tf_examples | TensorFlow and Scikit Flow examples | Machine Learning library

by ilblackdragon Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | tf_examples Summary

tf_examples is a Python library typically used in Artificial Intelligence, Machine Learning, Tensorflow applications. tf_examples has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However tf_examples build file is not available. You can download it from GitHub.

TensorFlow and Scikit Flow examples

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tf_examples has a low active ecosystem.

It has 144 star(s) with 89 fork(s). There are 13 watchers for this library.

It had no major release in the last 6 months.

There are 3 open issues and 3 have been closed. On average issues are closed in 17 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of tf_examples is current.

Quality

tf_examples has 0 bugs and 0 code smells.

Security

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

tf_examples code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

tf_examples is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

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

tf_examples has no build file. You will be need to create the build yourself to build the component from source.

tf_examples saves you 276 person hours of effort in developing the same functionality from scratch.

It has 667 lines of code, 46 functions and 12 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

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tf_examples Key Features

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tf_examples Examples and Code Snippets

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Community Discussions

Trending Discussions on tf_examples

Writing tfrecords in apche_beam with java

QUESTION

Writing tfrecords in apche_beam with java

Asked 2020-Apr-17 at 11:13

How can I write the following code in java? If I have list of records/dicts in java how can I write the beam code to write them in tfrecords where tf.train.Examples are serialized. There are lot of examples to do that with python, below is one example in python, how can I write the same logic in java ?

...

ANSWER

Answered 2020-Apr-17 at 11:13

I have attempted this with java but I am still getting some issues, The link to new to question is here Write tfrecords from beam pipeline?.

Source https://stackoverflow.com/questions/61247661

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

Vulnerabilities

No vulnerabilities reported

Install tf_examples

You can download it from GitHub.
You can use tf_examples 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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