Pip install tensorflow error

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pip Install Error: don’t could find version that satisfies the requirement tensorflow #39130

hi, I have win10 and I have tried install through cmd tensorflow with:
pip install tensorflow
pip install tensorflow-cpu
pip3 install —upgrade tensorflow

All these pip gave me the same error:

what’s happened? What I need do to fix it?

The text was updated successfully, but these errors were encountered:

I have a possibly related issue: when I use
pip install tensorflow
pip installs the most recent release candidate: https://pypi.org/project/tensorflow/2.2.0rc4/
I’m trying to get the most recent stable version, 2.1.0.

When I try:
pip install tensorflow==2.1.0

I get the error message:

I updated pip to 20.1. Same behavior.
I tried:
pip install tensorflow>=2.0.0
And still got ver 2.2.0rc4

Why is pip installing only the rc’s?

Okay, I think I figured out my issue: I was using Python 3.8 in my environment. I made a new environment using Python 3.7, and the install worked fine.

@an-white,
TensorFlow 2 packages require a pip version >19.0. Could you please upgrade pip using the below command and let us know if it works.

pip install —upgrade pip .

For more information please check this TensorFlow guide. Thanks!

hi, I forgot say that I have python 3.8, this can affect? When I have already upgrade pip, this occurs:

@an-white : I suggest creating a new env with python 3.7 and try installing TF2 there.

Okay, I think I figured out my issue: I was using Python 3.8 in my environment. I made a new environment using Python 3.7, and the install worked fine.

I saw this recommendation on other forums and tried it, but it didn’t work for me.

I’ve tried on 3.7.0 and 3.6.4

Okay, I think I figured out my issue: I was using Python 3.8 in my environment. I made a new environment using Python 3.7, and the install worked fine.

I saw this recommendation on other forums and tried it, but it didn’t work for me.

I’ve tried on 3.7.0 and 3.6.4

As I expected the problem was my fault. but I think is something that can pass unnoticed and explaining it here may help people with a similar setup and issue.

I’m using Python via pyenv-win which is great, but the thing is that I didn’t realize that pyenv install X.Y.Z will install the 32bit version and tensorflow requires 64bit. So, in my case, it was just a matter of installing an actual 64bit version with pyenv install X.Y.Z-amd64

hi, I forgot say that I have python 3.8, this can affect? When I have already upgrade pip, this occurs:

@an-white,
TensorFlow v2.1 is not compatible with Python 3.8. Instead, could you please try installing TF v2.2.0rc4 using the below command

pip install tensorflow==2.2.0rc4

@an-white,
Also, could you please check if you are using the 64 bit version of Python. TensorFlow is tested and supported only on 64-bit systems. Thanks!

Ok, thanks I’m going to check all this recommendation and find if works

Ready thank you so much, the problem was the version that I have of python 32 bit, and already I install the 64 bit version and only need wait for this finish

Now only need wait, any other problem I’ll tell you

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pip install tensorflow could not find a version #37457

System information

• macOS Catalina version 10.15.3
• pip install tensorflow
• GPU model and memory: Intel Iris Plus Graphics 645 1536 MB

The problem
Both pip install tensorflow and pip install tf-nightly lead to the following error messages:

ERROR: Could not find a version that satisfies the requirement tensorflow (from versions: none)

ERROR: No matching distribution found for tensorflow

The text was updated successfully, but these errors were encountered:

Did you try updating your pip version?

As per the documentation TensorFlow 2 packages require a pip version >19.0.

Could you please try the following commands and let us know if it works.
python3 -m pip install —upgrade pip or pip install —upgrade pip and then try

pip install tensorflow

@alexcreature Try updating pip version by:

and the you can again install tensorflow by:

or you can specify version which you want to install.

This seems to be the same as an issue I had previously with both Windows 10 and Ubuntu 18 and Ubuntu 16, no matter the operating system.
The previous issue ( #37205 ) was closed because I proposed a WORK AROUND of downloading the .whl and installing Tensorflow through the downloaded wheel, which worked just fine for me.

Something is broken in the pypi pipeline of installation and needs to be taken care of.

Yes, the issue is that systems use old pip / setuptools by default and these don’t know how to install packages with manylinux2010 tags. That’s why you need to upload pip and setuptools first (and always install in a virtualenv, not globally)

@alexcreature,
Any updates regarding this issue? Thanks!

