HindiMovieReviews.ipynb

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        "colab": {
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      "source": [
        "! pip install tensorboardX pandas simpletransformers transformers"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting tensorboardX\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/35/f1/5843425495765c8c2dd0784a851a93ef204d314fc87bcc2bbb9f662a3ad1/tensorboardX-2.0-py2.py3-none-any.whl (195kB)\n",
            "\u001b[K     |████████████████████████████████| 204kB 5.0MB/s \n",
            "\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.6/dist-packages (1.0.3)\n",
            "Collecting simpletransformers\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/7b/ba/2864d9f710147d7f33523b8b9e00500e4c0928c3fd150104c1b51f9a32a0/simpletransformers-0.22.1-py3-none-any.whl (144kB)\n",
            "\u001b[K     |████████████████████████████████| 153kB 16.1MB/s \n",
            "\u001b[?25hCollecting transformers\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/37/ba/dda44bbf35b071441635708a3dd568a5ca6bf29f77389f7c7c6818ae9498/transformers-2.7.0-py3-none-any.whl (544kB)\n",
            "\u001b[K     |████████████████████████████████| 552kB 11.1MB/s \n",
            "\u001b[?25hRequirement already satisfied: protobuf>=3.8.0 in /usr/local/lib/python3.6/dist-packages (from tensorboardX) (3.10.0)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from tensorboardX) (1.18.2)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from tensorboardX) (1.12.0)\n",
            "Requirement already satisfied: python-dateutil>=2.6.1 in /usr/local/lib/python3.6/dist-packages (from pandas) (2.8.1)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas) (2018.9)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.6/dist-packages (from simpletransformers) (4.38.0)\n",
            "Collecting seqeval\n",
            "  Downloading https://files.pythonhosted.org/packages/34/91/068aca8d60ce56dd9ba4506850e876aba5e66a6f2f29aa223224b50df0de/seqeval-0.0.12.tar.gz\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.6/dist-packages (from simpletransformers) (1.4.1)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.6/dist-packages (from simpletransformers) (0.22.2.post1)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (from simpletransformers) (2.21.0)\n",
            "Requirement already satisfied: regex in /usr/local/lib/python3.6/dist-packages (from simpletransformers) (2019.12.20)\n",
            "Collecting tokenizers==0.5.2\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/d1/3f/73c881ea4723e43c1e9acf317cf407fab3a278daab3a69c98dcac511c04f/tokenizers-0.5.2-cp36-cp36m-manylinux1_x86_64.whl (3.7MB)\n",
            "\u001b[K     |████████████████████████████████| 3.7MB 29.4MB/s \n",
            "\u001b[?25hCollecting sacremoses\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/a6/b4/7a41d630547a4afd58143597d5a49e07bfd4c42914d8335b2a5657efc14b/sacremoses-0.0.38.tar.gz (860kB)\n",
            "\u001b[K     |████████████████████████████████| 870kB 52.8MB/s \n",
            "\u001b[?25hRequirement already satisfied: boto3 in /usr/local/lib/python3.6/dist-packages (from transformers) (1.12.31)\n",
            "Collecting sentencepiece\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/74/f4/2d5214cbf13d06e7cb2c20d84115ca25b53ea76fa1f0ade0e3c9749de214/sentencepiece-0.1.85-cp36-cp36m-manylinux1_x86_64.whl (1.0MB)\n",
            "\u001b[K     |████████████████████████████████| 1.0MB 36.2MB/s \n",
            "\u001b[?25hRequirement already satisfied: dataclasses; python_version < \"3.7\" in /usr/local/lib/python3.6/dist-packages (from transformers) (0.7)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.6/dist-packages (from transformers) (3.0.12)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from protobuf>=3.8.0->tensorboardX) (46.0.0)\n",
            "Requirement already satisfied: Keras>=2.2.4 in /usr/local/lib/python3.6/dist-packages (from seqeval->simpletransformers) (2.2.5)\n",
            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.6/dist-packages (from scikit-learn->simpletransformers) (0.14.1)\n",
            "Requirement already satisfied: urllib3<1.25,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->simpletransformers) (1.24.3)\n",
            "Requirement already satisfied: chardet<3.1.0,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->simpletransformers) (3.0.4)\n",
            "Requirement already satisfied: idna<2.9,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->simpletransformers) (2.8)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->simpletransformers) (2019.11.28)\n",
            "Requirement already satisfied: click in /usr/local/lib/python3.6/dist-packages (from sacremoses->transformers) (7.1.1)\n",
            "Requirement already satisfied: s3transfer<0.4.0,>=0.3.0 in /usr/local/lib/python3.6/dist-packages (from boto3->transformers) (0.3.3)\n",
            "Requirement already satisfied: jmespath<1.0.0,>=0.7.1 in /usr/local/lib/python3.6/dist-packages (from boto3->transformers) (0.9.5)\n",
            "Requirement already satisfied: botocore<1.16.0,>=1.15.31 in /usr/local/lib/python3.6/dist-packages (from boto3->transformers) (1.15.31)\n",
            "Requirement already satisfied: keras-applications>=1.0.8 in /usr/local/lib/python3.6/dist-packages (from Keras>=2.2.4->seqeval->simpletransformers) (1.0.8)\n",
            "Requirement already satisfied: keras-preprocessing>=1.1.0 in /usr/local/lib/python3.6/dist-packages (from Keras>=2.2.4->seqeval->simpletransformers) (1.1.0)\n",
            "Requirement already satisfied: h5py in /usr/local/lib/python3.6/dist-packages (from Keras>=2.2.4->seqeval->simpletransformers) (2.10.0)\n",
            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.6/dist-packages (from Keras>=2.2.4->seqeval->simpletransformers) (3.13)\n",
            "Requirement already satisfied: docutils<0.16,>=0.10 in /usr/local/lib/python3.6/dist-packages (from botocore<1.16.0,>=1.15.31->boto3->transformers) (0.15.2)\n",
            "Building wheels for collected packages: seqeval, sacremoses\n",
            "  Building wheel for seqeval (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for seqeval: filename=seqeval-0.0.12-cp36-none-any.whl size=7424 sha256=fb00152aaf86487ffb7ff60d9b12fe1923799261d340a287e317bb7ad041f375\n",
            "  Stored in directory: /root/.cache/pip/wheels/4f/32/0a/df3b340a82583566975377d65e724895b3fad101a3fb729f68\n",
            "  Building wheel for sacremoses (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sacremoses: filename=sacremoses-0.0.38-cp36-none-any.whl size=884628 sha256=6c9559a7c33ccf152bb08214486e7cbd440d830f253f2792d098e328cfcf09e7\n",
            "  Stored in directory: /root/.cache/pip/wheels/6d/ec/1a/21b8912e35e02741306f35f66c785f3afe94de754a0eaf1422\n",
            "Successfully built seqeval sacremoses\n",
            "Installing collected packages: tensorboardX, seqeval, tokenizers, sacremoses, sentencepiece, transformers, simpletransformers\n",
            "Successfully installed sacremoses-0.0.38 sentencepiece-0.1.85 seqeval-0.0.12 simpletransformers-0.22.1 tensorboardX-2.0 tokenizers-0.5.2 transformers-2.7.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S-m1NBtpL13h",
        "colab_type": "code",
        "outputId": "6c183bb7-0ebc-4a98-cb28-5fbb96dc44fd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 82
        }
      },
      "source": [
        "!nvcc --version"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "nvcc: NVIDIA (R) Cuda compiler driver\n",
            "Copyright (c) 2005-2018 NVIDIA Corporation\n",
            "Built on Sat_Aug_25_21:08:01_CDT_2018\n",
            "Cuda compilation tools, release 10.0, V10.0.130\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r8z7JP2XS6E3",
        "colab_type": "code",
        "outputId": "020911bf-de51-4161-c841-1386908c5518",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 147
        }
      },
      "source": [
        "! pip install https://download.pytorch.org/whl/cu100/torch-1.4.0%2Bcu100-cp36-cp36m-linux_x86_64.whl"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting torch==1.4.0+cu100\n",
            "\u001b[?25l  Downloading https://download.pytorch.org/whl/cu100/torch-1.4.0%2Bcu100-cp36-cp36m-linux_x86_64.whl (723.9MB)\n",
            "\u001b[K     |████████████████████████████████| 723.9MB 25kB/s \n",
            "\u001b[?25hInstalling collected packages: torch\n",
            "  Found existing installation: torch 1.4.0\n",
            "    Uninstalling torch-1.4.0:\n",
            "      Successfully uninstalled torch-1.4.0\n",
            "Successfully installed torch-1.4.0+cu100\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WdiCz2GsUkqj",
        "colab_type": "code",
        "outputId": "358d51d7-8217-4031-fd53-c5660aabdc2d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 212
        }
      },
      "source": [
        "! pip uninstall torchvision -y\n",
