-02,  8.38675944e-04, ...,\n",
      "          -4.76626121e-03, -4.87527344e-03, -6.83464762e-03]],\n",
      "\n",
      "        [[-6.74894638e-03,  4.08497546e-03,  1.99278723e-03, ...,\n",
      "          -1.32070435e-02,  6.80110930e-03, -1.38106188e-02],\n",
      "         [-5.74127119e-03,  3.86035186e-03, -2.07123021e-03, ...,\n",
      "          -1.55830057e-02, -9.33692232e-03, -3.36189335e-03],\n",
      "         [ 2.10623369e-02,  6.44711405e-03,  3.90940160e-02, ...,\n",
      "           2.81947572e-02,  2.81029381e-02,  2.58975681e-02],\n",
      "         ...,\n",
      "         [ 2.77161086e-03, -9.33946855e-03, -3.96435941e-03, ...,\n",
      "           3.31284921e-03,  4.68998821e-03, -8.24241433e-03],\n",
      "         [ 9.93933622e-03, -1.26227587e-02, -5.30784763e-03, ...,\n",
      "           3.16704577e-03, -2.50813738e-02,  6.99498504e-03],\n",
      "         [-1.09259533e-02,  2.50802208e-02, -4.98637464e-03, ...,\n",
      "          -5.42974379e-03, -2.79875263e-03, -1.12388714e-03]]],\n",
      "\n",
      "\n",
      "       [[[-1.05695715e-02, -6.65004551e-03,  1.14270793e-02, ...,\n",
      "           1.13982856e-02,  2.48910710e-02, -2.01158524e-02],\n",
      "         [ 3.46275163e-03,  5.79921063e-03, -1.63540186e-03, ...,\n",
      "          -6.75595738e-03, -5.29716769e-03, -1.25067402e-02],\n",
      "         [-4.70241671e-03, -3.87823209e-03,  2.08221911e-03, ...,\n",
      "           3.55734415e-02,  1.33386767e-02,  4.47410196e-02],\n",
      "         ...,\n",
      "         [ 1.49224093e-02, -1.12200771e-02,  1.46477595e-02, ...,\n",
      "           7.56622152e-03,  3.02859787e-02, -3.93884303e-03],\n",
      "         [-5.07909758e-03,  1.31783877e-02, -1.02952961e-02, ...,\n",
      "           7.72063248e-03, -2.13399660e-02,  2.11469270e-03],\n",
      "         [ 1.11438399e-02, -1.19275544e-02,  3.20557575e-03, ...,\n",
      "           3.00401030e-03, -1.19526843e-02, -8.13317019e-03]],\n",
      "\n",
      "        [[-1.70508623e-02,  8.58010631e-03, -1.14486006e-03, ...,\n",
      "          -5.15660597e-03,  1.45966867e-02, -2.28679758e-02],\n",
      "         [-3.17657227e-03,  5.48885623e-03, -6.66785199e-05, ...,\n",
      "          -9.54495370e-03, -5.38741006e-03, -1.21885082e-02],\n",
      "         [ 1.06314057e-02,  3.72430380e-03,  2.05148254e-02, ...,\n",
      "           4.78186421e-02,  2.96977889e-02,  5.15434667e-02],\n",
      "         ...,\n",
      "         [ 3.04241665e-02, -1.32622952e-02,  8.83379206e-03, ...,\n",
      "           1.04780542e-03,  2.52286401e-02, -4.45278827e-03],\n",
      "         [-1.25949143e-03,  3.22387321e-03, -2.05024239e-02, ...,\n",
      "           5.14487643e-03, -2.70085242e-02,  2.27415795e-03],\n",
      "         [ 3.74635536e-04,  1.97586371e-03, -2.43942440e-03, ...,\n",
      "          -5.21882903e-03, -1.60979982e-02, -1.23087317e-02]],\n",
      "\n",
      "        [[-1.17229745e-02, -4.97850310e-03, -1.49952564e-02, ...,\n",
      "          -2.01662164e-02, -6.41265698e-03, -1.63828563e-02],\n",
      "         [-4.89720202e-04,  3.05005093e-03, -2.13698624e-03, ...,\n",
      "          -1.25116957e-02, -7.37623428e-04, -9.91498586e-03],\n",
      "         [ 3.77920503e-03,  4.25475789e-03,  4.48718248e-03, ...,\n",
      "           1.36323832e-02,  2.40158159e-02,  2.37192456e-02],\n",
      "         ...,\n",
      "         [ 2.55739931e-02, -8.89623910e-03, -4.37693624e-03, ...,\n",
      "          -1.07840088e-03,  1.47468811e-02, -7.86467455e-03],\n",
      "         [-2.09070556e-03, -6.24532858e-03, -2.55214944e-02, ...,\n",
      "          -1.60773040e-03, -2.46536992e-02,  2.47029914e-03],\n",
      "         [-9.88541869e-04,  3.25043732e-03, -7.95861613e-03, ...,\n",
      "          -6.07489794e-03, -1.01532796e-02, -7.52132060e-03]]]],\n",
      "      dtype=float32), array([ 1.96750183e-02, -1.37529126e-03,  9.24313217e-02,  1.27414614e-01,\n",
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      "       -8.83346796e-03,  7.88244158e-02,  9.81942266e-02,  1.63116872e-01],\n",
      "      dtype=float32), array([[[[ 2.49182852e-03, -8.25067237e-03, -1.34461222e-03, ...,\n",
      "           8.61167070e-03, -3.73780821e-03,  6.45499909e-04],\n",
      "         [-4.42567188e-03, -1.88350787e-05, -1.74789131e-02, ...,\n",
      "          -1.74075942e-02, -2.41387892e-03, -2.45446875e-03],\n",
      "         [-1.45422723e-02,  6.53489307e-03,  4.29056808e-02, ...,\n",
      "           2.32872367e-03, -8.22560862e-03, -1.34951407e-02],\n",
      "         ...,\n",
      "         [ 8.14430788e-03,  4.64800792e-03,  1.78648401e-02, ...,\n",
      "           1.30022259e-03, -1.02303829e-02, -8.59441701e-03],\n",
      "         [-1.25717523e-03, -4.16684226e-04, -5.34598716e-03, ...,\n",
      "          -1.43156825e-02, -5.26516093e-03, -1.92927010e-03],\n",
      "         [ 7.58334296e-03,  3.03687761e-04,  1.76798610e-03, ...,\n",
      "          -6.30416349e-03,  5.41360758e-04, -2.08757468e-03]],\n",
      "\n",
      "        [[ 5.62601024e-04, -1.57458056e-02, -1.89978105e-03, ...,\n",
      "           3.74664553e-03, -7.80931325e-04,  7.86909834e-03],\n",
      "         [-9.07994434e-03, -1.88095204e-03, -1.08374842e-02, ...,\n",
      "           3.25201056e-03, -8.60407297e-03, -1.06352521e-02],\n",
      "         [-1.02429595e-02,  8.97591282e-03,  2.03796718e-02, ...,\n",
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      "         ...,\n",
      "         [ 2.76015643e-02,  3.51342745e-02,  1.60577446e-02, ...,\n",
      "          -3.92214302e-03, -3.94038716e-03, -1.28798457e-02],\n",
      "         [-9.14710574e-03,  7.83217512e-03, -1.45204505e-03, ...,\n",
      "          -2.50025140e-03,  4.37620515e-03, -2.92862463e-03],\n",
      "         [ 1.53262382e-02,  3.19609744e-03, -3.10626184e-03, ...,\n",
      "          -1.26120343e-03,  1.93217583e-03, -4.34497744e-03]],\n",
      "\n",
      "        [[ 1.19078634e-02,  1.22632412e-02,  1.10837901e-02, ...,\n",
      "          -7.12652551e-03, -4.51076403e-03, -1.80176343e-04],\n",
      "         [ 1.09123939e-04, -2.57430226e-03,  5.92016324e-04, ...,\n",
      "           1.00612864e-02, -6.97242282e-03, -1.89536007e-03],\n",
      "         [-3.65449372e-03, -5.48841013e-03,  2.82002846e-03, ...,\n",
      "          -9.52219777e-03,  1.63100380e-03, -9.41131264e-03],\n",
      "         ...,\n",
      "         [ 2.27532778e-02,  2.56275944e-02,  1.38883954e-02, ...,\n",
      "          -3.09439981e-03,  8.96250270e-03, -1.08324187e-02],\n",
      "         [-1.14783114e-02, -4.79689304e-04, -5.75645873e-03, ...,\n",
      "           5.71634853e-03,  1.44765461e-02, -3.67933162e-03],\n",
      "         [ 1.40898814e-02, -3.01762018e-03, -1.16279358e-02, ...,\n",
      "          -3.89153371e-03,  4.75310662e-04, -1.12566911e-02]]],\n",
      "\n",
      "\n",
      "       [[[-9.41542629e-03, -9.80154704e-03, -3.69167840e-03, ...,\n",
      "           8.45058262e-03, -1.11409568e-03,  1.57259796e-02],\n",
      "         [-2.05228683e-02,  3.40567291e-04, -1.74381770e-02, ...,\n",
      "          -1.73003264e-02, -4.24027769e-03, -1.03721013e-02],\n",
      "         [-8.17882922e-03,  4.71192319e-03,  5.10138553e-03, ...,\n",
      "           2.30808929e-03, -3.67084774e-03, -6.74672890e-03],\n",
      "         ...,\n",
      "         [ 8.09922162e-03, -6.36649085e-03,  7.09572807e-03, ...,\n",
      "           1.55610824e-02, -4.00183955e-03,  8.52918660e-04],\n",
      "         [ 9.46240834e-06, -4.80348710e-03,  6.38567237e-03, ...,\n",
      "          -1.66918933e-02,  7.42614502e-03, -5.22509357e-03],\n",
      "         [ 6.23346865e-03, -8.45635124e-03,  1.28625380e-02, ...,\n",
      "           7.55864847e-03,  3.60822654e-03,  1.02037117e-02]],\n",
      "\n",
      "        [[-9.66143794e-03, -1.66031346e-02, -3.75456340e-03, ...,\n",
      "           3.77679267e-03,  8.85611749e-04,  3.90423387e-02],\n",
      "         [-2.29902640e-02, -5.48137818e-04,  6.26104232e-03, ...,\n",
      "           3.09622195e-03, -1.12797739e-02, -2.21406780e-02],\n",
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      "          -2.01132614e-02,  4.04101564e-03, -1.30811296e-02],\n",
      "         ...,\n",
      "         [ 2.91116592e-02,  2.56295223e-02, -5.18021779e-03, ...,\n",
      "           1.64482743e-02,  9.89971100e-04, -5.71119506e-03],\n",
      "         [-3.59656615e-03,  3.92737426e-03,  1.15985656e-02, ...,\n",
      "          -4.35973983e-03,  1.28727686e-02, -3.06857913e-03],\n",
      "         [ 1.48936510e-02, -2.79081590e-03,  1.20031787e-02, ...,\n",
      "           1.37832770e-02,  1.05134724e-02,  2.34108530e-02]],\n",
      "\n",
      "        [[ 4.74231754e-04,  3.63741280e-03,  2.15365533e-02, ...,\n",
      "          -1.89999817e-03, -5.15478104e-03,  1.31619368e-02],\n",
      "         [-9.18400660e-03,  1.93454546e-03,  1.09110810e-02, ...,\n",
      "           9.14575998e-03, -8.21557175e-03, -8.30788538e-03],\n",
      "         [-1.69444911e-03, -4.36456734e-03, -2.26653703e-02, ...,\n",
      "          -1.38805434e-02,  1.06112342e-02, -1.10037765e-02],\n",
      "         ...,\n",
      "         [ 2.16357969e-02,  1.74818505e-02, -4.67658462e-03, ...,\n",
      "          -9.58664925e-04,  1.37514127e-02, -7.61160767e-03],\n",
      "         [-1.90485851e-03, -4.57544671e-03,  5.04404213e-03, ...,\n",
      "           7.49490084e-03,  2.18671728e-02, -5.64512424e-03],\n",
      "         [ 1.06539074e-02, -6.43269531e-03, -5.04566648e-04, ...,\n",
      "           8.10153224e-03,  1.10825021e-02,  1.70141142e-02]]],\n",
      "\n",
      "\n",
      "       [[[-4.50136606e-03, -6.02411199e-03,  3.11873481e-03, ...,\n",
      "          -5.44655835e-04,  2.41484423e-03,  2.56585758e-02],\n",
      "         [-1.60623565e-02,  2.61958572e-03, -4.11093468e-03, ...,\n",
      "          -1.52113223e-02, -2.44396157e-03, -9.40611679e-03],\n",
      "         [ 1.03867343e-02,  9.93811246e-03, -6.63214130e-03, ...,\n",
      "           4.57423186e-04, -1.41171238e-03,  1.74400141e-03],\n",
      "         ...,\n",
      "         [-3.64836096e-03, -3.09328665e-03, -1.06807053e-02, ...,\n",
      "           1.12805534e-02, -2.41819987e-04,  9.97136254e-03],\n",
      "         [ 2.19470632e-04, -1.80030242e-03,  4.31476161e-03, ...,\n",
      "          -1.55662363e-02,  1.01363128e-02, -5.82250673e-03],\n",
      "         [-1.94603333e-03, -1.33034596e-02,  1.00488653e-02, ...,\n",
      "           1.57581102e-02,  6.38718856e-03,  9.57524404e-03]],\n",
      "\n",
      "        [[-1.47843594e-03, -1.02676339e-02,  1.72790524e-03, ...,\n",
      "          -7.44713098e-03,  7.77076697e-03,  6.32125139e-02],\n",
      "         [-1.55830020e-02, -9.06818022e-04,  1.38317700e-02, ...,\n",
      "           1.86586718e-03, -1.31476419e-02, -2.01811269e-02],\n",
      "         [ 4.06060950e-04,  1.30023547e-02, -2.33655237e-02, ...,\n",
      "          -2.13477034e-02,  1.25812916e-02, -6.86774962e-03],\n",
      "         ...,\n",
      "         [ 8.52249004e-03,  2.30366867e-02, -2.14423127e-02, ...,\n",
      "           2.31715962e-02,  7.81933870e-03,  9.37404856e-03],\n",
      "         [ 3.03807063e-03,  3.03328532e-04,  1.46860117e-02, ...,\n",
      "          -4.26525855e-03,  1.57574061e-02, -4.55228426e-03],\n",
