torch 设置gpu

最新推荐文章于 2024-12-16 19:22:40 发布

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#python #pytorch #开发语言

本文档记录了CUDA和cuDNN的安装过程，以及验证CUDA是否可用和TensorFlow-GPU的配置与运行。通过安装相应版本的CUDA、cuDNN和TensorFlow-GPU，成功在Python环境中运行了GPU加速的矩阵乘法操作，显示出设备已分配到GPU并返回了正确的计算结果。

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为了解决 torch.cuda.is_avalibale()

安装

472.12-desktop-win8-win7-64bit-international-whql.exe

cuda_11.5.0_496.13_win10.exe

torch-1.11.0.dev20211115+cu113-cp37-cp37m-win_amd64.whl

莫名的能用了

C:\Users\Administrator>nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Mon_Sep_13_20:11:50_Pacific_Daylight_Time_2021
Cuda compilation tools, release 11.5, V11.5.50
Build cuda_11.5.r11.5/compiler.30411180_0

C:\Users\Administrator>

(tf26) C:\Users\Administrator>pip list |grep cu
pycuda                           2021.1
torch                            1.11.0.dev20211115+cu113


(tf26) C:\Users\Administrator>pip list |grep tensor
tensorboard                      2.7.0
tensorboard-data-server          0.6.1
tensorboard-plugin-wit           1.8.0
tensorflow                       2.7.0
tensorflow-gpu                   2.7.0
tensorflow-io-gcs-filesystem     0.21.0

Python 3.7.11 (default, Jul 27 2021, 09:42:29) [MSC v.1916 64 bit (AMD64)]
Type 'copyright', 'credits' or 'license' for more information
IPython 7.29.0 -- An enhanced Interactive Python. Type '?' for help.
PyDev console: using IPython 7.29.0
Python 3.7.11 (default, Jul 27 2021, 09:42:29) [MSC v.1916 64 bit (AMD64)] on win32
import torch
import torch
torch.cuda.is_available()
Out[4]: True

import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
# Creates a graph.
a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
c = tf.matmul(a, b)
# Creates a session with log_device_placement set to True.
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
# Runs the op.
print(sess.run(c))

WARNING:tensorflow:From C:\Users\Administrator\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\compat\v2_compat.py:111: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.
Instructions for updating:
non-resource variables are not supported in the long term
Device mapping:
/job:localhost/replica:0/task:0/device:GPU:0 -> device: 0, name: NVIDIA GeForce GTX 1060 6GB, pci bus id: 0000:07:00.0, compute capability: 6.1

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