94 lines
2 KiB
Text
94 lines
2 KiB
Text
{
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"cells": [
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{
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"cell_type": "code",
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"id": "initial_id",
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"metadata": {
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"collapsed": true,
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"ExecuteTime": {
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"end_time": "2026-03-12T07:47:43.647984080Z",
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"start_time": "2026-03-12T07:47:42.201741749Z"
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}
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},
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"source": [
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"import torch\n",
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"import numpy\n",
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"import pandas\n",
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"\n"
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],
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"outputs": [],
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"execution_count": 4
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2026-03-12T07:48:05.008880758Z",
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"start_time": "2026-03-12T07:48:04.943146770Z"
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}
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},
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"cell_type": "code",
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"source": "torch.randn(3,4,2)",
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"id": "3e141a42d342fa96",
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"outputs": [
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{
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"data": {
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"text/plain": [
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"tensor([[[ 0.2132, 0.9767],\n",
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" [-1.0454, 0.1760],\n",
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" [ 1.1094, -1.8272],\n",
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" [ 0.3191, 0.6993]],\n",
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"\n",
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" [[ 0.1007, 2.2675],\n",
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" [-0.3900, 0.5697],\n",
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" [ 0.8869, 0.9942],\n",
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" [ 0.5918, -0.1472]],\n",
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"\n",
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" [[-0.8392, 0.5961],\n",
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" [ 0.7128, -0.3702],\n",
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" [-0.8278, 0.6045],\n",
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" [ 0.2568, -0.2580]]])"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"execution_count": 6
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2026-03-12T07:47:43.874354756Z",
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"start_time": "2026-03-12T07:47:43.725800097Z"
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}
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},
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"cell_type": "code",
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"source": "",
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"id": "8ae20ae68abbf32f",
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"outputs": [],
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"execution_count": 5
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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