experiment.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "584c3d28",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install clearml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb3a0d60",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "env: CLEARML_WEB_HOST=https://app.clear.ml/\n",
      "env: CLEARML_API_HOST=https://api.clear.ml\n",
      "env: CLEARML_FILES_HOST=https://files.clear.ml\n",
      "env: CLEARML_API_ACCESS_KEY=\n",
      "env: CLEARML_API_SECRET_KEY=\n",
      "env: CUDA_VISIBLE_DEVICES=2\n"
     ]
    }
   ],
   "source": [
    "%env CLEARML_WEB_HOST=https://app.clear.ml/\n",
    "%env CLEARML_API_HOST=https://api.clear.ml\n",
    "%env CLEARML_FILES_HOST=https://files.clear.ml\n",
    "%env CLEARML_API_ACCESS_KEY=PASTE_KEY\n",
    "%env CLEARML_API_SECRET_KEY=PASTE_KEY\n",
    "%env CUDA_VISIBLE_DEVICES=2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f2fe29f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ClearML Task: created new task id=1ee2da5430a5481d9c5000719ab8c7f1\n",
      "2025-01-19 17:20:35,258 - clearml.Task - INFO - Storing jupyter notebook directly as code\n",
      "ClearML results page: https://app.clear.ml/projects/9f16ed557f8e430c9fbdc9fde5d73b30/experiments/1ee2da5430a5481d9c5000719ab8c7f1/output/log\n"
     ]
    }
   ],
   "source": [
    "from clearml import Task, Logger\n",
    "\n",
    "# Initialize ClearML Task\n",
    "task = Task.init(\n",
    "    project_name=\"VAE Experiments\",\n",
    "    task_name=\"VAE with KL vs Wasserstein Loss\",\n",
    "    task_type=Task.TaskTypes.training\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fb252bdf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Log metrics and training progress\n",
    "def log_metrics(epoch, train_loss, recon_loss, reg_loss, func):\n",
    "    Logger.current_logger().report_scalar(f\"Loss ({func})\", \"Total Loss\", iteration=epoch, value=train_loss)\n",
    "    Logger.current_logger().report_scalar(f\"Loss ({func})\", \"Reconstruction Loss\", iteration=epoch, value=recon_loss)\n",
    "    Logger.current_logger().report_scalar(f\"Loss ({func})\", \"Regularization Loss\", iteration=epoch, value=reg_loss)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd84b313",
   "metadata": {},
   "source": [
    "# **Experiment Description**\n",
    "\n",
    "In this experiment, the goal is to compare the performance of a Variational Autoencoder (VAE) using two different loss functions: **KL divergence** and the **Wasserstein metric**.  \n",
    "\n",
    "1. **Objective**:\n",
    "   - Understand how the choice of the divergence/metric in the loss function affects the quality of latent representations and reconstructed data.\n",
    "   - Compare the performance in terms of reconstruction quality, latent space structure, and generalization ability.\n",
    "\n",
    "2. **Steps**:\n",
    "   - **Implement a Simple VAE**:\n",
    "     - Design a basic VAE architecture with fully connected layers for encoding and decoding.\n",
    "     - Use a Gaussian prior for the latent space and a reparameterization trick for sampling.\n",
    "   - **Train the VAE with KL Divergence**:\n",
    "     - Use the KL divergence to regularize the latent space to match the prior distribution.\n",
    "   - **Train the VAE with the Wasserstein Metric**:\n",
    "     - Replace the KL divergence with the Wasserstein metric to regularize the latent space.\n",
    "   - **Evaluate and Compare**:\n",
    "     - Assess reconstruction quality using metrics like Mean Squared Error (MSE) on the test dataset.\n",
    "     - Visualize the learned latent space for each loss function using 2D projections.\n",
    "     - Compare training stability and convergence speed for both loss functions.\n",
    "\n",
    "3. **Expected Outcome**:\n",
    "   - The KL divergence is likely to yield good performance for Gaussian priors but may suffer from issues like posterior collapse.\n",
    "   - The Wasserstein metric might provide smoother optimization and better latent space representations, especially if the data distribution differs significantly from the Gaussian prior.\n",
    "\n",
    "By comparing the results, you’ll gain insights into the strengths and weaknesses of each approach in the context of VAEs.\n",
    "\n",
    "___\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0685113a",
   "metadata": {},
   "source": [
    "### **1. What is a VAE?**\n",
    "A VAE is a type of neural network used to generate data, such as images or text. It learns to compress input data into a **latent space** (a compact, lower-dimensional representation) and then reconstruct or generate new data from this latent space.\n",
    "\n",
    "---\n",
    "\n",
    "### **2. How Does It Work?**\n",
    "VAEs consist of two main parts:\n",
    "\n",
    "#### **a) Encoder**\n",
    "- The encoder takes an input (e.g., an image) and compresses it into a **latent representation**.  \n",
    "- Instead of producing a single point, the encoder outputs the **parameters of a probability distribution** in the latent space (mean $\\mu$ and standard deviation $\\sigma$).\n",
    "- This means the latent space is a random variable, not a fixed value.  \n",
    "\n",
    "#### **b) Decoder**\n",
    "- The decoder takes a sample from the latent distribution and tries to reconstruct the original input from it.\n",
    "- It learns to map points in the latent space back to the input space.\n",
    "\n",
    "---\n",
    "\n",
    "### **3. Why Use a Latent Distribution?**\n",
    "Instead of just learning fixed points in the latent space, the VAE learns a **distribution** (e.g., a Gaussian) for each input. This has two advantages:\n",
    "1. **Generative Capability:** By sampling from the latent distribution, the VAE can generate new data points that resemble the training data.\n",
    "2. **Smooth Latent Space:** Close points in the latent space correspond to similar outputs, making it easier to interpolate between data points.\n",
    "\n",
    "---\n",
    "\n",
    "### **4. Loss Function**\n",
    "The VAE is trained using two objectives:\n",
    "1. **Reconstruction Loss:** Ensures the decoder reconstructs the input accurately. Typically, this is the mean squared error (for continuous data) or cross-entropy (for categorical data).\n",
    "   $$\n",
    "   \\text{Reconstruction Loss} = \\| x - \\hat{x} \\|^2\n",
    "   $$\n",
    "\n",
