lstm_with_attention.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'tensorflow'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[1], line 6\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdata\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m DataLoader, Dataset\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtorchvision\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtransforms\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ToTensor\n\u001b[1;32m----> 6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdatasets\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m imdb\n\u001b[0;32m      7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpreprocessing\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msequence\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m pad_sequences\n\u001b[0;32m      9\u001b[0m \u001b[38;5;66;03m# Hyperparameters\u001b[39;00m\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\__init__.py:4\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mos\u001b[39;00m\n\u001b[0;32m      3\u001b[0m \u001b[38;5;66;03m# DO NOT EDIT. Generated by api_gen.sh\u001b[39;00m\n\u001b[1;32m----> 4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mapi\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m DTypePolicy\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mapi\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m FloatDTypePolicy\n\u001b[0;32m      6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mapi\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Function\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\api\\__init__.py:8\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\"DO NOT EDIT.\u001b[39;00m\n\u001b[0;32m      2\u001b[0m \n\u001b[0;32m      3\u001b[0m \u001b[38;5;124;03mThis file was autogenerated. Do not edit it by hand,\u001b[39;00m\n\u001b[0;32m      4\u001b[0m \u001b[38;5;124;03msince your modifications would be overwritten.\u001b[39;00m\n\u001b[0;32m      5\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m----> 8\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mapi\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m activations\n\u001b[0;32m      9\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mapi\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m applications\n\u001b[0;32m     10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mapi\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m backend\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\api\\activations\\__init__.py:7\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\"DO NOT EDIT.\u001b[39;00m\n\u001b[0;32m      2\u001b[0m \n\u001b[0;32m      3\u001b[0m \u001b[38;5;124;03mThis file was autogenerated. Do not edit it by hand,\u001b[39;00m\n\u001b[0;32m      4\u001b[0m \u001b[38;5;124;03msince your modifications would be overwritten.\u001b[39;00m\n\u001b[0;32m      5\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m----> 7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mactivations\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m deserialize\n\u001b[0;32m      8\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mactivations\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m get\n\u001b[0;32m      9\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mactivations\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m serialize\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\src\\__init__.py:1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m activations\n\u001b[0;32m      2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m applications\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m backend\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\src\\activations\\__init__.py:3\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtypes\u001b[39;00m\n\u001b[1;32m----> 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mactivations\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mactivations\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m elu\n\u001b[0;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mactivations\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mactivations\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m exponential\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mactivations\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mactivations\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m gelu\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\src\\activations\\activations.py:1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m backend\n\u001b[0;32m      2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ops\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mapi_export\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m keras_export\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\src\\backend\\__init__.py:9\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m backend() \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtorch\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m      4\u001b[0m     \u001b[38;5;66;03m# When using the torch backend,\u001b[39;00m\n\u001b[0;32m      5\u001b[0m     \u001b[38;5;66;03m# torch needs to be imported first, otherwise it will segfault\u001b[39;00m\n\u001b[0;32m      6\u001b[0m     \u001b[38;5;66;03m# upon import.\u001b[39;00m\n\u001b[0;32m      7\u001b[0m     \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\n\u001b[1;32m----> 9\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbackend\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdtypes\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m result_type\n\u001b[0;32m     10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbackend\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mkeras_tensor\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m KerasTensor\n\u001b[0;32m     11\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbackend\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mkeras_tensor\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m any_symbolic_tensors\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\src\\backend\\common\\__init__.py:2\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbackend\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m backend_utils\n\u001b[1;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbackend\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdtypes\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m result_type\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbackend\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mvariables\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m