      "         [-1.30841765e-03, -5.18516358e-03,  4.14379733e-03, ...,\n",
      "           2.45135967e-02,  1.46029377e-02,  2.09346768e-02]],\n",
      "\n",
      "        [[ 1.05792219e-02,  7.71222962e-03,  1.60458777e-02, ...,\n",
      "          -1.14335474e-02,  1.80619667e-04,  3.85264903e-02],\n",
      "         [-3.40054696e-03,  3.24828108e-03, -2.46915198e-03, ...,\n",
      "           1.20599633e-02, -8.42132140e-03, -9.39693395e-03],\n",
      "         [-6.27992442e-03,  5.48810531e-05, -3.39485556e-02, ...,\n",
      "          -1.67110953e-02,  2.01697182e-02, -9.91834793e-03],\n",
      "         ...,\n",
      "         [ 6.44019945e-03,  1.73932556e-02, -1.23419259e-02, ...,\n",
      "           4.06535063e-03,  1.56269483e-02,  4.64981329e-03],\n",
      "         [ 4.31994861e-03, -6.28653821e-03,  1.34719890e-02, ...,\n",
      "           1.59082916e-02,  2.07160246e-02, -4.53479309e-03],\n",
      "         [-8.85906070e-03, -5.81115717e-03, -5.50442899e-04, ...,\n",
      "           1.17796622e-02,  1.62397400e-02,  2.18943544e-02]]]],\n",
      "      dtype=float32), array([ 3.54152434e-02,  1.07918017e-01, -1.80004574e-02,  4.33173068e-02,\n",
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      "      dtype=float32), array([[[[-1.24538150e-02,  8.40655994e-03, -5.28845051e-03, ...,\n",
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      "         ...,\n",
      "         [ 1.37888230e-02, -6.58180192e-03,  9.65370331e-03, ...,\n",
      "           7.17610447e-03,  3.45725450e-03,  5.33173978e-03],\n",
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      "           3.77660524e-03,  2.05454584e-02, -1.35868033e-02]],\n",
      "\n",
      "        [[-1.20176468e-02,  1.51250837e-03,  3.43130133e-03, ...,\n",
      "          -1.57830697e-02, -2.39501009e-03,  2.93573504e-03],\n",
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      "         [-2.78812763e-03,  1.09002152e-02,  7.31469830e-03, ...,\n",
      "           1.32350891e-03,  5.71234105e-03, -2.06499193e-02],\n",
      "         ...,\n",
      "         [ 5.34640905e-03, -7.61074666e-03, -2.95266091e-05, ...,\n",
      "           1.06462219e-03,  7.16414442e-03,  5.50952321e-03],\n",
      "         [-1.97489071e-03, -5.18740201e-03, -3.50479130e-03, ...,\n",
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      "         [-8.13952927e-03, -1.72344397e-03, -1.71952751e-02, ...,\n",
      "           6.51383121e-03,  2.62788888e-02, -7.40201725e-03]],\n",
      "\n",
      "        [[-1.13097280e-02, -2.71398202e-03,  5.21831634e-03, ...,\n",
      "           3.75532242e-03, -4.37350944e-03, -1.71778537e-03],\n",
      "         [ 9.51003470e-03,  2.10385933e-03, -6.23627566e-03, ...,\n",
      "           9.84872226e-04, -1.22357579e-02, -5.77230006e-03],\n",
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      "          -1.15952350e-03,  7.16441032e-03, -6.74266228e-03],\n",
      "         ...,\n",
      "         [ 3.84493452e-03,  6.50770171e-03, -3.08423012e-04, ...,\n",
      "           7.76557205e-03,  4.50123427e-03,  2.94768345e-03],\n",
      "         [-5.20469574e-03,  2.53336993e-03, -2.00857781e-03, ...,\n",
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      "         [-4.31006867e-03, -4.26639896e-03, -1.50389588e-02, ...,\n",
      "          -6.62087603e-03,  1.03521571e-02,  2.33515655e-03]]],\n",
      "\n",
      "\n",
      "       [[[-1.66037567e-02,  2.41671409e-02, -1.76821016e-02, ...,\n",
      "          -8.38128850e-03, -3.02293082e-03,  3.58365453e-03],\n",
      "         [ 9.80825536e-03,  1.05249183e-02, -4.66881320e-02, ...,\n",
      "          -7.78164901e-03, -3.83233977e-03,  2.94483802e-03],\n",
      "         [ 1.34947952e-02, -1.25661753e-02,  1.29038952e-02, ...,\n",
      "           1.43833098e-03, -5.72983874e-03, -1.78362131e-02],\n",
      "         ...,\n",
      "         [ 9.57040023e-03,  1.17314365e-02,  1.55258663e-02, ...,\n",
      "           2.69203974e-05,  2.30762083e-03,  7.98452704e-04],\n",
      "         [-2.26363889e-03, -2.44599045e-03,  5.42335818e-03, ...,\n",
      "          -7.61786243e-04,  7.27130566e-03,  2.00658664e-02],\n",
      "         [-6.25453144e-03,  8.70768726e-03,  5.96766314e-03, ...,\n",
      "           2.25311015e-02,  1.17731886e-02, -8.07471387e-03]],\n",
      "\n",
      "        [[-2.05247719e-02,  9.02097579e-03, -1.39437476e-03, ...,\n",
      "          -1.84835698e-02,  1.36483200e-02,  1.48000638e-03],\n",
      "         [ 8.35212879e-03, -3.76963033e-03, -2.36531124e-02, ...,\n",
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      "         [ 1.35796964e-02, -1.72847509e-02,  9.88537073e-03, ...,\n",
      "           7.85652269e-03,  1.02855563e-02, -2.21692659e-02],\n",
      "         ...,\n",
      "         [ 4.50371159e-03,  7.92721228e-04,  8.28000717e-03, ...,\n",
      "          -1.25710340e-03,  2.60498724e-03,  6.89739687e-03],\n",
      "         [-4.07085335e-03, -4.51655919e-03, -2.78022187e-03, ...,\n",
      "           1.75143685e-03,  7.57344998e-03,  1.27716700e-03],\n",
      "         [-4.38698288e-03,  1.11662695e-04, -1.52793936e-02, ...,\n",
      "           3.82050462e-02,  3.65496846e-03, -6.30834652e-03]],\n",
      "\n",
      "        [[-1.67291705e-02, -7.51205778e-04,  8.62288661e-03, ...,\n",
      "          -4.92068566e-03,  2.60210619e-03, -8.31924565e-03],\n",
      "         [ 7.60383205e-03, -2.44896696e-03, -9.95151792e-03, ...,\n",
      "           2.84005492e-03,  1.40986012e-04, -7.82902353e-03],\n",
      "         [ 2.45916261e-03, -6.49120752e-03, -8.32979660e-03, ...,\n",
      "           7.72433681e-03,  1.30170006e-02, -1.23488028e-02],\n",
      "         ...,\n",
      "         [ 1.33765105e-03,  7.21688429e-03,  1.26626331e-03, ...,\n",
      "           3.94847291e-03,  5.32880379e-03, -2.07663863e-03],\n",
      "         [-2.70236470e-03,  1.28381781e-03, -6.93748286e-03, ...,\n",
      "           8.98882467e-03,  1.46908136e-02, -4.21756599e-03],\n",
      "         [-2.33115349e-03, -6.12587482e-03, -2.12312099e-02, ...,\n",
      "           9.15342360e-04,  3.17362952e-04,  1.23123394e-03]]],\n",
      "\n",
      "\n",
      "       [[[-1.45651354e-02,  9.64931585e-03, -1.16087059e-02, ...,\n",
      "           2.59297341e-03, -8.05760548e-03,  2.21103709e-03],\n",
      "         [ 6.19267486e-03,  8.93716048e-03, -4.51339036e-02, ...,\n",
      "          -6.12378679e-03, -4.00708383e-03,  6.47111796e-03],\n",
      "         [ 1.43068740e-02, -2.66728899e-03,  3.41038289e-03, ...,\n",
      "           3.44638783e-03, -8.62873974e-04, -1.33675877e-02],\n",
      "         ...,\n",
      "         [ 1.29059236e-02,  9.14617069e-03,  8.28087237e-03, ...,\n",
      "          -4.39318595e-03, -8.14242568e-03, -2.26692040e-03],\n",
      "         [-1.31062279e-03, -5.64920157e-03,  6.37932634e-03, ...,\n",
      "           6.66187890e-03,  4.44209296e-03,  4.41963132e-03],\n",
      "         [-6.42832462e-03,  4.18221578e-03,  7.65334209e-03, ...,\n",
      "           1.20814089e-02, -6.66856999e-03,  3.25094647e-04]],\n",
      "\n",
      "        [[-1.66320223e-02,  4.54504183e-03, -6.67143054e-03, ...,\n",
      "           2.28197756e-03, -6.31665680e-05, -4.71796095e-03],\n",
      "         [ 2.97540380e-03, -6.40762178e-03, -2.85963546e-02, ...,\n",
      "          -2.35724798e-03,  4.74322308e-03,  4.67349339e-04],\n",
      "         [ 2.36185007e-02, -1.89911220e-02,  4.60000196e-03, ...,\n",
      "           1.08400211e-02, -9.18388832e-03, -2.74709109e-02],\n",
      "         ...,\n",
      "         [ 8.74977279e-03,  1.61244010e-03,  3.06530995e-03, ...,\n",
      "           4.53018304e-03, -7.39837857e-03,  4.47823061e-03],\n",
      "         [-1.20457367e-03, -2.87331175e-03, -5.18758828e-03, ...,\n",
      "           1.17142722e-02,  7.62202404e-03, -5.77956159e-03],\n",
      "         [-4.07704106e-03,  5.63840521e-03, -1.10617159e-02, ...,\n",
      "           2.38051061e-02, -1.34268589e-02, -2.97562080e-03]],\n",
      "\n",
      "        [[-8.99161492e-03,  5.84716024e-03,  5.29400352e-03, ...,\n",
      "           3.04830913e-03, -1.18276821e-02, -8.41523055e-03],\n",
      "         [ 3.12718400e-03, -5.05524641e-03, -1.94435567e-02, ...,\n",
      "           3.33701703e-03,  1.45587865e-02, -4.61388379e-03],\n",
      "         [ 1.11383200e-02, -2.28672028e-02,  2.00467315e-04, ...,\n",
      "          -3.49199137e-04, -8.52558948e-03, -1.46135921e-02],\n",
      "         ...,\n",
      "         [ 4.12542978e-03,  1.88087288e-03, -2.15299334e-03, ...,\n",
      "           3.59076308e-03, -1.91574858e-03, -3.53228627e-03],\n",
      "         [-2.84922371e-05,  9.47301451e-04, -8.46835505e-03, ...,\n",
      "           1.27441790e-02,  1.32457484e-02, -2.80284905e-03],\n",
      "         [-6.17068168e-03, -5.06139966e-03, -1.87711921e-02, ...,\n",
      "          -2.79223267e-03, -1.10712685e-02,  4.57540294e-03]]]],\n",
      "      dtype=float32), array([ 0.01348567,  0.00756114,  0.06701895,  0.04177905,  0.00131124,\n",
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      "       -0.0481341 , -0.00103277,  0.05884005,  0.01856414,  0.0359413 ,\n",
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      "       -0.00413027,  0.0101658 ], dtype=float32), array([[[[ 7.11654220e-03,  7.00819055e-06,  9.24700499e-03, ...,\n",
      "           4.03929735e-03,  8.05561524e-03, -3.74245713e-03],\n",
      "         [ 1.12781115e-03,  1.61532906e-03, -9.08267568e-04, ...,\n",
      "          -7.93790072e-03, -4.59095975e-03, -8.13464867e-04],\n",
      "         [-4.63789236e-03, -1.18727237e-02,  6.58529717e-03, ...,\n",
      "           7.42091658e-03, -6.53812988e-03, -2.42086244e-03],\n",
      "         ...,\n",
      "         [ 1.28063676e-03,  1.49819313e-03,  7.28668272e-03, ...,\n",
      "          -5.99841867e-03, -2.01151473e-03, -1.18386478e-03],\n",
      "         [-4.89709014e-03, -6.26946846e-03, -5.09714335e-03, ...,\n",
      "           1.26905064e-03,  1.07506765e-02, -2.44210777e-03],\n",
      "         [ 2.12570513e-03, -3.61318327e-03, -7.26481713e-03, ...,\n",
      "           3.64817417e-04,  1.50787262e-02,  4.10703570e-03]],\n",
      "\n",
      "        [[ 6.64269971e-03, -6.01840531e-03,  9.42177977e-03, ...,\n",
      "           4.53453884e-03,  4.71206789e-04,  3.50896595e-03],\n",
      "         [-1.24128824e-02,  1.62265194e-03,  2.18410187e-05, ...,\n",
      "          -9.26828291e-03, -1.32720219e-02,  7.84974638e-03],\n",
      "         [-2.27750093e-03, -1.37851508e-02,  6.04773080e-03, ...,\n",
      "           5.82123734e-03, -4.03309939e-03, -3.08526703e-03],\n",
      "         ...,\n",
      "         [ 9.42836609e-03, -7.80543603e-04,  1.71435010e-02, ...,\n",
      "          -7.94082507e-03, -7.73798907e-04,  3.02146119e-03],\n",
      "         [-3.22291674e-03, -2.85354297e-04, -2.08436535e-03, ...,\n",
      "          -4.60813055e-03, -5.56954136e-03,  6.86109858e-03],\n",
      "         [ 9.59297060e-04,  7.38721387e-03, -8.91729910e-03, ...,\n",
      "          -1.65850704e-03,  7.24582188e-03,  6.19835919e-03]],\n",
      "\n",
      "        [[ 2.34439736e-03, -9.28215683e-03, -3.19302635e-04, ...,\n",
      "           8.40835925e-03,  4.12485213e-04,  3.09582963e-03],\n",