Yes, the issue is that systems use old pip / setuptools by default and these don’t know how to install packages with manylinux2010 tags. That’s why you need to upload pip and setuptools first (and always install in a virtualenv, not globally)

Okay so here are ALL of the things I have tried in my attempts to simply install tensorflow via pip install:

pip 20.0.2
Python 3.7.6
Win10, globally
Ubuntu 18.04, globally (source built python 3.7.6 and alias setup to avoid breaking apt)
Ubuntu 16.xx, globally, same as above
Win10 pipenv environment (most recent version of pipenv)
Ubuntu 16, 18 pipenv environment (most recent version of pipenv)

I have tried and tested everything I can possibly come up with to make things different but nothing seems to install Tensorflow 2.1 for Python 3.7 for me, in any way shape or form. I have tried pip install tensorflow I have tried pip install tensorflow==2.1 and the absolute only thing I can do is install by downloading the wheel and installing that wheel directly.

Is there something we can do with pip or python source to get this back to working properly? I don’t have ANY issues with any other packages I use across the board, except for Black, but even then sometimes that will install without a hitch and other times I get the same error, though it’s been a long time since I tried and that is not relevant to Tensorflow.

Edit: I cannot find any PEP which shows a breaking change in manylinux tags and pip installs. The most relevant is 571 which states that any pip that is capable of installing manylinux2010 tags will be backwards compatible, and 600 which shows a new naming convention for manylinux tags, but also states that old tags should still work, if I’m reading correctly.
PEP 599 also adds the manylinux2014 tag, however in true python fashion, retains support for manylinux1 and manylinux2010 tags, so this definately should not be the issue, however, I am no source developer and am simply relaying the information I have found.

These are the most relevant PEP’s I have found regarding manylinux wheel tags.

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Tensorflow release 2.2.0 not found via pip install #39265

tldr; pip does not find the new release 2.2.0 published yesterday

System information

• Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Not Applicable
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu Server 20.04
• TensorFlow installed from (source or binary): binary
• TensorFlow version (use command below): Not Applicable
• Python version: 3.8.2
• PIP version: 20.1
• CUDA/cuDNN version: Not Applicable (10.2)
• GPU model and memory: Not Applicable (RTX 2080 Ti)

Describe the current behavior
From the change log and the Github releases I noticed that Tensorflow 2.2.0 was released and that I could upgrade the Tensorflow version currently used in my project (2.2.0rc4). Sadly, pip install failed to install the update as it was unable to find release 2.2.0. (Clearing the cache of pip didn’t help.) The PyPi website also says latest version is the rc4, not the 2.2.0 release.

Describe the expected behavior
Well, I would like to be able to install Tensorflow 2.2.0 over pip .

Standalone code to reproduce the issue
pip install tensorflow==2.2.0

Other info / logs

The text was updated successfully, but these errors were encountered:

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Tensorflow 1.15 doesn’t exists within pip install #34302

Thank you for submitting a TensorFlow documentation issue. Per our GitHub
policy, we only address code/doc bugs, performance issues, feature requests, and
build/installation issues on GitHub.

The TensorFlow docs are open source! To get involved, read the documentation
contributor guide: https://www.tensorflow.org/community/contribute/docs

URL(s) with the issue:

Please provide a link to the documentation entry, for example:
https://www.tensorflow.org/install/pip

Description of issue (what needs changing):

It says tensorflow 1.15 is final version for 1xx versions yet pip install 1.15 returns this

«$ pip3 install tensorflow==1.15
Collecting tensorflow==1.15
Could not find a version that satisfies the requirement tensorflow==1.15 (from versions: 0.12.1, 1.0.0, 1.0.1, 1.1.0rc0, 1.1.0rc1, 1.1.0rc2, 1.1.0, 1.2.0rc0, 1.2.0rc1, 1.2.0rc2, 1.2.0, 1.2.1, 1.3.0rc0, 1.3.0rc1, 1.3.0rc2, 1.3.0, 1.4.0rc0, 1.4.0rc1, 1.4.0, 1.4.1, 1.5.0rc0, 1.5.0rc1, 1.5.0, 1.5.1, 1.6.0rc0, 1.6.0rc1, 1.6.0, 1.7.0rc0, 1.7.0rc1, 1.7.0, 1.7.1, 1.8.0rc0, 1.8.0rc1, 1.8.0, 1.9.0rc0, 1.9.0rc1, 1.9.0rc2, 1.9.0, 1.10.0rc0, 1.10.0rc1, 1.10.0, 1.10.1, 1.11.0rc0, 1.11.0rc1, 1.11.0rc2, 1.11.0, 1.12.0rc0, 1.12.0rc1, 1.12.0rc2, 1.12.0, 1.12.2, 1.12.3, 1.13.0rc0, 1.13.0rc1, 1.13.0rc2, 1.13.1, 1.13.2, 1.14.0rc0, 1.14.0rc1, 1.14.0, 2.0.0a0, 2.0.0b0, 2.0.0b1)
No matching distribution found for tensorflow==1.15
«

It should be corrected I think.

