1、安装
Anaconda指的是一个开源的Python发行版本，其包含了conda、Python等180多个科学包及其依赖项。 [1] 因为包含了大量的科学包，Anaconda 的下载文件比较大（约 531 MB），如果只需要某些包，或者需要节省带宽或存储空间，也可以使用Miniconda这个较小的发行版（仅包含conda和 Python）。
https://www.jianshu.com/p/62f155eb6ac5
conda结合了pip和virtualenv的功能。
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2、参考文章
https://blog.csdn.net/cliukai/article/details/102051891
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3、创建环境
conda create -n TF_2C python=3.8
conda activate TF_2C
(TF_2C) C:\WINDOWS\system32>
conda activate TF_2C
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4、安装tf
pip install tensorflow==2.0.0 -i https://pypi.tuna.tsinghua.edu.cn/simple
报错了
pip install tensorflow==2.3.0 -i https://pypi.tuna.tsinghua.edu.cn/simple
切到2.3.0的版本
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Collecting tensorflow==2.3.0
Downloading https://pypi.tuna.tsinghua.edu.cn/packages/16/aa/3b0e0751a3bff298133941b54aad366230862c827b701f13d51e52bcc5ee/tensorflow-2.3.0-cp38-cp38-win_amd64.whl (342.5 MB)
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Collecting grpcio>=1.8.6
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Collecting six>=1.12.0
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Collecting astunparse==1.6.3
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Collecting termcolor>=1.1.0
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Collecting scipy==1.4.1
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Collecting absl-py>=0.7.0
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Requirement already satisfied: wheel>=0.26 in d:\programdata\anaconda3\envs\tf_2c\lib\site-packages (from tensorflow==2.3.0) (0.34.2)
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Collecting gast==0.3.3
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Collecting wrapt>=1.11.1
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Collecting google-auth-oauthlib<0.5,>=0.4.1
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Collecting markdown>=2.6.8
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Collecting werkzeug>=0.11.15
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Collecting tensorboard-plugin-wit>=1.6.0
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Collecting requests-oauthlib>=0.7.0
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Collecting chardet<4,>=3.0.2
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Collecting pyasn1-modules>=0.2.1
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Collecting rsa<5,>=3.1.4; python_version >= "3.5"
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Collecting cachetools<5.0,>=2.0.0
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Collecting oauthlib>=3.0.0
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Collecting pyasn1<0.5.0,>=0.4.6
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Building wheels for collected packages: termcolor, absl-py, wrapt
Building wheel for termcolor (setup.py) ... done
Created wheel for termcolor: filename=termcolor-1.1.0-py3-none-any.whl size=4835 sha256=7250f5ef320841f23b0bacbab0397bd0e228e9f195579f90f1ee1e4e16b51825
Stored in directory: c:\users\lemon\appdata\local\pip\cache\wheels\e3\de\40\cc69e66c496ef6bfe23010d31ca5584a6d58ab4cf2f5b5a187
Building wheel for absl-py (setup.py) ... done
Created wheel for absl-py: filename=absl_py-0.9.0-py3-none-any.whl size=121935 sha256=d658b2787203f64c8d9733560ecb157350c08f4cb570f489038f9a7b08c09a69
Stored in directory: c:\users\lemon\appdata\local\pip\cache\wheels\17\04\32\c00a5b5955b03178eb17879bb9dd937a13389eb8bec32d28ad
Building wheel for wrapt (setup.py) ... done
Created wheel for wrapt: filename=wrapt-1.12.1-cp38-cp38-win_amd64.whl size=33696 sha256=af9e69508cd702a9e7b7d1eb0fe6894766c7cb4dfff46f22b8d9988286355a2f
Stored in directory: c:\users\lemon\appdata\local\pip\cache\wheels\9b\c8\62\9d6aad874ab4f2600bf95167be834ab8abfdb1d73e3051c8c6
Successfully built termcolor absl-py wrapt
Installing collected packages: six, grpcio, protobuf, numpy, h5py, astunparse, google-pasta, pyasn1, pyasn1-modules, rsa, cachetools, google-auth, oauthlib, idna, chardet, urllib3, requests, requests-oauthlib, google-auth-oauthlib, markdown, werkzeug, tensorboard-plugin-wit, absl-py, tensorboard, termcolor, tensorflow-estimator, keras-preprocessing, scipy, gast, opt-einsum, wrapt, tensorflow
下载到了相当多的包
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5、测试安装
import tensorflow as tf
version = tf.__version__
gpu_ok = tf.test.is_gpu_available()
print("tf version:",version,"\nif use GPU",gpu_ok)
GPU那块估计还是需要启动的，这块稍后再看；
这个内存消耗啊，几百兆内存瞬间就出去了；
(TF_2C) D:\development\tf_demo>python test.py
2020-08-06 13:44:23.845676: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
2020-08-06 13:44:23.845876: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
WARNING:tensorflow:From test.py:3: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.config.list_physical_devices('GPU')` instead.
2020-08-06 13:46:09.966865: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2020-08-06 13:46:09.976087: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x2636c5b3b80 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-08-06 13:46:09.976202: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2020-08-06 13:46:09.977678: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library nvcuda.dll
2020-08-06 13:46:10.009138: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2070 with Max-Q Design computeCapability: 7.5
coreClock: 1.185GHz coreCount: 36 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 357.69GiB/s
2020-08-06 13:46:10.012615: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
2020-08-06 13:46:10.015965: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cublas64_10.dll'; dlerror: cublas64_10.dll not found
2020-08-06 13:46:10.019218: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cufft64_10.dll'; dlerror: cufft64_10.dll not found
2020-08-06 13:46:10.022966: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'curand64_10.dll'; dlerror: curand64_10.dll not found
2020-08-06 13:46:10.026259: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cusolver64_10.dll'; dlerror: cusolver64_10.dll not found
2020-08-06 13:46:10.029529: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cusparse64_10.dll'; dlerror: cusparse64_10.dll not found
2020-08-06 13:46:10.032883: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cudnn64_7.dll'; dlerror: cudnn64_7.dll not found
2020-08-06 13:46:10.032974: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1753] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2020-08-06 13:46:10.123444: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-08-06 13:46:10.123542: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263] 0
2020-08-06 13:46:10.123846: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 0: N
2020-08-06 13:46:10.126417: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x2636c5b4900 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2020-08-06 13:46:10.126500: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): GeForce RTX 2070 with Max-Q Design, Compute Capability 7.5
tf version: 2.3.0
if use GPU False
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