        "! pip install torchvision==0.5.0+cu100 -f https://download.pytorch.org/whl/torch_stable.html"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Uninstalling torchvision-0.5.0:\n",
            "  Successfully uninstalled torchvision-0.5.0\n",
            "Looking in links: https://download.pytorch.org/whl/torch_stable.html\n",
            "Collecting torchvision==0.5.0+cu100\n",
            "\u001b[?25l  Downloading https://download.pytorch.org/whl/cu100/torchvision-0.5.0%2Bcu100-cp36-cp36m-linux_x86_64.whl (4.0MB)\n",
            "\u001b[K     |████████████████████████████████| 4.1MB 658kB/s \n",
            "\u001b[?25hRequirement already satisfied: pillow>=4.1.1 in /usr/local/lib/python3.6/dist-packages (from torchvision==0.5.0+cu100) (7.0.0)\n",
            "Requirement already satisfied: torch==1.4.0 in /usr/local/lib/python3.6/dist-packages (from torchvision==0.5.0+cu100) (1.4.0+cu100)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from torchvision==0.5.0+cu100) (1.12.0)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from torchvision==0.5.0+cu100) (1.18.2)\n",
            "Installing collected packages: torchvision\n",
            "Successfully installed torchvision-0.5.0+cu100\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pjvRzZ4DUQtU",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "27cb6f31-7782-4af6-d35e-b437d5624f48"
      },
      "source": [
        "! pip uninstall apex -y\n",
        "! rm -rf apex\n",
        "! git clone https://www.github.com/nvidia/apex\n",
        "! cd apex && python setup.py install --cpp_ext --cuda_ext"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[33mWARNING: Skipping apex as it is not installed.\u001b[0m\n",
            "Cloning into 'apex'...\n",
            "warning: redirecting to https://github.com/nvidia/apex.git/\n",
            "remote: Enumerating objects: 85, done.\u001b[K\n",
            "remote: Counting objects: 100% (85/85), done.\u001b[K\n",
            "remote: Compressing objects: 100% (51/51), done.\u001b[K\n",
            "remote: Total 6254 (delta 56), reused 53 (delta 34), pack-reused 6169\u001b[K\n",
            "Receiving objects: 100% (6254/6254), 13.66 MiB | 20.24 MiB/s, done.\n",
            "Resolving deltas: 100% (4106/4106), done.\n",
            "torch.__version__  =  1.4.0+cu100\n",
            "setup.py:46: UserWarning: Option --pyprof not specified. Not installing PyProf dependencies!\n",
            "  warnings.warn(\"Option --pyprof not specified. Not installing PyProf dependencies!\")\n",
            "\n",
            "Compiling cuda extensions with\n",
            "nvcc: NVIDIA (R) Cuda compiler driver\n",
            "Copyright (c) 2005-2018 NVIDIA Corporation\n",
            "Built on Sat_Aug_25_21:08:01_CDT_2018\n",
            "Cuda compilation tools, release 10.0, V10.0.130\n",
            "from /usr/local/cuda/bin\n",
            "\n",
            "running install\n",
            "running bdist_egg\n",
            "running egg_info\n",
            "creating apex.egg-info\n",
            "writing apex.egg-info/PKG-INFO\n",
            "writing dependency_links to apex.egg-info/dependency_links.txt\n",
            "writing top-level names to apex.egg-info/top_level.txt\n",
            "writing manifest file 'apex.egg-info/SOURCES.txt'\n",
            "writing manifest file 'apex.egg-info/SOURCES.txt'\n",
            "installing library code to build/bdist.linux-x86_64/egg\n",
            "running install_lib\n",
            "running build_py\n",
            "creating build\n",
            "creating build/lib.linux-x86_64-3.6\n",
            "creating build/lib.linux-x86_64-3.6/apex\n",
            "copying apex/__init__.py -> build/lib.linux-x86_64-3.6/apex\n",
            "creating build/lib.linux-x86_64-3.6/apex/normalization\n",
            "copying apex/normalization/fused_layer_norm.py -> build/lib.linux-x86_64-3.6/apex/normalization\n",
            "copying apex/normalization/__init__.py -> build/lib.linux-x86_64-3.6/apex/normalization\n",
            "creating build/lib.linux-x86_64-3.6/apex/RNN\n",
            "copying apex/RNN/cells.py -> build/lib.linux-x86_64-3.6/apex/RNN\n",
            "copying apex/RNN/models.py -> build/lib.linux-x86_64-3.6/apex/RNN\n",
            "copying apex/RNN/RNNBackend.py -> build/lib.linux-x86_64-3.6/apex/RNN\n",
            "copying apex/RNN/__init__.py -> build/lib.linux-x86_64-3.6/apex/RNN\n",
            "creating build/lib.linux-x86_64-3.6/apex/multi_tensor_apply\n",
            "copying apex/multi_tensor_apply/multi_tensor_apply.py -> build/lib.linux-x86_64-3.6/apex/multi_tensor_apply\n",
            "copying apex/multi_tensor_apply/__init__.py -> build/lib.linux-x86_64-3.6/apex/multi_tensor_apply\n",
            "creating build/lib.linux-x86_64-3.6/apex/pyprof\n",
            "copying apex/pyprof/__init__.py -> build/lib.linux-x86_64-3.6/apex/pyprof\n",
            "creating build/lib.linux-x86_64-3.6/apex/parallel\n",
            "copying apex/parallel/optimized_sync_batchnorm.py -> build/lib.linux-x86_64-3.6/apex/parallel\n",
            "copying apex/parallel/sync_batchnorm_kernel.py -> build/lib.linux-x86_64-3.6/apex/parallel\n",
            "copying apex/parallel/multiproc.py -> build/lib.linux-x86_64-3.6/apex/parallel\n",
            "copying apex/parallel/optimized_sync_batchnorm_kernel.py -> build/lib.linux-x86_64-3.6/apex/parallel\n",
            "copying apex/parallel/distributed.py -> build/lib.linux-x86_64-3.6/apex/parallel\n",
            "copying apex/parallel/sync_batchnorm.py -> build/lib.linux-x86_64-3.6/apex/parallel\n",
            "copying apex/parallel/__init__.py -> build/lib.linux-x86_64-3.6/apex/parallel\n",
            "copying apex/parallel/LARC.py -> build/lib.linux-x86_64-3.6/apex/parallel\n",
            "creating build/lib.linux-x86_64-3.6/apex/fp16_utils\n",
            "copying apex/fp16_utils/fp16util.py -> build/lib.linux-x86_64-3.6/apex/fp16_utils\n",
            "copying apex/fp16_utils/loss_scaler.py -> build/lib.linux-x86_64-3.6/apex/fp16_utils\n",
            "copying apex/fp16_utils/__init__.py -> build/lib.linux-x86_64-3.6/apex/fp16_utils\n",
            "copying apex/fp16_utils/fp16_optimizer.py -> build/lib.linux-x86_64-3.6/apex/fp16_utils\n",
            "creating build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/handle.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/_initialize.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/scaler.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/__version__.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/opt.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/rnn_compat.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/utils.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/amp.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/_amp_state.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/_process_optimizer.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/frontend.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/compat.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/wrap.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "copying apex/amp/__init__.py -> build/lib.linux-x86_64-3.6/apex/amp\n",
            "creating build/lib.linux-x86_64-3.6/apex/contrib\n",
            "copying apex/contrib/__init__.py -> build/lib.linux-x86_64-3.6/apex/contrib\n",
            "creating build/lib.linux-x86_64-3.6/apex/reparameterization\n",
            "copying apex/reparameterization/weight_norm.py -> build/lib.linux-x86_64-3.6/apex/reparameterization\n",
            "copying apex/reparameterization/reparameterization.py -> build/lib.linux-x86_64-3.6/apex/reparameterization\n",
            "copying apex/reparameterization/__init__.py -> build/lib.linux-x86_64-3.6/apex/reparameterization\n",
            "creating build/lib.linux-x86_64-3.6/apex/optimizers\n",
            "copying apex/optimizers/fused_sgd.py -> build/lib.linux-x86_64-3.6/apex/optimizers\n",
            "copying apex/optimizers/fused_adam.py -> build/lib.linux-x86_64-3.6/apex/optimizers\n",
            "copying apex/optimizers/fused_novograd.py -> build/lib.linux-x86_64-3.6/apex/optimizers\n",
            "copying apex/optimizers/__init__.py -> build/lib.linux-x86_64-3.6/apex/optimizers\n",
            "copying apex/optimizers/fused_lamb.py -> build/lib.linux-x86_64-3.6/apex/optimizers\n",
            "creating build/lib.linux-x86_64-3.6/apex/pyprof/parse\n",
            "copying apex/pyprof/parse/parse.py -> build/lib.linux-x86_64-3.6/apex/pyprof/parse\n",
            "copying apex/pyprof/parse/db.py -> build/lib.linux-x86_64-3.6/apex/pyprof/parse\n",
            "copying apex/pyprof/parse/kernel.py -> build/lib.linux-x86_64-3.6/apex/pyprof/parse\n",
            "copying apex/pyprof/parse/nvvp.py -> build/lib.linux-x86_64-3.6/apex/pyprof/parse\n",
            "copying apex/pyprof/parse/__init__.py -> build/lib.linux-x86_64-3.6/apex/pyprof/parse\n",
            "copying apex/pyprof/parse/__main__.py -> build/lib.linux-x86_64-3.6/apex/pyprof/parse\n",