      "         [-1.55776711e-02, -1.08954648e-03, -4.28956561e-03, ...,\n",
      "          -1.46012632e-02, -1.17095094e-03, -1.09702547e-03],\n",
      "         [-7.46384822e-03, -6.07428560e-03,  1.01981256e-02, ...,\n",
      "          -3.00147524e-03,  6.63558196e-04, -6.11750875e-03],\n",
      "         ...,\n",
      "         [ 4.24216688e-03,  4.56949836e-03,  8.23827088e-03, ...,\n",
      "          -5.40188514e-03, -8.07413179e-03,  1.09999124e-02],\n",
      "         [-7.86238699e-04,  1.90356933e-03,  1.71771063e-03, ...,\n",
      "          -2.16562231e-03, -1.10405972e-02,  9.30893887e-03],\n",
      "         [ 6.02629362e-03,  1.86428446e-02, -1.34665128e-02, ...,\n",
      "          -8.40879139e-03,  7.48337386e-03, -4.10805363e-03]]],\n",
      "\n",
      "\n",
      "       [[[ 5.44611085e-03, -9.18421778e-04,  9.77920461e-03, ...,\n",
      "          -1.19165263e-04, -3.40916682e-03, -6.98734634e-03],\n",
      "         [ 2.51410692e-03,  4.60237265e-03, -2.46173400e-03, ...,\n",
      "          -5.48852608e-03, -7.09898863e-03,  5.42021822e-03],\n",
      "         [-9.05828271e-03, -1.00242114e-02,  2.94465595e-03, ...,\n",
      "           9.01548378e-03,  6.37277029e-04, -2.18915544e-03],\n",
      "         ...,\n",
      "         [-3.00789997e-03, -9.66227599e-05,  1.85708259e-03, ...,\n",
      "          -2.42409506e-03,  2.34206222e-04, -3.27465497e-03],\n",
      "         [-5.01462910e-03, -3.50114633e-03, -6.08791783e-03, ...,\n",
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      "         [-8.52283556e-03, -1.07422760e-02, -2.84677697e-03, ...,\n",
      "           6.36414066e-03,  1.55793177e-02,  2.62972061e-03]],\n",
      "\n",
      "        [[ 6.34042593e-03, -5.55177638e-03,  1.12122018e-02, ...,\n",
      "           3.84862011e-04, -7.39399204e-03, -2.59233406e-03],\n",
      "         [ 1.83797081e-03,  4.37067216e-03, -2.16640974e-03, ...,\n",
      "          -9.72099602e-03, -4.33123438e-03,  6.84785657e-03],\n",
      "         [-2.52128625e-03, -9.25008021e-03,  5.38919820e-03, ...,\n",
      "           6.01652497e-03,  7.39997532e-03, -3.47864232e-03],\n",
      "         ...,\n",
      "         [ 6.54197996e-03, -1.80534972e-03,  6.87478622e-03, ...,\n",
      "          -2.96625658e-03,  7.19870348e-03, -3.49612092e-03],\n",
      "         [-1.20014576e-02, -9.55184049e-04,  3.21550784e-03, ...,\n",
      "          -6.86675077e-03,  3.81029584e-03, -1.35953142e-03],\n",
      "         [-1.33076878e-02, -5.95784932e-03,  2.00847466e-03, ...,\n",
      "           3.71311558e-03, -4.85057989e-03,  6.59804884e-03]],\n",
      "\n",
      "        [[ 2.90424004e-03, -9.89661831e-03,  1.91741413e-03, ...,\n",
      "           5.65523747e-03, -6.10089628e-03, -2.42118305e-03],\n",
      "         [-3.49682709e-03,  1.72886357e-04, -5.87909436e-03, ...,\n",
      "          -1.28070693e-02,  4.43585636e-03,  6.80614915e-03],\n",
      "         [-1.09087434e-02, -7.73155596e-03,  1.13571603e-02, ...,\n",
      "          -1.85778399e-03,  4.53320518e-03, -6.28825603e-03],\n",
      "         ...,\n",
      "         [ 4.70118131e-03,  1.73194357e-03,  2.63497210e-03, ...,\n",
      "           2.44574575e-03, -1.33330061e-03, -3.43957436e-06],\n",
      "         [-8.93086009e-03,  3.52435117e-03,  3.11156409e-03, ...,\n",
      "          -6.06179424e-03, -1.80058610e-02,  1.25560276e-02],\n",
      "         [-1.18324636e-02,  8.83054268e-03,  3.15376674e-03, ...,\n",
      "          -1.96965900e-03, -5.68017829e-03,  7.08003854e-03]]],\n",
      "\n",
      "\n",
      "       [[[ 8.75416305e-03, -4.36640298e-03,  4.88167582e-03, ...,\n",
      "           8.39018787e-04, -5.99739561e-03, -1.24212792e-02],\n",
      "         [ 4.01801849e-03,  3.51571711e-04,  3.97934671e-03, ...,\n",
      "           1.03333630e-02, -1.19119482e-02,  1.45259704e-02],\n",
      "         [-1.23062739e-02, -7.49821402e-03, -1.16881379e-03, ...,\n",
      "           1.00372350e-02,  3.78591637e-03, -3.27527802e-03],\n",
      "         ...,\n",
      "         [ 3.92382033e-04, -5.11869090e-03, -5.72134461e-03, ...,\n",
      "          -5.19906683e-03,  2.44495110e-03, -2.64277123e-03],\n",
      "         [ 3.15165427e-03,  4.59999545e-03, -4.49594622e-03, ...,\n",
      "          -7.07745692e-03,  2.20317803e-02, -9.98178683e-03],\n",
      "         [ 2.48351321e-03, -4.45801299e-03, -1.41727342e-03, ...,\n",
      "           1.14606246e-02,  2.31800862e-02,  1.90563314e-03]],\n",
      "\n",
      "        [[ 9.47191007e-03, -3.94198066e-03,  3.83984810e-03, ...,\n",
      "           2.04855483e-03, -3.98352416e-03, -9.07041319e-03],\n",
      "         [ 4.09901841e-03, -5.52556419e-04,  9.95470490e-03, ...,\n",
      "           6.61444664e-03,  1.68336404e-03,  5.98631799e-03],\n",
      "         [-5.33673773e-03, -3.10067786e-03, -2.68109678e-03, ...,\n",
      "           6.30002609e-03,  9.23030172e-03, -1.12451822e-03],\n",
      "         ...,\n",
      "         [ 3.42691923e-03, -3.57319019e-03, -3.67652508e-03, ...,\n",
      "          -2.96659744e-03,  2.97217467e-03, -5.51824691e-03],\n",
      "         [-6.08776370e-03, -3.16021242e-03, -3.34903644e-03, ...,\n",
      "          -1.02244793e-02,  5.09558059e-03, -7.77694955e-03],\n",
      "         [-6.22821553e-03, -5.55740483e-03,  1.33099854e-02, ...,\n",
      "           1.53019335e-02, -1.71303935e-03,  3.84857692e-03]],\n",
      "\n",
      "        [[ 6.73177093e-03, -7.76051125e-03, -1.60716416e-03, ...,\n",
      "           3.37521662e-03, -3.43736820e-03, -7.08474452e-03],\n",
      "         [-1.92464353e-03, -1.43057271e-03,  1.68074947e-03, ...,\n",
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      "          -2.28520279e-04,  2.16215150e-04, -1.52036909e-03],\n",
      "         ...,\n",
      "         [ 4.53559542e-03, -1.34184927e-04, -9.41309205e-04, ...,\n",
      "           1.11481512e-03, -4.47113672e-03, -4.62406827e-03],\n",
      "         [ 9.73428891e-04, -9.99093894e-03, -3.64008895e-03, ...,\n",
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      "         [-8.02905019e-03,  7.79318798e-04,  2.27084830e-02, ...,\n",
      "           1.30782668e-02,  1.38504582e-03,  7.73181953e-03]]]],\n",
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      "        5.62454313e-02,  1.43612195e-02,  6.42168671e-02,  4.83797006e-02,\n",
      "        1.25911102e-01,  1.25651538e-01,  7.45308250e-02, -1.71924084e-02],\n",
      "      dtype=float32), array([[[[-4.13556537e-03,  7.47195398e-03, -3.50115891e-03, ...,\n",
      "           4.89854301e-06, -2.53839465e-03, -5.25326468e-03],\n",
      "         [-9.53834411e-03,  1.41056092e-03, -1.65442061e-02, ...,\n",
      "          -1.52774970e-03,  1.11036829e-03, -1.79786165e-03],\n",
      "         [-3.51967965e-03,  8.38233996e-03,  1.37014373e-03, ...,\n",
      "          -2.04362301e-03, -3.33098392e-03, -3.59164621e-03],\n",
      "         ...,\n",
      "         [-4.51420387e-03, -9.90713015e-03, -7.90119357e-03, ...,\n",
      "          -2.74181948e-04,  8.04592157e-04, -9.21490043e-03],\n",
      "         [ 4.13362030e-03,  1.64503278e-03, -1.24853069e-03, ...,\n",
      "          -4.80085961e-04,  1.43603736e-03, -2.37931171e-03],\n",
      "         [-9.46063921e-03, -3.02881887e-03, -3.93793161e-04, ...,\n",
      "          -8.37404653e-03, -8.49721371e-04,  2.19010212e-03]],\n",
      "\n",
      "        [[-4.10446478e-03, -1.54824147e-03, -5.41875651e-03, ...,\n",
      "          -2.24129972e-03, -2.28596875e-03, -3.34858289e-03],\n",
      "         [-4.84787673e-03,  2.47201161e-03, -1.29879676e-02, ...,\n",
      "           8.18996597e-03, -4.54588607e-03,  9.62644164e-03],\n",
      "         [-3.10205529e-03,  3.47901974e-03,  2.52036308e-03, ...,\n",
      "          -5.83003787e-03,  1.09997432e-04, -3.84454383e-03],\n",
      "         ...,\n",
      "         [-7.76591944e-03, -1.44146327e-02, -7.61551922e-03, ...,\n",
      "          -3.92687973e-03, -6.16982626e-03, -5.35330735e-03],\n",
      "         [ 1.01468374e-03,  1.67173836e-02, -6.25725277e-03, ...,\n",
      "          -2.52300198e-03, -4.94909706e-03, -9.14588978e-04],\n",
      "         [-7.97870383e-03, -4.20195796e-03,  1.45270012e-03, ...,\n",
      "          -1.22739337e-02, -2.10561347e-03,  5.49114076e-03]],\n",
      "\n",
      "        [[-2.88630649e-03,  2.41750688e-03,  1.50172273e-03, ...,\n",
      "          -1.28930504e-03, -4.96551802e-04,  2.69375363e-04],\n",
      "         [ 3.95747193e-05, -1.94887386e-03, -7.08143180e-03, ...,\n",
      "           1.00128017e-02, -4.74765385e-03,  1.33702094e-02],\n",
      "         [ 4.38523851e-03,  2.79099098e-03, -4.09206329e-03, ...,\n",
      "          -2.73540127e-03, -3.12048779e-03, -2.88168900e-03],\n",
      "         ...,\n",
      "         [-4.95913485e-03, -1.23296445e-02, -5.42156352e-03, ...,\n",
      "          -2.32423958e-03, -8.56377464e-03, -7.15223281e-03],\n",
      "         [-6.16921112e-03,  1.57617237e-02, -4.47978219e-03, ...,\n",
      "          -2.25248467e-03, -9.93228331e-03, -6.10898901e-03],\n",
      "         [-4.50641429e-03, -5.51745854e-03, -2.20075878e-03, ...,\n",
      "          -1.30875418e-02, -3.93497292e-03,  6.03448506e-03]]],\n",
      "\n",
      "\n",
      "       [[[-4.41893004e-03,  1.37486542e-02, -8.45907908e-03, ...,\n",
      "          -2.21222895e-03, -2.15952285e-03,  1.23409089e-02],\n",
      "         [-6.33585500e-03, -4.42368211e-03, -3.91021417e-03, ...,\n",
      "          -9.76585504e-03,  1.04509713e-02, -1.36236623e-02],\n",
      "         [-4.40114317e-03,  7.94552453e-03,  2.42980407e-03, ...,\n",
      "          -5.41694043e-03,  8.71099706e-04, -9.86627582e-03],\n",
      "         ...,\n",
      "         [-1.34519069e-02, -1.00430250e-02,  1.51449756e-04, ...,\n",
      "           1.60089054e-04,  3.75668914e-03, -9.09452140e-03],\n",
      "         [ 2.45954143e-03,  5.74873528e-03, -4.06519882e-03, ...,\n",
      "           4.02215123e-03,  7.62883713e-03,  5.94564248e-03],\n",
      "         [-9.32596903e-03, -1.13636081e-03, -6.24895329e-03, ...,\n",
      "          -1.08463904e-02,  1.40982226e-03, -7.70578452e-04]],\n",
      "\n",
      "        [[-5.51303476e-03,  5.81868412e-03, -1.07901720e-02, ...,\n",
      "          -3.43920151e-03, -7.63218326e-04,  1.36730876e-02],\n",
      "         [-1.67119992e-03, -3.32675921e-03,  7.43533950e-03, ...,\n",
      "          -3.50478198e-03,  6.62456639e-03, -4.99307271e-03],\n",
      "         [-5.86137315e-03,  6.13010547e-04,  8.30108393e-03, ...,\n",
      "          -9.87416040e-03,  5.06723206e-03, -7.71902688e-03],\n",
      "         ...,\n",
      "         [-1.29670175e-02, -1.55268898e-02, -8.49602278e-04, ...,\n",
      "           6.30461425e-03,  5.32882579e-04, -6.07468095e-03],\n",
      "         [-1.12099759e-03,  2.91328244e-02, -4.23871959e-03, ...,\n",
      "           2.93749222e-03,  3.47164372e-04,  8.26061238e-03],\n",
      "         [-5.98738715e-03, -9.14713892e-04, -3.92263103e-03, ...,\n",
      "          -1.36881256e-02, -8.12742568e-04,  7.36264093e-03]],\n",
      "\n",
      "        [[-3.41959228e-03,  4.66367882e-03,  3.37764691e-03, ...,\n",
      "          -2.56140856e-03, -1.21631820e-04,  1.15059484e-02],\n",
