[tf.data] Fix bugs in dataset hashing and add CheckGraphsEqual function.

The bugs were:
1. If an AttrValue contained a list of functions, we would hash the AttrValue using DeterministicProtoHash64. This would hash the function name, which is not stable and should not be hashed. This CL updates AttrValue hashing to handle lists of functions specially.
2. We perform a DFS at the start to decide which edges to ignore to avoid cycles. This DFS needs to be deterministic, but previously it relied on the ordering of control dependencies, which should be treated as unordered. This CL avoids recursing into control dependencies, so that they cannot introduce cycles.

This CL also adds a CheckGraphsEqual utility to help understand why two graphs might have different hash codes.

Lastly, this CL organizes our hashing code by moving it from dataset_utils to its own hash_utils file.

PiperOrigin-RevId: 333111866
Change-Id: Ic4a79c743a9c1d8e743f6a10bb2b578ad6e1246e
12 files changed
tree: f81b6b8b56ab9f5ee2891435025d4ab748794f38
  1. .github/
  2. tensorflow/
  3. third_party/
  4. tools/
  5. .bazelrc
  6. .bazelversion
  7. .gitignore
  8. ACKNOWLEDGMENTS
  9. arm_compiler.BUILD
  10. AUTHORS
  11. BUILD
  12. CODE_OF_CONDUCT.md
  13. CODEOWNERS
  14. configure
  15. configure.cmd
  16. configure.py
  17. CONTRIBUTING.md
  18. ISSUE_TEMPLATE.md
  19. ISSUES.md
  20. LICENSE
  21. models.BUILD
  22. README.md
  23. RELEASE.md
  24. SECURITY.md
  25. WORKSPACE
README.md

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TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.

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3
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