    "2. **KL Divergence:** Ensures the latent space follows a standard Gaussian distribution $\\mathcal{N}(0, I)$. This regularizes the latent space and encourages smoothness.\n",
    "   $$\n",
    "   \\text{KL Divergence} = D_{KL}(q(z|x) \\,||\\, p(z))\n",
    "   $$\n",
    "\n",
    "The total loss combines these two:\n",
    "$$\n",
    "\\text{Total Loss} = \\text{Reconstruction Loss} + \\beta \\cdot \\text{KL Divergence}\n",
    "$$\n",
    "(where $\\beta$ balances the two terms).\n",
    "\n",
    "---\n",
    "\n",
    "### **5. Training Process**\n",
    "1. **Input to Latent Space:** The encoder takes an input $x$ and outputs $\\mu(x)$ and $\\sigma(x)$, the parameters of the latent distribution $q(z|x)$.\n",
    "2. **Sampling (Reparameterization Trick):** A random sample $z$ is drawn from $q(z|x)$, using:\n",
    "   $$\n",
    "   z = \\mu(x) + \\sigma(x) \\cdot \\epsilon\n",
    "   $$\n",
    "   where $\\epsilon \\sim \\mathcal{N}(0, I)$.\n",
    "3. **Reconstruction:** The decoder uses $z$ to generate $\\hat{x}$, the reconstruction of the input.\n",
    "4. **Loss Minimization:** The loss (reconstruction + KL divergence) is minimized via gradient descent.\n",
    "\n",
    "---\n",
    "\n",
    "### **6. What Can VAEs Do?**\n",
    "- **Data Generation:** VAEs can generate new data by sampling from the latent space and passing it through the decoder.\n",
    "- **Interpolation:** Since the latent space is smooth, VAEs can interpolate between points, creating transitions between data samples (e.g., blending images).\n",
    "- **Anomaly Detection:** VAEs can identify anomalies by measuring how well they can reconstruct inputs (poor reconstruction indicates unusual data).\n",
    "\n",
    "---\n",
    "\n",
    "### **Simple Analogy**\n",
    "Think of the VAE like a painter:\n",
    "1. The **encoder** describes an image by summarizing it into a set of instructions (latent distribution).\n",
    "2. The **decoder** takes those instructions and tries to recreate the original image.\n",
    "3. During training, the VAE learns to make its instructions compact and consistent while still being able to reconstruct accurately."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc74157f",
   "metadata": {},
   "source": [
    "# **EXPERIMENT**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "819d9bc631955a87",
   "metadata": {},
   "source": [
    "### VAE Architecture\n",
    "A VAE consists of:\n",
    "- **Encoder:** Maps input data to a latent distribution (mean and log-variance).\n",
    "- **Latent Space Sampling:** Reparameterization trick for sampling latent vectors.\n",
    "- **Decoder:** Reconstructs data from latent vectors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c794ee4bf747ace3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-18T17:08:57.297402Z",
     "start_time": "2025-01-18T17:08:54.280007Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-01-19 17:20:40.566922: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
      "E0000 00:00:1737296440.581019    5497 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
      "E0000 00:00:1737296440.585327    5497 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
      "2025-01-19 17:20:40.603841: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "from torch import nn\n",
    "import os\n",
    "\n",
    "class VAE(nn.Module):\n",
    "    def __init__(self, input_dim, latent_dim):\n",
    "        super(VAE, self).__init__()\n",
    "        # Encoder\n",
    "        self.encoder = nn.Sequential(\n",
    "            nn.Linear(input_dim, 256),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(256, latent_dim * 2)  # Output both mean and log-variance\n",
    "        )\n",
    "        # Decoder\n",
    "        self.decoder = nn.Sequential(\n",
    "            nn.Linear(latent_dim, 256),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(256, input_dim),\n",
    "            nn.Sigmoid()\n",
    "        )\n",
    "\n",
    "    def reparameterize(self, mu, log_var):\n",
    "        std = torch.exp(0.5 * log_var)\n",
    "        eps = torch.randn_like(std)\n",
    "        return mu + eps * std\n",
    "\n",
    "    def forward(self, x):\n",
    "        # encoder pass\n",
    "        h = self.encoder(x)\n",
    "\n",
    "        # Attempts to split a tensor into the specified number of chunks. Each chunk is a view of the input tensor.\n",
    "        mu, log_var = torch.chunk(h, 2, dim=-1) \n",
    "        \n",
    "        # sampling\n",
    "        z = self.reparameterize(mu, log_var)\n",
    "\n",
    "        return self.decoder(z), mu, log_var\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be21d1e7",
   "metadata": {},
   "source": [
    "# Loss Functions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72b5b30e",
   "metadata": {},
   "source": [
    "**KL Divergence Loss:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "79f7ca18",
   "metadata": {},
   "outputs": [],
   "source": [
    "def kl_divergence_loss(mu, log_var):\n",
    "    return -0.5 * torch.sum(1 + log_var - mu.pow(2) - log_var.exp())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "caeda1e3",
   "metadata": {},
   "source": [
    "**Wasserstein Metric Loss:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f37f7ff8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def wasserstein_loss(real, fake):\n",
    "    return torch.mean(torch.abs(real - fake))  # Example metric\n",
    "\n",
    "# Above, for simplicity, PyTorch's Sinkhorn distance is used. Normal loss function will be introduced later."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "150fd818",
   "metadata": {},
   "source": [
    "**Reconstruction Loss (common for both):**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8b1cbcf5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def reconstruction_loss(recon_x, x):\n",
    "    return nn.BCELoss(reduction='sum')(recon_x, x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b4b41ef",
   "metadata": {},
   "source": [
    "### Total Loss:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2afb568b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def vae_loss(recon_x, x, mu, log_var):\n",
    "    recon_loss = reconstruction_loss(recon_x, x)\n",
    "    reg_loss = kl_divergence_loss(mu, log_var)\n",
    "    return recon_loss + reg_loss"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "624677a8",
   "metadata": {},
   "source": [
