Linux CUDA12.0安装Pytorch、Tensorflow、conda/pip添加清华源
(1) Pytorch安装成功PyTorch
Previous PyTorch Versions | PyTorch
GPU版PyTorch安装、GPU版TensorFlow安装(详细教程)_安装pytorch和tensorflow-CSDN博客
ccuda12.0 安装 pytorch_cuda12.0对应的pytorch版本-CSDN博客
汤米尼克说cuda向下兼容
准备安装CUDA11.8对应下令
https://i-blog.csdnimg.cn/direct/c465001ad1db44c3833704d5bb36f68d.png
GitHub - pytorch/vision: Datasets, Transforms and Models specific to Computer Vision
https://i-blog.csdnimg.cn/direct/4be9a9def5984362be4daae7526656fe.png
# 11.8
conda create -n pt21_c python==3.8
conda activate pt21_c
pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --index-url https://download.pytorch.org/whl/cu118
conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=11.8 -c pytorch -c nvidia
#由于网速太慢,开始山路十八弯...
$ conda config --show channels
channels:
- https://repo.anaconda.com/pkgs/main
- https://repo.anaconda.com/pkgs/r
$ conda config --show-sources
==> /home/user/anaconda3/.condarc <==
channels:
- https://repo.anaconda.com/pkgs/main
- https://repo.anaconda.com/pkgs/r
==> envvars <==
allow_softlinks: False
#conda添加清华镜像源
#法1:
vim ~/anaconda3/.condarc #直接编辑配置文件
channels:
- http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
- http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
- http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2/
- http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/
- http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch-lts/
- http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/simpleitk/
show_channel_urls: true
default_channels:
- http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
- http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
- http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
custom_channels:
conda-forge: http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
msys2: http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
bioconda: http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
menpo: http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
pytorch: http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
pytorch-lts: http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
simpleitk: http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
#法2:(一个个添加麻烦)
conda config --add channels http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
conda config --add channels http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
conda config --add channels http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --add channels http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/pro
conda config --set show_channel_urls yes
# conda config --remove-key channels #conda换回默认下载源
这个操作之后
$ conda config --show-sources
==> /home/user/anaconda3/.condarc <==
channels:
- https://repo.anaconda.com/pkgs/main
- https://repo.anaconda.com/pkgs/r
==> /home/user/.condarc <==
channels:
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
- https://repo.anaconda.com/pkgs/main
- https://repo.anaconda.com/pkgs/r
show_channel_urls: True
==> envvars <==
allow_softlinks: False
# 之后用vim ~/.condarc查看添加的镜像
$ conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=11.8 #包括11.7和12.1的命令都试过了,都是类似报错!
Solving environment: failed
LibMambaUnsatisfiableError: Encountered problems while solving:
- nothing provides cuda-cudart >=11.8,<12.0 needed by pytorch-cuda-11.8-h7e8668a_3
Could not solve for environment specs
The following packages are incompatible
└─ pytorch-cuda 11.8**is not installable because there are no viable options
├─ pytorch-cuda 11.8 would require
│└─ cuda-cudart >=11.8,<12.0 , which does not exist (perhaps a missing channel);
└─ pytorch-cuda 11.8 would require
└─ cuda 11.8.* , which does not exist (perhaps a missing channel).
# https://mp.weixin.qq.com/s/VK7QJlfxfnmwnLkZQYg1SQ
# https://mp.weixin.qq.com/s/D28hXv_k1nCjlAWnXN4wZQ
# cudatoolkit 是一个已编译好的 CUDA 库,它会在运行时被 PyTorch 使用,而不依赖于系统全局的 CUDA 安装。同时 torch 也会自动安装与指定版本的 PyTorch 兼容的 cuDNN
$ conda install cudatoolkit=11.8.0 #依旧安装失败
# 查看下载源
$ pip config list #默认下载源无输出
# CUDA 12.1
#pip添加清华镜像源
#~/.pip/pip.conf(新建文件夹.pip和文件pip.conf),写入:
index-url = https://pypi.tuna.tsinghua.edu.cn/simple
trusted-host = pypi.tuna.tsinghua.edu.cn
# 再次查看下载源
$ pip config list
global.index-url='https://pypi.tuna.tsinghua.edu.cn/simple'
install.trusted-host='pypi.tuna.tsinghua.edu.cn'
$ pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 #安装失败,出现CUDA版本不兼容的问题
>> import torch
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/torch/__init__.py", line 235, in <module>
from torch._C import *# noqa: F403
ImportError: /home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/torch/lib/../../nvidia/cusparse/lib/libcusparse.so.12: undefined symbol: __nvJitLinkAddData_12_1, version libnvJitLink.so.12
$ pip install torch-2.1.0+cu118-cp38-cp38-linux_x86_64.whl torchvision-0.16.0+cu118-cp38-cp38-linux_x86_64.whl torchaudio-2.1.0+cu118-cp38-cp38-linux_x86_64.whl
Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple
ERROR: torch-2.1.0+cu118-cp38-cp38-linux_x86_64.whl is not a supported wheel on this platform.
