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{
"cells": [
{
"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
}
|