    "# Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1d9446b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from torchvision import datasets, transforms\n",
    "\n",
    "transform = transforms.Compose([transforms.ToTensor()])\n",
    "train_dataset = datasets.MNIST(root='./data', train=True, download=True, transform=transform)\n",
    "train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=64, shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "bfb4f97b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Get a batch of images and labels\n",
    "images, labels = next(iter(train_loader))\n",
    "\n",
    "# Plot some examples from the dataset\n",
    "fig, axes = plt.subplots(1, 6, figsize=(15, 4))\n",
    "for i, ax in enumerate(axes):\n",
    "    ax.imshow(images[i].squeeze(), cmap=\"gray\")\n",
    "    ax.set_title(f\"Label: {labels[i].item()}\")\n",
    "    ax.axis(\"off\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.suptitle(\"Original MNIST\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "eb0c2708",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1, 28, 28])\n",
      "\n",
      "torch.Size([1, 784])\n"
     ]
    }
   ],
   "source": [
    "x = images[i]\n",
    "print(x.shape)\n",
    "print()\n",
    "print(x.view(x.size(0), -1).shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56c1b765",
   "metadata": {},
   "source": [
    "# Training with KL Divergence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2bc88728",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "device(type='cuda')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "use_cuda = torch.cuda.is_available()\n",
    "use_mps = torch.backends.mps.is_available()\n",
    "device = torch.device(\"cuda\" if use_cuda else \"mps\" if use_mps else \"cpu\")\n",
    "device"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f599c653",
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import tqdm\n",
    "\n",
    "# Training Function\n",
    "def train_vae(vae, data_loader, optimizer, epochs=10):\n",
    "    vae.train()\n",
    "    train_loss = []\n",
    "    for epoch in range(epochs):\n",
    "        total_loss, total_recon_loss, total_reg_loss = 0, 0, 0\n",
    "        with tqdm(data_loader, desc=f\"Epoch {epoch+1}/{epochs}\", unit=\"batch\") as pbar:\n",
    "            for x, _ in pbar:\n",
    "                x = x.view(x.size(0), -1).to(device)  # Flatten input\n",
    "                optimizer.zero_grad()\n",
    "                recon_x, mu, log_var = vae(x)\n",
    "\n",
    "                loss = vae_loss(recon_x, x, mu, log_var)\n",
    "                recon_loss = reconstruction_loss(recon_x, x).item()\n",
    "                reg_loss = loss.item() - recon_loss  # Calculate regularization loss\n",
    "                \n",
    "                loss.backward()\n",
    "                optimizer.step()\n",
    "                total_loss += loss.item()\n",
    "                total_recon_loss += recon_loss\n",
    "                total_reg_loss += reg_loss\n",
    "                pbar.set_postfix(loss=loss.item())\n",
    "\n",
    "        avg_loss = total_loss / len(data_loader.dataset)\n",
    "        avg_recon_loss = total_recon_loss / len(data_loader.dataset)\n",
    "        avg_reg_loss = total_reg_loss / len(data_loader.dataset)\n",
    "        train_loss.append(avg_loss)\n",
    "\n",
    "        # Log metrics to ClearML\n",
    "        log_metrics(epoch + 1, avg_loss, avg_recon_loss, avg_reg_loss, \"KL\")\n",
    "\n",
    "        print(f\"Epoch {epoch+1}, Total Loss: {avg_loss:.4f}, Recon Loss: {avg_recon_loss:.4f}, Reg Loss: {avg_reg_loss:.4f}\")\n",
    "        \n",
    "    return train_loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d48932b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Log hyperparameters\n",
    "hyperparameters = {\n",
    "    \"input_dim\": 28 * 28,  # Flattened MNIST images\n",
    "    \"latent_dim\": 10,\n",
    "    \"batch_size\": 64,\n",
    "    \"learning_rate\": 1e-3,\n",
    "    \"epochs\": 35,\n",
    "    \"loss_type\": \"kl\"  # Change to 'wasserstein' as needed\n",
    "}\n",
    "task.connect(hyperparameters)\n",
    "\n",
    "# Model, Optimizer\n",
    "vae = VAE(hyperparameters[\"input_dim\"], hyperparameters[\"latent_dim\"]).to(device)\n",
    "optimizer = torch.optim.Adam(vae.parameters(), lr=hyperparameters[\"learning_rate\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "fef63296",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save Model and Artifacts\n",
    "def save_and_log_model(vae, model_name):\n",
    "    model_path = f\"weights/{model_name}.pth\"\n",
    "    torch.save(vae.state_dict(), model_path)\n",
    "    task.upload_artifact(name=model_name, artifact_object=model_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "24fde18f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/bot_env/lib/python3.10/site-packages/clearml/binding/frameworks/pytorch_bind.py:277: FutureWarning:\n",
      "\n",
      "You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2025-01-19 17:20:48,968 - clearml.model - INFO - Selected model id: 2495b5ce4e7448689c208182e0689951\n"
     ]
    }
   ],
   "source": [
    "# # Train VAE\n",
    "# if os.path.exists(\"weights/vae_kl_divergence.pth\"):\n",
    "#     state_dict = torch.load(\"weights/vae_kl_divergence.pth\", map_location=device)\n",
    "#     vae.load_state_dict(state_dict)\n",
    "#     vae.eval()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3897d20e",
   "metadata": {},
   "source": [
    "# **EXECUTE CODE BELOW ONLY IF YOU WANT TO TRAIN MODEL**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "4523e6b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 1/35: 100%|██████████| 938/938 [00:07<00:00, 129.34batch/s, loss=3.99e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1, Total Loss: 151.6978, Recon Loss: 136.7565, Reg Loss: 14.9413\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 2/35: 100%|██████████| 938/938 [00:07<00:00, 119.89batch/s, loss=3.57e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2, Total Loss: 123.1423, Recon Loss: 106.3733, Reg Loss: 16.7691\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 3/35: 100%|██████████| 938/938 [00:07<00:00, 133.59batch/s, loss=4.18e+3]\n"
     ]
    },
    {
     "name": "stdout",
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      "Epoch 3, Total Loss: 118.9925, Recon Loss: 101.7895, Reg Loss: 17.2030\n"
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      "Epoch 4, Total Loss: 116.7896, Recon Loss: 99.3208, Reg Loss: 17.4688\n"
