Rest of the model refactors

.circleci/config.yml

@@ -116,7 +116,7 @@ jobs:
                 command: pip freeze | tee installed.txt
             - store_artifacts:
                   path: ~/transformers/installed.txt
-            - run: python -c "from transformers import *" || (echo '🚨 import failed, this means you introduced unprotected imports! 🚨'; exit 1)
+            - run: python -c "from transformers import *" || (echo '🚨 import failed, this means you introduced unprotected imports! Have you added this object to the __all__ object of the module? 🚨'; exit 1)
             - run: ruff check examples tests src utils
             - run: ruff format tests src utils --check
             - run: python utils/custom_init_isort.py --check_only

Makefile

@@ -50,7 +50,7 @@ repo-consistency:
 # this target runs checks on all files
 
 quality:
-	@python -c "from transformers import *" || (echo '🚨 import failed, this means you introduced unprotected imports! 🚨'; exit 1)
+	@python -c "from transformers import *" || (echo '🚨 import failed, this means you introduced unprotected imports! Have you added this object to the __all__ object of the module? 🚨'; exit 1)
 	ruff check $(check_dirs) setup.py conftest.py
 	ruff format --check $(check_dirs) setup.py conftest.py
 	python utils/sort_auto_mappings.py --check_only

src/transformers/models/audio_spectrogram_transformer/__init__.py

@@ -13,47 +13,16 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
-
-
-_import_structure = {
-    "configuration_audio_spectrogram_transformer": ["ASTConfig"],
-    "feature_extraction_audio_spectrogram_transformer": ["ASTFeatureExtractor"],
-}
-
-try:
-    if not is_torch_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["modeling_audio_spectrogram_transformer"] = [
-        "ASTForAudioClassification",
-        "ASTModel",
-        "ASTPreTrainedModel",
-    ]
+from ...utils import _LazyModule
+from ...utils.import_utils import define_import_structure
 
 
 if TYPE_CHECKING:
-    from .configuration_audio_spectrogram_transformer import (
-        ASTConfig,
-    )
-    from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor
-
-    try:
-        if not is_torch_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .modeling_audio_spectrogram_transformer import (
-            ASTForAudioClassification,
-            ASTModel,
-            ASTPreTrainedModel,
-        )
-
-
+    from .configuration_audio_spectrogram_transformer import *
+    from .feature_extraction_audio_spectrogram_transformer import *
+    from .modeling_audio_spectrogram_transformer import *
 else:
     import sys
 
-    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
+    _file = globals()["__file__"]
+    sys.modules[__name__] = _LazyModule(__name__, _file, define_import_structure(_file), module_spec=__spec__)

src/transformers/models/audio_spectrogram_transformer/configuration_audio_spectrogram_transformer.py

@@ -126,3 +126,6 @@ def __init__(
     # generative parameters deprecation cycle, overwriting this function prevents this from happening.
     def _get_non_default_generation_parameters(self) -> Dict[str, Any]:
         return {}
+
+
+__all__ = ["ASTConfig"]

src/transformers/models/audio_spectrogram_transformer/feature_extraction_audio_spectrogram_transformer.py

@@ -234,3 +234,6 @@ def __call__(
             padded_inputs = padded_inputs.convert_to_tensors(return_tensors)
 
         return padded_inputs
+
+
+__all__ = ["ASTFeatureExtractor"]

src/transformers/models/audio_spectrogram_transformer/modeling_audio_spectrogram_transformer.py

@@ -654,3 +654,6 @@ def forward(
             hidden_states=outputs.hidden_states,
             attentions=outputs.attentions,
         )
+
+
+__all__ = ["ASTPreTrainedModel", "ASTModel", "ASTForAudioClassification"]

src/transformers/models/autoformer/__init__.py

@@ -13,45 +13,15 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-# rely on isort to merge the imports
-from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
-
-
-_import_structure = {
-    "configuration_autoformer": ["AutoformerConfig"],
-}
-
-try:
-    if not is_torch_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["modeling_autoformer"] = [
-        "AutoformerForPrediction",
-        "AutoformerModel",
-        "AutoformerPreTrainedModel",
-    ]
+from ...utils import _LazyModule
+from ...utils.import_utils import define_import_structure
 
 
 if TYPE_CHECKING:
-    from .configuration_autoformer import (
-        AutoformerConfig,
-    )
-
-    try:
-        if not is_torch_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .modeling_autoformer import (
-            AutoformerForPrediction,
-            AutoformerModel,
-            AutoformerPreTrainedModel,
-        )
-
+    from .configuration_autoformer import *
+    from .modeling_autoformer import *
 else:
     import sys
 