            "creating build/lib.linux-x86_64-3.6/apex/pyprof/nvtx\n",
            "copying apex/pyprof/nvtx/__init__.py -> build/lib.linux-x86_64-3.6/apex/pyprof/nvtx\n",
            "copying apex/pyprof/nvtx/nvmarker.py -> build/lib.linux-x86_64-3.6/apex/pyprof/nvtx\n",
            "creating build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/pooling.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/softmax.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/pointwise.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/usage.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/dropout.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/data.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/base.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/index_slice_join_mutate.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/recurrentCell.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/utility.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/activation.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/optim.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/output.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/prof.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/convert.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/normalization.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/loss.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/blas.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/reduction.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/misc.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/randomSample.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/conv.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/embedding.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/linear.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/__init__.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "copying apex/pyprof/prof/__main__.py -> build/lib.linux-x86_64-3.6/apex/pyprof/prof\n",
            "creating build/lib.linux-x86_64-3.6/apex/amp/lists\n",
            "copying apex/amp/lists/torch_overrides.py -> build/lib.linux-x86_64-3.6/apex/amp/lists\n",
            "copying apex/amp/lists/functional_overrides.py -> build/lib.linux-x86_64-3.6/apex/amp/lists\n",
            "copying apex/amp/lists/tensor_overrides.py -> build/lib.linux-x86_64-3.6/apex/amp/lists\n",
            "copying apex/amp/lists/__init__.py -> build/lib.linux-x86_64-3.6/apex/amp/lists\n",
            "creating build/lib.linux-x86_64-3.6/apex/contrib/groupbn\n",
            "copying apex/contrib/groupbn/batch_norm.py -> build/lib.linux-x86_64-3.6/apex/contrib/groupbn\n",
            "copying apex/contrib/groupbn/__init__.py -> build/lib.linux-x86_64-3.6/apex/contrib/groupbn\n",
            "creating build/lib.linux-x86_64-3.6/apex/contrib/multihead_attn\n",
            "copying apex/contrib/multihead_attn/self_multihead_attn.py -> build/lib.linux-x86_64-3.6/apex/contrib/multihead_attn\n",
            "copying apex/contrib/multihead_attn/fast_self_multihead_attn_func.py -> build/lib.linux-x86_64-3.6/apex/contrib/multihead_attn\n",
            "copying apex/contrib/multihead_attn/self_multihead_attn_func.py -> build/lib.linux-x86_64-3.6/apex/contrib/multihead_attn\n",
            "copying apex/contrib/multihead_attn/fast_encdec_multihead_attn_func.py -> build/lib.linux-x86_64-3.6/apex/contrib/multihead_attn\n",
            "copying apex/contrib/multihead_attn/encdec_multihead_attn_func.py -> build/lib.linux-x86_64-3.6/apex/contrib/multihead_attn\n",
            "copying apex/contrib/multihead_attn/fast_self_multihead_attn_norm_add_func.py -> build/lib.linux-x86_64-3.6/apex/contrib/multihead_attn\n",
            "copying apex/contrib/multihead_attn/encdec_multihead_attn.py -> build/lib.linux-x86_64-3.6/apex/contrib/multihead_attn\n",
            "copying apex/contrib/multihead_attn/fast_encdec_multihead_attn_norm_add_func.py -> build/lib.linux-x86_64-3.6/apex/contrib/multihead_attn\n",
            "copying apex/contrib/multihead_attn/__init__.py -> build/lib.linux-x86_64-3.6/apex/contrib/multihead_attn\n",
            "creating build/lib.linux-x86_64-3.6/apex/contrib/xentropy\n",
            "copying apex/contrib/xentropy/softmax_xentropy.py -> build/lib.linux-x86_64-3.6/apex/contrib/xentropy\n",
            "copying apex/contrib/xentropy/__init__.py -> build/lib.linux-x86_64-3.6/apex/contrib/xentropy\n",
            "creating build/lib.linux-x86_64-3.6/apex/contrib/optimizers\n",
            "copying apex/contrib/optimizers/fused_sgd.py -> build/lib.linux-x86_64-3.6/apex/contrib/optimizers\n",
            "copying apex/contrib/optimizers/fused_adam.py -> build/lib.linux-x86_64-3.6/apex/contrib/optimizers\n",
            "copying apex/contrib/optimizers/__init__.py -> build/lib.linux-x86_64-3.6/apex/contrib/optimizers\n",
            "copying apex/contrib/optimizers/fp16_optimizer.py -> build/lib.linux-x86_64-3.6/apex/contrib/optimizers\n",
            "running build_ext\n",
            "building 'apex_C' extension\n",
            "creating build/temp.linux-x86_64-3.6\n",
            "creating build/temp.linux-x86_64-3.6/csrc\n",
            "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/include/python3.6m -c csrc/flatten_unflatten.cpp -o build/temp.linux-x86_64-3.6/csrc/flatten_unflatten.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=apex_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/csrc/flatten_unflatten.o -o build/lib.linux-x86_64-3.6/apex_C.cpython-36m-x86_64-linux-gnu.so\n",
            "building 'amp_C' extension\n",
            "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/amp_C_frontend.cpp -o build/temp.linux-x86_64-3.6/csrc/amp_C_frontend.o -O3 -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=amp_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/multi_tensor_sgd_kernel.cu -o build/temp.linux-x86_64-3.6/csrc/multi_tensor_sgd_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -lineinfo -O3 --use_fast_math -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=amp_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++11\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/multi_tensor_scale_kernel.cu -o build/temp.linux-x86_64-3.6/csrc/multi_tensor_scale_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -lineinfo -O3 --use_fast_math -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=amp_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++11\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/multi_tensor_axpby_kernel.cu -o build/temp.linux-x86_64-3.6/csrc/multi_tensor_axpby_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -lineinfo -O3 --use_fast_math -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=amp_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++11\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/multi_tensor_l2norm_kernel.cu -o build/temp.linux-x86_64-3.6/csrc/multi_tensor_l2norm_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -lineinfo -O3 --use_fast_math -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=amp_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++11\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/multi_tensor_lamb_stage_1.cu -o build/temp.linux-x86_64-3.6/csrc/multi_tensor_lamb_stage_1.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -lineinfo -O3 --use_fast_math -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=amp_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++11\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/multi_tensor_lamb_stage_2.cu -o build/temp.linux-x86_64-3.6/csrc/multi_tensor_lamb_stage_2.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -lineinfo -O3 --use_fast_math -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=amp_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++11\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/multi_tensor_adam.cu -o build/temp.linux-x86_64-3.6/csrc/multi_tensor_adam.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -lineinfo -O3 --use_fast_math -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=amp_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++11\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/multi_tensor_novograd.cu -o build/temp.linux-x86_64-3.6/csrc/multi_tensor_novograd.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -lineinfo -O3 --use_fast_math -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=amp_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++11\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/multi_tensor_lamb.cu -o build/temp.linux-x86_64-3.6/csrc/multi_tensor_lamb.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -lineinfo -O3 --use_fast_math -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=amp_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++11\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/csrc/amp_C_frontend.o build/temp.linux-x86_64-3.6/csrc/multi_tensor_sgd_kernel.o build/temp.linux-x86_64-3.6/csrc/multi_tensor_scale_kernel.o build/temp.linux-x86_64-3.6/csrc/multi_tensor_axpby_kernel.o build/temp.linux-x86_64-3.6/csrc/multi_tensor_l2norm_kernel.o build/temp.linux-x86_64-3.6/csrc/multi_tensor_lamb_stage_1.o build/temp.linux-x86_64-3.6/csrc/multi_tensor_lamb_stage_2.o build/temp.linux-x86_64-3.6/csrc/multi_tensor_adam.o build/temp.linux-x86_64-3.6/csrc/multi_tensor_novograd.o build/temp.linux-x86_64-3.6/csrc/multi_tensor_lamb.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.6/amp_C.cpython-36m-x86_64-linux-gnu.so\n",
