[Init refactor] Modular changes (#35240)

* Modular changes * Gemma * Gemma
huggingface · Dec 12, 2024 · 11ba1d4 · 11ba1d4
1 parent a691ccb
commit 11ba1d4
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Showing 19 changed files with 129 additions and 253 deletions.
diff --git a/src/transformers/models/gemma/__init__.py b/src/transformers/models/gemma/__init__.py
@@ -1,4 +1,4 @@
-# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
+# Copyright 2024 The HuggingFace Team. All rights reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -13,111 +13,18 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import (
-    OptionalDependencyNotAvailable,
-    _LazyModule,
-    is_flax_available,
-    is_sentencepiece_available,
-    is_tokenizers_available,
-    is_torch_available,
-)
-
-
-_import_structure = {
-    "configuration_gemma": ["GemmaConfig"],
-}
-
-try:
-    if not is_sentencepiece_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["tokenization_gemma"] = ["GemmaTokenizer"]
-
-try:
-    if not is_tokenizers_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["tokenization_gemma_fast"] = ["GemmaTokenizerFast"]
-
-
-try:
-    if not is_torch_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["modeling_gemma"] = [
-        "GemmaForCausalLM",
-        "GemmaModel",
-        "GemmaPreTrainedModel",
-        "GemmaForSequenceClassification",
-        "GemmaForTokenClassification",
-    ]
-
-try:
-    if not is_flax_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["modeling_flax_gemma"] = [
-        "FlaxGemmaForCausalLM",
-        "FlaxGemmaModel",
-        "FlaxGemmaPreTrainedModel",
-    ]
+from ...utils import _LazyModule
+from ...utils.import_utils import define_import_structure
 
 
 if TYPE_CHECKING:
-    from .configuration_gemma import GemmaConfig
-
-    try:
-        if not is_sentencepiece_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .tokenization_gemma import GemmaTokenizer
-
-    try:
-        if not is_tokenizers_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .tokenization_gemma_fast import GemmaTokenizerFast
-
-    try:
-        if not is_torch_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .modeling_gemma import (
-            GemmaForCausalLM,
-            GemmaForSequenceClassification,
-            GemmaForTokenClassification,
-            GemmaModel,
-            GemmaPreTrainedModel,
-        )
-
-    try:
-        if not is_flax_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .modeling_flax_gemma import (
-            FlaxGemmaForCausalLM,
-            FlaxGemmaModel,
-            FlaxGemmaPreTrainedModel,
-        )
-
-
+    from .configuration_gemma import *
+    from .modeling_flax_gemma import *
+    from .modeling_gemma import *
+    from .tokenization_gemma import *
+    from .tokenization_gemma_fast 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__)
diff --git a/src/transformers/models/gemma/modeling_flax_gemma.py b/src/transformers/models/gemma/modeling_flax_gemma.py
@@ -772,3 +772,6 @@ def update_inputs_for_generation(self, model_outputs, model_kwargs):
     _CONFIG_FOR_DOC,
     real_checkpoint=_REAL_CHECKPOINT_FOR_DOC,
 )
+
+
+__all__ = ["FlaxGemmaForCausalLM", "FlaxGemmaModel", "FlaxGemmaPreTrainedModel"]
diff --git a/src/transformers/models/gemma/modeling_gemma.py b/src/transformers/models/gemma/modeling_gemma.py
@@ -1295,4 +1295,10 @@ def forward(
         )
 
 
-__all__ = ["GemmaModel", "GemmaForCausalLM", "GemmaForSequenceClassification", "GemmaForTokenClassification"]
+__all__ = [
+    "GemmaModel",
+    "GemmaForCausalLM",
+    "GemmaForSequenceClassification",
+    "GemmaForTokenClassification",
+    "GemmaPreTrainedModel",
+]
diff --git a/src/transformers/models/gemma/modular_gemma.py b/src/transformers/models/gemma/modular_gemma.py
@@ -36,6 +36,7 @@
     LlamaForSequenceClassification,
     LlamaForTokenClassification,
     LlamaModel,
+    LlamaPreTrainedModel,
     apply_rotary_pos_emb,
     repeat_kv,
 )
@@ -803,6 +804,10 @@ def forward(
         return outputs
 
 
+class GemmaPreTrainedModel(LlamaPreTrainedModel):
+    pass
+
+
 class GemmaModel(LlamaModel):
     def __init__(self, config: GemmaConfig):
         super().__init__(config)
@@ -1040,4 +1045,5 @@ def __init__(self, config):
     "GemmaForCausalLM",
     "GemmaForSequenceClassification",
     "GemmaForTokenClassification",
+    "GemmaPreTrainedModel",
 ]
diff --git a/src/transformers/models/gemma/tokenization_gemma_fast.py b/src/transformers/models/gemma/tokenization_gemma_fast.py
@@ -197,3 +197,6 @@ def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None):
             output = output + bos_token_id + token_ids_1 + eos_token_id
 