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      "Epoch 5, Total Loss: 115.3106, Recon Loss: 97.6161, Reg Loss: 17.6945\n"
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     "text": [
      "Epoch 6, Total Loss: 114.2376, Recon Loss: 96.3915, Reg Loss: 17.8461\n"
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     "text": [
      "Epoch 7, Total Loss: 113.3947, Recon Loss: 95.4517, Reg Loss: 17.9430\n"
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     "text": [
      "Epoch 8/35: 100%|██████████| 938/938 [00:07<00:00, 126.63batch/s, loss=3.76e+3]\n"
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     "text": [
      "Epoch 8, Total Loss: 112.7113, Recon Loss: 94.6711, Reg Loss: 18.0402\n"
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     "text": [
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     "text": [
      "Epoch 9, Total Loss: 112.1494, Recon Loss: 94.0392, Reg Loss: 18.1102\n"
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     "text": [
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     "text": [
      "Epoch 10, Total Loss: 111.6640, Recon Loss: 93.4672, Reg Loss: 18.1968\n"
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     "text": [
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     "text": [
      "Epoch 11, Total Loss: 111.2252, Recon Loss: 92.9716, Reg Loss: 18.2535\n"
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     "text": [
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     "text": [
      "Epoch 12, Total Loss: 110.8488, Recon Loss: 92.5418, Reg Loss: 18.3070\n"
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     "text": [
      "Epoch 13, Total Loss: 110.5230, Recon Loss: 92.1712, Reg Loss: 18.3519\n"
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     "text": [
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     "text": [
      "Epoch 14, Total Loss: 110.1789, Recon Loss: 91.8029, Reg Loss: 18.3760\n"
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     "output_type": "stream",
     "text": [
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     "text": [
      "Epoch 15, Total Loss: 109.8966, Recon Loss: 91.4891, Reg Loss: 18.4075\n"
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     "output_type": "stream",
     "text": [
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     "text": [
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     "text": [
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     "text": [
      "Epoch 18, Total Loss: 109.2008, Recon Loss: 90.6997, Reg Loss: 18.5011\n"
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     "text": [
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     "text": [
      "Epoch 19, Total Loss: 108.9745, Recon Loss: 90.4669, Reg Loss: 18.5076\n"
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     "output_type": "stream",
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     "text": [
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     "output_type": "stream",
     "text": [
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     "text": [
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     "text": [
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     "text": [
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     "text": [
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     "output_type": "stream",
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     "text": [
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     "text": [
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     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_loss = train_vae(vae, train_loader, optimizer, hyperparameters[\"epochs\"])\n",
    "# Save and upload the trained model\n",
    "save_and_log_model(vae, \"vae_kl_divergence\")\n",
    "\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.plot(train_loss, label='Training Loss (KL)')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Loss')\n",
    "plt.title('VAE Training Loss')\n",
    "plt.legend()\n",
    "plt.savefig(\"training_loss.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c621f7d",
   "metadata": {},
   "source": [
    "# Plot Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "cc518049",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plot Results\n",
    "def plot_results(vae, data_loader, num_samples=10, name=\"KL\"):\n",
    "    vae.eval()\n",
    "    with torch.no_grad():\n",
    "        # Get a batch of samples\n",
    "        x, _ = next(iter(data_loader))\n",
    "        x = x.view(x.size(0), -1).to(device)\n",
    "\n",
    "        # Generate Reconstructions\n",
    "        recon_x, _, _ = vae(x)\n",
    "\n",
    "        # Plot Original and Reconstructed Images\n",
    "        fig, axes = plt.subplots(2, num_samples, figsize=(num_samples * 2, 4))\n",
    "        for i in range(num_samples):\n",
    "            # Original images\n",
    "            axes[0, i].imshow(x[i].cpu().view(28, 28), cmap='gray')\n",
    "            axes[0, i].axis('off')\n",
    "            # Reconstructed images\n",
    "            axes[1, i].imshow(recon_x[i].cpu().view(28, 28), cmap='gray')\n",
    "            axes[1, i].axis('off')\n",
    "        axes[0, 0].set_ylabel(\"Original\", fontsize=14)\n",
    "        axes[1, 0].set_ylabel(\"Reconstructed\", fontsize=14)\n",
    "        plt.title(f\"VAE Reconstructions with {name} in Loss F.\")\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "0cdafa1a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2000x400 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot Reconstructions\n",
    "plot_results(vae, train_loader)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2425bb4d",
   "metadata": {},
   "source": [
    "In the plot above:\n",
    "- **first row:** original image from MNIST\n",
    "- **second row:** reconstructed image with VAE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "567aa887",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.manifold import TSNE\n",
    "\n",
    "def plot_latent_space(vae, data_loader, name=\"KL\"):\n",
    "    vae.eval()\n",
    "    with torch.no_grad():\n",
    "        all_mu = []\n",
    "        all_labels = []\n",
    "        for x, y in data_loader:\n",
    "            x = x.view(x.size(0), -1).to(device)\n",
    "            _, mu, _ = vae(x)\n",
    "            all_mu.append(mu.cpu())\n",