      "         [ 2.40420690e-04, -3.77301918e-03,  6.58437563e-03, ...,\n",
      "           9.60138626e-03,  2.05660984e-03,  9.79973841e-03],\n",
      "         [ 1.32909336e-04,  1.90253675e-04,  6.17130077e-04, ...,\n",
      "          -8.72793701e-03, -1.45053165e-03, -3.49612208e-03],\n",
      "         ...,\n",
      "         [-9.77272261e-03, -1.07788146e-02, -9.54640738e-04, ...,\n",
      "           6.30754652e-03, -2.78572715e-03, -5.98356128e-03],\n",
      "         [-1.03954598e-02,  2.61091348e-02, -5.07673249e-03, ...,\n",
      "          -2.80671171e-03, -5.53699769e-03, -2.10620486e-03],\n",
      "         [-3.11570894e-03, -3.08538810e-03, -3.10157356e-03, ...,\n",
      "          -1.59878880e-02, -3.33151151e-03,  1.18652089e-02]]],\n",
      "\n",
      "\n",
      "       [[[-4.26715612e-03,  8.63417238e-03,  1.76529714e-03, ...,\n",
      "          -2.84227985e-03, -1.75439665e-04,  2.90537663e-02],\n",
      "         [-6.29396923e-03, -1.76275475e-03, -6.42163330e-04, ...,\n",
      "          -1.01052411e-02,  3.43423686e-03, -1.41305421e-02],\n",
      "         [-3.68094444e-03,  6.39184844e-03,  7.07066664e-03, ...,\n",
      "          -2.24087667e-03,  8.55041016e-03, -8.31523445e-03],\n",
      "         ...,\n",
      "         [-1.18850870e-02, -7.78572122e-03, -4.24755132e-03, ...,\n",
      "          -1.43992031e-04,  2.01374627e-04, -2.33163615e-03],\n",
      "         [ 2.30761128e-03, -9.47567285e-04, -1.79581740e-03, ...,\n",
      "          -4.05802298e-03,  5.83436852e-03,  1.24853859e-02],\n",
      "         [-7.39294710e-03,  6.41175592e-03, -1.01529667e-02, ...,\n",
      "          -1.17332852e-02,  1.69780722e-03,  1.15358143e-03]],\n",
      "\n",
      "        [[-4.61219344e-03, -3.59420269e-03, -8.21814407e-04, ...,\n",
      "          -4.81084595e-03, -4.44865436e-04,  3.18669118e-02],\n",
      "         [-1.15395896e-03, -5.12891915e-03,  9.74675361e-03, ...,\n",
      "          -7.82980397e-03,  7.25134509e-03, -6.98588043e-03],\n",
      "         [-5.98424906e-03,  1.12204099e-04,  9.43994615e-03, ...,\n",
      "          -4.51271143e-03,  8.94110464e-03, -8.36270489e-03],\n",
      "         ...,\n",
      "         [-1.31882168e-02, -9.57226939e-03, -6.37137098e-03, ...,\n",
      "           1.04999328e-02, -1.76120212e-03, -3.13745732e-05],\n",
      "         [ 1.22509198e-03,  1.17349727e-02, -2.26895651e-03, ...,\n",
      "          -6.69820094e-03,  4.28338209e-03,  1.29151903e-02],\n",
      "         [-2.21199635e-03,  1.19306184e-02, -3.41698364e-03, ...,\n",
      "          -1.32360598e-02, -4.97587898e-04,  1.26575744e-02]],\n",
      "\n",
      "        [[-3.64933652e-03, -4.82958928e-03,  9.14632156e-03, ...,\n",
      "          -4.02110023e-03, -1.57763090e-04,  1.70223936e-02],\n",
      "         [ 6.29810616e-04, -2.43360968e-03,  6.34040590e-03, ...,\n",
      "           3.36989964e-04,  6.95535308e-03,  1.70514290e-03],\n",
      "         [-3.24976468e-03,  2.30040471e-03,  4.15086048e-03, ...,\n",
      "          -4.70836135e-03, -1.04901823e-03, -6.13272097e-03],\n",
      "         ...,\n",
      "         [-1.13391438e-02, -4.96303104e-03, -2.09907000e-03, ...,\n",
      "           9.20415949e-03, -3.33326217e-03, -1.52914249e-03],\n",
      "         [-3.99327371e-03,  1.23460982e-02, -3.62788007e-04, ...,\n",
      "          -9.96733084e-03, -2.58089555e-03,  4.87980247e-03],\n",
      "         [-1.03235664e-03,  1.21477433e-03,  4.89632657e-04, ...,\n",
      "          -1.49842957e-02, -3.02216387e-03,  1.48773128e-02]]]],\n",
      "      dtype=float32), array([ 3.75776812e-02,  2.33153161e-02,  4.87732068e-02, -1.31543912e-02,\n",
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      "       -6.31701499e-02,  4.49785119e-04,  1.11907467e-01,  3.42719327e-03,\n",
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      "       -9.37856138e-02,  4.62724715e-02,  3.18735167e-02, -1.16503248e-02,\n",
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      "       -7.91937932e-02,  7.22831637e-02, -1.29031166e-01,  5.37225716e-02],\n",
      "      dtype=float32), array([[[[-6.0689339e-04,  1.4231558e-03,  7.3316055e-03, ...,\n",
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      "         [-4.8605306e-03,  4.9075234e-04, -1.2511463e-03, ...,\n",
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      "         [ 2.0234480e-03, -5.8380342e-03, -2.3825851e-03, ...,\n",
      "           1.3192679e-03, -8.6920448e-03, -8.2156417e-04],\n",
      "         [ 7.9414165e-03, -8.0086980e-03,  7.7348115e-04, ...,\n",
      "           9.1014095e-03,  6.8836473e-04, -9.8630879e-03],\n",
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      "          -1.8046533e-03, -7.7111748e-05,  3.5778836e-03]],\n",
      "\n",
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      "          -8.1634670e-03, -8.1500728e-03, -5.8323247e-03],\n",
      "         [-1.2195857e-03, -5.4482273e-03, -8.4939813e-03, ...,\n",
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      "         ...,\n",
      "         [-6.8472535e-04, -2.8301261e-03,  1.2871494e-03, ...,\n",
      "           1.8639782e-02, -1.4961872e-02, -1.3423259e-03],\n",
      "         [-1.5397326e-02, -1.0199412e-03,  1.0786263e-02, ...,\n",
      "           1.0112063e-02, -6.9852192e-03, -6.4757215e-03],\n",
      "         [ 1.0720392e-02, -3.2282835e-03, -1.0194050e-04, ...,\n",
      "          -4.7621364e-03,  1.0120733e-02,  5.2126674e-03]],\n",
      "\n",
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      "          -2.5150599e-03, -3.5095667e-03, -5.6064618e-03],\n",
      "         [ 1.0596886e-02, -1.0044489e-02,  1.8063044e-03, ...,\n",
      "          -2.9223200e-03,  8.0995419e-04, -2.0323446e-02],\n",
      "         [-1.7607687e-03,  2.3017763e-03, -1.5706603e-03, ...,\n",
      "          -1.1904801e-02, -5.6624818e-03, -2.7024033e-03],\n",
      "         ...,\n",
      "         [-8.9463210e-03, -7.5343349e-03,  7.4039923e-04, ...,\n",
      "           1.2268053e-02, -1.3198548e-02, -3.2026084e-05],\n",
      "         [-3.9164912e-02, -7.5820535e-03,  1.3907746e-03, ...,\n",
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      "         [ 6.8326667e-03, -2.0392942e-03,  4.8815343e-03, ...,\n",
      "          -2.2594277e-03,  1.3842926e-03,  7.3076310e-03]]],\n",
      "\n",
      "\n",
      "       [[[ 4.3825014e-03, -8.4557459e-03,  6.0976552e-05, ...,\n",
      "          -1.5721424e-03, -6.2847957e-03, -6.0747643e-03],\n",
      "         [-1.9328265e-02,  4.7232583e-03,  5.4184967e-03, ...,\n",
      "          -7.3021773e-04,  5.4419693e-03, -1.3912930e-02],\n",
      "         [ 5.5229296e-03,  4.6481588e-03, -7.7780159e-03, ...,\n",
      "           2.7554642e-04, -1.3050669e-02, -3.9565605e-03],\n",
      "         ...,\n",
      "         [ 3.2179512e-04, -3.4885360e-03, -1.0874616e-02, ...,\n",
      "           8.2677584e-03, -1.1178210e-02,  7.5714481e-03],\n",
      "         [ 4.0616496e-03, -7.2419085e-03, -1.3705336e-03, ...,\n",
      "           1.0747767e-02, -7.4744545e-04, -1.1671883e-02],\n",
      "         [ 1.2030830e-03,  7.4582128e-04,  3.5220869e-03, ...,\n",
      "          -1.7955588e-04,  2.9120417e-03,  6.2693246e-03]],\n",
      "\n",
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      "          -8.2665663e-03, -1.9626400e-02, -7.4289762e-03],\n",
      "         [-6.0759084e-03, -9.6884841e-04,  6.0364590e-03, ...,\n",
      "          -9.3692346e-03,  4.3691956e-03, -1.3639066e-02],\n",
      "         [-9.0519208e-03,  9.6781654e-03,  8.6934352e-03, ...,\n",
      "           9.1049206e-03, -9.7425170e-03, -7.6264590e-03],\n",
      "         ...,\n",
      "         [-3.8311486e-03,  7.1369117e-04, -1.1714270e-02, ...,\n",
      "           1.6859323e-02, -1.6344676e-02,  1.2910481e-02],\n",
      "         [ 9.2128823e-03, -1.5336460e-03,  5.2924841e-03, ...,\n",
      "           3.0931132e-03, -9.8296702e-03, -5.3623371e-04],\n",
      "         [ 3.9525158e-03,  9.3688892e-04,  3.7328359e-03, ...,\n",
      "          -5.5979183e-03,  1.0980255e-02,  1.2100901e-02]],\n",
      "\n",
      "        [[-1.7740640e-03, -1.1662573e-02,  1.6112716e-03, ...,\n",
      "           1.2962105e-04, -1.1654774e-02, -5.4892940e-03],\n",
      "         [ 1.5333769e-02, -6.9049154e-03,  9.9986177e-03, ...,\n",
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      "         [-1.9262903e-04,  2.8037187e-03, -1.7493139e-03, ...,\n",
      "           2.6137648e-02, -9.3979454e-03, -4.5618960e-03],\n",
      "         ...,\n",
      "         [-6.4418763e-03, -2.7641824e-03, -8.7552797e-03, ...,\n",
      "           1.0848792e-02, -1.2664125e-02,  1.1188427e-02],\n",
      "         [-1.4976529e-02, -8.0800392e-03,  1.1753010e-03, ...,\n",
      "          -1.4212406e-02, -1.4587110e-02, -5.5110687e-04],\n",
      "         [ 4.9651507e-03,  1.9658136e-03,  4.4132387e-03, ...,\n",
      "          -3.2392361e-03,  3.2961257e-03,  1.0079567e-02]]],\n",
      "\n",
      "\n",
      "       [[[-1.0813643e-02, -1.2109953e-03,  4.0739947e-03, ...,\n",
      "          -3.7609618e-03, -8.4045194e-03, -4.1101421e-03],\n",
      "         [-1.6155045e-02,  3.3042664e-04,  2.8314698e-03, ...,\n",
      "           3.8799408e-03,  1.0882318e-02, -1.2172839e-02],\n",
      "         [ 1.3959367e-02,  4.1269679e-03, -5.6302696e-03, ...,\n",
      "           8.7758545e-03, -3.2438899e-03, -3.4345812e-03],\n",
      "         ...,\n",
      "         [ 9.1708098e-03, -6.2859273e-03, -1.2609004e-02, ...,\n",
      "           1.6977531e-03, -9.6289860e-03,  5.1916544e-05],\n",
      "         [-9.7496519e-03, -2.1479633e-03, -1.9520836e-02, ...,\n",
      "          -9.5207070e-04,  6.3222921e-03, -1.7897552e-02],\n",
      "         [ 3.9352821e-03,  4.7744825e-03,  2.0808049e-03, ...,\n",
      "           9.7545320e-03, -1.2982457e-02,  4.6863281e-03]],\n",
      "\n",
      "        [[-6.3140173e-03, -2.0006283e-03, -4.0322897e-04, ...,\n",
      "           7.0220581e-03, -1.3161357e-02, -7.2546205e-03],\n",
      "         [-7.1486277e-03,  7.5339980e-04,  1.3867128e-03, ...,\n",
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      "         [-1.4313880e-03,  7.5597558e-03, -2.7771997e-03, ...,\n",
      "           3.3415109e-02, -3.9894031e-03, -6.9557610e-03],\n",
      "         ...,\n",
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      "          -6.8885856e-04, -1.6479922e-02, -1.7523849e-04],\n",
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      "          -5.6522340e-03, -8.0006220e-04, -1.0039192e-02],\n",
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      "          -5.3754007e-04, -1.7849701e-02,  5.1220311e-03]],\n",
      "\n",
      "        [[ 6.7127135e-04, -3.2391129e-03,  7.8760099e-04, ...,\n",
      "           7.2297198e-03, -5.2612908e-03, -4.2801294e-03],\n",
      "         [ 5.4616379e-03, -1.8265145e-03,  8.0440696e-03, ...,\n",
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      "         [ 4.7172702e-04,  6.6203335e-03, -5.3720833e-03, ...,\n",
      "           4.0812425e-02, -3.6152611e-03, -5.1507959e-03],\n",
      "         ...,\n",
      "         [-1.1449282e-03, -6.4645633e-03, -1.2517356e-02, ...,\n",
      "          -6.6413991e-03, -1.0809171e-02, -2.6953095e-03],\n",