         return output
+
+
+__all__ = ["GemmaTokenizerFast"]
diff --git a/src/transformers/models/gemma2/__init__.py b/src/transformers/models/gemma2/__init__.py
@@ -1,4 +1,4 @@
-# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
+# Copyright 2024 The HuggingFace Team. All rights reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -13,49 +13,15 @@
 # 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_gemma2": ["Gemma2Config"],
-}
-
-try:
-    if not is_torch_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["modeling_gemma2"] = [
-        "Gemma2ForCausalLM",
-        "Gemma2Model",
-        "Gemma2PreTrainedModel",
-        "Gemma2ForSequenceClassification",
-        "Gemma2ForTokenClassification",
-    ]
-
 if TYPE_CHECKING:
-    from .configuration_gemma2 import Gemma2Config
-
-    try:
-        if not is_torch_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .modeling_gemma2 import (
-            Gemma2ForCausalLM,
-            Gemma2ForSequenceClassification,
-            Gemma2ForTokenClassification,
-            Gemma2Model,
-            Gemma2PreTrainedModel,
-        )
-
+    from .configuration_gemma2 import *
+    from .modeling_gemma2 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__)
diff --git a/src/transformers/models/gemma2/configuration_gemma2.py b/src/transformers/models/gemma2/configuration_gemma2.py
@@ -153,3 +153,6 @@ def __init__(
         self.final_logit_softcapping = final_logit_softcapping
         self.attn_logit_softcapping = attn_logit_softcapping
         self.cache_implementation = cache_implementation
+
+
+__all__ = ["Gemma2Config"]
diff --git a/src/transformers/models/gemma2/modeling_gemma2.py b/src/transformers/models/gemma2/modeling_gemma2.py
@@ -1280,3 +1280,12 @@ def forward(
             hidden_states=outputs.hidden_states,
             attentions=outputs.attentions,
         )
+
+
+__all__ = [
+    "Gemma2ForCausalLM",
+    "Gemma2Model",
+    "Gemma2PreTrainedModel",
+    "Gemma2ForSequenceClassification",
+    "Gemma2ForTokenClassification",
+]
diff --git a/src/transformers/models/gemma2/modular_gemma2.py b/src/transformers/models/gemma2/modular_gemma2.py
@@ -903,3 +903,13 @@ def __init__(self, config):
         super().__init__(config)
         self.model = Gemma2Model(config)
         self.post_init()
+
+
+__all__ = [
+    "Gemma2Config",
+    "Gemma2ForCausalLM",
+    "Gemma2Model",
+    "Gemma2PreTrainedModel",
+    "Gemma2ForSequenceClassification",
+    "Gemma2ForTokenClassification",
+]
diff --git a/src/transformers/models/llava_next_video/__init__.py b/src/transformers/models/llava_next_video/__init__.py
@@ -13,58 +13,17 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
+from ...utils import _LazyModule
+from ...utils.import_utils import define_import_structure
 
 
-_import_structure = {
-    "configuration_llava_next_video": ["LlavaNextVideoConfig"],
-    "processing_llava_next_video": ["LlavaNextVideoProcessor"],
-}
-
-
-try:
-    if not is_vision_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["image_processing_llava_next_video"] = ["LlavaNextVideoImageProcessor"]
-
-try:
-    if not is_torch_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["modeling_llava_next_video"] = [
-        "LlavaNextVideoForConditionalGeneration",
-        "LlavaNextVideoPreTrainedModel",
-    ]
-
 if TYPE_CHECKING:
-    from .configuration_llava_next_video import LlavaNextVideoConfig
-    from .processing_llava_next_video import LlavaNextVideoProcessor
-
-    try:
-        if not is_vision_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .image_processing_llava_next_video import LlavaNextVideoImageProcessor
-
-    try:
-        if not is_torch_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .modeling_llava_next_video import (
-            LlavaNextVideoForConditionalGeneration,
-            LlavaNextVideoPreTrainedModel,
-        )
-
+    from .configuration_llava_next_video import *
+    from .image_processing_llava_next_video import *
+    from .modeling_llava_next_video import *
+    from .processing_llava_next_video import *
 else:
     import sys
 
-    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure)
+    _file = globals()["__file__"]
+    sys.modules[__name__] = _LazyModule(__name__, _file, define_import_structure(_file), module_spec=__spec__)
diff --git a/src/transformers/models/llava_next_video/configuration_llava_next_video.py b/src/transformers/models/llava_next_video/configuration_llava_next_video.py
@@ -158,3 +158,6 @@ def __init__(
         self.text_config = text_config
 
         super().__init__(tie_word_embeddings=tie_word_embeddings, **kwargs)
+
+
+__all__ = ["LlavaNextVideoConfig"]
diff --git a/src/transformers/models/llava_next_video/image_processing_llava_next_video.py b/src/transformers/models/llava_next_video/image_processing_llava_next_video.py
@@ -414,3 +414,6 @@ def preprocess(
 
         data = {"pixel_values_videos": pixel_values}
         return BatchFeature(data=data, tensor_type=return_tensors)
+
+
+__all__ = ["LlavaNextVideoImageProcessor"]
Original file line number	Diff line number	Diff line change
Expand Up		@@ -197,3 +197,6 @@ def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None):
		output = output + bos_token_id + token_ids_1 + eos_token_id

		return output


		__all__ = ["GemmaTokenizerFast"]
Original file line number	Diff line number	Diff line change
Expand Up		@@ -158,3 +158,6 @@ def __init__(
		self.text_config = text_config

		super().__init__(tie_word_embeddings=tie_word_embeddings, **kwargs)


		__all__ = ["LlavaNextVideoConfig"]
Original file line number	Diff line number	Diff line change
Expand Up		@@ -414,3 +414,6 @@ def preprocess(

		data = {"pixel_values_videos": pixel_values}
		return BatchFeature(data=data, tensor_type=return_tensors)


		__all__ = ["LlavaNextVideoImageProcessor"]