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It was reported in #1478 that spectrogram masking operations were done in-place and modified the original input tensors. This PR fixes this behavior and adds tests to ensure that the input tensor is not changed.

Replace the prototype RNNT implementation (using warp-transducer) with one without external library dependencies

- Put functional test logic into one place, `functional_impl.py`
- Tidy imports

* Fixed floor_divide deprecation warnings seen in pytest output

* Fixed warning in test_flanger_triangle_linear

The VAD function trims the input tensor to the first instance of voice
activity on any channel or item. Trimming batches this way may be
undesirable as the item with earliest activity will dominate. Either
way, the batch behaviour does not match the itemwise behaviour.

The VAD batch consistency tests currently pass out of coincidence, but
they specify incorrect behaviour. This commit removes them.

Use shorter input sequences to avoid time out error on CI

* Remove an invalid InverseMel comparison unit test

Similar to #1426 `test_InverseMelScale` in `librosa_compatibility_test` is not
ensuring the comaptibility to librosa. Having this test can give a wrong statement
about the librosa numerical compatibility about the function.

* Add test for InverseMelScale

The new test compares the result of inverse mel scale against the reference spectrogram, so no need to use librosa.
This test serves as more like an insurance that the change to the implementation of InverseMelScale only improves the result, not the other way.

Merges lfilter and spectrogram classes together in the common implementation and modifies the cpu and gpu test definitions accordingly

* Update spectrogram to use complex
* Update autograd test
* Update TS test
* Update librosa test

1. `F.phase_vocoder` accepts Tensor with complex dtype.
    * The implementation path has been updated from #758 so that they share the same code path by internally converting the input Tensor to complex dtype and performing all the operation on top of it.
    * Adopted `torch.polar` for simpler Tensor generation from magnitude and angle.
2. Updated tests
    * librosa compatibility test for complex dtype and pseudo complex dtype
        * Extracted the output shape check test and moved it to functional so that it will be tested on all the combination of `{CPU | CUDA} x {complex64 | complex128}`
    * TorchScript compatibility test for `F.phase_vocoder` and `T.TimeStretch`.
    * batch consistency test for `T.TimeStretch`.

Co-authored-by: krishnakalyan3 <skalyan@cloudera.com>

Co-authored-by: krishnakalyan3 <skalyan@cloudera.com>

This PR additionally adds batching to kaldi compliance resample interface.