            "building 'syncbn' extension\n",
            "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/syncbn.cpp -o build/temp.linux-x86_64-3.6/csrc/syncbn.o -O3 -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=syncbn -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/welford.cu -o build/temp.linux-x86_64-3.6/csrc/welford.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -O3 -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=syncbn -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++11\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/csrc/syncbn.o build/temp.linux-x86_64-3.6/csrc/welford.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.6/syncbn.cpython-36m-x86_64-linux-gnu.so\n",
            "building 'fused_layer_norm_cuda' extension\n",
            "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/layer_norm_cuda.cpp -o build/temp.linux-x86_64-3.6/csrc/layer_norm_cuda.o -O3 -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=fused_layer_norm_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c csrc/layer_norm_cuda_kernel.cu -o build/temp.linux-x86_64-3.6/csrc/layer_norm_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -maxrregcount=50 -O3 --use_fast_math -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=fused_layer_norm_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_60,code=sm_60 -std=c++11\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign\n",
            "\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/csrc/layer_norm_cuda.o build/temp.linux-x86_64-3.6/csrc/layer_norm_cuda_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.6/fused_layer_norm_cuda.cpython-36m-x86_64-linux-gnu.so\n",
            "creating build/bdist.linux-x86_64\n",
            "creating build/bdist.linux-x86_64/egg\n",
            "copying build/lib.linux-x86_64-3.6/fused_layer_norm_cuda.cpython-36m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n",
            "copying build/lib.linux-x86_64-3.6/apex_C.cpython-36m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n",
            "copying build/lib.linux-x86_64-3.6/syncbn.cpython-36m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n",
            "copying build/lib.linux-x86_64-3.6/amp_C.cpython-36m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg\n",
            "creating build/bdist.linux-x86_64/egg/apex\n",
            "creating build/bdist.linux-x86_64/egg/apex/normalization\n",
            "copying build/lib.linux-x86_64-3.6/apex/normalization/fused_layer_norm.py -> build/bdist.linux-x86_64/egg/apex/normalization\n",
            "copying build/lib.linux-x86_64-3.6/apex/normalization/__init__.py -> build/bdist.linux-x86_64/egg/apex/normalization\n",
            "creating build/bdist.linux-x86_64/egg/apex/RNN\n",
            "copying build/lib.linux-x86_64-3.6/apex/RNN/cells.py -> build/bdist.linux-x86_64/egg/apex/RNN\n",
            "copying build/lib.linux-x86_64-3.6/apex/RNN/models.py -> build/bdist.linux-x86_64/egg/apex/RNN\n",
            "copying build/lib.linux-x86_64-3.6/apex/RNN/RNNBackend.py -> build/bdist.linux-x86_64/egg/apex/RNN\n",
            "copying build/lib.linux-x86_64-3.6/apex/RNN/__init__.py -> build/bdist.linux-x86_64/egg/apex/RNN\n",
            "creating build/bdist.linux-x86_64/egg/apex/multi_tensor_apply\n",
            "copying build/lib.linux-x86_64-3.6/apex/multi_tensor_apply/multi_tensor_apply.py -> build/bdist.linux-x86_64/egg/apex/multi_tensor_apply\n",
            "copying build/lib.linux-x86_64-3.6/apex/multi_tensor_apply/__init__.py -> build/bdist.linux-x86_64/egg/apex/multi_tensor_apply\n",
            "creating build/bdist.linux-x86_64/egg/apex/pyprof\n",
            "creating build/bdist.linux-x86_64/egg/apex/pyprof/parse\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/parse/parse.py -> build/bdist.linux-x86_64/egg/apex/pyprof/parse\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/parse/db.py -> build/bdist.linux-x86_64/egg/apex/pyprof/parse\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/parse/kernel.py -> build/bdist.linux-x86_64/egg/apex/pyprof/parse\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/parse/nvvp.py -> build/bdist.linux-x86_64/egg/apex/pyprof/parse\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/parse/__init__.py -> build/bdist.linux-x86_64/egg/apex/pyprof/parse\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/parse/__main__.py -> build/bdist.linux-x86_64/egg/apex/pyprof/parse\n",
            "creating build/bdist.linux-x86_64/egg/apex/pyprof/nvtx\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/nvtx/__init__.py -> build/bdist.linux-x86_64/egg/apex/pyprof/nvtx\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/nvtx/nvmarker.py -> build/bdist.linux-x86_64/egg/apex/pyprof/nvtx\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/__init__.py -> build/bdist.linux-x86_64/egg/apex/pyprof\n",
            "creating build/bdist.linux-x86_64/egg/apex/pyprof/prof\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/prof/pooling.py -> build/bdist.linux-x86_64/egg/apex/pyprof/prof\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/prof/softmax.py -> build/bdist.linux-x86_64/egg/apex/pyprof/prof\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/prof/pointwise.py -> build/bdist.linux-x86_64/egg/apex/pyprof/prof\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/prof/usage.py -> build/bdist.linux-x86_64/egg/apex/pyprof/prof\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/prof/dropout.py -> build/bdist.linux-x86_64/egg/apex/pyprof/prof\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/prof/data.py -> build/bdist.linux-x86_64/egg/apex/pyprof/prof\n",
            "copying build/lib.linux-x86_64-3.6/apex/pyprof/prof/base.py -> build/bdist.linux-x86_64/egg/apex/pyprof/prof\n",
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            "byte-compiling build/bdist.linux-x86_64/egg/apex/amp/lists/__init__.py to __init__.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/groupbn/batch_norm.py to batch_norm.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/groupbn/__init__.py to __init__.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/multihead_attn/self_multihead_attn.py to self_multihead_attn.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/multihead_attn/fast_self_multihead_attn_func.py to fast_self_multihead_attn_func.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/multihead_attn/self_multihead_attn_func.py to self_multihead_attn_func.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/multihead_attn/fast_encdec_multihead_attn_func.py to fast_encdec_multihead_attn_func.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/multihead_attn/encdec_multihead_attn_func.py to encdec_multihead_attn_func.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/multihead_attn/fast_self_multihead_attn_norm_add_func.py to fast_self_multihead_attn_norm_add_func.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/multihead_attn/encdec_multihead_attn.py to encdec_multihead_attn.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/multihead_attn/fast_encdec_multihead_attn_norm_add_func.py to fast_encdec_multihead_attn_norm_add_func.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/multihead_attn/__init__.py to __init__.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/__init__.py to __init__.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/xentropy/softmax_xentropy.py to softmax_xentropy.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/xentropy/__init__.py to __init__.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/optimizers/fused_sgd.py to fused_sgd.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/optimizers/fused_adam.py to fused_adam.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/optimizers/__init__.py to __init__.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/contrib/optimizers/fp16_optimizer.py to fp16_optimizer.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/__init__.py to __init__.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/reparameterization/weight_norm.py to weight_norm.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/reparameterization/reparameterization.py to reparameterization.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/reparameterization/__init__.py to __init__.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/optimizers/fused_sgd.py to fused_sgd.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/optimizers/fused_adam.py to fused_adam.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/optimizers/fused_novograd.py to fused_novograd.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/optimizers/__init__.py to __init__.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex/optimizers/fused_lamb.py to fused_lamb.cpython-36.pyc\n",