由于我是12.0,连轮子都不能安装吗,救命!!!
https://i-blog.csdnimg.cn/direct/1546ce6b6128462dad5fa34e126a93c1.png $ pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0https://i-blog.csdnimg.cn/direct/9efa7cb1fa3f4860846d780f357d97d8.png
https://i-blog.csdnimg.cn/direct/33d13f876a5040fb847630f025097a48.png
#终于
pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --index-url https://download.pytorch.org/whl/cu118 #我回到开始,竟然成功了(灬ꈍ ꈍ灬),看来还是要相信官网,不能盲目追求网速!
测试:
python
import torch
if torch.cuda.is_available():
num_gpus = torch.cuda.device_count()
print(f"检测到 {num_gpus} 个可用的 GPU 设备。")
for i in range(num_gpus):
gpu_name = torch.cuda.get_device_name(i)
print(f"GPU {i}: {gpu_name}")
else:
print("未检测到可用的 GPU 设备,当前使用 CPU 进行计算。")
exit()
记录一个网速bug :
ERROR: Exception:
Traceback (most recent call last):
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_vendor/urllib3/response.py", line 438, in _error_catcher
yield
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_vendor/urllib3/response.py", line 561, in read
data = self._fp_read(amt) if not fp_closed else b""
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_vendor/urllib3/response.py", line 527, in _fp_read
return self._fp.read(amt) if amt is not None else self._fp.read()
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_vendor/cachecontrol/filewrapper.py", line 98, in read
data: bytes = self.__fp.read(amt)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/http/client.py", line 454, in read
n = self.readinto(b)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/http/client.py", line 498, in readinto
n = self.fp.readinto(b)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/socket.py", line 669, in readinto
return self._sock.recv_into(b)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/ssl.py", line 1241, in recv_into
return self.read(nbytes, buffer)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/ssl.py", line 1099, in read
return self._sslobj.read(len, buffer)
ConnectionResetError: Connection reset by peer
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/cli/base_command.py", line 105, in _run_wrapper
status = _inner_run()
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/cli/base_command.py", line 96, in _inner_run
return self.run(options, args)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/cli/req_command.py", line 67, in wrapper
return func(self, options, args)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/commands/install.py", line 379, in run
requirement_set = resolver.resolve(
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/resolver.py", line 95, in resolve
result = self._result = resolver.resolve(
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_vendor/resolvelib/resolvers.py", line 546, in resolve
state = resolution.resolve(requirements, max_rounds=max_rounds)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_vendor/resolvelib/resolvers.py", line 397, in resolve
self._add_to_criteria(self.state.criteria, r, parent=None)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_vendor/resolvelib/resolvers.py", line 173, in _add_to_criteria
if not criterion.candidates:
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_vendor/resolvelib/structs.py", line 156, in __bool__
return bool(self._sequence)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/found_candidates.py", line 174, in __bool__
return any(self)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/found_candidates.py", line 162, in <genexpr>
return (c for c in iterator if id(c) not in self._incompatible_ids)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/found_candidates.py", line 53, in _iter_built
candidate = func()
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/factory.py", line 187, in _make_candidate_from_link
base: Optional = self._make_base_candidate_from_link(
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/factory.py", line 233, in _make_base_candidate_from_link
self._link_candidate_cache = LinkCandidate(
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/candidates.py", line 304, in __init__
super().__init__(
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/candidates.py", line 159, in __init__