    "            all_labels.append(y)\n",
    "        \n",
    "        all_mu = torch.cat(all_mu)\n",
    "        all_labels = torch.cat(all_labels)\n",
    "\n",
    "        # Dimensionality reduction\n",
    "        \n",
    "        reduced = TSNE(n_components=2).fit_transform(all_mu)\n",
    "\n",
    "        # Plot\n",
    "        plt.figure(figsize=(8, 6))\n",
    "        scatter = plt.scatter(reduced[:, 0], reduced[:, 1], c=all_labels, cmap='tab10', alpha=0.7)\n",
    "        plt.colorbar(scatter, label=\"Digit Label\")\n",
    "        plt.title(f\"VAE with {name} Latent Space Visualization (TSNE)\")\n",
    "        plt.xlabel(\"Component 1\")\n",
    "        plt.ylabel(\"Component 2\")\n",
    "        # plt.suptitle(\"VAE Latent Space with KL in Loss F.\", fontsize=16)\n",
    "        plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "987ff534",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_latent_space(vae, train_loader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "30c5d6cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "def plot_latent_distributions(vae, data_loader, name=\"KL\"):\n",
    "    vae.eval()\n",
    "    with torch.no_grad():\n",
    "        all_mu = []\n",
    "        for x, _ in data_loader:\n",
    "            x = x.view(x.size(0), -1).to(device)\n",
    "            _, mu, _ = vae(x)\n",
    "            all_mu.append(mu.cpu())\n",
    "        all_mu = torch.cat(all_mu)\n",
    "\n",
    "    # Plot distribution for each latent dimension\n",
    "    num_latent_dims = all_mu.shape[1]\n",
    "    fig, axes = plt.subplots(1, num_latent_dims, figsize=(num_latent_dims * 3, 4), sharey=True)\n",
    "    for i in range(num_latent_dims):\n",
    "        sns.kdeplot(all_mu[:, i], ax=axes[i], fill=True)\n",
    "        axes[i].set_title(f\"Latent Dim {i+1}\")\n",
    "\n",
    "    plt.suptitle(f\"VAE Latent Distributions with {name} in Loss F.\")\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "114137ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 3000x400 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# This helps to see how well the latent space approximates a Gaussian distribution.\n",
    "plot_latent_distributions(vae, train_loader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d08c9224",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_interpolation(vae, data_loader, dim=0, num_steps=10, name=\"KL\"):\n",
    "    vae.eval()\n",
    "    with torch.no_grad():\n",
    "        # Get two random samples\n",
    "        x, _ = next(iter(data_loader))\n",
    "        x = x.view(x.size(0), -1).to(device)\n",
    "        _, mu, _ = vae(x)\n",
    "\n",
    "        # Select two points in the latent space\n",
    "        z1, z2 = mu[0], mu[1]\n",
    "        interpolation = torch.stack([z1 * (1 - t) + z2 * t for t in torch.linspace(0, 1, num_steps)])\n",
    "\n",
    "        # Decode interpolated points\n",
    "        reconstructions = vae.decoder(interpolation)\n",
    "\n",
    "        # Plot\n",
    "        fig, axes = plt.subplots(1, num_steps, figsize=(num_steps * 2, 2))\n",
    "        for i in range(num_steps):\n",
    "            axes[i].imshow(reconstructions[i].cpu().view(28, 28), cmap='gray')\n",
    "            axes[i].axis('off')\n",
    "        \n",
    "        plt.suptitle(f\"VAE with {name} interpolation\")\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c14aece3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x200 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_interpolation(vae, train_loader, num_steps=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "002d2121",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_reconstruction_error(vae, data_loader, name=\"KL\"):\n",
    "    vae.eval()\n",
    "    errors = []\n",
    "    with torch.no_grad():\n",
    "        for x, _ in data_loader:\n",
    "            x = x.view(x.size(0), -1).to(device)\n",
    "            recon_x, _, _ = vae(x)\n",
    "            error = ((x - recon_x) ** 2).sum(dim=1)\n",
    "            errors.extend(error.cpu().numpy())\n",
    "    \n",
    "    # Plot histogram of reconstruction errors\n",
    "    plt.figure(figsize=(8, 6))\n",
    "    plt.hist(errors, bins=50, alpha=0.7)\n",
    "    plt.title(f\"Reconstruction Error Distribution ({name})\")\n",
    "    plt.xlabel(\"Reconstruction Error\")\n",
    "    plt.ylabel(\"Frequency\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "28e1171b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/bot_env/lib/python3.10/site-packages/clearml/utilities/plotlympl/renderer.py:210: UserWarning:\n",
      "\n",
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_reconstruction_error(vae, train_loader)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f71e595",
   "metadata": {},
   "source": [
    "# **BEFORE YOU SAW THE ORIGINAL VAE WITH KL DIVERGENCE IN THE LOSS FUNCTUON**\n",
    "\n",
    "NOW, LETS SEE WHAT WILL HAPPEN, IF WE USE WASSERSTEIN DISTANCE"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b11c22b9",
   "metadata": {},
   "source": [
    "# True Wasserstein loss\n",
    "\n",
    "The Wasserstein loss isn't the same as the simple absolute difference metric I used as a placeholder before. Let’s dive deeper into the exact Wasserstein loss and its correct application.\n",
    "\n",
    "The exact Wasserstein distance, however, is computationally expensive because it requires solving an optimization problem. Instead, **Wasserstein GANs (WGANs)** introduce the **Kantorovich-Rubinstein duality**, making it feasible to approximate Wasserstein distance efficiently by parameterizing the critic as a neural network.\n",
    "\n",
    "### Correct Implementation of Wasserstein Loss in a VAE\n",
    "\n",
    "Here’s how we can incorporate the Wasserstein loss correctly in a VAE:\n",
    "\n",
    "1. **Latent Space Comparison**:\n",
    "   - Instead of KL divergence between the latent distribution $q(z|x)$ and a prior distribution $p(z)$ (usually a standard Gaussian), we use the Wasserstein distance between these distributions.\n",
    "\n",
    "2. **Dual Form Approximation**:\n",
    "   - To approximate the Wasserstein distance, use a critic (discriminator-like network) that estimates the cost of transporting probability mass.\n",
    "\n",
    "3. **Key Additions**:\n",
    "   - Introduce a **critic network** $D(z)$ for the latent space.\n",