The text was updated successfully, but these errors were encountered:

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Python is known for its versatile syntax and English-like keywords. With thousands of modules, you can do data visualization, data processing and even deploy machine learning models. There are many known machine learning models published which help you, namely, Keras, Sklearn, Tensorflow, and PyTorch. Although, while using Tensorflow, you can encounter a No Module named Tensorflow error while running your first program.

No Module Named Tensorflow Error is a known error that arises when the Python Environment is unable to fetch TensorFlow files in site-packages. There are two main reasons for this error to appear, either you have not installed the TensorFlow external module or you are working on a different python environment that doesn’t have Tensorflow. There are several easy ways to fix this error which are mentioned later in this post. Let’s understand the root cause of the error before jumping on the solution.

When a module is absent from the external site-library of the environment, the Python interpreter throws ModuleNotFoundError No Module Named Tensorflow. This error arises most of the time on low-end devices because TensorFlow requires proper setup of the c++ path and other requirements. Most of the time, this error is solved by using the pip install method. But if you have multiple Python versions installed, then you’ll definitely face this error.

Why do I get No Module Named Tensorflow Error?

There is no other reason for the No Module Named Tensorflow error other than missing module files. The main problem arises when you’re using multiple python versions and their virtual environment. Keep in mind that, Anaconda, PyCharm, Jupyter, and Spyder have their own virtual environment and it’s tricky to install modules in that environment.

Causes of No Module Named Tensorflow Error

There are some known causes of this ModuleNotFoundError. As Python lets you handle these errors easily, you can debug them quickly. Following are the cause of the No Module Tensorflow error –

Module Not Installed

If you haven’t installed TensorFlow yet and tried importing TensorFlow in code, then it’ll throw this error. Modules are managed by ‘pip’ which is a package management system for your python. Most of the time, the users forget to tick Add Python to the PATH option while installing it. This creates problems in managing the modules.

Supporting Module Not Installed

Tensorflow has many other supporting modules like numpy, scipy, jupyter, matplotlib, pillow, and scikit-learn. If any of these modules is absent, then it’ll throw an error. Make sure that these modules exist in your library.

Moreover, there are other supporting TensorFlow modules like, tensorflow-addons, tensorflow.contrib which might be absent from your library leading to this error.

Tip: To check which libraries are installed in your environment, enter pip list on your console.

Working on Different Virtual Environment

Virtual Environment: Method by which you isolate your working Python environment from the globally installed Python. This environment has its own installation directories and doesn’t share the libraries from globally installed Python.

Many of the code editors in Windows come with their own virtual environment. Each of these environments acts independently to global python installation and is started with blank external modules. Many times, you install a module but it’s installed on global python, not the python from your virtual environment. This can lead to ModuleNotFoundError No Module named Tensorflow in the code execution.

Code editors namely, Anaconda, Jupyter, and Spyder have their own virtual environment. If you have a similar case, head over to the corresponding solution for each code editor.

Solutions for No Module Named Tensorflow

Following are the solutions for this error in each code editor and OS –

Windows

In Windows, the path-related issues harras the programmers all the time. As you have limited functionality over the terminal, you’re constantly facing with ModuleNotFoundError error. To install TensorFlow in your Windows, make sure you follow these steps –

1. Uninstall existing python versions to avoid any conflicts.
2. Go to Python.org and install the Python setup. Make sure you install the 64-bit version. Unfortunately, Tensorflow is not supported in 32 bit systems.
3. Open the installer and select the “Add Python x.x to your PATH” option. This will ensure, that python executes from the path.
4. After installing, open the command terminal or PowerShell and enter the command pip install tensorflow in it.
5. Wait for it to finish the installation and run your python file by command python file.py

Linux

In Linux, it’s relatively easier to install TensorFlow. First of all, check if you are working on a virtual environment by a command which python. This command will return the path of python which you’re going to execute. If you are in a virtual environment, either leave the environment directory or enter the command deactivate to deactivate the virtual environment.

Note: Please do not try to uninstall python in Linux as it’ll interfere with your GDM (Graphical Display Manager). Instead, install a new version and then create your own virtual environment.