self.dist = self._prepare()
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/candidates.py", line 236, in _prepare
dist = self._prepare_distribution()
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/candidates.py", line 315, in _prepare_distribution
return preparer.prepare_linked_requirement(self._ireq, parallel_builds=True)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/operations/prepare.py", line 527, in prepare_linked_requirement
return self._prepare_linked_requirement(req, parallel_builds)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/operations/prepare.py", line 598, in _prepare_linked_requirement
local_file = unpack_url(
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/operations/prepare.py", line 170, in unpack_url
file = get_http_url(
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/operations/prepare.py", line 111, in get_http_url
from_path, content_type = download(link, temp_dir.path)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/network/download.py", line 148, in __call__
for chunk in chunks:
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/cli/progress_bars.py", line 55, in _rich_progress_bar
for chunk in iterable:
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_internal/network/utils.py", line 65, in response_chunks
for chunk in response.raw.stream(
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_vendor/urllib3/response.py", line 622, in stream
data = self.read(amt=amt, decode_content=decode_content)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_vendor/urllib3/response.py", line 587, in read
raise IncompleteRead(self._fp_bytes_read, self.length_remaining)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/contextlib.py", line 131, in __exit__
self.gen.throw(type, value, traceback)
File "/home/user/anaconda3/envs/pt21_c/lib/python3.8/site-packages/pip/_vendor/urllib3/response.py", line 455, in _error_catcher
raise ProtocolError("Connection broken: %r" % e, e)
pip._vendor.urllib3.exceptions.ProtocolError: ("Connection broken: ConnectionResetError(104, 'Connection reset by peer')", ConnectionResetError(104, 'Connection reset by peer'))
网络不好的意思 Anaconda中如何配置国内镜像源安装外部库(含conda永久配置和pip临时配置方法)_conda中科大镜像源-CSDN博客
Linux安装anaconda,换镜像,创建虚拟环境_linux anaconda镜像-CSDN博客
linux 添加清华镜像并安装 pytorch_清华镜像 pytorch-CSDN博客
添加清华镜像-CSDN博客
Linux/Windows下 Anaconda 添加、删除清华/中科大镜像源_linux 删除镜像源-CSDN博客
https://blog.csdn.net/qq_51465572/article/details/142374467
Windows 和 Linux 给 python pip 设置永久清华镜像源_python windous清华源-CSDN博客
⭐️pip使用清华镜像源安装_pip清华源-CSDN博客
pip和conda 添加国内清华镜像 让他下的更快_pip 和 conda 网络毗连速度慢,可以尝试使用镜像,-CSDN博客
GPU版PyTorch安装、GPU版TensorFlow安装(详细教程)_安装pytorch和tensorflow-CSDN博客
(2)TensorFlow安装成功
非常钟安装Tensorflow-gpu2.6.0+本机CUDA12 以及numpy+matplotlib各包版本和谐题目_tensorflow cuda12-CSDN博客
非常钟安装Tensorflow-gpu2.6.0+本机CUDA12 以及numpy+matplotlib各包版本和谐题目,按照自己的来:_tensorflow cuda 12-CSDN博客
【win11 cuda12.0安装tensorflow-gpu】_tensorflow cuda12-CSDN博客
TensorFlow GPU 2.10+CUDA+cuDNN全环境设置指南及安装教程(已避坑)_tensorflow2.10-CSDN博客 TensorFlow-GPU 2.7.0安装教程及PyCharm接入指南(实用于弟子党,详细教程,Windows 10,Anaconda3,Python 3.9)-物联沃-IOTWORD物联网
#安装成功:十分钟安装Tensorflow-gpu2.6.0+本机CUDA12 以及numpy+matplotlib各包版本协调问题
conda env list
conda create -n tf26_c python==3.9
conda activate tf26_c
conda install cudatoolkit=11.2.0
conda install cudnn=8.1.0.77
pip install tensorflow-gpu==2.6.0 protobuf==3.20.0 numpy==1.19.5 matplotlib==3.3.4
测试:
python
import tensorflow as tf
gpu_devices = tf.config.list_physical_devices('GPU')
if gpu_devices:
print("可用的 GPU 设备:", gpu_devices)
else:
print("未检测到可用的 GPU 设备。")
exit()
整合如下:
if tf.test.is_gpu_available():
gpus = tf.config.list_physical_devices('GPU')
num_gpus = len(gpus)
print(f"检测到 {num_gpus} 个可用的 GPU 设备。")
for i, gpu in enumerate(gpus):
gpu_name = gpu.name
print(f"GPU {i}: {gpu_name}")
else:
print("未检测到可用的 GPU 设备,当前使用 CPU 进行计算。")
记录两个安装失败的环境:
#TensorFlow-GPU 2.7.0
# 安装失败1:【win11 cuda12.0安装tensorflow-gpu】
conda create -n tf27_c python==3.8
conda activate tf27_c
pip install tensorflow-gpu==2.7.0 protobuf==3.19.0
conda deactivate
conda remove -n tf27_c --all
# 安装失败2:
(tf27_c) user@user:~$ conda list