            "creating stub loader for apex_C.cpython-36m-x86_64-linux-gnu.so\n",
            "creating stub loader for amp_C.cpython-36m-x86_64-linux-gnu.so\n",
            "creating stub loader for syncbn.cpython-36m-x86_64-linux-gnu.so\n",
            "creating stub loader for fused_layer_norm_cuda.cpython-36m-x86_64-linux-gnu.so\n",
            "byte-compiling build/bdist.linux-x86_64/egg/apex_C.py to apex_C.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/amp_C.py to amp_C.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/syncbn.py to syncbn.cpython-36.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/fused_layer_norm_cuda.py to fused_layer_norm_cuda.cpython-36.pyc\n",
            "creating build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying apex.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying apex.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying apex.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying apex.egg-info/top_level.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "writing build/bdist.linux-x86_64/egg/EGG-INFO/native_libs.txt\n",
            "zip_safe flag not set; analyzing archive contents...\n",
            "__pycache__.amp_C.cpython-36: module references __file__\n",
            "__pycache__.apex_C.cpython-36: module references __file__\n",
            "__pycache__.fused_layer_norm_cuda.cpython-36: module references __file__\n",
            "__pycache__.syncbn.cpython-36: module references __file__\n",
            "apex.pyprof.nvtx.__pycache__.nvmarker.cpython-36: module references __file__\n",
            "apex.pyprof.nvtx.__pycache__.nvmarker.cpython-36: module references __path__\n",
            "creating dist\n",
            "creating 'dist/apex-0.1-py3.6-linux-x86_64.egg' and adding 'build/bdist.linux-x86_64/egg' to it\n",
            "removing 'build/bdist.linux-x86_64/egg' (and everything under it)\n",
            "Processing apex-0.1-py3.6-linux-x86_64.egg\n",
            "creating /usr/local/lib/python3.6/dist-packages/apex-0.1-py3.6-linux-x86_64.egg\n",
            "Extracting apex-0.1-py3.6-linux-x86_64.egg to /usr/local/lib/python3.6/dist-packages\n",
            "Adding apex 0.1 to easy-install.pth file\n",
            "\n",
            "Installed /usr/local/lib/python3.6/dist-packages/apex-0.1-py3.6-linux-x86_64.egg\n",
            "Processing dependencies for apex==0.1\n",
            "Finished processing dependencies for apex==0.1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r0fKNCGVbQu1",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "! cp ./drive/My\\ Drive/mlin/hindicorpus/hi_3500.csv ./"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OBxAA3FNL_2c",
        "colab_type": "code",
        "outputId": "3337b569-eb04-4899-8645-f7b3e931057e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 115
        }
      },
      "source": [
        "import pandas as pd \n",
        "\n",
        "df = pd.read_csv(\"./hi_3500.csv\", header=0, names=['review', 'sentiment'])\n",
        "print(df.head())"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                                              review sentiment\n",
            "0  गुमनाम है वतन पर मिटने वाले लोग आतन्कवादियों स...  negative\n",
            "1  ज़ंजीर बदली जा रही थी मैं समझा था रिहाई हो गयी है  negative\n",
            "2  यूपी में बड़े स्तर पर दंगे करवा सकती है बीजेपी...  negative\n",
            "3  अंग्रेजी नहीं आती है इसलिए हिन्दी ट्विट ज्यादा...  negative\n",
            "4                    कश्मीर में हो रहा है जल जिहाद ।  negative\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l5XutXILb53g",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "X_train, X_test, y_train, y_test = train_test_split(df['review'], df['sentiment'], random_state=91)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mmllbmrlYaHM",
        "colab_type": "code",
        "outputId": "bd40995f-39ae-49cb-865a-2a1b3e50f9a2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        }
      },
      "source": [
        "print(set(y_train.values))"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "{'neutral', 'negative', 'positive'}\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EFCEz905cl94",
        "colab_type": "code",
        "outputId": "207ff7e4-8dfb-4bc9-d32b-3b3285678654",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 115
        }
      },
      "source": [
        "from sklearn import preprocessing\n",
        "labeler = preprocessing.LabelEncoder()\n",
        "\n",
        "df2 = pd.DataFrame(X_train)\n",
        "df2['label'] = labeler.fit_transform(y_train)\n",
        "print(df2.head())"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                                                 review  label\n",
            "2378  RT @itsparvezsagar: शैलजा मर्डरः मृतका का पोस्...      1\n",
            "1450  सेट और कॉस्ट्यूम में कल्पना और बजट की कटौती से...      0\n",
            "5513  स प्रदर्शन से मुझे और परिपक्व गेंदबाज बनने में...      2\n",
            "3061  RT @neerajjournalis: वोट के तैयार है काशी और ह...      1\n",
            "5975                           मेरी यात्रा आनंदप्रद रही      2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T8UXEFknQ8j4",
        "colab_type": "code",
        "outputId": "2a169245-7c9d-427b-81ec-18b69daa60fb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 765,
          "referenced_widgets": [
            "8c453b13ecff454aba7e152f657e016c",
            "8e66d2615b1f42479e5bcf6f83997237",
            "8d12b220ea374a6fbb0e6a9c74a89691",
            "e3458b8cea6e497e86853e0d39ee3cea",
            "c831761e6e1d43f4885904acd261c80b",
            "a62666589b2440aebfce7348179b4377",
            "fe4ced5b658c4664b2a15a4bcf8215b8",
            "9dcefb7d7abd4e54a012c9a90a3ad258",
            "07eff3a4ce2e4490af655035be86931d",
            "af8fe44d3ef94089adefcb5018dd6893",
            "fa48b7f125834c49ad37e1d2cdaf0d6a",
            "b33b8b62b5f74d76942d5b5c6683ad0b",
            "5c77a552a0364c099cbee220a840ce06",
            "e66be2de9e8d4a3f986d2dd6a827f93d",
            "83db7b7f4b4a4111921e68e09ed2a5b9",
            "064de4a0772c4abd90e47dbb631f1672",
            "f554db627b774a109757dbc7b800b5f0",
            "d008b3862fb048928c99ff5b209022d0",
            "af58635e972246d7bb94d389aa147fbb",
            "d7d2b341825a446a9d576079390e4e3c",
            "fb819b14bac54f37b7e57fe5dd2f139f",
            "b4ee1939f8a44006922f78c24ea94999",
            "e71f9d5f6fc64f90a7574f3d3a95ce3b",
            "2d36f37694ed405fb63614168d1e69b9",
            "6ff0db4307ac45b9b5d6b6b7f703909d",
            "3dabdcd3eace4d1899d4e65f43a8f630",
            "db1aca4554e1428cbc299af68789e2d3",
            "9d2f396402764a4399f4517a97f46c92",
            "2f11d325727f46cea56b3aca4cd3e045",
            "90aecfc017664969951548df7d002043",
            "2d40d00443af4120b5177f490fd62749",
            "73588cc6f4c54a8f8ce03d36b0620129",
            "9926af23388949669fbd66c747758a8e",
            "81ba3094b75540a5ada3cc9d69822644",
            "f34e94c7cf3943ec9783df48d14b091b",
            "7aaf3cf6e65c443d9a2fe901623ea464",
            "fa6f5a91c3404fdd81284cd659f0c67e",
            "a048cda8b2fa4b6aa8ca560af3dbcdb7",
            "aa41401df1e847c48ec90324e01a6791",
            "5ee0028b293945e8a321a44ecf6e4b7e"
          ]
        }
      },
      "source": [
        "from simpletransformers.classification import ClassificationModel\n",
        "\n",
        "# set use_cuda=False on CPU-only platforms\n",
        "model = ClassificationModel('bert', 'bert-base-multilingual-uncased', num_labels=3, use_cuda=True, args={\n",
        "    'reprocess_input_data': True,\n",
        "    'use_cached_eval_features': False,\n",
        "    'overwrite_output_dir': True,\n",
        "    'num_train_epochs': 3\n",
        "})\n",
        "model.train_model(df2)\n",
        "print(\"trained model\")"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/simpletransformers/classification/classification_model.py:249: UserWarning: Dataframe headers not specified. Falling back to using column 0 as text and column 1 as labels.\n",
            "  \"Dataframe headers not specified. Falling back to using column 0 as text and column 1 as labels.\"\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "8c453b13ecff454aba7e152f657e016c",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=6807), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Selected optimization level O1:  Insert automatic casts around Pytorch functions and Tensor methods.\n",
            "\n",
            "Defaults for this optimization level are:\n",
            "enabled                : True\n",
            "opt_level              : O1\n",
            "cast_model_type        : None\n",
            "patch_torch_functions  : True\n",
            "keep_batchnorm_fp32    : None\n",
