Performance issues in /src/python/tensorflow_cloud/core (by P3)

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Assessment

Difficulty
2/5
Estimated time
1-3 hours
Newbie friendliness
38/100
Issue type
Refactor
Clarity
Mostly clear
Activity status
Stale
Tech stack
python, tensorflow
Domain
machine-learning, performance

Research direction

Start in src/python/tensorflow_cloud/core/tests/testdata/keras_tuner_cifar_example.py at the train_dataset pipeline around the referenced lines. Inspect the scale function's expected input shape, then verify the batch and map ordering for both listed cases. Run the Keras tuner CIFAR example and confirm the changed pipeline works without shape errors.

Written by the indexing model from the issue text.

Description

Hello! I've found a performance issue in /tests/testdata/keras_tuner_cifar_example.py: batch() should be called before map(), which could make your program more efficient. Here is the tensorflow document to support it.

Detailed description is listed below:

  • .batch(BATCH_SIZE)(here) should be called before train_dataset.map(scale)(here).
  • .batch(BATCH_SIZE)(here) should be called before .map(scale)(here).

Besides, you need to check the function called in map()(e.g., scale called in .map(scale)) whether to be affected or not to make the changed code work properly. For example, if scale needs data with shape (x, y, z) as its input before fix, it would require data with shape (batch_size, x, y, z).

Looking forward to your reply. Btw, I am very glad to create a PR to fix it if you are too busy.

Dominant language
Python
Stars
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Forks
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Avg merge
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Merged PRs (30d)
1

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