Add missing deprecations for classes and constants in the prototypes directory (#3953)

Co-authored-by: Sam Anklesaria <[email protected]>

Author: samanklesaria

docs/source/prototype.rst

@@ -1,6 +1,10 @@
 torchaudio.prototype
 ====================
 
+.. warning::
+    As TorchAudio is no longer being actively developed, this functionality will no longer be supported.
+    See https://github.com/pytorch/audio/issues/3902 for more details.
+
 ``torchaudio.prototype`` provides prototype features;
 they are at an early stage for feedback and testing.
 Their interfaces might be changed without prior notice.

examples/tutorials/audio_io_tutorial.py

@@ -9,10 +9,8 @@
 load them into PyTorch Tensors and save PyTorch Tensors.
 
 .. warning::
-
-   There are multiple changes planned/made to audio I/O in recent releases.
-   For the detail of these changes please refer to
-   :ref:`Introduction of Dispatcher <dispatcher_migration>`.
+    IO functionality within TorchAudio has been superseded by `AudioDecoder` from the TorchCodec library.
+    See https://github.com/pytorch/audio/issues/3902 for more details.`.
 
 """
 

examples/tutorials/ctc_forced_alignment_api_tutorial.py

@@ -4,6 +4,10 @@
 
 **Author**: `Xiaohui Zhang <[email protected]>`__, `Moto Hira <[email protected]>`__
 
+.. warning::
+    As TorchAudio is no longer being actively developed, this functionality will no longer be supported.
+    See https://github.com/pytorch/audio/issues/3902 for more details.
+
 The forced alignment is a process to align transcript with speech.
 This tutorial shows how to align transcripts to speech using
 :py:func:`torchaudio.functional.forced_align` which was developed along the work of

examples/tutorials/effector_tutorial.py

@@ -4,6 +4,10 @@
 
 **Author**: `Moto Hira <[email protected]>`__
 
+.. warning::
+    As TorchAudio is no longer being actively developed, this functionality will no longer be supported.
+    See https://github.com/pytorch/audio/issues/3902 for more details.
+
 This tutorial shows how to use :py:class:`torchaudio.io.AudioEffector` to
 apply various effects and codecs to waveform tensor.
 

src/torchaudio/_internal/module_utils.py

@@ -123,6 +123,16 @@ def dropping_class_support(c, msg=DEPRECATION_MSG):
     UNSUPPORTED.append(c)
     return c
 
+def dropping_const_support(c, msg=DEPRECATION_MSG, name=None):
+    c.__doc__ = f"""[DEPRECATED] {c.__doc__}
+
+.. warning::
+
+    This object has been deprecated. It will be removed from the 2.9 release.
+    {msg}
+    """
+    return c
+
 dropping_class_io_support = partial(dropping_class_support, msg=IO_DEPRECATION_MSG)
 
 dropping_io_support = deprecated(IO_DEPRECATION_MSG, version="2.9", remove=True)

src/torchaudio/prototype/datasets/musan.py

@@ -4,13 +4,13 @@
 import torch
 from torch.utils.data import Dataset
 from torchaudio.datasets.utils import _load_waveform
-from torchaudio._internal.module_utils import dropping_support
+from torchaudio._internal.module_utils import dropping_support, dropping_class_support
 
 
 _SUBSETS = ["music", "noise", "speech"]
 _SAMPLE_RATE = 16_000
 
-
+@dropping_class_support
 class Musan(Dataset):
     r"""*MUSAN* :cite:`musan2015` dataset.
 
@@ -19,7 +19,6 @@ class Musan(Dataset):
         subset (str): Subset of the dataset to use. Options: [``"music"``, ``"noise"``, ``"speech"``].
     """
 
-    @dropping_support
     def __init__(self, root: Union[str, Path], subset: str):
         if subset not in _SUBSETS:
             raise ValueError(f"Invalid subset '{subset}' given. Please provide one of {_SUBSETS}")

src/torchaudio/prototype/models/__init__.py

@@ -1,3 +1,4 @@
+from torchaudio._internal.module_utils import dropping_const_support
 from ._conformer_wav2vec2 import (
     conformer_wav2vec2_base,
     conformer_wav2vec2_model,
@@ -10,7 +11,9 @@
 from .conv_emformer import ConvEmformer
 from .hifi_gan import hifigan_vocoder, hifigan_vocoder_v1, hifigan_vocoder_v2, hifigan_vocoder_v3, HiFiGANVocoder
 from .rnnt import conformer_rnnt_base, conformer_rnnt_biasing, conformer_rnnt_biasing_base, conformer_rnnt_model
-from .rnnt_decoder import Hypothesis, RNNTBeamSearchBiasing
+from .rnnt_decoder import Hypothesis as _Hypothesis, RNNTBeamSearchBiasing
+
+Hypothesis = dropping_const_support(_Hypothesis, name="Hypothesis")
 
 __all__ = [
     "conformer_rnnt_base",

src/torchaudio/prototype/models/_conformer_wav2vec2.py

@@ -7,7 +7,7 @@
 from torchaudio.models.conformer import ConformerLayer
 from torchaudio.models.rnnt import _TimeReduction
 from torchaudio.models.wav2vec2 import components
-from torchaudio._internal.module_utils import dropping_support
+from torchaudio._internal.module_utils import dropping_class_support, dropping_support
 
 
 def _buffered_arange(max) -> Tensor:
@@ -253,6 +253,7 @@ def extract_features(
         return self._get_intermediate_outputs(x, mask=masks, num_layers=num_layers)
 
 
+@dropping_class_support
 class ConformerWav2Vec2PretrainModel(Module):
     """Conformer Wav2Vec2 pre-train model for training from scratch.
 

src/torchaudio/prototype/models/conv_emformer.py

@@ -3,7 +3,7 @@
 
 import torch
 from torchaudio.models.emformer import _EmformerAttention, _EmformerImpl, _get_weight_init_gains
-from torchaudio._internal.module_utils import dropping_support
+from torchaudio._internal.module_utils import dropping_class_support, dropping_support
 
 
 
@@ -443,6 +443,7 @@ def infer(
         return output_utterance, output_right_context, output_state, next_m
 
 
+@dropping_class_support
 class ConvEmformer(_EmformerImpl):
     r"""Implements the convolution-augmented streaming transformer architecture introduced in
     *Streaming Transformer Transducer based Speech Recognition Using Non-Causal Convolution*

src/torchaudio/prototype/models/hifi_gan.py

@@ -28,9 +28,10 @@
 import torch.nn as nn
 import torch.nn.functional as F
 from torch.nn import Conv1d, ConvTranspose1d
-from torchaudio._internal.module_utils import dropping_support
+from torchaudio._internal.module_utils import dropping_class_support, dropping_support
 
 
+@dropping_class_support
 class HiFiGANVocoder(torch.nn.Module):
     """Generator part of *HiFi GAN* :cite:`NEURIPS2020_c5d73680`.
     Source: https://github.com/jik876/hifi-gan/blob/4769534d45265d52a904b850da5a622601885777/models.py#L75