            "master_weights         : None\n",
            "loss_scale             : dynamic\n",
            "Processing user overrides (additional kwargs that are not None)...\n",
            "After processing overrides, optimization options are:\n",
            "enabled                : True\n",
            "opt_level              : O1\n",
            "cast_model_type        : None\n",
            "patch_torch_functions  : True\n",
            "keep_batchnorm_fp32    : None\n",
            "master_weights         : None\n",
            "loss_scale             : dynamic\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "07eff3a4ce2e4490af655035be86931d",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, description='Epoch', max=3, style=ProgressStyle(description_width='initial…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f554db627b774a109757dbc7b800b5f0",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, description='Current iteration', max=851, style=ProgressStyle(description_…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Running loss: 1.102954"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/torch/optim/lr_scheduler.py:113: UserWarning: Seems like `optimizer.step()` has been overridden after learning rate scheduler initialization. Please, make sure to call `optimizer.step()` before `lr_scheduler.step()`. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate\n",
            "  \"https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate\", UserWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Running loss: 1.090263Gradient overflow.  Skipping step, loss scaler 0 reducing loss scale to 32768.0\n",
            "Running loss: 0.994698"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/torch/optim/lr_scheduler.py:224: UserWarning: To get the last learning rate computed by the scheduler, please use `get_last_lr()`.\n",
            "  warnings.warn(\"To get the last learning rate computed by the scheduler, \"\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Running loss: 0.510946Gradient overflow.  Skipping step, loss scaler 0 reducing loss scale to 16384.0\n",
            "Running loss: 0.929150Gradient overflow.  Skipping step, loss scaler 0 reducing loss scale to 8192.0\n",
            "Running loss: 0.521209Gradient overflow.  Skipping step, loss scaler 0 reducing loss scale to 4096.0\n",
            "Running loss: 0.492807\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "6ff0db4307ac45b9b5d6b6b7f703909d",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, description='Current iteration', max=851, style=ProgressStyle(description_…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Running loss: 0.102267\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "9926af23388949669fbd66c747758a8e",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, description='Current iteration', max=851, style=ProgressStyle(description_…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Running loss: 0.242605\n",
            "\n",
            "trained model\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9Qco4_PoYi50",
        "colab_type": "code",
        "outputId": "74c81f6a-9985-42d4-d8b5-8ed87aab1e7b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 115
        }
      },
      "source": [
        "eval_frame = pd.DataFrame(X_test)\n",
        "eval_frame['label'] = labeler.fit_transform(y_test)\n",
        "print(eval_frame.head())"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                                                 review  label\n",
            "8596  RT @aajtak: #HallaBol\\n@sambitswaraj बीजेपी की...      1\n",
            "8098  RT @aajtak: पीएम मोदी ने बताई सर्जिकल स्ट्राइक...      1\n",
            "117   ~चप्पड़गंजू नसीहत दे रहा है की गुरु का सम्मान ...      0\n",
            "7407                             यह वस्त्र परिधानीय है\"      0\n",
            "4836  इस पर चुप्पी तोड़ते हुए रामपाल ने कहा है कि उन...      2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qkc7k9iHZRPK",
        "colab_type": "code",
        "outputId": "8c74bc16-7862-40e2-9b98-519d0cd7643a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        }
      },
      "source": [
        "print(len(eval_frame))"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2269\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_bKdqe_dYm5m",
        "colab_type": "code",
        "outputId": "db4987e9-55f2-44f2-ef2c-f9237e5bb598",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198,
          "referenced_widgets": [
            "389d44d67b2849aaa8ae1490213591b2",
            "91b79998437f49df9c6c88ee4a2195a4",
            "c8a91438232e4dc392464e2e528bb432",
            "e5ab7006c9794f91a424459de5a20d42",
            "b25576babb6b4c67a64791fc19105953",
            "a3bff0dc7ec949edb72aadf8f18597d6",
            "f3661f70df7c4a4397847d3a96d0ea42",
            "0544abfbb943451c856e84a1c026d0c0",
            "7be28bd5dedd4bc19b9ee240c2d5a1b5",
            "31da6e635af54223aeec41767e99d773",
            "84d6ccf8e17543548ab7ebccf769f87e",
            "84554c934d1d4b32887fa8f2eb311fb2",
            "8df91ec5ef4a42aba6da20d6833eb99f",
            "62c500c60b944aef9dcdb15c8df47e1b",
            "eac6fe9d9e92456e801be8c18a2b9e2b",
            "85b5334fb4764fbf88a1527e0636120b"
          ]
        }
      },
      "source": [
        "result, model_outputs, wrong_predictions = model.eval_model(eval_frame)\n",
        "bads = {}\n",
        "for pred in wrong_predictions:\n",
        "    if pred.label in bads:\n",
        "        bads[pred.label] += 1\n",
        "    else:\n",
        "        bads[pred.label] = 1\n",
        "print(\"wrong predictions (by input I think?):\")\n",
        "print(bads)"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/simpletransformers/classification/classification_model.py:587: UserWarning: Dataframe headers not specified. Falling back to using column 0 as text and column 1 as labels.\n",
            "  \"Dataframe headers not specified. Falling back to using column 0 as text and column 1 as labels.\"\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "389d44d67b2849aaa8ae1490213591b2",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=2269), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "7be28bd5dedd4bc19b9ee240c2d5a1b5",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=284), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "wrong predictions (by input I think?):\n",
            "{0: 208, 2: 208, 1: 36}\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bLGONGR0Ye4P",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        },
        "outputId": "0acc4287-8c7a-4352-880d-1869a07069a3"
      },
      "source": [
        "(1 - (208 + 208 + 36) / 2269) * 100"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "80.07933010136624"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Hv1bhXGCigkY",
        "colab_type": "text"
      },
      "source": [
        "80.1% Accuracy, 4 epochs, SimpleTransformers + Multilingual BERT"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HTqFLdp8Wl7X",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 883
        },
        "outputId": "7737be12-bdac-439c-9922-4b7fab4e85a4"
      },
      "source": [
        "! pip install tensorflow==1.15"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting tensorflow==1.15\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/3f/98/5a99af92fb911d7a88a0005ad55005f35b4c1ba8d75fba02df726cd936e6/tensorflow-1.15.0-cp36-cp36m-manylinux2010_x86_64.whl (412.3MB)\n",
            "\u001b[K     |████████████████████████████████| 412.3MB 37kB/s \n",
            "\u001b[?25hCollecting tensorflow-estimator==1.15.1\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/de/62/2ee9cd74c9fa2fa450877847ba560b260f5d0fb70ee0595203082dafcc9d/tensorflow_estimator-1.15.1-py2.py3-none-any.whl (503kB)\n",
            "\u001b[K     |████████████████████████████████| 512kB 40.0MB/s \n",
            "\u001b[?25hCollecting tensorboard<1.16.0,>=1.15.0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/1e/e9/d3d747a97f7188f48aa5eda486907f3b345cd409f0a0850468ba867db246/tensorboard-1.15.0-py3-none-any.whl (3.8MB)\n",
            "\u001b[K     |████████████████████████████████| 3.8MB 44.5MB/s \n",
            "\u001b[?25hRequirement already satisfied: google-pasta>=0.1.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (0.2.0)\n",
            "Requirement already satisfied: grpcio>=1.8.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.27.2)\n",
            "Requirement already satisfied: wheel>=0.26 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (0.34.2)\n",
            "Requirement already satisfied: opt-einsum>=2.3.2 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (3.2.0)\n",
            "Requirement already satisfied: wrapt>=1.11.1 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.12.1)\n",
            "Requirement already satisfied: keras-applications>=1.0.8 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.0.8)\n",
