You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
248 lines
7.4 KiB
248 lines
7.4 KiB
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 1,
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2019-05-15T16:12:27.380643Z",
|
|
"start_time": "2019-05-15T16:12:25.699672Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Thu May 16 00:12:26 2019 \n",
|
|
"+-----------------------------------------------------------------------------+\n",
|
|
"| NVIDIA-SMI 390.48 Driver Version: 390.48 |\n",
|
|
"|-------------------------------+----------------------+----------------------+\n",
|
|
"| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n",
|
|
"| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n",
|
|
"|===============================+======================+======================|\n",
|
|
"| 0 TITAN X (Pascal) Off | 00000000:02:00.0 Off | N/A |\n",
|
|
"| 46% 75C P2 87W / 250W | 10995MiB / 12196MiB | 0% Default |\n",
|
|
"+-------------------------------+----------------------+----------------------+\n",
|
|
"| 1 TITAN X (Pascal) Off | 00000000:04:00.0 Off | N/A |\n",
|
|
"| 54% 83C P2 93W / 250W | 11671MiB / 12196MiB | 64% Default |\n",
|
|
"+-------------------------------+----------------------+----------------------+\n",
|
|
"| 2 TITAN X (Pascal) Off | 00000000:83:00.0 Off | N/A |\n",
|
|
"| 62% 83C P2 193W / 250W | 12096MiB / 12196MiB | 92% Default |\n",
|
|
"+-------------------------------+----------------------+----------------------+\n",
|
|
"| 3 TITAN X (Pascal) Off | 00000000:84:00.0 Off | N/A |\n",
|
|
"| 51% 82C P2 166W / 250W | 8144MiB / 12196MiB | 58% Default |\n",
|
|
"+-------------------------------+----------------------+----------------------+\n",
|
|
" \n",
|
|
"+-----------------------------------------------------------------------------+\n",
|
|
"| Processes: GPU Memory |\n",
|
|
"| GPU PID Type Process name Usage |\n",
|
|
"|=============================================================================|\n",
|
|
"| 0 44683 C python 3289MiB |\n",
|
|
"| 0 155760 C python 4345MiB |\n",
|
|
"| 0 158310 C python 2297MiB |\n",
|
|
"| 0 172338 C /home/yzs/anaconda3/bin/python 1031MiB |\n",
|
|
"| 1 139985 C python 11653MiB |\n",
|
|
"| 2 38630 C python 5547MiB |\n",
|
|
"| 2 43127 C python 5791MiB |\n",
|
|
"| 2 156710 C python3 725MiB |\n",
|
|
"| 3 14444 C python3 1891MiB |\n",
|
|
"| 3 43407 C python 5841MiB |\n",
|
|
"| 3 88478 C /home/tangss/.conda/envs/py36/bin/python 379MiB |\n",
|
|
"+-----------------------------------------------------------------------------+\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"!nvidia-smi"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 2,
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2019-05-15T16:12:29.958567Z",
|
|
"start_time": "2019-05-15T16:12:27.383299Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import torch"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2019-05-15T16:12:47.137875Z",
|
|
"start_time": "2019-05-15T16:12:29.962468Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Linear(in_features=10, out_features=1, bias=True)"
|
|
]
|
|
},
|
|
"execution_count": 3,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"net = torch.nn.Linear(10, 1).cuda()\n",
|
|
"net"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2019-05-15T16:12:47.143709Z",
|
|
"start_time": "2019-05-15T16:12:47.139895Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"DataParallel(\n",
|
|
" (module): Linear(in_features=10, out_features=1, bias=True)\n",
|
|
")"
|
|
]
|
|
},
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"net = torch.nn.DataParallel(net)\n",
|
|
"net"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2019-05-15T16:12:47.206714Z",
|
|
"start_time": "2019-05-15T16:12:47.145069Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"torch.save(net.state_dict(), \"./8.4_model.pt\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2019-05-15T16:12:47.260076Z",
|
|
"start_time": "2019-05-15T16:12:47.208314Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"new_net = torch.nn.Linear(10, 1)\n",
|
|
"# new_net.load_state_dict(torch.load(\"./8.4_model.pt\")) # 加载失败"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2019-05-15T16:12:47.317397Z",
|
|
"start_time": "2019-05-15T16:12:47.262131Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"torch.save(net.module.state_dict(), \"./8.4_model.pt\")\n",
|
|
"new_net.load_state_dict(torch.load(\"./8.4_model.pt\")) # 加载成功"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2019-05-15T16:12:47.370299Z",
|
|
"start_time": "2019-05-15T16:12:47.319323Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"torch.save(net.state_dict(), \"./8.4_model.pt\")\n",
|
|
"new_net = torch.nn.Linear(10, 1)\n",
|
|
"new_net = torch.nn.DataParallel(new_net)\n",
|
|
"new_net.load_state_dict(torch.load(\"./8.4_model.pt\")) # 加载成功"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python [default]",
|
|
"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": "3.6.8"
|
|
},
|
|
"varInspector": {
|
|
"cols": {
|
|
"lenName": 16,
|
|
"lenType": 16,
|
|
"lenVar": 40
|
|
},
|
|
"kernels_config": {
|
|
"python": {
|
|
"delete_cmd_postfix": "",
|
|
"delete_cmd_prefix": "del ",
|
|
"library": "var_list.py",
|
|
"varRefreshCmd": "print(var_dic_list())"
|
|
},
|
|
"r": {
|
|
"delete_cmd_postfix": ") ",
|
|
"delete_cmd_prefix": "rm(",
|
|
"library": "var_list.r",
|
|
"varRefreshCmd": "cat(var_dic_list()) "
|
|
}
|
|
},
|
|
"types_to_exclude": [
|
|
"module",
|
|
"function",
|
|
"builtin_function_or_method",
|
|
"instance",
|
|
"_Feature"
|
|
],
|
|
"window_display": false
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|