Fast imports part 3 (#9474)

* New intermediate inits

* Update template

* Avoid importing torch/tf/flax in tokenization unless necessary

* Styling

* Shutup flake8

* Better python version check

src/transformers/models/bert/__init__.py

@@ -16,47 +16,121 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from ...file_utils import is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available
-from .configuration_bert import BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, BertConfig
-from .tokenization_bert import BasicTokenizer, BertTokenizer, WordpieceTokenizer
+from typing import TYPE_CHECKING
 
+from ...file_utils import (
+    _BaseLazyModule,
+    is_flax_available,
+    is_tf_available,
+    is_tokenizers_available,
+    is_torch_available,
+)
+
+
+_import_structure = {
+    "configuration_bert": ["BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BertConfig"],
+    "tokenization_bert": ["BasicTokenizer", "BertTokenizer", "WordpieceTokenizer"],
+}
 
 if is_tokenizers_available():
-    from .tokenization_bert_fast import BertTokenizerFast
+    _import_structure["tokenization_bert_fast"] = ["BertTokenizerFast"]
 
 if is_torch_available():
-    from .modeling_bert import (
-        BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
-        BertForMaskedLM,
-        BertForMultipleChoice,
-        BertForNextSentencePrediction,
-        BertForPreTraining,
-        BertForQuestionAnswering,
-        BertForSequenceClassification,
-        BertForTokenClassification,
-        BertLayer,
-        BertLMHeadModel,
-        BertModel,
-        BertPreTrainedModel,
-        load_tf_weights_in_bert,
-    )
+    _import_structure["modeling_bert"] = [
+        "BERT_PRETRAINED_MODEL_ARCHIVE_LIST",
+        "BertForMaskedLM",
+        "BertForMultipleChoice",
+        "BertForNextSentencePrediction",
+        "BertForPreTraining",
+        "BertForQuestionAnswering",
+        "BertForSequenceClassification",
+        "BertForTokenClassification",
+        "BertLayer",
+        "BertLMHeadModel",
+        "BertModel",
+        "BertPreTrainedModel",
+        "load_tf_weights_in_bert",
+    ]
 
 if is_tf_available():
-    from .modeling_tf_bert import (
-        TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
-        TFBertEmbeddings,
-        TFBertForMaskedLM,
-        TFBertForMultipleChoice,
-        TFBertForNextSentencePrediction,
-        TFBertForPreTraining,
-        TFBertForQuestionAnswering,
-        TFBertForSequenceClassification,
-        TFBertForTokenClassification,
-        TFBertLMHeadModel,
-        TFBertMainLayer,
-        TFBertModel,
-        TFBertPreTrainedModel,
-    )
+    _import_structure["modeling_tf_bert"] = [
+        "TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST",
+        "TFBertEmbeddings",
+        "TFBertForMaskedLM",
+        "TFBertForMultipleChoice",
+        "TFBertForNextSentencePrediction",
+        "TFBertForPreTraining",
+        "TFBertForQuestionAnswering",
+        "TFBertForSequenceClassification",
+        "TFBertForTokenClassification",
+        "TFBertLMHeadModel",
+        "TFBertMainLayer",
+        "TFBertModel",
+        "TFBertPreTrainedModel",
+    ]
 
 if is_flax_available():
-    from .modeling_flax_bert import FlaxBertForMaskedLM, FlaxBertModel
+    _import_structure["modeling_flax_bert"] = ["FlaxBertForMaskedLM", "FlaxBertModel"]
+
+
+if TYPE_CHECKING:
+    from .configuration_bert import BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, BertConfig
+    from .tokenization_bert import BasicTokenizer, BertTokenizer, WordpieceTokenizer
+
+    if is_tokenizers_available():
+        from .tokenization_bert_fast import BertTokenizerFast
+
+    if is_torch_available():
+        from .modeling_bert import (
+            BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
+            BertForMaskedLM,
+            BertForMultipleChoice,
+            BertForNextSentencePrediction,
+            BertForPreTraining,
+            BertForQuestionAnswering,
+            BertForSequenceClassification,
+            BertForTokenClassification,
+            BertLayer,
+            BertLMHeadModel,
+            BertModel,
+            BertPreTrainedModel,
+            load_tf_weights_in_bert,
+        )
+
+    if is_tf_available():
+        from .modeling_tf_bert import (
+            TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
+            TFBertEmbeddings,
+            TFBertForMaskedLM,
+            TFBertForMultipleChoice,
+            TFBertForNextSentencePrediction,
+            TFBertForPreTraining,
+            TFBertForQuestionAnswering,
+            TFBertForSequenceClassification,
+            TFBertForTokenClassification,
+            TFBertLMHeadModel,
+            TFBertMainLayer,
+            TFBertModel,
+            TFBertPreTrainedModel,
+        )
+
+    if is_flax_available():
+        from .modeling_flax_bert import FlaxBertForMaskedLM, FlaxBertModel
+
+else:
+    import importlib
+    import os
+    import sys
+
+    class _LazyModule(_BaseLazyModule):
+        """
+        Module class that surfaces all objects but only performs associated imports when the objects are requested.
+        """
+
+        __file__ = globals()["__file__"]
+        __path__ = [os.path.dirname(__file__)]
+
+        def _get_module(self, module_name: str):
+            return importlib.import_module("." + module_name, self.__name__)
+
+    sys.modules[__name__] = _LazyModule(__name__, _import_structure)