            "Requirement already satisfied: protobuf>=3.6.1 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (3.10.0)\n",
            "Requirement already satisfied: six>=1.10.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.12.0)\n",
            "Requirement already satisfied: keras-preprocessing>=1.0.5 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.1.0)\n",
            "Requirement already satisfied: numpy<2.0,>=1.16.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.18.2)\n",
            "Requirement already satisfied: absl-py>=0.7.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (0.9.0)\n",
            "Requirement already satisfied: astor>=0.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (0.8.1)\n",
            "Requirement already satisfied: termcolor>=1.1.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.1.0)\n",
            "Collecting gast==0.2.2\n",
            "  Downloading https://files.pythonhosted.org/packages/4e/35/11749bf99b2d4e3cceb4d55ca22590b0d7c2c62b9de38ac4a4a7f4687421/gast-0.2.2.tar.gz\n",
            "Requirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.16.0,>=1.15.0->tensorflow==1.15) (46.0.0)\n",
            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.16.0,>=1.15.0->tensorflow==1.15) (3.2.1)\n",
            "Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.16.0,>=1.15.0->tensorflow==1.15) (1.0.0)\n",
            "Requirement already satisfied: h5py in /usr/local/lib/python3.6/dist-packages (from keras-applications>=1.0.8->tensorflow==1.15) (2.10.0)\n",
            "Building wheels for collected packages: gast\n",
            "  Building wheel for gast (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for gast: filename=gast-0.2.2-cp36-none-any.whl size=7540 sha256=51fc313adb53e4bda760e1ed2933f1269a1bf300d8d58a3a9172c15b1f4afa44\n",
            "  Stored in directory: /root/.cache/pip/wheels/5c/2e/7e/a1d4d4fcebe6c381f378ce7743a3ced3699feb89bcfbdadadd\n",
            "Successfully built gast\n",
            "Installing collected packages: tensorflow-estimator, tensorboard, gast, tensorflow\n",
            "  Found existing installation: tensorflow-estimator 2.2.0rc0\n",
            "    Uninstalling tensorflow-estimator-2.2.0rc0:\n",
            "      Successfully uninstalled tensorflow-estimator-2.2.0rc0\n",
            "  Found existing installation: tensorboard 2.2.0\n",
            "    Uninstalling tensorboard-2.2.0:\n",
            "      Successfully uninstalled tensorboard-2.2.0\n",
            "  Found existing installation: gast 0.3.3\n",
            "    Uninstalling gast-0.3.3:\n",
            "      Successfully uninstalled gast-0.3.3\n",
            "  Found existing installation: tensorflow 2.2.0rc2\n",
            "    Uninstalling tensorflow-2.2.0rc2:\n",
            "      Successfully uninstalled tensorflow-2.2.0rc2\n",
            "Successfully installed gast-0.2.2 tensorboard-1.15.0 tensorflow-1.15.0 tensorflow-estimator-1.15.1\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "gast",
                  "tensorboard",
                  "tensorflow"
                ]
              }
            }
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T34iLaWMYpEM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 115
        },
        "outputId": "13a02cc2-9d78-49ad-a470-696f3b121887"
      },
      "source": [
        "! rm -rf electra\n",
        "! git clone https://github.com/MonsoonNLP/electra"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'electra'...\n",
            "remote: Enumerating objects: 14, done.\u001b[K\n",
            "remote: Counting objects: 100% (14/14), done.\u001b[K\n",
            "remote: Compressing objects: 100% (10/10), done.\u001b[K\n",
            "remote: Total 95 (delta 6), reused 11 (delta 4), pack-reused 81\u001b[K\n",
            "Unpacking objects: 100% (95/95), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wAyBpK2nZpg_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "! mkdir ./drive/My\\ Drive/mlin/hindicorpus/trainer/finetuning_data/movies"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ni3ONet2Y8yk",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df2.to_csv(\"./drive/My Drive/mlin/hindicorpus/trainer/finetuning_data/movies/train.tsv\", sep=\"\\t\")\n",
        "eval_frame.to_csv(\"./drive/My Drive/mlin/hindicorpus/trainer/finetuning_data/movies/dev.tsv\", sep=\"\\t\")"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vJQ50tkwYuz5",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "44f3b83a-9778-4696-c282-811449a52e40"
      },
      "source": [
        "! cd electra && python run_finetuning.py --data-dir ../drive/My\\ Drive/mlin/hindicorpus/trainer --model-name babylil --hparams '{\"task_names\": [\"movies\"], \"num_train_epochs\": 3}'"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "================================================================================\n",
            "Config: model=babylil, trial 1/1\n",
            "================================================================================\n",
            "answerable_classifier True\n",
            "answerable_uses_start_logits True\n",
            "answerable_weight 0.5\n",
            "beam_size 20\n",
            "data_dir ../drive/My Drive/mlin/hindicorpus/trainer\n",
            "debug False\n",
            "do_eval True\n",
            "do_lower_case True\n",
            "do_train True\n",
            "doc_stride 128\n",
            "double_unordered True\n",
            "embedding_size 128\n",
            "eval_batch_size 32\n",
            "gcp_project None\n",
            "init_checkpoint ../drive/My Drive/mlin/hindicorpus/trainer/models/babylil\n",
            "iterations_per_loop 1000\n",
            "joint_prediction True\n",
            "keep_all_models True\n",
            "layerwise_lr_decay 0.8\n",
            "learning_rate 0.0001\n",
            "log_examples False\n",
            "max_answer_length 30\n",
            "max_query_length 64\n",
            "max_seq_length 128\n",
            "model_dir ../drive/My Drive/mlin/hindicorpus/trainer/models/babylil/finetuning_models/movies_model\n",
            "model_hparam_overrides {}\n",
            "model_name babylil\n",
            "model_size small\n",
            "n_best_size 20\n",
            "n_writes_test 5\n",
            "num_tpu_cores 1\n",
            "num_train_epochs 3\n",
            "num_trials 1\n",
            "predict_batch_size 32\n",
            "preprocessed_data_dir ../drive/My Drive/mlin/hindicorpus/trainer/models/babylil/finetuning_tfrecords/movies_tfrecords\n",
            "qa_eval_file <built-in method format of str object at 0x7f01f8ebf0c0>\n",
            "qa_na_file <built-in method format of str object at 0x7f01f8ebf1e0>\n",
            "qa_na_threshold -2.75\n",
            "qa_preds_file <built-in method format of str object at 0x7f01f8ebf150>\n",
            "raw_data_dir <built-in method format of str object at 0x7f01f8ea1a40>\n",
            "results_pkl ../drive/My Drive/mlin/hindicorpus/trainer/models/babylil/results/movies_results.pkl\n",
            "results_txt ../drive/My Drive/mlin/hindicorpus/trainer/models/babylil/results/movies_results.txt\n",
            "save_checkpoints_steps 1000000\n",
            "task_names ['movies']\n",
            "test_predictions <built-in method format of str object at 0x7f01fa275dd8>\n",
            "tpu_job_name None\n",
            "tpu_name None\n",
            "tpu_zone None\n",
            "train_batch_size 32\n",
            "use_tfrecords_if_existing True\n",
            "use_tpu False\n",
            "vocab_file ../drive/My Drive/mlin/hindicorpus/trainer/vocab.txt\n",
            "vocab_size 30522\n",
            "warmup_proportion 0.1\n",
            "weight_decay_rate 0.01\n",
            "write_test_outputs False\n",
            "\n",
            "Loading dataset movies_train\n",
            "================================================================================\n",
            "Start training: model=babylil, trial 1/1\n",
            "================================================================================\n",
            "Training for 525 steps\n",
            "Building model...\n",
            "Building complete\n",
            "2020-04-01 02:14:47.070928: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA\n",
            "2020-04-01 02:14:47.076023: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2200000000 Hz\n",
            "2020-04-01 02:14:47.076252: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x190fb80 initialized for platform Host (this does not guarantee that XLA will be used). Devices:\n",
            "2020-04-01 02:14:47.076280: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version\n",
            "2020-04-01 02:14:47.089321: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1\n",
            "2020-04-01 02:14:47.190923: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2020-04-01 02:14:47.191490: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x190fd40 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:\n",