Follow these steps to install Tensorflow in Linux –

sudo pip3 install tensorflow

Mac

In Mac, No Module named Tensorflow is a persistent error because of environment errors. If you are working on your virtual environment, you need to deactivate and activate it again. Then use the pip list command to check if the TensorFlow module exists in your library. If not, then use the pip3 install tensorflow to install TensorFlow.

Anaconda

If you’re using Anaconda and you face no module named Tensorflow error, then you probably haven’t installed TensorFlow in the conda environment. As anaconda has a different environment than your default python environment, you need to install TensorFlow in it. To do it follow these steps –

1. Open Anaconda Prompt on your computer.
2. Enter the command conda install tensorflow in it.
3. Wait for the installation to complete and restart the conda shell and run your program.

Jupyter

If you’ve installed Juptyter Notebook from Anaconda, it’ll use a conda environment. By default, the libraries in this environment need to be installed via command. To do the same, open your Conda Prompt and enter the command conda install tensorflow. This will ensure that your Juptyer Notebook has TensorFlow in it.

If your Jupyter is not installed via Anaconda, then use the pip install tensorflow to install the TensorFlow module. This will resolve the error ModuleNotFoundError No module named Tensorflow instantly.

Spyder

Spyder is installed via Anaconda which operates an Anaconda environment. Simply use the command conda install tensorflow in your Anaconda Prompt to install TensorFlow.

PyCharm

PyCharm is a special application that operates in its own virtual environment. Due to the unavailability of the TensorFlow error, you can face the no module found error. Follow these steps to install TensorFlow –

1. Press Settings and select the Project Interpreter tab under projects.
2. Now enter Tensorflow in the box and install it.
3. After installing the package, your error will be resolved.

Supporting ModuleNotFoundError for Tensorflow

Tensorflow has many addons which come in handy to avoid writing long code. These addons and contributions are added separately in other packages and combine with the original TensorFlow module. Following are the examples of ModuleNotFoundError –

No module named ‘tensorflow.contrib’

Unfortunately, the contrib module in TensorFlow is not included in version 2.0. If you still want to use the contrib module, you’ll have to install the previous version of TensorFlow. Follow these steps –

pip uninstall tensorflow
pip install tensorflow==1.13.2

No module named ‘tensorflow_addons’

Use pip install tensorflow-addons to install the addons for TensorFlow.

No Module Named Tensorflow Still Not Resolved?

If you’ve tried all the methods and were still not able to solve the issue then, there might be some hardware limitations. Tensorflow requires Python 3.5-3.7, 64-bit system, and pip>=19.0. If you’re unable to fulfill these hardware + software requirements, then don’t worry, we still have a solution for you!

Google released a free product named ‘Colab‘ in 2018. Colab allows you to run and test machine learning models online. To explain more, it’s a replica of the jupyter notebook with all modules installed. To use Tensorflow in Google Colab follow these steps –

1. Sign in to your Google account.
2. Open Colab in your browser.
3. Create a new Jupyter Notebook. (This notebook will be saved in your google drive).
4. Type your code and run it.

Colab has many libraries like TensorFlow, numpy, pandas, etc pre-installed in its shell. Make sure you make good use of it.

Tip: Do not use Colab to store/process peer-to-peer files. This may result in a ban!

See Also

Conclusion

Tensor flow has a flexible architecture. The easy deployment of the code makes it special in nature. However, we have to be very careful before using it. Any small syntax error can result in incorrect importing of the library.

Tensorflow – это платформа для искусственного интеллекта с открытым исходным кодом, которая включает обширные библиотеки и ресурсы сообщества, которые позволяют исследователям продвигать новейшие достижения в машинном обучении и инженерам. эффективно создавать и встраивать приложения, управляемые с помощью машинного обучения, в микроконтроллеры и микропроцессоры. Компьютерные фанаты могут легко установить Python и PyCharm в свои системы, но при попытке установить Tensorflow они сталкиваются с сообщением об ошибке: «Не удалось найти версию, удовлетворяющую требованию TensorFlow (из версий:) Нет соответствия Распределение найдено для TensorFlow ». Многие люди установили Flask, чтобы избавиться от этой проблемы, но, следовательно, они не могут этого сделать. Помня об этом, я собрал несколько возможных решений этой проблемы и следую этому руководству, чтобы избавиться от этой ошибки.

Как оказалось, есть несколько разных причин, которые могут в конечном итоге вызвать эту проблему, поэтому давайте перейдем шаг вперед и протестируйте некоторые исправления, пока мы не сможем устранить этот сбой в Windows.