    "   - Train the critic to maximize the difference between the real distribution $p(z)$ (e.g., standard Gaussian) and the generated distribution $q(z|x)$.\n",
    "\n",
    "### Wasserstein Loss Implementation for VAE\n",
    "\n",
    "Here’s how to adapt the VAE with Wasserstein loss:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "fde78b74",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define a simple fully connected network as the critic:\n",
    "class Critic(nn.Module):\n",
    "    def __init__(self, input_dim):\n",
    "        super(Critic, self).__init__()\n",
    "        self.model = nn.Sequential(\n",
    "            nn.Linear(input_dim, 512),  # Increase hidden layer size\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(512, 256),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(256, 10)\n",
    "        )\n",
    "\n",
    "\n",
    "    def forward(self, x):\n",
    "        return self.model(x)\n",
    "\n",
    "\n",
    "def wasserstein_loss_vae(critic, z_real, z_fake):\n",
    "    \"\"\"\n",
    "    Wasserstein loss for the latent space.\n",
    "    \"\"\"\n",
    "    real_score = critic(z_real)  # Critic output for real samples (from prior p(z))\n",
    "    fake_score = critic(z_fake)  # Critic output for generated samples (from q(z|x))\n",
    "    return torch.mean(fake_score) - torch.mean(real_score)  # W-distance approximation\n",
    "\n",
    "'''\n",
    "In Wasserstein GANs (WGANs), the discriminator (critic) must be 1-Lipschitz continuous \n",
    "to calculate the Wasserstein distance accurately. The Lipschitz constraint ensures that \n",
    "the critic does not \"explode\" and maintains meaningful gradients for optimization. This \n",
    "is crucial for stable training and meaningful results.\n",
    "''' \n",
    "\n",
    "# To ensure the critic satisfies the Lipschitz constraint, add a gradient penalty:\n",
    "def gradient_penalty(critic, z_real, z_fake):\n",
    "    \"\"\"\n",
    "    Compute gradient penalty for Lipschitz constraint.\n",
    "    \"\"\"\n",
    "    alpha = torch.rand(z_real.size(0), 1).to(z_real.device)\n",
    "    z_interpolates = alpha * z_real + (1 - alpha) * z_fake \n",
    "    z_interpolates.requires_grad_(True)\n",
    "\n",
    "    critic_scores = critic(z_interpolates)\n",
    "    gradients = torch.autograd.grad(\n",
    "        outputs=critic_scores,\n",
    "        inputs=z_interpolates,\n",
    "        grad_outputs=torch.ones_like(critic_scores),\n",
    "        create_graph=True,\n",
    "        retain_graph=True,\n",
    "    )[0]\n",
    "    gradients = gradients.view(gradients.size(0), -1)\n",
    "    gp = ((gradients.norm(2, dim=1) - 1) ** 2).mean()\n",
    "    return gp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "a37457a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Training Function\n",
    "def train_wvae(vae, critic, data_loader, vae_optimizer, critic_optimizer, epochs=10, gp_weight=10.0, critic_updates_per_step=5, recon_weight=0.5):\n",
    "    vae.train()\n",
    "    critic.train()\n",
    "\n",
    "    for epoch in range(epochs):\n",
    "        total_critic_loss = 0\n",
    "        total_vae_loss, total_recon_loss, total_reg_loss = 0, 0, 0\n",
    "\n",
    "        with tqdm(data_loader, desc=f\"Epoch {epoch+1}/{epochs}\", unit=\"batch\") as pbar:\n",
    "            for x, _ in pbar:\n",
    "            \n",
    "                x = x.view(x.size(0), -1).to(device)\n",
    "\n",
    "                # Update Critic multiple times per VAE step\n",
    "                for _ in range(critic_updates_per_step):\n",
    "                    # Forward pass through VAE (detach z_fake for critic update)\n",
    "                    recon_x, mu, log_var = vae(x)\n",
    "                    z_fake = vae.reparameterize(mu, log_var).detach()\n",
    "\n",
    "                    # Returns a tensor with the same size as input that is filled \n",
    "                    # with random numbers from a normal distribution with mean 0 and variance 1.\n",
    "                    z_real = torch.randn_like(z_fake).to(device)  # Prior samples\n",
    "\n",
    "                    # Critic loss\n",
    "                    critic_optimizer.zero_grad()\n",
    "                    w_loss = wasserstein_loss_vae(critic, z_real, z_fake)\n",
    "                    gp = gradient_penalty(critic, z_real, z_fake)\n",
    "                    critic_loss = w_loss + gp_weight * gp\n",
    "                    critic_loss.backward()\n",
    "                    critic_optimizer.step()\n",
    "\n",
    "                    total_critic_loss += critic_loss.item()\n",
    "\n",
    "                # Update VAE\n",
    "                vae_optimizer.zero_grad()\n",
    "                \n",
    "                recon_loss = recon_weight * reconstruction_loss(recon_x, x)\n",
    "                total_recon_loss += recon_loss\n",
    "\n",
    "                z_fake = vae.reparameterize(mu, log_var)  # Recompute z_fake for VAE update\n",
    "                z_real = torch.rand_like(z_fake).to(device)\n",
    "                w_loss_vae = -100.0 * wasserstein_loss_vae(critic, z_real, z_fake)\n",
    "                \n",
    "                total_reg_loss += w_loss_vae\n",
    "\n",
    "\n",
    "                vae_loss = recon_loss + w_loss_vae\n",
    "                vae_loss.backward()\n",
    "                vae_optimizer.step()\n",
    "\n",
    "                total_vae_loss += vae_loss.item()\n",
    "                pbar.set_postfix(loss=vae_loss.item())\n",
    "\n",
    "        avg_loss = total_vae_loss / len(data_loader.dataset)\n",
    "        avg_recon_loss = total_recon_loss / len(data_loader.dataset)\n",
    "        avg_reg_loss = total_reg_loss / len(data_loader.dataset)\n",
    "\n",
    "        log_metrics(epoch + 1, avg_loss, avg_recon_loss, avg_reg_loss, \"Wass\")\n",
    "        \n",
    "        print(\n",
    "            f\"Epoch {epoch + 1}, Critic Loss: {total_critic_loss / len(data_loader):.4f}, \"\n",
    "            f\"VAE Loss: {avg_loss:.4f}, Recon Loss: {avg_recon_loss:.4f}, Reg Loss: {avg_reg_loss:.4f}\"\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "46d40137",
   "metadata": {},
   "outputs": [],
   "source": [
    "hyperparameters_wass = {\n",
    "    \"input_dim\": 28 * 28,  # Flattened MNIST images\n",
    "    \"latent_dim\": 10,\n",
    "    \"batch_size\": 64,\n",
    "    \"learning_rate\": 1e-3,\n",
    "    \"epochs\": 35,\n",
    "    \"loss_type\": \"wasserstein\",  # Change to 'wasserstein' as needed\n",