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      "          -1.0663199e-02, -5.6493361e-03, -4.9214857e-03],\n",
      "         [ 4.3073772e-03,  3.5157984e-03,  4.7004086e-04, ...,\n",
      "          -2.4001813e-04, -1.6719183e-02,  4.8483759e-03]]]],\n",
      "      dtype=float32), array([ 9.72232521e-02, -7.32301399e-02,  1.51504159e-01,  1.07368380e-01,\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "           3.34846694e-03,  1.33423917e-02,  4.46979143e-03]]],\n",
      "\n",
      "\n",
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      "         [-6.78315479e-03,  7.97655899e-03,  1.22533282e-02, ...,\n",
      "           1.35311754e-02,  1.13436170e-02,  1.00916745e-02],\n",
      "         ...,\n",
      "         [-5.42715983e-03,  6.82500936e-03,  2.06867745e-03, ...,\n",
      "           1.15423445e-02,  1.35911524e-03, -5.60511416e-03],\n",
      "         [ 4.61982097e-03,  8.86386912e-03, -5.09008206e-03, ...,\n",
      "           2.30618101e-03, -2.10025930e-03, -1.28205456e-02],\n",
      "         [-1.71301316e-03, -1.08229686e-02, -6.23088004e-03, ...,\n",
      "          -9.36139748e-03,  4.23580030e-04,  6.02343772e-03]],\n",
      "\n",
      "        [[-7.84571003e-03, -7.72077264e-03, -4.10368491e-04, ...,\n",
      "          -4.64761769e-03,  4.84151114e-03, -8.10108799e-03],\n",
      "         [ 7.03802519e-03, -6.14652690e-03, -3.35389609e-03, ...,\n",
      "          -7.66926736e-04, -4.10724850e-03,  3.30237439e-03],\n",
      "         [-1.26976296e-02,  4.06949688e-03,  1.57761611e-02, ...,\n",
      "           2.05063750e-03,  1.35973999e-02,  2.45495401e-02],\n",
      "         ...,\n",
      "         [-4.94020339e-03, -6.04472240e-04,  3.70768807e-03, ...,\n",
      "           5.28301718e-03,  5.77830663e-03, -5.73270582e-03],\n",
      "         [ 6.47951430e-03,  5.04286960e-03, -5.76301245e-03, ...,\n",
      "          -3.84971802e-03, -1.53160375e-02, -1.36713414e-02],\n",
      "         [-6.13218453e-03, -7.85352290e-03, -2.66636047e-03, ...,\n",
      "          -2.86623905e-03,  8.13857932e-03,  3.23665445e-03]],\n",
      "\n",
      "        [[-1.03016887e-02, -7.32906163e-03, -1.26632303e-02, ...,\n",
      "          -1.51485833e-03, -4.73790773e-04, -1.50191726e-03],\n",
      "         [ 2.47099600e-03, -3.58005147e-03, -8.92815471e-04, ...,\n",
      "           2.19221620e-04, -5.89206407e-04,  1.02671504e-03],\n",
      "         [-7.04030367e-03,  2.31858669e-03,  1.17366202e-02, ...,\n",
      "          -1.00303544e-02,  9.60416254e-03,  3.07981335e-02],\n",
      "         ...,\n",
      "         [ 1.02732638e-02, -4.61639231e-03, -3.90697533e-04, ...,\n",
      "           5.76351210e-03,  5.99978026e-03, -6.46614050e-03],\n",
      "         [ 1.79310958e-03, -1.10877156e-02, -4.39016009e-03, ...,\n",
      "          -3.89495096e-03, -1.43652763e-02, -1.33516490e-02],\n",
      "         [-4.76273848e-03,  9.76819452e-03, -6.88574556e-03, ...,\n",
      "           7.87178893e-03,  2.10002940e-02,  2.46465113e-03]]]],\n",
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      "      dtype=float32), array([[[[ 4.07882966e-04,  4.82621184e-03, -9.11695044e-03, ...,\n",
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      "\n",
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      "         [-9.60117579e-03,  5.01031429e-03, -1.13053191e-02, ...,\n",
      "           8.86707660e-03,  6.21224102e-03,  2.48882570e-03],\n",
      "         [-1.13499342e-02, -4.72285505e-03, -8.57903156e-03, ...,\n",
      "          -3.04920389e-03,  9.67197306e-03,  1.90250184e-02],\n",
      "         ...,\n",
      "         [-4.48127137e-03,  5.53716440e-03,  4.68912302e-03, ...,\n",
      "          -4.91005788e-03,  6.40070112e-03, -8.28019064e-03],\n",
      "         [-6.00830279e-03, -7.51605199e-04,  8.29616503e-04, ...,\n",
      "           2.07461347e-03,  3.22994636e-03, -1.69727230e-03],\n",
      "         [-2.81035155e-03,  1.36994272e-02, -2.04460253e-03, ...,\n",
      "          -5.17683988e-03, -9.04289633e-03, -1.79657899e-03]],\n",
      "\n",
      "        [[ 3.09069827e-03, -7.85107608e-04, -1.12262042e-02, ...,\n",
      "           1.38624888e-02, -1.50248851e-03, -2.83075101e-03],\n",
      "         [-1.78263709e-02, -4.06336552e-03, -1.11764381e-02, ...,\n",
      "           1.76884588e-02, -1.14172359e-03,  1.50952139e-03],\n",
      "         [-1.26420632e-02, -1.19902752e-03, -1.03873471e-02, ...,\n",
      "          -1.54873531e-03,  3.21487361e-03,  1.84067711e-02],\n",
      "         ...,\n",
      "         [ 4.99952445e-03,  8.96072667e-03,  2.35912274e-03, ...,\n",
      "          -6.95799524e-03,  9.11425054e-03, -1.76598097e-03],\n",
      "         [-3.11188446e-03, -4.81695170e-03,  2.14671413e-03, ...,\n",
      "           8.69878661e-03,  4.66441829e-03,  3.96351190e-03],\n",
      "         [-1.56560540e-03,  1.01758400e-02, -1.81451999e-03, ...,\n",
      "          -7.93038029e-03, -7.92690739e-03,  9.85421613e-03]]],\n",
      "\n",
      "\n",
      "       [[[ 2.21009902e-03,  5.53841889e-03, -1.51329748e-02, ...,\n",
      "           1.92244705e-02, -2.94085429e-03, -2.05214042e-03],\n",
      "         [ 4.31180233e-03, -4.67703957e-03, -9.83539224e-03, ...,\n",
      "          -1.16664264e-03, -7.47026131e-03,  8.98758229e-03],\n",
      "         [-1.00150378e-02, -3.31197702e-03, -4.38165246e-03, ...,\n",
      "           1.28704909e-04,  6.90069282e-05,  5.32614533e-03],\n",
      "         ...,\n",
      "         [-1.65325180e-02,  5.79520175e-03, -1.08136714e-03, ...,\n",
      "          -3.87264206e-03,  3.87065555e-03, -8.52444116e-03],\n",
      "         [-1.10835498e-02,  6.04208373e-03,  6.12878706e-03, ...,\n",
      "          -4.66409931e-03, -1.65367487e-03, -4.93706390e-03],\n",
      "         [-5.82469627e-03,  2.77068373e-03,  2.59765168e-03, ...,\n",
      "          -9.57501866e-03, -3.32338479e-03,  3.07677989e-03]],\n",
      "\n",
      "        [[ 3.59932799e-03,  1.19693214e-02, -1.60994809e-02, ...,\n",
      "           1.80910621e-02,  3.29896147e-06, -6.10836258e-04],\n",
      "         [-7.41903298e-03, -5.61146066e-03, -1.38216335e-02, ...,\n",
      "           2.96197180e-03,  2.69207382e-03,  7.01817824e-03],\n",
      "         [-8.48251395e-03,  9.95878596e-04,  6.25522574e-04, ...,\n",
      "          -3.68017773e-03,  1.27349654e-02,  4.87677474e-03],\n",
      "         ...,\n",
      "         [-8.20725970e-03,  1.95525214e-03,  2.69707199e-03, ...,\n",
      "          -4.49266564e-03,  6.45229314e-03, -1.28380703e-02],\n",
      "         [-5.50353806e-03,  1.61080994e-03,  1.39699667e-03, ...,\n",
      "          -2.52319360e-03, -4.11227718e-03, -5.21757640e-03],\n",
      "         [-2.69698747e-03,  2.70054420e-03,  3.79564380e-03, ...,\n",
      "          -7.66708190e-03, -9.20492224e-03, -4.52092383e-03]],\n",
      "\n",
      "        [[ 2.48262100e-03,  6.13112841e-03, -1.47995697e-02, ...,\n",
      "           1.69335436e-02,  1.16662926e-03,  1.17623655e-03],\n",
      "         [-1.69411730e-02, -8.71018134e-03, -1.29530905e-02, ...,\n",
      "           1.87354535e-03, -6.88433880e-04, -1.68701622e-03],\n",
      "         [-6.59902534e-03,  3.46401357e-03, -3.11806914e-03, ...,\n",
      "          -4.05590283e-03,  7.37769250e-03,  5.51742781e-03],\n",
      "         ...,\n",
      "         [ 9.51702707e-04,  1.64372730e-03,  1.49127271e-03, ...,\n",
      "          -7.65326899e-03,  1.19846454e-02, -9.10102390e-03],\n",
      "         [ 2.88849953e-03, -5.35335718e-03, -3.08376068e-04, ...,\n",
      "           3.87483276e-04, -4.36716061e-03, -2.73425644e-03],\n",
      "         [-1.54271268e-03,  4.30263951e-03, -4.31923472e-05, ...,\n",
      "          -5.21167647e-03, -8.79874174e-03, -2.11346560e-04]]],\n",
      "\n",
      "\n",
      "       [[[-2.93453527e-03,  4.62880917e-03, -9.69677325e-03, ...,\n",
      "           1.48544796e-02,  3.87839018e-03,  1.85810984e-03],\n",
      "         [ 5.63784037e-03, -6.04889123e-03, -5.59245935e-03, ...,\n",
      "          -4.98529337e-03, -1.92062720e-03,  4.07473044e-03],\n",
      "         [-4.84194839e-03,  2.70295335e-04, -3.02166585e-03, ...,\n",
      "          -1.49492722e-03, -1.31164724e-02,  2.69274553e-03],\n",
      "         ...,\n",
      "         [-1.79702230e-02, -3.29879066e-03, -6.12194091e-03, ...,\n",
      "          -7.89267663e-03, -1.74841529e-03, -2.64002383e-03],\n",
      "         [-1.11466460e-02,  5.13884844e-03,  1.51880039e-02, ...,\n",
      "          -4.87166690e-03,  2.45198980e-03, -3.42866592e-03],\n",
      "         [-6.12380216e-03,  8.87359586e-03, -3.45014478e-03, ...,\n",
      "          -1.09723555e-02,  2.66773975e-03, -4.79325093e-03]],\n",
      "\n",
      "        [[-6.14633691e-03,  1.40388934e-02, -9.19489283e-03, ...,\n",
      "           1.60656814e-02,  8.88941437e-03,  6.56510517e-03],\n",
      "         [-5.72578516e-03, -3.33702704e-03, -8.64025764e-03, ...,\n",
      "           1.98416272e-03,  7.86264334e-03,  2.50778953e-03],\n",
      "         [-3.77366156e-03,  9.24240507e-04,  7.29091058e-04, ...,\n",
      "          -4.96890210e-03,  3.85057204e-03, -7.15580711e-04],\n",
      "         ...,\n",
      "         [-1.22111076e-02, -2.42003356e-03, -4.81141545e-03, ...,\n",
      "          -4.22020489e-03, -1.01946108e-02, -5.80721162e-03],\n",
      "         [-9.04400460e-03,  1.94370467e-03,  7.34009594e-03, ...,\n",
      "          -5.14973374e-03,  3.66879918e-04, -5.37241250e-03],\n",
      "         [-3.53684562e-04,  1.53788179e-02, -8.76262202e-04, ...,\n",
      "          -7.13666994e-03, -4.27656015e-03, -1.42133404e-02]],\n",
      "\n",
      "        [[-6.67408668e-03,  9.11168288e-03, -9.18486901e-03, ...,\n",
      "           1.21346870e-02,  8.51947255e-03,  7.15135690e-03],\n",
      "         [-1.64910071e-02, -2.04550894e-03, -7.30760070e-03, ...,\n",
      "          -2.89353775e-03,  1.16095145e-03, -6.60440046e-03],\n",
      "         [-7.68517129e-05,  4.32093628e-03, -6.93119306e-04, ...,\n",
      "          -3.48316878e-03, -1.47545757e-03, -2.85687298e-03],\n",
      "         ...,\n",
      "         [-4.66702832e-03, -1.39780261e-03,  3.67210196e-05, ...,\n",
      "          -4.95146902e-04,  7.23151665e-04, -6.29519764e-03],\n",
      "         [ 3.63699184e-03, -4.63909749e-03,  5.31478412e-03, ...,\n",
      "          -1.50180201e-03, -7.48660788e-03, -1.94359326e-03],\n",
      "         [-1.03440508e-03,  1.57131702e-02, -1.98940560e-03, ...,\n",
      "          -5.38550608e-04, -5.37431426e-03, -9.20103770e-03]]]],\n",
      "      dtype=float32), array([ 1.88378572e-01, -5.00367463e-01,  5.42223394e-01,  2.46460959e-01,\n",
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      "       -1.18016593e-01,  3.89179081e-01,  6.13915585e-02,  1.58884943e-01,\n",
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      "        8.00405815e-03,  1.03328384e-01,  6.38187110e-01, -2.65396535e-02],\n",
      "      dtype=float32), array([[ 1.9745843e-05,  3.5308721e-04, -1.8327669e-03, ...,\n",
      "         3.9865216e-05, -2.8762815e-03,  3.3547997e-03],\n",
      "       [-5.3512463e-03, -1.5712962e-03, -3.3635952e-04, ...,\n",
      "         1.8792559e-03,  1.2153931e-04,  4.3403511e-03],\n",
      "       [ 6.6062581e-04,  1.3003269e-03, -1.2985406e-03, ...,\n",
