python运行时：ModuleNotFoundError: No module named ‘tensorflow‘

https://blog.csdn.net/guangwulv/article/details/109559583

 

TensorFlow报错：
python或者anaconda运行时显示：

一般的解决方案：

pip install --upgrade --ignore-installed tensorflow
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或者

pip install --user --upgrade --ignore-installed tensorflow
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在DOS窗口运行结果如下：

输入以下命令也是报错：

pip install --upgrade --ignore-installed tensorflow-gpu
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pip3 install tensorflow #cpu
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pip3 install tensorflow-gpu
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那么------既然找不到TensorFlow的版本，那我们就自行查找，输入：

pip3 search tensorflow
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会出现一大堆的信息

tensorflow (2.3.1) - TensorFlow is an open source machine learning framework for
everyone.
tensorflow-qndex (0.0.22) - tensorflow-qnd x tensorflow-extenteten
tensorflow-plot (0.3.2) - TensorFlow Plot
tensorflow-addons (0.11.2) - TensorFlow Addons.
tensorflow-estimator (2.3.0) - TensorFlow Estimator.
tensorflow-ops (0.0.0) - tensorflow-ops
mesh-tensorflow (0.1.17) - Mesh TensorFlow
tensorflow-io (0.16.0) - TensorFlow IO
tensorflow-recommenders (0.2.0) - Tensorflow Recommenders, a TensorFlow library for recommender
systems.
tensorflow-datasets (4.1.0) - tensorflow/datasets is a library of datasets ready to use with
TensorFlow.
tensorflow-scientific (0.2.0.dev0) - Scientific modeling in TensorFlow
tensorflow-k8s (0.0.2) - Tensorflow serving extension
emloop-tensorflow (0.6.0) - TensorFlow extension for emloop.
axion-tensorflow (0.0.5) - axion for TensorFlow >=2.2.
daltons-tensorflow (0.0.17) - Daltons Tensorflow bindings
tensorflow-extenteten (0.0.22) - TensorFlow extention library
Tensorflow-ChatBots (0.0.12) - ChatBots supporting TensorFlow
cxflow-tensorflow (0.5.0) - TensorFlow extension for cxflow.
tensorflow-compression (1.3) - Data compression in TensorFlow
syft-tensorflow (0.1.0) - TensorFlow Bindings for PySyft
tensorflow-coder (0.0.2) - TensorFlow Coder (TF-Coder): A Program Synthesis Tool for
TensorFlow
dask-tensorflow (0.0.2) - Interactions between Dask and Tensorflow
tensorflow-tracer (1.1.0) - Runtime Tracing Library for TensorFlow
tensorflow-radam (0.15.0) - RAdam implemented in Keras & TensorFlow
redhat-tensorflow (0.0.0) - A build of TensorFlow by Red Hat
aicoe-tensorflow (0.0.0) - A build of TensorFlow by Red Hat
gmlsnets-tensorflow (0.1) - GMLS-Nets Tensorflow implementation
tensorflow-transform (0.25.0) - A library for data preprocessing with TensorFlow
rh-tensorflow (0.0.0) - A build of TensorFlow by Red Hat
sagemaker-tensorflow (2.3.0.1.0.0) - Amazon Sagemaker specific TensorFlow extensions.
tensorflow-manopt (0.1.0) - A library for manifold-constrained optimization in TensorFlow
tensorflow-qnd (0.1.11) - Quick and Dirty TensorFlow command framework
tensorflow-probability (0.11.1) - Probabilistic modeling and statistical inference in TensorFlow
tensorflow-determinism (0.3.0) - Tracking, debugging, and patching non-determinism in TensorFlow
tensorflow-model (0.1.1) - Command-line tool to inspect TensorFlow models
tensorflow-utils (0.1.0) - Classes and methods to make using TensorFlow easier
tensorflow-ranking (0.3.2) - Pip package setup file for TensorFlow Ranking.
tensorflow-cpu-estimator (1.15.1) - TensorFlow Estimator.
tensorflow-io-nightly (0.17.0.dev20201108041428) - TensorFlow IO
tensorflow-gpu-estimator (2.3.0) - TensorFlow Estimator.
tensorflow-lattice-gpu (0.9.8) - TensorFlow Lattice provides lattice models in TensorFlow
tensorflow-directml (1.15.3.dev200911) - TensorFlow is an open source machine learning framework for
everyone.
tensorflow-aarch64 (1.2) - Tensorflow r1.2 for aarch64[arm64,pine64] CPU only.
tensorflow-gan (2.0.0) - TF-GAN: A Generative Adversarial Networks library for TensorFlow.
tensorflow-tflex (1.13.1rc3) - TensorFlow is an open source machine learning framework for
everyone.
tensorflow-fedora28 (1.9.0rc0) - TensorFlow is an open source machine learning framework for
everyone.
tensorflow-federated (0.17.0) - TensorFlow Federated is an open-source federated learning
framework.
tensorflow-rl (0.2.2) - tensorflow-rl: Modular Deep Reinforcement Learning Framework.
tensorflow-gpu (2.3.1) - TensorFlow is an open source machine learning framework for
everyone.
intel-tensorflow (2.3.0) - TensorFlow is an open source machine learning framework for
everyone.
tensorflow-font2char2word2sent2doc (0.0.12) - TensorFlow implementation of Hierarchical Attention Networks for
Document Classification
tensorflow-template (0.2) - A tensorflow template for quick starting a deep learning project.
tensorflow-rocm (2.3.2) - TensorFlow is an open source machine learning framework for
everyone.
tensorflow-cpu (2.3.1) - TensorFlow is an open source machine learning framework for
everyone.
essentia-tensorflow (2.1b6.dev236) - Library for audio and music analysis, description and synthesis,
