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

我会带着你远行 2022-11-20 04:54 886阅读 0赞

**TensorFlow报错：**  
python或者anaconda运行时显示：  
![在这里插入图片描述][20201108145945787.png_pic_center]  
**一般的解决方案：**

pip install --upgrade --ignore-installed tensorflow

或者

pip install --user --upgrade --ignore-installed tensorflow

在DOS窗口运行结果如下：  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center]  
输入以下命令也是报错：

pip install --upgrade --ignore-installed tensorflow-gpu

pip3 install tensorflow #cpu

pip3 install tensorflow-gpu

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 1]  
那么------既然找不到TensorFlow的版本，那我们就自行查找，输入：

pip3 search tensorflow

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

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.

\-----------------------------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

# 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'>
    >>>

如下图：Python是3.9 环境是64bit  
![在这里插入图片描述][20201108152658504.png_pic_center]  
版本高于3.6,打开Anaconda查看其Python版本  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 2]  
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/

3：然后再输入：

conda config --set show_channel_urls yes

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

anaconda在这里的意思安装依赖包，所以要下载一会~~~~

![在这里插入图片描述][20201108153607370.png_pic_center]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 3]  
5：询问是否安装:![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 4]6：输入

>> y

然后开始出现下图的趋势：![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 5]  
\-----done-------![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 6]  
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：  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 7]  
7：在Anaconda的启动TensorFlow：

activate tensorflow

![在这里插入图片描述][20201108161228464.png_pic_center]  
8：安装cpu版本的TensorFlow

pip install --upgrade --ignore-installed tensorflow

响应结果如下图：

![在这里插入图片描述][2020110816172067.png_pic_center]

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

>> deactivate

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

[20201108145945787.png_pic_center]: /images/20221120/29989b227930404086ea302461d08c3d.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center]: /images/20221120/6c757d370b1a477eae7e9b3085896239.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 1]: /images/20221120/bbfffee55cd64652983e8f15ca6944dd.png
[20201108152658504.png_pic_center]: /images/20221120/7fc614285bbc401eaca156a05b46f373.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 2]: /images/20221120/61c1790e4b044da193eeabb1855ca20d.png
[20201108153607370.png_pic_center]: /images/20221120/862ee4a9b32b40ef9dd7d4d5158122e0.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 3]: /images/20221120/898f4a08a9e649918cc8859c33407b93.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 4]: /images/20221120/5d7dcd20d34942b2a0d5ac47f50229b5.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 5]: https://img-blog.csdnimg.cn/20201108154645398.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg==,size_16,color_FFFFFF,t_70#pic_center
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 6]: https://img-blog.csdnimg.cn/2020110815481277.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg==,size_16,color_FFFFFF,t_70#pic_center
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg_size_16_color_FFFFFF_t_70_pic_center 7]: https://img-blog.csdnimg.cn/20201108161107627.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2d1YW5nd3Vsdg==,size_16,color_FFFFFF,t_70#pic_center
[20201108161228464.png_pic_center]: https://img-blog.csdnimg.cn/20201108161228464.png#pic_center
[2020110816172067.png_pic_center]: https://img-blog.csdnimg.cn/2020110816172067.png#pic_center