-    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
+    _file = globals()["__file__"]
+    sys.modules[__name__] = _LazyModule(__name__, _file, define_import_structure(_file), module_spec=__spec__)

src/transformers/models/autoformer/configuration_autoformer.py

@@ -240,3 +240,6 @@ def _number_of_features(self) -> int:
             + self.num_static_real_features
             + self.input_size * 2  # the log1p(abs(loc)) and log(scale) features
         )
+
+
+__all__ = ["AutoformerConfig"]

src/transformers/models/autoformer/modeling_autoformer.py

@@ -2150,3 +2150,6 @@ def generate(
                 (-1, num_parallel_samples, self.config.prediction_length) + self.target_shape,
             )
         )
+
+
+__all__ = ["AutoformerPreTrainedModel", "AutoformerModel", "AutoformerForPrediction"]

src/transformers/models/bark/__init__.py

@@ -13,63 +13,16 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import (
-    OptionalDependencyNotAvailable,
-    _LazyModule,
-    is_torch_available,
-)
+from ...utils import _LazyModule
+from ...utils.import_utils import define_import_structure
 
 
-_import_structure = {
-    "configuration_bark": [
-        "BarkCoarseConfig",
-        "BarkConfig",
-        "BarkFineConfig",
-        "BarkSemanticConfig",
-    ],
-    "processing_bark": ["BarkProcessor"],
-}
-
-try:
-    if not is_torch_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["modeling_bark"] = [
-        "BarkFineModel",
-        "BarkSemanticModel",
-        "BarkCoarseModel",
-        "BarkModel",
-        "BarkPreTrainedModel",
-        "BarkCausalModel",
-    ]
-
 if TYPE_CHECKING:
-    from .configuration_bark import (
-        BarkCoarseConfig,
-        BarkConfig,
-        BarkFineConfig,
-        BarkSemanticConfig,
-    )
-    from .processing_bark import BarkProcessor
-
-    try:
-        if not is_torch_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .modeling_bark import (
-            BarkCausalModel,
-            BarkCoarseModel,
-            BarkFineModel,
-            BarkModel,
-            BarkPreTrainedModel,
-            BarkSemanticModel,
-        )
-
+    from .configuration_bark import *
+    from .modeling_bark import *
+    from .processing_bark import *
 else:
     import sys
 
-    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
+    _file = globals()["__file__"]
+    sys.modules[__name__] = _LazyModule(__name__, _file, define_import_structure(_file), module_spec=__spec__)

src/transformers/models/bark/configuration_bark.py

@@ -323,3 +323,6 @@ def from_sub_model_configs(
             codec_config=codec_config.to_dict(),
             **kwargs,
         )
+
+
+__all__ = ["BarkSemanticConfig", "BarkCoarseConfig", "BarkFineConfig", "BarkConfig"]

src/transformers/models/bark/modeling_bark.py

@@ -546,6 +546,8 @@ def device(self) -> torch.device:
 
 
 # GPT2-like autoregressive model
+
+
 class BarkCausalModel(BarkPreTrainedModel):
     config_class = BarkSubModelConfig
 
@@ -1811,3 +1813,13 @@ def _check_and_enable_flash_attn_2(
         config.coarse_acoustics_config._attn_implementation = config._attn_implementation
         config.fine_acoustics_config._attn_implementation = config._attn_implementation
         return config
+
+
+__all__ = [
+    "BarkPreTrainedModel",
+    "BarkCausalModel",
+    "BarkFineModel",
+    "BarkCoarseModel",
+    "BarkSemanticModel",
+    "BarkModel",
+]

src/transformers/models/bark/processing_bark.py

@@ -285,3 +285,6 @@ def __call__(
             encoded_text["history_prompt"] = voice_preset
 
         return encoded_text
+
+
+__all__ = ["BarkProcessor"]