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      "       ...,\n",
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      "        -1.1366602e-03, -2.6967376e-03, -4.3831998e-03],\n",
      "       [ 1.1018270e-05, -6.4710301e-04, -3.5804727e-03, ...,\n",
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      "       ...,\n",
      "       [-4.2402726e-03, -4.1440636e-04, -7.8919629e-04, ...,\n",
      "         6.7993044e-03,  3.3782453e-03,  2.1300779e-03],\n",
      "       [ 2.7873128e-04,  9.5619177e-03, -6.2027783e-04, ...,\n",
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      "       -5.23509048e-02, -3.27926353e-02, -4.29225296e-01,  9.61615294e-02,\n",
      "       -2.68748164e-01,  3.48229222e-02, -9.26967636e-02,  3.02183889e-02,\n",
      "       -1.82041228e-01,  3.01436245e-01,  2.19889745e-01, -3.02020669e-01,\n",
      "       -2.99036473e-01, -2.29967833e-01, -4.03366759e-02,  2.74010119e-03,\n",
      "       -7.60478377e-02,  2.14070175e-02, -9.92808957e-03,  1.09518096e-01,\n",
      "        5.47809452e-02, -2.14443997e-01, -3.88127640e-02,  1.10027112e-01,\n",
      "        8.63001794e-02, -1.09026894e-01, -4.44379926e-01,  1.57961577e-01,\n",
      "        3.88418078e-01, -9.30987224e-02, -2.00593799e-01, -3.94143015e-01,\n",
      "        2.76999384e-01, -2.76881754e-01, -2.45977994e-02,  6.18116520e-02,\n",
      "       -1.54404044e-01,  5.95636517e-02, -9.68015492e-02, -3.80554795e-02,\n",
      "        1.92538202e-01, -2.53902704e-01,  1.26906797e-01, -4.18434322e-01,\n",
      "        3.59356664e-02,  1.06743202e-01,  3.03134918e-02,  7.96772167e-02,\n",
      "        1.53593987e-01,  2.81762034e-01, -9.64698941e-03, -2.39103213e-01,\n",
      "        2.00148374e-01,  6.83301091e-02, -1.12748824e-01, -1.41695827e-01,\n",
      "        7.72262886e-02,  4.37719285e-01,  3.28358859e-01, -9.87312943e-02,\n",
      "        2.35043928e-01,  1.29182693e-02, -2.29334682e-01, -7.31632710e-02,\n",
      "       -3.56310494e-02, -7.71469623e-02, -4.11267467e-02, -1.84743181e-01,\n",
      "        1.97621323e-02, -1.54743701e-01, -9.44059044e-02,  1.70897409e-01,\n",
      "        2.05339968e-01,  5.79193421e-02, -1.47543788e-01,  1.40179403e-03,\n",
      "       -1.59304962e-01,  2.41777733e-01,  3.13533276e-01,  9.94566828e-02,\n",
      "       -2.15047851e-01,  6.61554277e-01,  2.15601802e-01, -3.26034635e-01,\n",
      "        3.62915963e-01, -1.25578746e-01,  1.30391777e-01, -2.03896046e-01,\n",
      "       -1.01061620e-01,  2.35982344e-01, -1.08665332e-01,  3.19816679e-01,\n",
      "       -5.96375823e-01,  3.58648747e-01, -1.66183963e-01,  2.11995900e-01,\n",
      "        2.71255195e-01, -1.51585326e-01, -3.68063539e-01,  1.71736702e-01,\n",
      "        3.28822583e-01, -5.14503896e-01,  1.06420293e-01, -9.34555531e-02,\n",
      "        8.85837153e-03, -4.79865894e-02, -2.78120041e-01,  2.66117603e-01,\n",
      "        1.53323188e-01,  1.88923091e-01, -5.50708234e-01, -3.17821652e-01,\n",
      "       -3.97314969e-03,  3.36861581e-01, -3.53023075e-02,  8.11930969e-02,\n",
      "        2.01493874e-02,  1.13539979e-01, -2.57008851e-01,  1.20594323e-01,\n",
      "       -6.07023090e-02,  2.53488541e-01, -1.93311870e-01,  2.22055800e-02,\n",
      "        3.40380799e-03,  8.13584551e-02,  2.13198051e-01,  1.06076859e-01,\n",
      "        8.93639550e-02, -1.16665944e-01,  5.07529736e-01,  2.82721758e-01,\n",
      "       -4.85968739e-02,  2.36526996e-01, -9.78009477e-02,  1.08019106e-01,\n",
      "        1.10580362e-02,  4.45747636e-02,  7.24380836e-02,  7.33082891e-02,\n",
      "       -1.83945850e-01,  7.50664026e-02, -1.07252218e-01,  9.72431004e-02,\n",
      "       -1.26904279e-01, -2.21656069e-01, -3.16477823e-03, -1.57726929e-01,\n",
      "        8.37494805e-02,  4.73893844e-02, -1.26203075e-01, -1.58091143e-01,\n",
      "        2.56713152e-01,  2.39656374e-01,  2.41455734e-01,  2.86579162e-01,\n",
      "       -5.89559004e-02, -7.70056620e-02, -1.27792493e-01,  1.08871132e-01,\n",
      "       -1.80923402e-01,  2.04007596e-01, -2.77992725e-01, -2.99343556e-01,\n",
      "       -3.47748756e-01,  1.03403002e-01, -2.65172809e-01,  3.17481279e-01,\n",
      "        4.92871813e-02, -2.82148272e-01, -2.99710687e-02, -2.01014772e-01,\n",
      "        8.91936645e-02,  1.29341409e-01,  1.58690795e-01, -2.31155492e-02,\n",
      "       -9.80640426e-02, -2.63858438e-01, -1.05089135e-01,  7.02425977e-03,\n",
      "       -1.54035792e-01,  2.88572237e-02, -9.40687880e-02,  1.37397973e-02,\n",
      "       -1.85936883e-01, -1.99694633e-01, -1.88284636e-01,  1.11082152e-01,\n",
      "       -2.98224032e-01,  2.64982283e-01,  1.02928899e-01,  3.10218275e-01,\n",
      "        6.37436509e-02,  1.87500566e-01, -7.08252341e-02,  1.78866297e-01,\n",
      "       -1.33074969e-02,  6.07544789e-03,  1.71582147e-01, -2.00540990e-01,\n",
      "        1.77108720e-01,  3.83099943e-01,  3.11959125e-02, -1.12747177e-02,\n",
      "       -1.88991070e-01,  1.06476126e-02, -2.41802081e-01,  2.04456866e-01,\n",
      "       -7.02743009e-02,  8.08617920e-02,  9.99190882e-02, -2.96304584e-01,\n",
      "        1.56103358e-01, -3.30614075e-02,  7.68040195e-02,  7.13191032e-02,\n",
      "        1.09010130e-01,  2.18562987e-02, -1.32266283e-01, -3.66455764e-01,\n",
      "       -3.09116870e-01,  2.46384665e-01,  3.83441150e-02, -1.35635167e-01,\n",
      "        1.54956892e-01,  8.23109671e-02, -1.90329432e-01,  5.62940612e-02,\n",
      "        2.08148494e-01, -6.86692521e-02, -6.46717623e-02,  1.78772002e-01,\n",
      "       -3.54407094e-02,  6.61408249e-03,  3.19102481e-02,  2.43296757e-01,\n",
      "       -7.89071843e-02,  2.71633059e-01,  3.53015721e-01,  6.49214610e-02,\n",
      "       -4.93360311e-02, -2.53010899e-01, -2.20387116e-01, -2.12388903e-01,\n",
      "       -6.46074414e-02, -2.34868914e-01,  4.86683026e-02, -1.73911035e-01,\n",
      "       -2.49400318e-01, -8.87992755e-02, -1.01867363e-01,  1.10653363e-01,\n",
      "        2.95795351e-01, -1.04534365e-01,  5.02307303e-02,  2.32064411e-01,\n",
      "        3.03720366e-02,  2.28106797e-01,  3.42497155e-02,  4.23023641e-01,\n",
      "        3.24395865e-01,  1.14638172e-01,  1.40322417e-01, -1.24564677e-01,\n",
      "        4.03874665e-02,  5.32965958e-02,  1.08100004e-01, -9.97158214e-02,\n",
      "       -8.61078352e-02,  9.24116150e-02,  7.92659074e-02, -5.05171157e-02,\n",
      "        1.25704318e-01,  1.04924835e-01,  1.19186878e-01,  3.99102718e-01,\n",
      "        5.69467479e-03,  2.62577444e-01,  1.96448743e-01, -5.57917878e-02,\n",
      "       -2.83148378e-01, -5.71238659e-02, -4.18196283e-02, -1.34959996e-01,\n",
      "        2.44432747e-01,  1.96212813e-01,  1.76779076e-01, -2.82300353e-01,\n",
      "       -3.63970757e-01,  1.06617555e-01, -5.49449399e-02, -2.69589666e-02,\n",
      "       -7.15252105e-03,  6.78250939e-02,  4.73630019e-02,  2.12414730e-02,\n",
      "        1.51467890e-01, -3.08990121e-01,  3.65680866e-02,  8.44068602e-02,\n",
      "        2.92029738e-01,  5.76959401e-02,  7.19695911e-02, -6.48553967e-02,\n",
      "       -5.92227131e-02, -6.63810447e-02, -1.56919926e-01,  1.33844599e-01,\n",
      "        6.46995530e-02, -3.79350543e-01,  2.07627267e-01,  1.97371587e-01,\n",
      "       -1.44551784e-01,  1.61238596e-01,  2.03476269e-02,  8.17952156e-02,\n",
      "        1.69843912e-01,  2.65522212e-01, -2.47451484e-01, -1.04817912e-01,\n",
      "       -5.95463403e-02,  1.93816096e-01, -6.51506409e-02, -4.01689187e-02,\n",
      "        2.83639997e-01,  1.85533717e-01,  8.50528404e-02, -1.74677238e-01,\n",
      "        3.15265991e-02,  7.46492371e-02,  2.13453308e-01, -1.24020875e-01,\n",
      "        1.91519365e-01,  1.78387798e-02, -2.83224076e-01,  1.73476890e-01,\n",
      "       -1.59820512e-01, -2.07712919e-01, -9.83787403e-02, -1.17707163e-01,\n",
      "       -2.99897313e-01,  1.97331998e-02, -1.30447000e-01,  5.68884909e-01,\n",
      "        2.02400357e-01,  9.53263342e-02,  1.09425671e-01,  2.17016503e-01,\n",
      "       -1.16832331e-01,  1.31859794e-01, -2.93441117e-01,  9.95540619e-03,\n",
      "        1.91912919e-01,  1.83856502e-01,  6.28124736e-03,  2.33748883e-01,\n",
      "        6.95756972e-02, -2.84148932e-01, -2.28914022e-01,  1.14056818e-01,\n",
      "        3.10754597e-01,  1.30028361e-02,  1.07273541e-01, -1.49803549e-01,\n",
      "        2.18955293e-01,  9.68839601e-03,  1.54492613e-02,  2.40088105e-01,\n",
      "        1.37932509e-01, -1.65427938e-01, -2.00555414e-01,  1.54215485e-01,\n",
      "       -3.49219590e-02,  9.86149013e-02, -1.36984587e-02, -5.27915284e-02,\n",
      "       -3.73023301e-01, -1.16201438e-01, -6.46326020e-02,  2.48952329e-01,\n",
      "        1.94591254e-01,  2.54418850e-01, -1.66224346e-01, -4.12210226e-01,\n",
      "        1.77814230e-01, -9.66862813e-02, -1.80993870e-01, -2.21908018e-01,\n",
      "        1.15384631e-01,  3.85584295e-01,  6.33145198e-02, -9.78029296e-02,\n",
      "        2.13495135e-01, -1.01017216e-02, -3.74827951e-01,  5.78340515e-02,\n",
      "        1.85769886e-01,  1.28680319e-01,  3.46764982e-01, -2.88785577e-01,\n",
      "       -1.55606970e-01, -4.98000979e-02, -8.68151411e-02,  1.56666309e-01,\n",
      "       -4.54940677e-01,  2.88726598e-01, -1.78260416e-01, -1.81515068e-02,\n",
      "       -3.79383191e-02, -2.54814565e-01, -1.92338735e-01,  8.07066336e-02,\n",
      "       -2.27573365e-02,  2.66216874e-01, -2.47544155e-01, -1.62488446e-01,\n",
      "       -3.86822037e-03, -1.42082954e-02, -1.01989619e-01,  5.81471808e-02,\n",
      "        4.43896472e-01, -2.09462136e-01, -1.44992396e-01,  1.18998215e-01,\n",
      "       -2.08252698e-01,  1.03888009e-03,  1.25588447e-01,  8.77775550e-02,\n",
      "        4.91692424e-02,  4.57712077e-02, -6.72740415e-02, -1.40756741e-01,\n",
      "        2.95674652e-01, -1.94071963e-01, -5.38161620e-02,  1.03020057e-01,\n",
      "       -4.06550430e-02,  5.53897619e-02,  3.16263407e-01,  4.94446047e-03,\n",
      "        4.25704243e-03,  1.64224878e-02,  1.36242703e-01, -5.03990501e-02,\n",
      "        4.39317338e-02, -4.33006249e-02,  2.97178477e-01,  6.68855384e-02,\n",
      "       -3.18897575e-01,  2.87862033e-01, -8.61071944e-02, -4.33747284e-02,\n",
      "        4.23714221e-01,  1.36175096e-01,  1.70700014e-01, -1.28886417e-01,\n",
      "       -1.13043129e-01, -9.36776772e-02, -1.45163909e-01,  1.52960867e-01,\n",
      "       -1.64776385e-01,  4.20643277e-02, -3.29479963e-01, -1.76425476e-03,\n",
      "        2.03022644e-01, -2.42612045e-02, -1.43776894e-01, -1.55589879e-02,\n",
      "        2.31185272e-01,  3.16479951e-01, -2.24453323e-02, -1.69366643e-01,\n",
      "        7.30249584e-02,  4.30509336e-02,  9.77676362e-02, -1.28292903e-01,\n",
      "       -4.14665528e-02, -1.81730893e-02, -2.19049051e-01, -7.10237622e-02,\n",
      "        4.96124104e-02, -4.39426750e-02, -3.34551185e-02, -6.80715069e-02,\n",
      "        2.98058003e-01, -7.57186860e-02,  3.38989943e-01, -2.00808048e-01,\n",
      "        1.28271684e-01, -1.61066711e-01, -7.84389302e-02,  2.79846396e-02,\n",
      "       -1.29030854e-01,  6.65723309e-02, -4.73634303e-02,  8.44092946e-03,\n",
      "       -4.31498475e-02,  3.50858659e-01,  2.47312561e-01,  1.71012580e-02,\n",
      "        8.30148831e-02,  6.95716217e-02,  8.06149319e-02, -2.99709439e-01,\n",
