Rename to ForAudioClassification

docs/source/en/model_doc/audio-spectrogram-transformer.mdx

@@ -54,7 +54,7 @@ The original code can be found [here](https:/YuanGongND/ast).
 [[autodoc]] ASTModel
  - forward
 
-## ASTForSequenceClassification
+## ASTForAudioClassification
 
-[[autodoc]] ASTForSequenceClassification
+[[autodoc]] ASTForAudioClassification
  - forward

src/transformers/__init__.py

@@ -900,7 +900,7 @@
  "AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
  "ASTModel",
  "ASTPreTrainedModel",
- "ASTForSequenceClassification",
+ "ASTForAudioClassification",
  ]
  )
  _import_structure["models.auto"].extend(
@@ -3958,7 +3958,7 @@
  )
  from .models.audio_spectrogram_transformer import (
  AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
- ASTForSequenceClassification,
+ ASTForAudioClassification,
  ASTModel,
  ASTPreTrainedModel,
  )

src/transformers/models/audio_spectrogram_transformer/__init__.py

@@ -35,7 +35,7 @@
 else:
  _import_structure["modeling_audio_spectrogram_transformer"] = [
  "AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
- "ASTForSequenceClassification",
+ "ASTForAudioClassification",
  "ASTModel",
  "ASTPreTrainedModel",
  ]
@@ -62,7 +62,7 @@
  else:
  from .modeling_audio_spectrogram_transformer import (
  AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
- ASTForSequenceClassification,
+ ASTForAudioClassification,
  ASTModel,
  ASTPreTrainedModel,
  )

src/transformers/models/audio_spectrogram_transformer/convert_audio_spectrogram_transformer_original_to_pytorch.py

@@ -24,7 +24,7 @@
 from datasets import load_dataset
 
 from huggingface_hub import hf_hub_download
-from transformers import ASTConfig, ASTFeatureExtractor, ASTForSequenceClassification
+from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
 from transformers.utils import logging
 
 
@@ -193,7 +193,7 @@ def convert_audio_spectrogram_transformer_checkpoint(model_name, pytorch_dump_fo
  new_state_dict = convert_state_dict(state_dict, config)
 
  # load 🤗 model
- model = ASTForSequenceClassification(config)
+ model = ASTForAudioClassification(config)
  model.eval()
 
  model.load_state_dict(new_state_dict)

src/transformers/models/audio_spectrogram_transformer/modeling_audio_spectrogram_transformer.py

@@ -543,7 +543,7 @@ def forward(self, hidden_state):
  """,
  AUDIO_SPECTROGRAM_TRANSFORMER_START_DOCSTRING,
 )
-class ASTForSequenceClassification(ASTPreTrainedModel):
+class ASTForAudioClassification(ASTPreTrainedModel):
  def __init__(self, config: ASTConfig) -> None:
  super().__init__(config)
 

src/transformers/models/auto/modeling_auto.py

@@ -783,7 +783,7 @@
 MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES = OrderedDict(
  [
  # Model for Audio Classification mapping
- ("audio-spectrogram-transformer", "ASTForSequenceClassification"),
+ ("audio-spectrogram-transformer", "ASTForAudioClassification"),
  ("data2vec-audio", "Data2VecAudioForSequenceClassification"),
  ("hubert", "HubertForSequenceClassification"),
  ("sew", "SEWForSequenceClassification"),

src/transformers/utils/doc.py

@@ -1087,7 +1087,7 @@ def docstring_decorator(fn):
  expected_loss=expected_loss,
  )
 
- if "SequenceClassification" in model_class and modality == "audio":
+ if ["SequenceClassification" in model_class or "AudioClassification" in model_class] and modality == "audio":
  code_sample = sample_docstrings["AudioClassification"]
  elif "SequenceClassification" in model_class:
  code_sample = sample_docstrings["SequenceClassification"]

src/transformers/utils/dummy_pt_objects.py

@@ -353,7 +353,7 @@ def load_tf_weights_in_albert(*args, **kwargs):
 AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST = None
 
 
-class ASTForSequenceClassification(metaclass=DummyObject):
+class ASTForAudioClassification(metaclass=DummyObject):
  _backends = ["torch"]
 
  def __init__(self, *args, **kwargs):

tests/models/audio_spectrogram_transformer/test_modeling_audio_spectrogram_transformer.py

@@ -30,7 +30,7 @@
  import torch
  from torch import nn
 
- from transformers import ASTForSequenceClassification, ASTModel
+ from transformers import ASTForAudioClassification, ASTModel
  from transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer import (
  AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
  )
@@ -148,7 +148,7 @@ class ASTModelTest(ModelTesterMixin, unittest.TestCase):
  all_model_classes = (
  (
  ASTModel,
- ASTForSequenceClassification,
+ ASTForAudioClassification,
  )
  if is_torch_available()
  else ()
@@ -227,9 +227,7 @@ def default_feature_extractor(self):
  def test_inference_audio_classification(self):
 
  feature_extractor = self.default_feature_extractor
- model = ASTForSequenceClassification.from_pretrained("MIT/ast-finetuned-audioset-10-10-0.4593").to(
- torch_device
- )
+ model = ASTForAudioClassification.from_pretrained("MIT/ast-finetuned-audioset-10-10-0.4593").to(torch_device)
 
  feature_extractor = self.default_feature_extractor
  audio, sampling_rate = prepare_audio()