    "    \"gp_weight\": 5.0,\n",
    "    \"recon_weight_wass\": 0.9,\n",
    "    \"critic_updates_per_step_wass\": 6\n",
    "}\n",
    "task.connect(hyperparameters_wass)\n",
    "\n",
    "# Model, Optimizers\n",
    "vae2 = VAE(hyperparameters_wass[\"input_dim\"], \n",
    "           hyperparameters_wass[\"latent_dim\"]\n",
    "           ).to(device)\n",
    "critic = Critic(hyperparameters_wass[\"latent_dim\"]).to(device)\n",
    "vae2_optimizer = torch.optim.Adam(vae2.parameters(), lr=hyperparameters_wass[\"learning_rate\"])\n",
    "critic_optimizer = torch.optim.Adam(critic.parameters(), lr=hyperparameters_wass[\"learning_rate\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6a892f14",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/bot_env/lib/python3.10/site-packages/clearml/binding/frameworks/pytorch_bind.py:277: FutureWarning:\n",
      "\n",
      "You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2025-01-19 17:05:22,702 - clearml.model - WARNING - Connecting multiple input models with the same name: `critic`. This might result in the wrong model being used when executing remotely\n"
     ]
    }
   ],
   "source": [
    "# if os.path.exists(\"weights/vae_wass_disrance.pth\"):\n",
    "#     state_dict = torch.load(\"weights/vae_wass_disrance.pth\", map_location=device)\n",
    "#     vae2.load_state_dict(state_dict)\n",
    "#     vae2.eval()\n",
    "\n",
    "# if os.path.exists(\"weights/critic.pth\"):\n",
    "#     state_dict = torch.load(\"weights/critic.pth\", map_location=device)\n",
    "#     critic.load_state_dict(state_dict)\n",
    "#     critic.eval()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a9c3679",
   "metadata": {},
   "source": [
    "# **EXECUTE CODE BELOW ONLY IF YOU WANT TRAIN MODEL**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "5e9985a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 1/35: 100%|██████████| 938/938 [00:24<00:00, 37.89batch/s, loss=2.87e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1, Critic Loss: -5.6419, VAE Loss: 116.9524, Recon Loss: 115.2509, Reg Loss: 1.7014\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 2/35: 100%|██████████| 938/938 [00:24<00:00, 38.12batch/s, loss=2.98e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2, Critic Loss: -4.9796, VAE Loss: 89.4394, Recon Loss: 87.8981, Reg Loss: 1.5414\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 3/35: 100%|██████████| 938/938 [00:24<00:00, 38.07batch/s, loss=2.66e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3, Critic Loss: -4.5815, VAE Loss: 85.4934, Recon Loss: 84.0617, Reg Loss: 1.4317\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 4/35: 100%|██████████| 938/938 [00:25<00:00, 36.77batch/s, loss=2.53e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4, Critic Loss: -4.2671, VAE Loss: 83.1917, Recon Loss: 81.8497, Reg Loss: 1.3419\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 5/35: 100%|██████████| 938/938 [00:24<00:00, 37.76batch/s, loss=2.66e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5, Critic Loss: -3.9854, VAE Loss: 81.6222, Recon Loss: 80.3570, Reg Loss: 1.2652\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 6/35: 100%|██████████| 938/938 [00:24<00:00, 38.07batch/s, loss=2.56e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6, Critic Loss: -3.7513, VAE Loss: 80.4465, Recon Loss: 79.2480, Reg Loss: 1.1985\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 7/35: 100%|██████████| 938/938 [00:24<00:00, 38.27batch/s, loss=2.56e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7, Critic Loss: -3.5434, VAE Loss: 79.5265, Recon Loss: 78.3861, Reg Loss: 1.1404\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 8/35: 100%|██████████| 938/938 [00:26<00:00, 35.39batch/s, loss=2.65e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8, Critic Loss: -3.3605, VAE Loss: 78.7564, Recon Loss: 77.6683, Reg Loss: 1.0881\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 9/35: 100%|██████████| 938/938 [00:38<00:00, 24.61batch/s, loss=2.45e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9, Critic Loss: -3.2005, VAE Loss: 78.1346, Recon Loss: 77.0929, Reg Loss: 1.0417\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 10/35: 100%|██████████| 938/938 [00:43<00:00, 21.50batch/s, loss=2.81e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10, Critic Loss: -3.0608, VAE Loss: 77.6100, Recon Loss: 76.6067, Reg Loss: 1.0033\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 11/35: 100%|██████████| 938/938 [00:30<00:00, 30.83batch/s, loss=2.44e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11, Critic Loss: -2.9365, VAE Loss: 77.1523, Recon Loss: 76.1858, Reg Loss: 0.9665\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 12/35: 100%|██████████| 938/938 [00:24<00:00, 38.15batch/s, loss=2.6e+3] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 12, Critic Loss: -2.8175, VAE Loss: 76.7443, Recon Loss: 75.8127, Reg Loss: 0.9316\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 13/35: 100%|██████████| 938/938 [00:40<00:00, 23.33batch/s, loss=2.69e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13, Critic Loss: -2.7058, VAE Loss: 76.3716, Recon Loss: 75.4724, Reg Loss: 0.8992\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 14/35: 100%|██████████| 938/938 [00:32<00:00, 29.15batch/s, loss=2.37e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 14, Critic Loss: -2.6117, VAE Loss: 76.0602, Recon Loss: 75.1871, Reg Loss: 0.8731\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 15/35: 100%|██████████| 938/938 [00:24<00:00, 38.19batch/s, loss=2.5e+3] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 15, Critic Loss: -2.5163, VAE Loss: 75.7862, Recon Loss: 74.9408, Reg Loss: 0.8455\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 16/35: 100%|██████████| 938/938 [00:28<00:00, 32.37batch/s, loss=2.46e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 16, Critic Loss: -2.4265, VAE Loss: 75.5189, Recon Loss: 74.7010, Reg Loss: 0.8178\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 17/35: 100%|██████████| 938/938 [00:24<00:00, 37.85batch/s, loss=2.42e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 17, Critic Loss: -2.3420, VAE Loss: 75.2971, Recon Loss: 74.4968, Reg Loss: 0.8004\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 18/35: 100%|██████████| 938/938 [00:32<00:00, 29.10batch/s, loss=2.29e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 18, Critic Loss: -2.2669, VAE Loss: 