# packages in environment at /home/user/anaconda3/envs/tf27_c:
#
# Name Version BuildChannel
_libgcc_mutex 0.1 conda_forge http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
_openmp_mutex 4.5 2_gnu http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
absl-py 2.2.2 pypi_0 pypi
astunparse 1.6.3 pypi_0 pypi
c-ares 1.19.1 h5eee18b_0 defaults
ca-certificates 2025.2.25 h06a4308_0 defaults
cachetools 5.5.2 pypi_0 pypi
certifi 2025.1.31 pypi_0 pypi
charset-normalizer 3.4.1 pypi_0 pypi
cudatoolkit 11.2.0 h73cb219_9 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
cudnn 8.1.0.77 h90431f1_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
curl 7.88.1 hdc1c0ab_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
flatbuffers 2.0.7 pypi_0 pypi
gast 0.4.0 pypi_0 pypi
google-auth 2.38.0 pypi_0 pypi
google-auth-oauthlib 1.0.0 pypi_0 pypi
google-pasta 0.2.0 pypi_0 pypi
graalpy 22.3.0 0_graalvm_native http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
grpcio 1.70.0 pypi_0 pypi
h5py 3.11.0 pypi_0 pypi
idna 3.10 pypi_0 pypi
importlib-metadata 8.5.0 pypi_0 pypi
keras 2.7.0 pypi_0 pypi
keras-preprocessing 1.1.2 pypi_0 pypi
krb5 1.20.1 h143b758_1 defaults
ld_impl_linux-64 2.43 h712a8e2_4 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libclang 18.1.1 pypi_0 pypi
libcurl 7.88.1 hdc1c0ab_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libedit 3.1.20230828 h5eee18b_0 defaults
libev 4.33 h7f8727e_1 defaults
libffi 3.2.1 1 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
libgcc 14.2.0 h767d61c_2 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libgcc-ng 14.2.0 h69a702a_2 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libgomp 14.2.0 h767d61c_2 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
liblzma 5.6.4 hb9d3cd8_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
liblzma-devel 5.6.4 hb9d3cd8_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libnghttp2 1.52.0 h61bc06f_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libssh2 1.10.0 hdbd6064_3 defaults
libstdcxx 14.2.0 h8f9b012_2 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libstdcxx-ng 14.2.0 h4852527_2 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libzlib 1.3.1 hb9d3cd8_2 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
markdown 3.7 pypi_0 pypi
markupsafe 2.1.5 pypi_0 pypi
ncurses 6.5 h2d0b736_3 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
numpy 1.24.4 pypi_0 pypi
oauthlib 3.2.2 pypi_0 pypi
openssl 3.0.16 h5eee18b_0 defaults
opt-einsum 3.4.0 pypi_0 pypi
patch 2.7.6 h7b6447c_1001 defaults
pip 24.3.1 pyh8b19718_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
protobuf 3.19.0 pypi_0 pypi
pyasn1 0.6.1 pypi_0 pypi
pyasn1-modules 0.4.2 pypi_0 pypi
python 3.8.5 0_native223_graalpy http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
python_abi 3.8 4_graalpy223_38_native http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
readline 8.2 h8c095d6_2 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
requests 2.32.3 pypi_0 pypi
requests-oauthlib 2.0.0 pypi_0 pypi
rsa 4.9 pypi_0 pypi
setuptools 75.3.0 pyhd8ed1ab_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
six 1.17.0 pypi_0 pypi
sqlite 3.31.1 h7b6447c_0 defaults
tensorboard 2.14.0 pypi_0 pypi
tensorboard-data-server 0.7.2 pypi_0 pypi
tensorflow-estimator 2.7.0 pypi_0 pypi
tensorflow-gpu 2.7.0 pypi_0 pypi
tensorflow-io-gcs-filesystem 0.34.0 pypi_0 pypi
termcolor 2.4.0 pypi_0 pypi
tk 8.6.7 hc745277_3 defaults
typing-extensions 4.13.1 pypi_0 pypi
urllib3 2.2.3 pypi_0 pypi
werkzeug 3.0.6 pypi_0 pypi
wheel 0.45.1 pyhd8ed1ab_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
wrapt 1.17.2 pypi_0 pypi
xz 5.6.4 hbcc6ac9_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
xz-gpl-tools 5.6.4 hbcc6ac9_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
xz-tools 5.6.4 hb9d3cd8_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
zipp 3.20.2 pypi_0 pypi
zlib 1.3.1 hb9d3cd8_2 http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
(tf27_c) user@user:~$ python
Python 3.8.5 (Fri Jan 13 20:30:28 CST 2023)
on linux
Type "help", "copyright", "credits" or "license" for more information.
