{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "#!pip install torch torchvision torchaudio\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.optim as optim\n",
    "from torchvision import datasets, transforms, models\n",
    "from torch.utils.data import DataLoader\n",
    "from sklearn.metrics import accuracy_score\n",
    "import matplotlib.pyplot as plt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CUDA não disponível. Treinando na CPU.\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "if torch.cuda.is_available():\n",
    "    print(\"CUDA disponível. Treinando na GPU.\")\n",
    "    device = torch.device(\"cuda\")\n",
    "else:\n",
    "    print(\"CUDA não disponível. Treinando na CPU.\")\n",
    "    device = torch.device(\"cpu\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using device: cpu\n"
     ]
    }
   ],
   "source": [
    "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "print(f\"Using device: {device}\")\n"
   ]
  }
 ],
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