75.0893, Recon Loss: 74.3090, Reg Loss: 0.7803\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 19/35: 100%|██████████| 938/938 [00:41<00:00, 22.68batch/s, loss=2.71e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 19, Critic Loss: -2.1962, VAE Loss: 74.8983, Recon Loss: 74.1364, Reg Loss: 0.7619\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 20/35: 100%|██████████| 938/938 [00:46<00:00, 20.19batch/s, loss=2.34e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 20, Critic Loss: -2.1278, VAE Loss: 74.7181, Recon Loss: 73.9793, Reg Loss: 0.7388\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 21/35: 100%|██████████| 938/938 [00:24<00:00, 37.83batch/s, loss=2.46e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 21, Critic Loss: -2.0664, VAE Loss: 74.5586, Recon Loss: 73.8373, Reg Loss: 0.7212\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 22/35: 100%|██████████| 938/938 [00:24<00:00, 37.73batch/s, loss=2.44e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 22, Critic Loss: -2.0021, VAE Loss: 74.4033, Recon Loss: 73.7002, Reg Loss: 0.7031\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 23/35: 100%|██████████| 938/938 [00:33<00:00, 28.40batch/s, loss=2.37e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 23, Critic Loss: -1.9464, VAE Loss: 74.2569, Recon Loss: 73.5705, Reg Loss: 0.6863\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 24/35: 100%|██████████| 938/938 [00:26<00:00, 34.90batch/s, loss=2.65e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 24, Critic Loss: -1.8980, VAE Loss: 74.1123, Recon Loss: 73.4418, Reg Loss: 0.6705\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 25/35: 100%|██████████| 938/938 [00:25<00:00, 36.89batch/s, loss=2.44e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 25, Critic Loss: -1.8501, VAE Loss: 73.9877, Recon Loss: 73.3303, Reg Loss: 0.6575\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 26/35: 100%|██████████| 938/938 [00:47<00:00, 19.83batch/s, loss=2.36e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 26, Critic Loss: -1.8022, VAE Loss: 73.8696, Recon Loss: 73.2268, Reg Loss: 0.6428\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 27/35: 100%|██████████| 938/938 [00:24<00:00, 37.88batch/s, loss=2.38e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 27, Critic Loss: -1.7585, VAE Loss: 73.7485, Recon Loss: 73.1192, Reg Loss: 0.6293\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 28/35: 100%|██████████| 938/938 [00:24<00:00, 38.21batch/s, loss=2.39e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 28, Critic Loss: -1.7182, VAE Loss: 73.6422, Recon Loss: 73.0295, Reg Loss: 0.6128\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 29/35: 100%|██████████| 938/938 [00:24<00:00, 38.12batch/s, loss=2.45e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 29, Critic Loss: -1.6764, VAE Loss: 73.5474, Recon Loss: 72.9431, Reg Loss: 0.6042\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 30/35: 100%|██████████| 938/938 [00:24<00:00, 38.12batch/s, loss=2.44e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 30, Critic Loss: -1.6440, VAE Loss: 73.4439, Recon Loss: 72.8505, Reg Loss: 0.5934\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 31/35: 100%|██████████| 938/938 [00:24<00:00, 38.07batch/s, loss=2.35e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 31, Critic Loss: -1.6104, VAE Loss: 73.3552, Recon Loss: 72.7762, Reg Loss: 0.5790\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 32/35: 100%|██████████| 938/938 [00:24<00:00, 38.19batch/s, loss=2.35e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 32, Critic Loss: -1.5757, VAE Loss: 73.2799, Recon Loss: 72.7093, Reg Loss: 0.5706\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 33/35: 100%|██████████| 938/938 [00:24<00:00, 38.17batch/s, loss=2.42e+3]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 33, Critic Loss: -1.5409, VAE Loss: 73.2064, Recon Loss: 72.6414, Reg Loss: 0.5649\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 34/35: 100%|██████████| 938/938 [00:24<00:00, 38.09batch/s, loss=2.2e+3] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 34, Critic Loss: -1.5097, VAE Loss: 73.1348, Recon Loss: 72.5809, Reg Loss: 0.5539\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 35/35: 100%|██████████| 938/938 [00:24<00:00, 38.18batch/s, loss=2.1e+3] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 35, Critic Loss: -1.4772, VAE Loss: 73.0538, Recon Loss: 72.5112, Reg Loss: 0.5425\n"
     ]
    }
   ],
   "source": [
    "# Train W-VAE\n",
    "train_wvae(vae2,\n",
    "          critic, \n",
    "          train_loader, \n",
    "          vae2_optimizer, \n",
    "          critic_optimizer, \n",
    "          hyperparameters_wass[\"epochs\"], \n",
    "          hyperparameters_wass[\"gp_weight\"],\n",
    "          hyperparameters_wass[\"critic_updates_per_step_wass\"],\n",
    "          hyperparameters_wass[\"recon_weight_wass\"]\n",
    "          )\n",
    "\n",
    "save_and_log_model(vae2, \"vae_wass_distance\")\n",
    "save_and_log_model(critic, \"critic\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "e8d38a2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x400 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_results(vae2, train_loader, name=\"Wasserstein\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "db70ff42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_latent_space(vae2, train_loader, name=\"WS\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "e03b4161",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 3000x400 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# This helps to see how well the latent space approximates a Gaussian distribution.\n",
    "plot_latent_distributions(vae2, train_loader, name=\"Wassersten\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "65f92caa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x200 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_interpolation(vae2, train_loader, num_steps=10, name=\"Wasserstein\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "ce4c338f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/bot_env/lib/python3.10/site-packages/clearml/utilities/plotlympl/renderer.py:210: UserWarning:\n",
      "\n",
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_reconstruction_error(vae2, train_loader, name=\"Wasserstein\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "bot_env",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}