AutocastScope\n\u001b[0;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbackend\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mvariables\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m KerasVariable\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\src\\backend\\common\\dtypes.py:5\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mapi_export\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m keras_export\n\u001b[0;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbackend\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m config\n\u001b[1;32m----> 5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbackend\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mvariables\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m standardize_dtype\n\u001b[0;32m      7\u001b[0m BOOL_TYPES \u001b[38;5;241m=\u001b[39m (\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbool\u001b[39m\u001b[38;5;124m\"\u001b[39m,)\n\u001b[0;32m      8\u001b[0m INT_TYPES \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m      9\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muint8\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     10\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muint16\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     16\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mint64\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     17\u001b[0m )\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\src\\backend\\common\\variables.py:11\u001b[0m\n\u001b[0;32m      9\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbackend\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mstateless_scope\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m get_stateless_scope\n\u001b[0;32m     10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbackend\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mstateless_scope\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m in_stateless_scope\n\u001b[1;32m---> 11\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmodule_utils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m tensorflow \u001b[38;5;28;01mas\u001b[39;00m tf\n\u001b[0;32m     12\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mnaming\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m auto_name\n\u001b[0;32m     15\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01mKerasVariable\u001b[39;00m:\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\src\\utils\\__init__.py:1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01maudio_dataset_utils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m audio_dataset_from_directory\n\u001b[0;32m      2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdataset_utils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m split_dataset\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mfile_utils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m get_file\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\src\\utils\\audio_dataset_utils.py:4\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mapi_export\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m keras_export\n\u001b[1;32m----> 4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m dataset_utils\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmodule_utils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m tensorflow \u001b[38;5;28;01mas\u001b[39;00m tf\n\u001b[0;32m      6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmodule_utils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m tensorflow_io \u001b[38;5;28;01mas\u001b[39;00m tfio\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\src\\utils\\dataset_utils.py:9\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mmultiprocessing\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpool\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ThreadPool\n\u001b[0;32m      7\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[1;32m----> 9\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m tree\n\u001b[0;32m     10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mapi_export\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m keras_export\n\u001b[0;32m     11\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m io_utils\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\src\\tree\\__init__.py:1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtree\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtree_api\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m assert_same_structure\n\u001b[0;32m      2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtree\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtree_api\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m flatten\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtree\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtree_api\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m is_nested\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\src\\tree\\tree_api.py:6\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmodule_utils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m optree\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m optree\u001b[38;5;241m.\u001b[39mavailable:\n\u001b[1;32m----> 6\u001b[0m     \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtree\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m optree_impl \u001b[38;5;28;01mas\u001b[39;00m tree_impl\n\u001b[0;32m      7\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m dmtree\u001b[38;5;241m.\u001b[39mavailable:\n\u001b[0;32m      8\u001b[0m     \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mkeras\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msrc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtree\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m dmtree_impl \u001b[38;5;28;01mas\u001b[39;00m tree_impl\n",