      "       -1.18023872e-01, -9.03939828e-02, -9.29232780e-03,  3.15105021e-02,\n",
      "        2.79686868e-01,  2.06215411e-01, -1.24735445e-01,  1.25766218e-01,\n",
      "       -1.97523445e-01,  9.39313471e-02,  2.32210457e-01, -2.20749810e-01,\n",
      "       -2.17107475e-01,  1.89073324e-01, -2.92044818e-01,  1.45295607e-02,\n",
      "        1.37102613e-02,  2.79758453e-01,  3.15825194e-01,  1.66462526e-01,\n",
      "       -2.04868197e-01,  3.67377341e-01,  2.88046330e-01,  2.12331444e-01,\n",
      "        8.13924670e-02,  2.92219184e-02,  4.26095605e-01, -1.10298648e-01,\n",
      "        2.13743925e-01,  4.50479209e-01,  2.79854797e-02,  4.78031337e-02,\n",
      "       -2.62548029e-01,  2.22016856e-01,  2.69986063e-01,  5.69859207e-01,\n",
      "        1.06991112e-01, -7.44247437e-02, -1.06252879e-01,  2.80053392e-02,\n",
      "        1.37361407e-01,  1.12478398e-01,  8.59951749e-02,  1.88605711e-01,\n",
      "       -3.55958283e-01,  2.01783646e-02, -5.25891632e-02, -3.70123386e-01,\n",
      "        1.17209004e-02, -2.47027010e-01, -1.97182924e-01,  1.83795597e-02,\n",
      "       -3.78327928e-02, -1.44162744e-01, -3.15390490e-02,  1.93142131e-01,\n",
      "       -1.94201559e-01, -1.09726980e-01, -1.05162881e-01, -1.20475190e-02,\n",
      "        5.05213961e-02,  1.61664739e-01,  2.60368526e-01,  1.99650526e-02,\n",
      "       -2.45607588e-02,  4.94334280e-01, -6.90028071e-02,  1.90971166e-01,\n",
      "       -3.54829967e-01,  1.30861267e-01,  8.78338411e-04,  2.82411665e-01,\n",
      "       -6.83389008e-02, -1.79678407e-02,  3.48581523e-02,  9.36345533e-02,\n",
      "        1.06942348e-01,  3.35311353e-01, -1.95149288e-01,  1.13856271e-01,\n",
      "       -1.75176784e-02,  2.07067057e-01,  3.09330225e-01,  1.15253121e-01,\n",
      "       -1.90390095e-01, -3.61254513e-01, -2.33271167e-01,  1.05221532e-02,\n",
      "        2.05175385e-01,  1.15790188e-01, -1.09400995e-01, -3.78039986e-01,\n",
      "       -1.19622044e-01, -3.06981206e-01, -2.28698120e-01, -3.59551072e-01,\n",
      "       -3.53780180e-01,  1.17287606e-01, -4.48820367e-02,  1.18562914e-01],\n",
      "      dtype=float32)]\n"
     ]
    }
   ],
   "source": [
    "print vgg16.get_weights()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "for layer in model.layers[:10]:\n",
    "    layer.trainable = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.optimizers import SGD\n",
    "sgd = SGD(lr=1e-3, decay=1e-6, momentum=0.9, nesterov=True)\n",
    "model.compile(optimizer=sgd, loss='categorical_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.preprocessing.image import ImageDataGenerator\n",
    "train_datagen=ImageDataGenerator(shear_range=0.2,zoom_range=0.2,horizontal_flip=True,validation_split=0.1)\n",
    "test_datagen=ImageDataGenerator()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 28366 images belonging to 256 classes.\n"
     ]
    }
   ],
   "source": [
    "train_generator=train_datagen.flow_from_directory(\n",
    "    '/Users/sks000y/Downloads/UECFOOD256',\n",
    "    target_size=(224,224),batch_size=32,class_mode='categorical',subset='training')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 3029 images belonging to 256 classes.\n"
     ]
    }
   ],
   "source": [
    "test_generator=train_datagen.flow_from_directory(\n",
    "    '/Users/sks000y/Downloads/UECFOOD256',\n",
    "    target_size=(224,224),batch_size=32,class_mode='categorical',subset='validation')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "   2/1000 [..............................] - ETA: 5:51:48 - loss: 8.2735 - acc: 0.0000e+00"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-86-154a7168c60a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0mepochs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0mvalidation_data\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtest_generator\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m     validation_steps=50)\n\u001b[0m",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/keras/legacy/interfaces.pyc\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     89\u001b[0m                 warnings.warn('Update your `' + object_name +\n\u001b[1;32m     90\u001b[0m                               '` call to the Keras 2 API: ' + signature, stacklevel=2)\n\u001b[0;32m---> 91\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     92\u001b[0m         \u001b[0mwrapper\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_original_function\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     93\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/keras/engine/training.pyc\u001b[0m in \u001b[0;36mfit_generator\u001b[0;34m(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)\u001b[0m\n\u001b[1;32m   1424\u001b[0m             \u001b[0muse_multiprocessing\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0muse_multiprocessing\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1425\u001b[0m             \u001b[0mshuffle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mshuffle\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1426\u001b[0;31m             initial_epoch=initial_epoch)\n\u001b[0m\u001b[1;32m   1427\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1428\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0minterfaces\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlegacy_generator_methods_support\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/keras/engine/training_generator.pyc\u001b[0m in \u001b[0;36mfit_generator\u001b[0;34m(model, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)\u001b[0m\n\u001b[1;32m    189\u001b[0m                 outs = model.train_on_batch(x, y,\n\u001b[1;32m    190\u001b[0m                                             \u001b[0msample_weight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msample_weight\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 191\u001b[0;31m                                             class_weight=class_weight)\n\u001b[0m\u001b[1;32m    192\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    193\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mouts\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/keras/engine/training.pyc\u001b[0m in \u001b[0;36mtrain_on_batch\u001b[0;34m(self, x, y, sample_weight, class_weight)\u001b[0m\n\u001b[1;32m   1218\u001b[0m             \u001b[0mins\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0msample_weights\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1219\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_train_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1220\u001b[0;31m         \u001b[0moutputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mins\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1221\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutputs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1222\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0moutputs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/keras/backend/tensorflow_backend.pyc\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, inputs)\u001b[0m\n\u001b[1;32m   2659\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_legacy_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2660\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2661\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2662\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2663\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mpy_any\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mis_tensor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/keras/backend/tensorflow_backend.pyc\u001b[0m in \u001b[0;36m_call\u001b[0;34m(self, inputs)\u001b[0m\n\u001b[1;32m   2629\u001b[0m                                 \u001b[0msymbol_vals\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2630\u001b[0m                                 session)\n\u001b[0;32m-> 2631\u001b[0;31m         \u001b[0mfetched\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_callable_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0marray_vals\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2632\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mfetched\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moutputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2633\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda2/envs/Keras/lib/python2.7/site-packages/tensorflow/python/client/session.pyc\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m   1449\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_session\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_created_with_new_api\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1450\u001b[0m           return tf_session.TF_SessionRunCallable(\n\u001b[0;32m-> 1451\u001b[0;31m               self._session._session, self._handle, args, status, None)\n\u001b[0m\u001b[1;32m   1452\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1453\u001b[0m           return tf_session.TF_DeprecatedSessionRunCallable(\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "model.fit_generator(\n",
    "    train_generator,\n",
    "    steps_per_epoch=1000,\n",
    "    epochs=1,\n",
    "    validation_data=test_generator,\n",
    "    validation_steps=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save_weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.simplefilter('ignore', UserWarning)\n",
    "warnings.simplefilter('ignore', DeprecationWarning)\n",
    "\n",
    "from __future__ import print_function\n",
    "from itertools import izip_longest as zip_longest\n",
    "from pprint import pformat as pf\n",
    "from pprint import pprint as pp\n",
    "import os\n",
    "\n",
    "from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img\n",
    "from keras.layers import Conv2D, MaxPooling2D, MaxPooling2D, ZeroPadding2D\n",
    "from keras.layers import Dropout, Flatten, Dense, InputLayer, Lambda\n",
    "from keras.models import Sequential, Model, load_model\n",
    "from keras.utils.data_utils import get_file\n",
    "from keras.optimizers import SGD\n",
    "import keras.backend as K\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "RANDOM_STATE = 1\n",
    "IMAGE_WIDTH = 224\n",
    "IMAGE_HEIGHT = 224\n",
    "BATCH_SIZE = 4\n",
    "VGG_MEAN = np.array([123.68, 116.779, 103.939]).reshape((3, 1, 1))\n",
    "VGG16_WEIGHTS_PATH = 'http://www.platform.ai/models/vgg16.h5'\n",
    "DATA_ROOT = os.path.join(os.path.expanduser('~'), 'data', 'dogscats')\n",
    "TRAIN_DIR = os.path.join(DATA_ROOT, 'train')\n",
    "VALID_DIR = os.path.join(DATA_ROOT, 'valid')\n",
    "SAMPLES_DIR = os.path.expanduser('~/dogscats_samples')\n",
    "\n",
    "\n",
    "np.random.seed(RANDOM_STATE)\n",
    "K.set_image_dim_ordering('th')\n",
    "\n",
    "\n",
    "def get_batches(dirname, gen=ImageDataGenerator(), shuffle=True, \n",
    "                batch_size=BATCH_SIZE, class_mode='categorical'):\n",
    "    return gen.flow_from_directory(\n",
    "        os.path.join(SAMPLES_DIR, dirname),\n",
    "        target_size=(IMAGE_WIDTH, IMAGE_HEIGHT),\n",
    "        class_mode=class_mode,\n",
    "        shuffle=shuffle,\n",
    "        batch_size=batch_size)\n",
    "\n",
    "def vgg_preprocess(x):\n",
    "    x = x - VGG_MEAN\n",
    "    return x[:, ::-1]\n",
    "\n",
    "def conv_block(model, n_layers, n_filters, name='block'):\n",