with TensorFlow support
tensorflow-quantum (0.4.0) - TensorFlow Quantum is a library for hybrid quantum-classical
machine learning.
tensorflow-encrypted (0.4.0) - Layer on top of TensorFlow for doing machine learning on
encrypted data.
tensorflow-text (2.3.0) - TF.Text is a TensorFlow library of text related ops, modules, and
subgraphs.
silence-tensorflow (1.1.1) - Simple python package to shut up Tensorflow warnings and logs.
tensorflow-cloud (0.1.9) - The TensorFlow Cloud repository provides APIs that will allow to
easily go from debugging and training your Keras and TensorFlow
code in a local environment to distributed training in the cloud.
tensorflow-fewshot (0.0.3) - A Python package for few shot learning training and inference in
computer vision using Tensorflow.
tensorflow-serving-client (1.0.0) - Python client for tensorflow serving
tensorflow-transform-canary (0.9.0) - A library for data preprocessing with TensorFlow
rav-tensorflow-transform (0.7.0.910) - A library for data preprocessing with TensorFlow
tensorflow-serving-api (2.3.0) - TensorFlow Serving Python API.
tensorflow-model-analysis (0.25.0) - A library for analyzing TensorFlow models
tensorflow-onmttok-ops (0.4.0) - OpenNMT Tokenizer as TensorFlow Operations
tensorflow-play (0.0.1) - The lightweight engineering TensorFlow wrapper for AI engineer.
Write less, Reuse more, Scale easily.
tensorflow-hub (0.10.0) - TensorFlow Hub is a library to foster the publication, discovery,
and consumption of reusable parts of machine learning models.
tensorflow-kernels (0.1.2) - A package with Tensorflow (both CPU and GPU) implementation of
most popular Kernels for kernels methods (SVM, MKL...).
tensorflow-graphics (2020.5.20) - A library that contains well defined, reusable and cleanly
written graphics related ops and utility functions for
TensorFlow.
tensorflow-io-2.0-preview (0.7.0.dev1369) - TensorFlow IO
tensorflow-constrained-optimization (0.2) - A library for performing constrained optimization in TensorFlow
ngraph-tensorflow-bridge (0.18.0) - Intel nGraph compiler and runtime for TensorFlow
tensorflow-technical-indicators (0.1.2) - Technical Indicators as TensorFlow Graph Functions
tensorflow-deploy-utils (1.0.0) - Utils for managing and communication with TensorFlow Deploy
intel-tensorflow-avx512 (2.3.0) - TensorFlow is an open source machine learning framework for
everyone.
tensorflow-federated-nightly (0.17.0.dev20201107) - TensorFlow Federated is an open-source federated learning
framework.
tensorflow-rocm-enhanced (2.3.2) - TensorFlow is an open source machine learning framework for
everyone.
simple-tensorflow-serving (0.8.1.1) - The simpler and easy-to-use serving service for TensorFlow models
Tensorflow-Telegram-Bot (0.0.2) - TensorFlow Telegram Bot which can be used as callback
tensorflow-serving-client-grpc (2.3.0) - A prebuilt tensorflow serving client from the tensorflow serving
proto files
neuraxle-tensorflow (0.1.2) - TensorFlow steps, savers, and utilities for Neuraxle. Neuraxle is
a Machine Learning (ML) library for building neat pipelines,
providing the right abstractions to both ease research,
development, and deployment of your ML applications.
attention-tensorflow-mesh (0.0.2) - A bunch of attention related functions, for constructing
transformers in tensorflow mesh
tensorflow-serving-api-gpu (2.3.0) - TensorFlow Serving Python API.
spark-tensorflow-distributor (0.1.0) - This package helps users do distributed training with TensorFlow
on their Spark clusters.
tensorflow-auto-detect (1.11.0) - Automatically install CPU or GPU tensorflow determined by looking
for a CUDA installation.
tensorflow-gcs-config (2.3.0) - TensorFlow operations for configuring access to GCS (Google
Compute Storage) resources.
sagemaker-tensorflow-training (20.1.4) - Open source library for creating TensorFlow containers to run on
Amazon SageMaker.
tensorflow-object-detection-api (0.1.1) - Tensorflow Object Detection Library Packaged
tensorflow-coder-colab-logging (0.0.2) - Logging utilities for TensorFlow Coder's Colab interface
tensorflow-serving-api-python3 (1.8.0) - *UNOFFICIAL* TensorFlow Serving API libraries for Python3
tensorflow-graphics-gpu (1.0.0) - A library that contains well defined, reusable and cleanly
written graphics related ops and utility functions for
TensorFlow.
yifeif-tensorflow-graphics (2020.6.11) - A library that contains well defined, reusable and cleanly
written graphics related ops and utility functions for
TensorFlow.
tensorflow-exercise-hx (1.0.1) - tensorflow练习：鸢尾花&#31181
;类预测，加州房价
预测
tensorflow-enterprise-addons (0.1.1) - Client-side library suite of TensorFlow Enterprise on Google
CloudPlatform (GCP), which implements specific integration
between GCP andTensorFlow APIs.
tensorflow-consciousness (0.1) - Supports a variety of biological learning algorithms.
mlops-tensorflow (0.1.0) -
tensorflow-privacy (0.5.1) -
resnet-tensorflow (0.0.1) - Deep Residual Neural Network

