Disable tests for deprecated functionality (#3942)

Author: samanklesaria

.github/scripts/unittest-linux/install.sh

@@ -92,11 +92,10 @@ if [[ "$(python --version)" = *3.9* || "$(python --version)" = *3.10* ]]; then
     # See https://github.com/librosa/librosa/issues/1270#issuecomment-759065048
     NUMBA_DEV_CHANNEL="-c numba/label/dev"
 fi
-# Note: installing librosa via pip fail because it will try to compile numba.
 (
     set -x
-    conda install -y -c conda-forge ${NUMBA_DEV_CHANNEL} sox libvorbis librosa parameterized 'requests>=2.20' 'ffmpeg>=6,<7'
-    pip install kaldi-io SoundFile coverage pytest pytest-cov scipy expecttest unidecode inflect Pillow sentencepiece pytorch-lightning 'protobuf<4.21.0' demucs tinytag pyroomacoustics flashlight-text git+https://github.com/kpu/kenlm
+    conda install -y -c conda-forge ${NUMBA_DEV_CHANNEL} sox libvorbis parameterized 'requests>=2.20' 'ffmpeg>=6,<7'
+    pip install kaldi-io SoundFile librosa coverage pytest pytest-cov scipy expecttest unidecode inflect Pillow sentencepiece pytorch-lightning 'protobuf<4.21.0' demucs tinytag pyroomacoustics flashlight-text git+https://github.com/kpu/kenlm
 
     # TODO: might be better to fix the single call to `pip install` above
     pip install "pillow<10.0" "scipy<1.10" "numpy<2.0"

.github/scripts/unittest-linux/run_test.sh

@@ -30,6 +30,5 @@ fi
 
 (
     cd test
-    pytest "${args[@]}" torchaudio_unittest
-    coverage html
+    pytest torchaudio_unittest -k "not backend and not /io/ and not prototype and not sox and not ffmpeg and not fairseq and not hdemucs"
 )

.github/workflows/unittest-linux-cpu.yml

@@ -56,6 +56,7 @@ jobs:
         export TORCHAUDIO_TEST_ALLOW_SKIP_IF_TEMPORARY_DISABLED=true
         export TORCHAUDIO_TEST_ALLOW_SKIP_IF_NO_SOX_DECODER=true
         export TORCHAUDIO_TEST_ALLOW_SKIP_IF_NO_SOX_ENCODER=true
+        export TORCHAUDIO_TEST_ALLOW_SKIP_IF_NO_FFMPEG=true
         echo '::endgroup::'
 
         set -euxo pipefail

examples/asr/emformer_rnnt/common.py

@@ -95,7 +95,7 @@ def forward(self, input):
 class WarmupLR(torch.optim.lr_scheduler._LRScheduler):
     def __init__(self, optimizer, warmup_updates, last_epoch=-1, verbose=False):
         self.warmup_updates = warmup_updates
-        super().__init__(optimizer, last_epoch=last_epoch, verbose=verbose)
+        super().__init__(optimizer, last_epoch=last_epoch)
 
     def get_lr(self):
         return [(min(1.0, self._step_count / self.warmup_updates)) * base_lr for base_lr in self.base_lrs]

src/torchaudio/_backend/sox.py

@@ -41,7 +41,7 @@ def load(
                 "Please use an alternative backend that does support loading from file-like objects, e.g. FFmpeg.",
             )
         else:
-            ret = sox_ext.load_audio_file(uri, frame_offset, num_frames, normalize, channels_first, format)
+            ret = sox_ext.load_audio_file(str(uri), frame_offset, num_frames, normalize, channels_first, format)
             if not ret:
                 raise RuntimeError(f"Failed to load audio from {uri}.")
             return ret
@@ -70,7 +70,7 @@ def save(
             )
         else:
             sox_ext.save_audio_file(
-                uri,
+                str(uri),
                 src,
                 sample_rate,
                 channels_first,

src/torchaudio/functional/__init__.py

@@ -68,7 +68,6 @@
 )
 
 rnnt_loss = dropping_support(_rnnt_loss)
-
 __all__ = [
     "amplitude_to_DB",
     "compute_deltas",

src/torchaudio/transforms/__init__.py

@@ -1,3 +1,4 @@
+from torchaudio._internal.module_utils import dropping_support
 from ._multi_channel import MVDR, PSD, RTFMVDR, SoudenMVDR
 from ._transforms import (
     AddNoise,
@@ -34,6 +35,7 @@
     Vol,
 )
 
+RNNTLoss.__init__ = dropping_support(RNNTLoss.__init__)
 
 __all__ = [
     "AddNoise",

src/torchaudio/transforms/_transforms.py

@@ -10,6 +10,7 @@
 from torch.nn.parameter import UninitializedParameter
 
 from torchaudio import functional as F
+from torchaudio.functional.functional import rnnt_loss
 from torchaudio.functional.functional import (
     _apply_sinc_resample_kernel,
     _check_convolve_mode,
@@ -1846,7 +1847,7 @@ def forward(
             Tensor: Loss with the reduction option applied. If ``reduction`` is  ``"none"``, then size (batch),
             otherwise scalar.
         """
-        return F.rnnt_loss(
+        return rnnt_loss(
             logits,
             targets,
             logit_lengths,

test/torchaudio_unittest/functional/functional_cpu_test.py

@@ -3,6 +3,7 @@
 import torch
 import torchaudio.functional as F
 from parameterized import parameterized
+import unittest
 from torchaudio_unittest.common_utils import PytorchTestCase, skipIfNoSox, TorchaudioTestCase
 
 from .functional_impl import Functional, FunctionalCPUOnly
@@ -22,6 +23,7 @@ class TestFunctionalFloat64(Functional, PytorchTestCase):
     device = torch.device("cpu")
 
 
+@unittest.skip("deprecated")
 @skipIfNoSox
 class TestApplyCodec(TorchaudioTestCase):
     def _smoke_test(self, format, compression, check_num_frames):

test/torchaudio_unittest/functional/torchscript_consistency_impl.py

@@ -6,6 +6,8 @@
 from parameterized import parameterized
 from torchaudio_unittest import common_utils
 from torchaudio_unittest.common_utils import skipIfRocm, TempDirMixin, TestBaseMixin, torch_script
+from torchaudio.functional.functional import rnnt_loss
+
 
 
 class Functional(TempDirMixin, TestBaseMixin):
@@ -801,7 +803,7 @@ def func(tensor):
             targets = torch.tensor([[1, 2]], device=tensor.device, dtype=torch.int32)
             logit_lengths = torch.tensor([2], device=tensor.device, dtype=torch.int32)
             target_lengths = torch.tensor([2], device=tensor.device, dtype=torch.int32)
-            return F.rnnt_loss(tensor, targets, logit_lengths, target_lengths)
+            return rnnt_loss(tensor, targets, logit_lengths, target_lengths)
 
         logits = torch.tensor(
             [