[UT] small bugs in ut_function when one uses data length = 1

[cfiken]

Summary

I found and fixed small bugs in UT implements in special case length=1 for universal_transformer_util.py.
Addition to that, I fixed an operation by having some codes out of loop which looks meaningless iteration (this is not main).

Bugs Detail

I found bugs on a special case in universal_transformer_util.py:

• squeeze operations in ut_function without axis make the dimensions unknown and fail successive operation
  • L1136, L1288

The flow for L1136 is below:

1. the dimensions of state is [batch_size, length, channel] as mentioned in comment at L1110
2. it reduce to [batch_size, length, 1] in common_layers.dense at L1129
3. p is [batch_size, length] by p = tf.squeeze(p) at L1136

In this case, the shape of p would be unknown if length = 1 after squeeze operation, and that may makes successive operation fail.

Modification Detail

There are 2 modifications:

• assign axis at tf.squeeze in ut_function
  • I don't fix L1363 because it has reduce_mean operation before squeeze.
• have new_state.set_shape(state_shape) out of loop because it looks meaningless 👀

It's ok to revert latter one because it is not a main fix.

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[cfiken]

@googlebot I signed it!

[googlebot]

CLAs look good, thanks!

[afrozenator]

@MostafaDehghani - Can you please help greenlight this? Thanks!

[MostafaDehghani]

Thanks @afrozenator for pinging me. Alwayse enjoy/learn when there is a PR on UT :)
Ah! yes... defining squeeze dimension is needed to not mess up the shape when the length is one. Seems the set_shape doesn't need to be in the loop and taking it out from the loop is correct. Thanks a lot @cfiken for catching these and sending the PR :)

[cfiken]

Thanks @afrozenator for mentioning!
Thanks @MostafaDehghani for checking and accepting my PR 😄
I'm glad I could contribute great project 👍

[afrozenator]

Many thanks @cfiken for fixing and @MostafaDehghani for verifying!