fake_tf | 模仿Tensorflow的API，自己实现自动求导、训练等功能

by SnowWalkerJ Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | fake_tf Summary

fake_tf is a Python library. fake_tf has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

模仿Tensorflow的API，自己实现自动求导、训练等功能

Support

Quality

Security

License

Reuse

Support

fake_tf has a low active ecosystem.

It has 1 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

fake_tf has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of fake_tf is current.

Quality

fake_tf has no bugs reported.

Security

fake_tf has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

fake_tf does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

fake_tf releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

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fake_tf Key Features

No Key Features are available at this moment for fake_tf.

fake_tf Examples and Code Snippets

No Code Snippets are available at this moment for fake_tf.

Community Discussions

No Community Discussions are available at this moment for fake_tf.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install fake_tf

You can download it from GitHub.
You can use fake_tf like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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