Audio_Swin_Transformer_Inference.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ea2a5c2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Inference \n",
    "from transformers import AutoFeatureExtractor, SwinForImageClassification\n",
    "import torch\n",
    "from datasets import load_dataset\n",
    "\n",
    "dataset = load_dataset(\"huggingface/cats-image\")\n",
    "image = dataset[\"test\"][\"image\"][0]\n",
    "\n",
    "feature_extractor = AutoFeatureExtractor.from_pretrained(\"microsoft/swin-tiny-patch4-window7-224\")\n",
    "model = SwinForImageClassification.from_pretrained(\"microsoft/swin-tiny-patch4-window7-224\")\n",
    "\n",
    "inputs = feature_extractor(image, return_tensors=\"pt\")\n",
    "\n",
    "with torch.no_grad():\n",
    "    logits = model(**inputs).logits\n",
    "\n",
    "# model predicts one of the 1000 ImageNet classes\n",
    "predicted_label = logits.argmax(-1).item()\n",
    "print(model.config.id2label[predicted_label])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c7f30276",
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "The directory at /home/ubuntu/audio_transformer/data/train doesn't contain any data file",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-98aa44747a94>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mdatasets\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mload_dataset\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mtrain_ds\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mload_dataset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"imagefolder\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata_dir\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"audio_transformer/data/train\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msplit\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"train\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/aws_neuron_pytorch_p36/lib/python3.6/site-packages/datasets/load.py\u001b[0m in \u001b[0;36mload_dataset\u001b[0;34m(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs)\u001b[0m\n\u001b[1;32m   1713\u001b[0m         \u001b[0mrevision\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrevision\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1714\u001b[0m         \u001b[0muse_auth_token\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0muse_auth_token\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1715\u001b[0;31m         \u001b[0;34m**\u001b[0m\u001b[0mconfig_kwargs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1716\u001b[0m     )\n\u001b[1;32m   1717\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/aws_neuron_pytorch_p36/lib/python3.6/site-packages/datasets/load.py\u001b[0m in \u001b[0;36mload_dataset_builder\u001b[0;34m(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, **config_kwargs)\u001b[0m\n\u001b[1;32m   1534\u001b[0m         \u001b[0mdownload_mode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdownload_mode\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1535\u001b[0m         \u001b[0mdata_dir\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata_dir\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1536\u001b[0;31m         \u001b[0mdata_files\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata_files\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1537\u001b[0m     )\n\u001b[1;32m   1538\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/aws_neuron_pytorch_p36/lib/python3.6/site-packages/datasets/load.py\u001b[0m in \u001b[0;36mdataset_module_factory\u001b[0;34m(path, revision, download_config, download_mode, force_local_path, dynamic_modules_path, data_dir, data_files, **download_kwargs)\u001b[0m\n\u001b[1;32m   1193\u001b[0m             \u001b[0mdata_files\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata_files\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1194\u001b[0m             \u001b[0mdownload_config\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdownload_config\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1195\u001b[0;31m             \u001b[0mdownload_mode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdownload_mode\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1196\u001b[0m         ).get_module()\n\u001b[1;32m   1197\u001b[0m     \u001b[0;31m# Try locally\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/aws_neuron_pytorch_p36/lib/python3.6/site-packages/datasets/load.py\u001b[0m in \u001b[0;36mget_module\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    829\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata_files\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    830\u001b[0m             \u001b[0;32melse\u001b[0m \u001b[0mget_patterns_locally\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mPath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata_dir\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresolve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 831\u001b[0;31m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata_dir\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    832\u001b[0m             \u001b[0;32melse\u001b[0m \u001b[0mget_patterns_locally\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mPath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresolve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    833\u001b[0m         )\n",
      "\u001b[0;32m~/anaconda3/envs/aws_neuron_pytorch_p36/lib/python3.6/site-packages/datasets/data_files.py\u001b[0m in \u001b[0;36mget_patterns_locally\u001b[0;34m(base_path)\u001b[0m\n\u001b[1;32m    291\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0m_get_data_files_patterns\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresolver\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    292\u001b[0m     \u001b[0;32mexcept\u001b[0m \u001b[0mFileNotFoundError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 293\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mFileNotFoundError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"The directory at {base_path} doesn't contain any data file\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    294\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    295\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: The directory at /home/ubuntu/audio_transformer/data/train doesn't contain any data file"
     ]
    }
   ],
   "source": [
    "from datasets import load_dataset\n",
    "\n",
    "train_ds = load_dataset(\"imagefolder\", data_dir=\"audio_transformer/data/train\", split=\"train\")\n",
    "\n",
    "\n",
    "# split up training into training + validation\n",
    "splits = train_ds.train_test_split(test_size=0.3)\n",
    "train_val_ds = splits['train']\n",
    "test_ds = splits['test']\n",
    "\n",
    "splits = train_val_ds.train_test_split(test_size=0.1)\n",
    "train_ds = splits['train']\n",
    "val_ds = splits['test']\n",
    "\n",
    "\n",
    "print(len(train_ds),len(test_ds),len(val_ds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cd34f229",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Environment (conda_aws_neuron_pytorch_p36)",
   "language": "python",
   "name": "conda_aws_neuron_pytorch_p36"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}