    "    for i in range(n_layers):\n",
    "        model.add(ZeroPadding2D((1, 1), name='%s_padding_%s' % (name, i)))\n",
    "        model.add(Conv2D(n_filters, (3, 3), activation='relu', name='%s_conv2d_%s' % (name, i)))\n",
    "    model.add(MaxPooling2D((2, 2), strides=(2, 2), name='%s_maxpool' % name))\n",
    "\n",
    "def fc_block(model, name='block'):\n",
    "    model.add(Dense(4096, activation='relu', name=name + '_dense'))\n",
    "    model.add(Dropout(0.5))\n",
    "\n",
    "def build_vgg_16():\n",
    "    model = Sequential()\n",
    "    input_shape = (3, IMAGE_WIDTH, IMAGE_HEIGHT) \n",
    "    model.add(InputLayer(input_shape=input_shape))\n",
    "    model.add(Lambda(vgg_preprocess))\n",
    "    conv_block(model, n_layers=2, n_filters=64, name='block1')\n",
    "    conv_block(model, n_layers=2, n_filters=128, name='block2')\n",
    "    conv_block(model, n_layers=3, n_filters=256, name='block3')\n",
    "    conv_block(model, n_layers=3, n_filters=512, name='block4')\n",
    "    conv_block(model, n_layers=3, n_filters=512, name='block5')\n",
    "    model.add(Flatten())\n",
    "    fc_block(model,'1')\n",
    "    fc_block(model,'2')\n",
    "    model.add(Dense(1000, activation='softmax'))\n",
    "    return model\n",
    "\n",
    "def train_finetuned_model(lr=1e-5, verbose=True):\n",
    "    file_path = get_file('vgg16.h5', VGG16_WEIGHTS_PATH, cache_subdir='models')\n",
    "    if verbose:\n",
    "        print('Building VGG16 (no-top) model to generate bottleneck features.')\n",
    "\n",
    "    vgg16_notop = build_vgg_16()\n",
    "    vgg16_notop.load_weights(file_path)\n",
    "    for _ in range(6):\n",
    "        vgg16_notop.pop()\n",
    "    vgg16_notop.compile(optimizer=RMSprop(lr=lr), loss='categorical_crossentropy', metrics=['accuracy'])    \n",
    "\n",
    "    if verbose:\n",
    "        print('Bottleneck features generation.')\n",
    "\n",
    "    train_batches = get_batches('train', shuffle=False, class_mode=None, batch_size=BATCH_SIZE)\n",
    "    train_labels = np.array([0]*1000 + [1]*1000)\n",
    "    train_bottleneck = vgg16_notop.predict_generator(train_batches, steps=2000 // BATCH_SIZE)\n",
    "    valid_batches = get_batches('valid', shuffle=False, class_mode=None, batch_size=BATCH_SIZE)\n",
    "    valid_labels = np.array([0]*400 + [1]*400)\n",
    "    valid_bottleneck = vgg16_notop.predict_generator(valid_batches, steps=800 // BATCH_SIZE)\n",
    "\n",
    "    if verbose:\n",
    "        print('Training top model on bottleneck features.')\n",
    "\n",
    "    top_model = Sequential()\n",
    "    top_model.add(Flatten(input_shape=train_bottleneck.shape[1:]))\n",
    "    top_model.add(Dense(4096, activation='relu'))\n",
    "    top_model.add(Dropout(0.5))\n",
    "    top_model.add(Dense(4096, activation='relu'))\n",
    "    top_model.add(Dropout(0.5))\n",
    "    top_model.add(Dense(2, activation='softmax'))\n",
    "    top_model.compile(optimizer=RMSprop(lr=lr), loss='categorical_crossentropy', metrics=['accuracy'])\n",
    "    top_model.fit(train_bottleneck, to_categorical(train_labels),\n",
    "                  batch_size=32, epochs=10,\n",
    "                  validation_data=(valid_bottleneck, to_categorical(valid_labels)))\n",
    "\n",
    "    if verbose:\n",
    "        print('Concatenate new VGG16 (without top layer) with pretrained top model.')\n",
    "\n",
    "    vgg16_fine = build_vgg_16()\n",
    "    vgg16_fine.load_weights(file_path)\n",
    "    for _ in range(6):\n",
    "        vgg16_fine.pop()\n",
    "    vgg16_fine.add(Flatten(name='top_flatten'))    \n",
    "    vgg16_fine.add(Dense(4096, activation='relu'))\n",
    "    vgg16_fine.add(Dropout(0.5))\n",
    "    vgg16_fine.add(Dense(4096, activation='relu'))\n",
    "    vgg16_fine.add(Dropout(0.5))\n",
    "    vgg16_fine.add(Dense(2, activation='softmax'))\n",
    "    vgg16_fine.compile(optimizer=RMSprop(lr=lr), loss='categorical_crossentropy', metrics=['accuracy'])\n",
    "\n",
    "    if verbose:\n",
    "        print('Loading pre-trained weights into concatenated model')\n",
    "\n",
    "    for i, layer in enumerate(reversed(top_model.layers), 1):\n",
    "        pretrained_weights = layer.get_weights()\n",
    "        vgg16_fine.layers[-i].set_weights(pretrained_weights)\n",
    "\n",
    "    for layer in vgg16_fine.layers[:26]:\n",
    "        layer.trainable = False\n",
    "\n",
    "    if verbose:\n",
    "        print('Layers training status:')\n",
    "        for layer in vgg16_fine.layers:\n",
    "            print('[%6s] %s' % ('' if layer.trainable else 'FROZEN', layer.name))        \n",
    "\n",
    "    vgg16_fine.compile(optimizer=RMSprop(lr=1e-6), loss='binary_crossentropy', metrics=['accuracy'])\n",
    "\n",
    "    if verbose:\n",
    "        print('Train concatenated model on dogs/cats dataset sample.')\n",
    "\n",
    "    train_datagen = ImageDataGenerator(rescale=1./255,\n",
    "                                       shear_range=0.2,\n",
    "                                       zoom_range=0.2,\n",
    "                                       horizontal_flip=True)\n",
    "    test_datagen = ImageDataGenerator(rescale=1./255)\n",
    "    train_batches = get_batches('train', gen=train_datagen, class_mode='categorical', batch_size=BATCH_SIZE)\n",
    "    valid_batches = get_batches('valid', gen=test_datagen, class_mode='categorical', batch_size=BATCH_SIZE)\n",
    "    vgg16_fine.fit_generator(train_batches, epochs=100,\n",
    "                             steps_per_epoch=2000 // BATCH_SIZE,\n",
    "                             validation_data=valid_batches,\n",
    "                             validation_steps=800 // BATCH_SIZE)\n",
    "    \n",
    "    \n",
    "    \n",
    "    \n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "vgg16_notop = build_vgg_16()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "lambda_3 (Lambda)            (None, 3, 224, 224)       0         \n",
      "_________________________________________________________________\n",
      "block1_padding_0 (ZeroPaddin (None, 3, 226, 226)       0         \n",
      "_________________________________________________________________\n",
      "block1_conv2d_0 (Conv2D)     (None, 64, 224, 224)      1792      \n",
      "_________________________________________________________________\n",
      "block1_padding_1 (ZeroPaddin (None, 64, 226, 226)      0         \n",
      "_________________________________________________________________\n",
      "block1_conv2d_1 (Conv2D)     (None, 64, 224, 224)      36928     \n",
      "_________________________________________________________________\n",
      "block1_maxpool (MaxPooling2D (None, 64, 112, 112)      0         \n",
      "_________________________________________________________________\n",
      "block2_padding_0 (ZeroPaddin (None, 64, 114, 114)      0         \n",
      "_________________________________________________________________\n",
      "block2_conv2d_0 (Conv2D)     (None, 128, 112, 112)     73856     \n",
      "_________________________________________________________________\n",
      "block2_padding_1 (ZeroPaddin (None, 128, 114, 114)     0         \n",
      "_________________________________________________________________\n",
      "block2_conv2d_1 (Conv2D)     (None, 128, 112, 112)     147584    \n",
      "_________________________________________________________________\n",
      "block2_maxpool (MaxPooling2D (None, 128, 56, 56)       0         \n",
      "_________________________________________________________________\n",
      "block3_padding_0 (ZeroPaddin (None, 128, 58, 58)       0         \n",
      "_________________________________________________________________\n",
      "block3_conv2d_0 (Conv2D)     (None, 256, 56, 56)       295168    \n",
      "_________________________________________________________________\n",
      "block3_padding_1 (ZeroPaddin (None, 256, 58, 58)       0         \n",
      "_________________________________________________________________\n",
      "block3_conv2d_1 (Conv2D)     (None, 256, 56, 56)       590080    \n",
      "_________________________________________________________________\n",
      "block3_padding_2 (ZeroPaddin (None, 256, 58, 58)       0         \n",
      "_________________________________________________________________\n",
      "block3_conv2d_2 (Conv2D)     (None, 256, 56, 56)       590080    \n",
      "_________________________________________________________________\n",
      "block3_maxpool (MaxPooling2D (None, 256, 28, 28)       0         \n",
      "_________________________________________________________________\n",
      "block4_padding_0 (ZeroPaddin (None, 256, 30, 30)       0         \n",
      "_________________________________________________________________\n",
      "block4_conv2d_0 (Conv2D)     (None, 512, 28, 28)       1180160   \n",
      "_________________________________________________________________\n",
      "block4_padding_1 (ZeroPaddin (None, 512, 30, 30)       0         \n",
      "_________________________________________________________________\n",
      "block4_conv2d_1 (Conv2D)     (None, 512, 28, 28)       2359808   \n",
      "_________________________________________________________________\n",
      "block4_padding_2 (ZeroPaddin (None, 512, 30, 30)       0         \n",
      "_________________________________________________________________\n",
      "block4_conv2d_2 (Conv2D)     (None, 512, 28, 28)       2359808   \n",
      "_________________________________________________________________\n",
      "block4_maxpool (MaxPooling2D (None, 512, 14, 14)       0         \n",
      "_________________________________________________________________\n",
      "block5_padding_0 (ZeroPaddin (None, 512, 16, 16)       0         \n",
      "_________________________________________________________________\n",
      "block5_conv2d_0 (Conv2D)     (None, 512, 14, 14)       2359808   \n",
      "_________________________________________________________________\n",
      "block5_padding_1 (ZeroPaddin (None, 512, 16, 16)       0         \n",
      "_________________________________________________________________\n",
      "block5_conv2d_1 (Conv2D)     (None, 512, 14, 14)       2359808   \n",
      "_________________________________________________________________\n",
      "block5_padding_2 (ZeroPaddin (None, 512, 16, 16)       0         \n",
      "_________________________________________________________________\n",
      "block5_conv2d_2 (Conv2D)     (None, 512, 14, 14)       2359808   \n",
      "_________________________________________________________________\n",
      "block5_maxpool (MaxPooling2D (None, 512, 7, 7)         0         \n",
      "=================================================================\n",
      "Total params: 14,714,688\n",
      "Trainable params: 14,714,688\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "vgg16_notop.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "for _ in range(6):\n",
    "    vgg16_notop.pop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_labels = np.array([0]*1000 + [1]*1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2000,)"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_labels.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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