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[ENH] Test coverage for AEAttentionBiGRUNetwork Improved #2540

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[ENH] Test coverage for AEAttentionBiGRUNetwork Improved #2540

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Reference Issues/PRs

Contributes to #2497. Reference PRs #2518 and #2534.

What does this implement/fix? Explain your changes.

The given issue improvises the test coverage of AEAttentionBiGRUNetwork class.

Does your contribution introduce a new dependency? If yes, which one?

No.

Any other comments?

No.

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@aeon-actions-bot aeon-actions-bot bot added enhancement New feature, improvement request or other non-bug code enhancement networks Networks package labels Feb 16, 2025
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Thank you for contributing to aeon

I have added the following labels to this PR based on the title: [ $\color{#FEF1BE}{\textsf{enhancement}}$ ].
I have added the following labels to this PR based on the changes made: [ $\color{#379E11}{\textsf{networks}}$ ]. Feel free to change these if they do not properly represent the PR.

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Refer issue #2560

@lucifer4073 lucifer4073 mentioned this pull request Feb 28, 2025
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baraline
baraline reviewed Mar 1, 2025
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Comments applies to pretty much all functions, instead of asserting the instance type, I would rather assert the values the test functions are meant to be checking. Is it possible?

aeon/networks/tests/test_ae_abgru.py
Comment on lines +20 to +21
assert isinstance(encoder, tf.keras.models.Model)
assert isinstance(decoder, tf.keras.models.Model)
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Is there any way to test that the latent_space_dim in the produced network has the desired value instead of simply testing the instance type ?

aeon/networks/tests/test_ae_abgru.py
Comment on lines +42 to +43
assert isinstance(encoder, tf.keras.models.Model)
assert isinstance(decoder, tf.keras.models.Model)
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Likewise here, could we rather check the number of layers in the produced network ?

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@baraline baraline baraline left review comments

@hadifawaz1999 hadifawaz1999 Awaiting requested review from hadifawaz1999 hadifawaz1999 is a code owner

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@lucifer4073 @baraline