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查询python 的版本：

>>>C:\Users\pc>python
Python 3.9.0a4 (tags/v3.9.0a4:6e02691, Feb 25 2020, 23:23:54) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
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-----------------------------发现问题----------------------
安装不成功的原因是：
1：电脑是32bit的
2：Python版本高于3.6

查询系统版本：

python -v
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# D:\Python3.9\lib\__pycache__\_sitebuiltins.cpython-39.pyc matches D:\Python3.9\lib\_sitebuiltins.py
# code object from 'D:\\Python3.9\\lib\\__pycache__\\_sitebuiltins.cpython-39.pyc'
import '_sitebuiltins' # <_frozen_importlib_external.SourceFileLoader object at 0x000002885BD175E0>
import 'site' # <_frozen_importlib_external.SourceFileLoader object at 0x000002885BD05280>
Python 3.9.0a4 (tags/v3.9.0a4:6e02691, Feb 25 2020, 23:23:54) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
import 'atexit' # <class '_frozen_importlib.BuiltinImporter'>
>>>
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如下图：Python是3.9 环境是64bit

版本高于3.6,打开Anaconda查看其Python版本

安装TensorFlow方法：
CPU版本的安装

pip install --ignore-installed --upgrade tensorflow

安装步骤：
1：TensorFlow在Windows下，支持Python 3.6版本
2：在DOS窗口中输入：[目的：输入清华仓库镜像，加快更新速度]

conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
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3：然后再输入：

conda config --set show_channel_urls yes
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4：Anaconda3创建一个python3.6的环境，环境名称为tensorflow ，命令如下：

conda create -n tensorflow python=3.6
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anaconda在这里的意思安装依赖包，所以要下载一会~~~~

 

5：询问是否安装:6：输入

>> y
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然后开始出现下图的趋势：
-----done-------
此时的Anaconda已经显示在更新新动态
打开Anaconda>>Environments 就可看到TensorFlow的选项：
表示TensorFlow的环境已经建好：

7：在Anaconda的启动TensorFlow：

activate tensorflow
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8：安装cpu版本的TensorFlow

pip install --upgrade --ignore-installed tensorflow
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响应结果如下图：

 

当不使用TensorFlow时，可以通过deactivate来关闭TensorFlow环境：

>> deactivate
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9:测试cpu版本的TensorFlow:
先启动：activate tensorflow
再进入Python：python

文章知识点与官方知识档案匹配，可进一步学习相关知识
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版权声明：本文为CSDN博主「lenatu」的原创文章，遵循CC 4.0 BY-SA版权协议，转载请附上原文出处链接及本声明。
原文链接：https://blog.csdn.net/guangwulv/article/details/109559583