      "File \u001b[1;32mc:\\Users\\harsh\\Desktop\\ML Projects\\Unsupervised Representation Learning with DCGAN\\venv\\lib\\site-packages\\keras\\src\\tree\\optree_impl.py:17\u001b[0m\n\u001b[0;32m     15\u001b[0m \u001b[38;5;66;03m# Register backend-specific node classes\u001b[39;00m\n\u001b[0;32m     16\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m backend() \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtensorflow\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m---> 17\u001b[0m     \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtensorflow\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpython\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtrackable\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdata_structures\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ListWrapper\n\u001b[0;32m     19\u001b[0m     optree\u001b[38;5;241m.\u001b[39mregister_pytree_node(\n\u001b[0;32m     20\u001b[0m         ListWrapper,\n\u001b[0;32m     21\u001b[0m         \u001b[38;5;28;01mlambda\u001b[39;00m x: (x, \u001b[38;5;28;01mNone\u001b[39;00m),\n\u001b[0;32m     22\u001b[0m         \u001b[38;5;28;01mlambda\u001b[39;00m metadata, children: ListWrapper(\u001b[38;5;28mlist\u001b[39m(children)),\n\u001b[0;32m     23\u001b[0m         namespace\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mkeras\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     24\u001b[0m     )\n\u001b[0;32m     27\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mis_nested\u001b[39m(structure):\n",
      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'tensorflow'"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.optim as optim\n",
    "from torch.utils.data import DataLoader, Dataset\n",
    "from torchvision.transforms import ToTensor\n",
    "from keras.datasets import imdb\n",
    "from keras.preprocessing.sequence import pad_sequences\n",
    "\n",
    "# Hyperparameters\n",
    "max_features = 20000  # Vocabulary size\n",
    "max_len = 100  # Max length of input sequence\n",
    "embedding_dim = 128\n",
    "hidden_dim = 128\n",
    "batch_size = 32\n",
    "num_epochs = 3\n",
    "\n",
    "# Load and preprocess data\n",
    "(X_train, y_train), (X_test, y_test) = imdb.load_data(num_words=max_features)\n",
    "X_train = pad_sequences(X_train, maxlen=max_len)\n",
    "X_test = pad_sequences(X_test, maxlen=max_len)\n",
    "\n",
    "# Custom PyTorch Dataset\n",
    "class IMDBDataset(Dataset):\n",
    "    def __init__(self, data, labels):\n",
    "        self.data = torch.LongTensor(data)\n",
    "        self.labels = torch.FloatTensor(labels)\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.labels)\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        return self.data[idx], self.labels[idx]\n",
    "\n",
    "train_dataset = IMDBDataset(X_train, y_train)\n",
    "test_dataset = IMDBDataset(X_test, y_test)\n",
    "\n",
    "train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True)\n",
    "test_loader = DataLoader(test_dataset, batch_size=batch_size)\n",
    "\n",
    "# Custom Attention Layer\n",
    "class Attention(nn.Module):\n",
    "    def __init__(self, hidden_dim):\n",
    "        super(Attention, self).__init__()\n",
    "        self.attention_weights = nn.Linear(hidden_dim, 1)\n",
    "\n",
    "    def forward(self, lstm_output):\n",
    "        # Compute attention scores\n",
    "        attention_scores = torch.tanh(self.attention_weights(lstm_output))\n",
    "        attention_scores = torch.softmax(attention_scores, dim=1)\n",
    "        \n",
    "        # Compute the context vector\n",
    "        context_vector = torch.sum(attention_scores * lstm_output, dim=1)\n",
    "        return context_vector, attention_scores\n",
    "\n",
    "# LSTM with Attention Model\n",
    "class LSTMWithAttention(nn.Module):\n",
    "    def __init__(self, vocab_size, embedding_dim, hidden_dim, output_dim):\n",
    "        super(LSTMWithAttention, self).__init__()\n",
    "        self.embedding = nn.Embedding(vocab_size, embedding_dim)\n",
    "        self.lstm = nn.LSTM(embedding_dim, hidden_dim, batch_first=True)\n",
    "        self.attention = Attention(hidden_dim)\n",
    "        self.fc = nn.Linear(hidden_dim, output_dim)\n",
    "        self.sigmoid = nn.Sigmoid()\n",
    "\n",
    "    def forward(self, x):\n",
    "        embedded = self.embedding(x)\n",
    "        lstm_output, _ = self.lstm(embedded)\n",
    "        context_vector, attention_weights = self.attention(lstm_output)\n",
    "        output = self.sigmoid(self.fc(context_vector))\n",
    "        return output, attention_weights\n",
    "\n",
    "# Initialize Model, Loss, and Optimizer\n",
    "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "model = LSTMWithAttention(max_features, embedding_dim, hidden_dim, 1).to(device)\n",
    "criterion = nn.BCELoss()\n",
    "optimizer = optim.Adam(model.parameters(), lr=0.001)\n",
    "\n",
    "# Training Loop\n",
    "def train(model, loader, optimizer, criterion):\n",
    "    model.train()\n",
    "    total_loss = 0\n",
    "    for inputs, labels in loader:\n",
    "        inputs, labels = inputs.to(device), labels.to(device)\n",
    "        optimizer.zero_grad()\n",
    "        outputs, _ = model(inputs)\n",
    "        loss = criterion(outputs.squeeze(), labels)\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        total_loss += loss.item()\n",
    "    return total_loss / len(loader)\n",
    "\n",
    "# Testing Loop\n",
    "def evaluate(model, loader):\n",
    "    model.eval()\n",
    "    total_accuracy = 0\n",
    "    with torch.no_grad():\n",
    "        for inputs, labels in loader:\n",
    "            inputs, labels = inputs.to(device), labels.to(device)\n",
    "            outputs, _ = model(inputs)\n",
    "            predictions = (outputs.squeeze() > 0.5).float()\n",
    "            total_accuracy += (predictions == labels).float().mean()\n",
    "    return total_accuracy / len(loader)\n",
    "\n",
    "# Training the Model\n",
    "for epoch in range(num_epochs):\n",
    "    train_loss = train(model, train_loader, optimizer, criterion)\n",
    "    val_accuracy = evaluate(model, test_loader)\n",
    "    print(f\"Epoch {epoch + 1}/{num_epochs} - Loss: {train_loss:.4f}, Val Accuracy: {val_accuracy:.4f}\")\n",
    "\n",
    "# Visualizing Attention Weights\n",
    "def visualize_attention(model, input_sequence):\n",
    "    model.eval()\n",
    "    input_tensor = torch.LongTensor(input_sequence).unsqueeze(0).to(device)\n",
    "    _, attention_weights = model(input_tensor)\n",
    "    attention_weights = attention_weights.squeeze().cpu().detach().numpy()\n",
    "    return attention_weights\n",
    "\n",
    "# Example Visualization\n",
    "example_idx = 0\n",
    "attention_weights = visualize_attention(model, X_test[example_idx])\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.bar(range(len(X_test[example_idx])), attention_weights.squeeze())\n",
    "plt.title(\"Attention Weights for an Example Sequence\")\n",
    "plt.xlabel(\"Word Index\")\n",
    "plt.ylabel(\"Attention Weight\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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