routine
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@@ -2,8 +2,54 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 1,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-20T07:32:36.354335Z",
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"start_time": "2025-01-20T07:32:35.224080Z"
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}
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},
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"outputs": [],
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"source": [
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"import torch\n",
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"import torch.nn as nn"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"# 设置使用gpu7 cuda\n",
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"device = torch.device(\"cuda:7\" if torch.cuda.is_available() and torch.cuda.get_device_properties(0).total_memory >= 6*1024**3 else \"cpu\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-20T07:32:38.297401Z",
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"start_time": "2025-01-20T07:32:38.261009Z"
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}
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},
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"outputs": [],
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"source": [
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"# 设置使用mps mps设备当前未支持限制内存\n",
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"device = torch.device(\"mps\" if torch.backends.mps.is_available() else \"cpu\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-01-20T07:32:39.972353Z",
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"start_time": "2025-01-20T07:32:39.958549Z"
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}
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},
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"outputs": [
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{
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"name": "stdout",
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@@ -20,12 +66,6 @@
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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 torch.nn as nn\n",
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"\n",
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"# 设置使用gpu7\n",
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"device = torch.device(\"cuda:7\" if torch.cuda.is_available() else \"cpu\")\n",
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"\n",
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"# 定义一个简单的神经元层\n",
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"class MultiLayerPerceptron(nn.Module):\n",
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" def __init__(self, input_size, hidden_size1, hidden_size2, output_size):\n",
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@@ -55,7 +95,7 @@
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"mlp = MultiLayerPerceptron(input_size=10, hidden_size1=20, hidden_size2=10, output_size=2)\n",
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"\n",
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"# 打印模型结构\n",
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"print(mlp)\n"
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"print(mlp)"
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]
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}
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],
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@@ -75,7 +115,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.9"
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"version": "3.10.14"
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}
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},
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"nbformat": 4,
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