Метод 1: проверка Python Версия в вашей системе

Если вы используете Windows 10 с версией Python 3.6.X в вашей системе, то, скорее всего, 32-битная версия Python могла бы работать на 64-битной машине. Имейте в виду, что TensorFlow совместим только с 64-битной установкой python, а не с 32-битной версией python. Если вы загрузили Python с python.org , установка по умолчанию будет 32-битной, поэтому, чтобы избавиться от этой проблемы, скачайте 64-битный установщик отсюда. Теперь нам нужно установить переменную среды PATH , потому что в ней перечислены каталоги, в которых будет производиться поиск исполняемых файлов при вводе команды в командной строке. Добавив путь к исполняемому файлу Python, вы сможете получить доступ к python.exe , набрав ключевое слово python (вам не нужно указывать полный путь к программе). Если переменная PATH не установлена, возникает следующая ошибка:

 C: > python'python 'не распознается как внутренняя или внешняя команда, работающая программа или командный файл. 

Как видите, команда не была найдена, следовательно, для запуска python.exe , вам необходимо указать полный путь к исполняемому файлу, следовательно, указать полный путь к переменной, выполните шаги, указанные ниже:

1. Щелкните правой кнопкой мыши на “Мой компьютер”, а затем нажмите кнопку Свойства .
2. Вкл. В левой части окна найдите Расширенные настройки системы, и после нажатия на него вы увидите, что откроется окно Свойства системы .
3. Теперь найдите параметр переменной PATH и нажмите Изменить.. Поместите курсор в конец строки Variable value и добавьте путь к файлу python.exe, которому предшествует точка с запятой (;). В моем случае я добавил следующее значение: C: Python36, потому что я хочу запустить версию Python 3.6.
4. Закройте все окна и найдите командную строку. В командном окне введите следующую команду и нажмите Enter. Вы увидите, что теперь в вашей системе присутствует 64-битная версия, и теперь я попытаюсь установить TensorFlow и проверить, сохраняется ли ошибка:

    C: > python --versionPython 3.7.6  (по умолчанию, 8 января 2020 г., 20:23:39) [MSC v.1916, 64 бит (AMD64)] 

5. Выполните следующую команду, чтобы установить TensorFlow в вашей системе и, надеюсь, сейчас установка будет продолжена без сообщений об ошибках. Примечание: TensorFlow еще не находится в репозитории PyPI, поэтому вам необходимо указать URL-адрес соответствующего «файла колеса» для вашей операционной системы и версии Python.

    pip install -  -обновите https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.12.0-py3-none-any.whl

   

Метод 2: Понизьте версию Python на Anaconda

Tensorflow поддерживает только Python 3.6.x и только 64-битную версию. Следовательно, если вы используете графический интерфейс, такой как anaconda, и python 3.7 установлен на нем по умолчанию, следовательно, мы должны понизить его до 3.6, чтобы установить Tensorflow. Для выполнения этой задачи выполните указанные ниже команды в командной строке Anaconda:

 conda install python = 3.6.4 

После выполнения этой команды подождите пару секунд и затем создайте виртуальную среду для установки Tensorflow. Назовите виртуальную среду, например, «ab», а затем установите текущую версию TensorFlow только для ЦП:

 conda create -n ab tensorflowconda activate tf 

После понижения версии Версия python, Tensorflow теперь будет установлен без каких-либо ошибок, и даже если вы установили настольную версию Ubuntu, он будет работать и для этого.

Метод 3: Обновить установщик пакетов для Python

Pip – это установщик пакетов для Python, и мы можем использовать pip для установки пакетов из индекса пакетов Python и других индексов. Хотя обновления выпускаются регулярно через три месяца, и эти пакеты необходимо обновить вручную в вашей системе, выполнив определенные команды. Если они не устарели, они могут вызвать эту ошибку установки Tensorflow, поэтому мы обновим пакет pip, выполнив следующие команды ниже, чтобы все пакеты обновились автоматически:

 pip install --upgrade pippip  install --upgrade https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.12.0-py3-none-any.whl

После обновления пакетов pip, надеюсь, ваш установка пройдет гладко, и теперь вы сможете разрабатывать интересные программные проекты с помощью Tensorflow..

Обход проблемы. Возможно, не существует версии TensorFlow, совместимой с вашей версией Python. Это особенно верно, если вы используете новую версию Python. Например, может быть задержка между выпуском новой версии Python и выпуском TensorFlow для этой версии Python. В этом случае я считаю, что упомянутые выше параметры, такие как переход на предыдущую версию Python, компиляцию TensorFlow из исходного кода и ожидание выпуска соответствующей версии TensorFlow, являются всеми возможными средствами, которые могут позволить вам установить Tensorflow на ваша система без сбоев.