>>>
#TensorFlow-GPU 2.10.0
conda install cudnn=8.2.1
conda install cudatoolkit=11.3.1
pip install tensorflow-gpu==2.10.0
(tf210_c) user@user:~$ conda list
# packages in environment at /home/user/anaconda3/envs/tf210_c:
#
# Name Version BuildChannel
_libgcc_mutex 0.1 conda_forge https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
_openmp_mutex 4.5 2_gnu https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
absl-py 2.2.2 pypi_0 pypi
astunparse 1.6.3 pypi_0 pypi
bzip2 1.0.8 h4bc722e_7 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
ca-certificates 2025.1.31 hbcca054_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
cachetools 5.5.2 pypi_0 pypi
certifi 2025.1.31 pypi_0 pypi
charset-normalizer 3.4.1 pypi_0 pypi
cudatoolkit 11.3.1 hb98b00a_13 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
cudnn 8.2.1.32 h86fa8c9_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
flatbuffers 25.2.10 pypi_0 pypi
gast 0.4.0 pypi_0 pypi
google-auth 2.38.0 pypi_0 pypi
google-auth-oauthlib 0.4.6 pypi_0 pypi
google-pasta 0.2.0 pypi_0 pypi
grpcio 1.71.0 pypi_0 pypi
h5py 3.13.0 pypi_0 pypi
idna 3.10 pypi_0 pypi
importlib-metadata 8.6.1 pypi_0 pypi
keras 2.10.0 pypi_0 pypi
keras-preprocessing 1.1.2 pypi_0 pypi
ld_impl_linux-64 2.43 h712a8e2_4 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libclang 18.1.1 pypi_0 pypi
libffi 3.4.6 h2dba641_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libgcc 14.2.0 h767d61c_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libgcc-ng 14.2.0 h69a702a_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libgomp 14.2.0 h767d61c_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
liblzma 5.8.1 hb9d3cd8_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
liblzma-devel 5.8.1 hb9d3cd8_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libnsl 2.0.1 hd590300_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libsqlite 3.49.1 hee588c1_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libstdcxx 14.2.0 h8f9b012_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libstdcxx-ng 14.2.0 h4852527_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libuuid 2.38.1 h0b41bf4_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libxcrypt 4.4.36 hd590300_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
libzlib 1.3.1 hb9d3cd8_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
markdown 3.7 pypi_0 pypi
markupsafe 3.0.2 pypi_0 pypi
ncurses 6.5 h2d0b736_3 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
numpy 1.22.0 pypi_0 pypi
oauthlib 3.2.2 pypi_0 pypi
openssl 3.4.1 h7b32b05_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
opt-einsum 3.4.0 pypi_0 pypi
packaging 24.2 pypi_0 pypi
pip 25.0.1 pyh8b19718_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
protobuf 3.19.6 pypi_0 pypi
pyasn1 0.6.1 pypi_0 pypi
pyasn1-modules 0.4.2 pypi_0 pypi
python 3.9.21 h9c0c6dc_1_cpython https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
readline 8.2 h8c095d6_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
requests 2.32.3 pypi_0 pypi
requests-oauthlib 2.0.0 pypi_0 pypi
rsa 4.9 pypi_0 pypi
setuptools 78.1.0 pyhff2d567_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
six 1.17.0 pypi_0 pypi
sqlite 3.49.1 h9eae976_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
tensorboard 2.10.1 pypi_0 pypi
tensorboard-data-server 0.6.1 pypi_0 pypi
tensorboard-plugin-wit 1.8.1 pypi_0 pypi
tensorflow-estimator 2.10.0 pypi_0 pypi
tensorflow-gpu 2.10.0 pypi_0 pypi
tensorflow-io-gcs-filesystem 0.37.1 pypi_0 pypi
termcolor 3.0.1 pypi_0 pypi
tk 8.6.13 noxft_h4845f30_101 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
typing-extensions 4.13.1 pypi_0 pypi
tzdata 2025b h78e105d_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
urllib3 2.3.0 pypi_0 pypi
werkzeug 3.1.3 pypi_0 pypi
wheel 0.45.1 pyhd8ed1ab_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
wrapt 1.17.2 pypi_0 pypi
xz 5.8.1 hbcc6ac9_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
xz-gpl-tools 5.8.1 hbcc6ac9_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
xz-tools 5.8.1 hb9d3cd8_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
zipp 3.21.0 pypi_0 pypi
zlib 1.3.1 hb9d3cd8_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
(tf210_c) user@user:~$ python
Python 3.9.21 | packaged by conda-forge | (main, Dec5 2024, 13:51:40)
on linux
Type "help", "copyright", "credits" or "license" for more information.
>>>
免责声明:如果侵犯了您的权益,请联系站长,我们会及时删除侵权内容,谢谢合作!更多信息从访问主页:qidao123.com:ToB企服之家,中国第一个企服评测及商务社交产业平台。
页:
[1]