• 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
    1
    或者

    pip install --user --upgrade --ignore-installed tensorflow
    1
    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
    1
    pip3 install tensorflow #cpu
    1
    pip3 install tensorflow-gpu
    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
    1
    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.
    1
    2
    3
    -----------------------------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
    1
    # 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'>
    >>>
    1
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    8
    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/
    1
    3:然后再输入:

    conda config --set show_channel_urls yes
    1
    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
    1
    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
    1
    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
    1

    8:安装cpu版本的TensorFlow

    pip install --upgrade --ignore-installed tensorflow
    1
    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
    1
    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
    ————————————————
    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

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  • 原文地址:https://www.cnblogs.com/chinasoft/p/16303908.html
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