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{
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   "cell_type": "code",
   "execution_count": 1,
   "id": "5a2a1e37-f4db-4963-a0ac-7b39353f826f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[0.2226, 0.2227, 0.1347],\n",
      "        [0.7975, 0.3823, 0.9395],\n",
      "        [0.1675, 0.9185, 0.4175],\n",
      "        [0.0476, 0.1244, 0.6878],\n",
      "        [0.5177, 0.7245, 0.2723]])\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "x = torch.rand(5, 3)\n",
    "print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "53469c52-9438-4d62-aa2a-e93fb3fef23b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "torch.cuda.is_available()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f13c7010-acb0-4870-aa6f-1294701cfc7e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}