            "2020-04-01 02:14:47.191519: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Tesla P100-PCIE-16GB, Compute Capability 6.0\n",
            "2020-04-01 02:14:47.191687: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2020-04-01 02:14:47.192122: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: \n",
            "name: Tesla P100-PCIE-16GB major: 6 minor: 0 memoryClockRate(GHz): 1.3285\n",
            "pciBusID: 0000:00:04.0\n",
            "2020-04-01 02:14:47.195470: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0\n",
            "2020-04-01 02:14:47.204707: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0\n",
            "2020-04-01 02:14:47.209917: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0\n",
            "2020-04-01 02:14:47.220583: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0\n",
            "2020-04-01 02:14:47.229146: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0\n",
            "2020-04-01 02:14:47.235816: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0\n",
            "2020-04-01 02:14:47.251344: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7\n",
            "2020-04-01 02:14:47.251478: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2020-04-01 02:14:47.252145: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2020-04-01 02:14:47.252677: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0\n",
            "2020-04-01 02:14:47.252793: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0\n",
            "2020-04-01 02:14:47.253936: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
            "2020-04-01 02:14:47.253966: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0 \n",
            "2020-04-01 02:14:47.253976: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N \n",
            "2020-04-01 02:14:47.254106: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2020-04-01 02:14:47.254523: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2020-04-01 02:14:47.254897: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\n",
            "2020-04-01 02:14:47.254927: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9278 MB memory) -> physical GPU (device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0)\n",
            "2020-04-01 02:15:05.109639: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0\n",
            "10/525 = 1.9%, SPS: 1.1, ELAP: 9, ETA: 7:41 - loss: 32.7902\n",
            "20/525 = 3.8%, SPS: 2.0, ELAP: 10, ETA: 4:14 - loss: 37.4011\n",
            "30/525 = 5.7%, SPS: 2.7, ELAP: 11, ETA: 3:04 - loss: 29.2553\n",
            "40/525 = 7.6%, SPS: 3.3, ELAP: 12, ETA: 2:28 - loss: 33.8487\n",
            "50/525 = 9.5%, SPS: 3.7, ELAP: 13, ETA: 2:07 - loss: 25.1003\n",
            "60/525 = 11.4%, SPS: 4.2, ELAP: 14, ETA: 1:52 - loss: 23.9019\n",
            "70/525 = 13.3%, SPS: 4.5, ELAP: 16, ETA: 1:41 - loss: 26.9028\n",
            "80/525 = 15.2%, SPS: 4.8, ELAP: 17, ETA: 1:32 - loss: 24.2504\n",
            "90/525 = 17.1%, SPS: 5.1, ELAP: 18, ETA: 1:25 - loss: 26.0357\n",
            "100/525 = 19.0%, SPS: 5.3, ELAP: 19, ETA: 1:20 - loss: 19.8114\n",
            "110/525 = 21.0%, SPS: 5.5, ELAP: 20, ETA: 1:15 - loss: 19.7766\n",
            "120/525 = 22.9%, SPS: 5.7, ELAP: 21, ETA: 1:11 - loss: 20.2009\n",
            "130/525 = 24.8%, SPS: 5.9, ELAP: 22, ETA: 1:07 - loss: 16.0704\n",
            "140/525 = 26.7%, SPS: 6.1, ELAP: 23, ETA: 1:04 - loss: 20.7603\n",
            "150/525 = 28.6%, SPS: 6.2, ELAP: 24, ETA: 1:01 - loss: 27.5041\n",
            "160/525 = 30.5%, SPS: 6.3, ELAP: 25, ETA: 58 - loss: 20.5232\n",
            "170/525 = 32.4%, SPS: 6.4, ELAP: 26, ETA: 55 - loss: 25.0168\n",
            "180/525 = 34.3%, SPS: 6.6, ELAP: 27, ETA: 53 - loss: 27.4390\n",
            "190/525 = 36.2%, SPS: 6.7, ELAP: 29, ETA: 50 - loss: 16.5455\n",
            "200/525 = 38.1%, SPS: 6.7, ELAP: 30, ETA: 48 - loss: 16.4275\n",
            "210/525 = 40.0%, SPS: 6.8, ELAP: 31, ETA: 46 - loss: 18.0374\n",
            "220/525 = 41.9%, SPS: 6.9, ELAP: 32, ETA: 44 - loss: 22.5701\n",
            "230/525 = 43.8%, SPS: 7.0, ELAP: 33, ETA: 42 - loss: 22.9722\n",
            "240/525 = 45.7%, SPS: 7.1, ELAP: 34, ETA: 40 - loss: 21.6456\n",
            "250/525 = 47.6%, SPS: 7.1, ELAP: 35, ETA: 39 - loss: 21.2054\n",
            "260/525 = 49.5%, SPS: 7.2, ELAP: 36, ETA: 37 - loss: 23.9448\n",
            "270/525 = 51.4%, SPS: 7.2, ELAP: 37, ETA: 35 - loss: 15.1761\n",
            "280/525 = 53.3%, SPS: 7.3, ELAP: 38, ETA: 34 - loss: 22.7700\n",
            "290/525 = 55.2%, SPS: 7.3, ELAP: 39, ETA: 32 - loss: 23.6858\n",
            "300/525 = 57.1%, SPS: 7.4, ELAP: 41, ETA: 30 - loss: 16.2105\n",
            "310/525 = 59.0%, SPS: 7.4, ELAP: 42, ETA: 29 - loss: 21.8406\n",
            "320/525 = 61.0%, SPS: 7.5, ELAP: 43, ETA: 27 - loss: 14.6349\n",
            "330/525 = 62.9%, SPS: 7.5, ELAP: 44, ETA: 26 - loss: 24.8544\n",
            "340/525 = 64.8%, SPS: 7.6, ELAP: 45, ETA: 24 - loss: 19.2474\n",
            "350/525 = 66.7%, SPS: 7.6, ELAP: 46, ETA: 23 - loss: 17.7212\n",
            "360/525 = 68.6%, SPS: 7.6, ELAP: 47, ETA: 22 - loss: 28.3945\n",
            "370/525 = 70.5%, SPS: 7.7, ELAP: 48, ETA: 20 - loss: 24.4807\n",
            "380/525 = 72.4%, SPS: 7.7, ELAP: 49, ETA: 19 - loss: 12.7141\n",
            "390/525 = 74.3%, SPS: 7.7, ELAP: 50, ETA: 17 - loss: 14.9763\n",
            "400/525 = 76.2%, SPS: 7.8, ELAP: 51, ETA: 16 - loss: 14.8261\n",
            "410/525 = 78.1%, SPS: 7.8, ELAP: 52, ETA: 15 - loss: 20.7282\n",
            "420/525 = 80.0%, SPS: 7.8, ELAP: 54, ETA: 13 - loss: 15.5033\n",
            "430/525 = 81.9%, SPS: 7.9, ELAP: 55, ETA: 12 - loss: 19.7251\n",
            "440/525 = 83.8%, SPS: 7.9, ELAP: 56, ETA: 11 - loss: 20.5936\n",
            "450/525 = 85.7%, SPS: 7.9, ELAP: 57, ETA: 9 - loss: 23.6937\n",
            "460/525 = 87.6%, SPS: 7.9, ELAP: 58, ETA: 8 - loss: 15.9897\n",
            "470/525 = 89.5%, SPS: 8.0, ELAP: 59, ETA: 7 - loss: 14.1433\n",
            "480/525 = 91.4%, SPS: 8.0, ELAP: 1:00, ETA: 6 - loss: 20.5681\n",
            "490/525 = 93.3%, SPS: 8.0, ELAP: 1:01, ETA: 4 - loss: 18.7154\n",
            "500/525 = 95.2%, SPS: 8.0, ELAP: 1:02, ETA: 3 - loss: 12.7106\n",
            "510/525 = 97.1%, SPS: 8.1, ELAP: 1:03, ETA: 2 - loss: 16.9792\n",
            "520/525 = 99.0%, SPS: 8.1, ELAP: 1:04, ETA: 1 - loss: 19.4775\n",
            "\n",
            "================================================================================\n",
            "Run dev set evaluation: model=babylil, trial 1/1\n",
            "================================================================================\n",
            "Evaluating movies\n",
            "Loading dataset movies_dev\n",
            "Building model...\n",
            "Building complete\n",
            "2020-04-01 02:16:10.509116: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2020-04-01 02:16:10.509541: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: \n",
            "name: Tesla P100-PCIE-16GB major: 6 minor: 0 memoryClockRate(GHz): 1.3285\n",
            "pciBusID: 0000:00:04.0\n",
            "2020-04-01 02:16:10.509636: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0\n",
            "2020-04-01 02:16:10.509663: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0\n",
            "2020-04-01 02:16:10.509686: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0\n",
            "2020-04-01 02:16:10.509709: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0\n",
            "2020-04-01 02:16:10.509732: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0\n",
            "2020-04-01 02:16:10.509753: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0\n",
            "2020-04-01 02:16:10.509776: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7\n",
            "2020-04-01 02:16:10.509858: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2020-04-01 02:16:10.510287: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2020-04-01 02:16:10.510608: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0\n",
            "2020-04-01 02:16:10.510649: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
            "2020-04-01 02:16:10.510662: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0 \n",
            "2020-04-01 02:16:10.510672: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N \n",
            "2020-04-01 02:16:10.510755: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2020-04-01 02:16:10.511123: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2020-04-01 02:16:10.511439: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9278 MB memory) -> physical GPU (device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:00:04.0, compute capability: 6.0)\n",
            "movies: accuracy: 71.96 - loss: 0.63\n",
            "\n",
            "Writing results to ../drive/My Drive/mlin/hindicorpus/trainer/models/babylil/results/movies_results.txt\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}