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TensorFlow Record Reader

The project provides a binary that can read and display TF records.

Development environment

  • Get PyCharm and Docker

  • Go to the project root and start a Docker image

sudo docker build -t tfreader .
docker run -v ${PWD}:/code -w /code -i -t tfreader
source .bashrc
  • Run all the tests run_tests.

TODO list a.k.a. feature requests

  • Loading a proto definition dynamically.
  • Scan the whole project and keep a global DB of protos.
  • Reloading the proto DB.
  • Tab-completion.
  • Selecting sub-fields.
  • Value filtering.
  • Add limit.
  • Add key and size options.
  • Add options to write data back to a file (text format, proto).
  • Colorful output.
  • Globbing support.
  • Support for archives.

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