[WIP] Fix Pyright static type checking by replacing if-else imports with try-except (#16578)

* rebase and isort

* modify cookiecutter init

* fix cookiecutter auto imports

* fix clean_frameworks_in_init

* fix add_model_to_main_init

* blackify

* replace unnecessary f-strings

* update yolos imports

* fix roberta import bug

* fix yolos missing dependency

* fix add_model_like and cookiecutter bug

* fix repository consistency error

* modify cookiecutter, fix add_new_model_like

* remove stale line
Co-authored-by: Dom Miketa <dmiketa@exscientia.co.uk>

src/transformers/models/sew/__init__.py

@@ -17,14 +17,19 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_torch_available
+from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
 
 
 _import_structure = {
     "configuration_sew": ["SEW_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWConfig"],
 }
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_sew"] = [
         "SEW_PRETRAINED_MODEL_ARCHIVE_LIST",
         "SEWForCTC",
@@ -36,7 +41,12 @@ if is_torch_available():
 if TYPE_CHECKING:
     from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_sew import (
             SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
             SEWForCTC,

src/transformers/models/sew_d/__init__.py

@@ -17,14 +17,19 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_torch_available
+from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
 
 
 _import_structure = {
     "configuration_sew_d": ["SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWDConfig"],
 }
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_sew_d"] = [
         "SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST",
         "SEWDForCTC",
@@ -36,7 +41,12 @@ if is_torch_available():
 if TYPE_CHECKING:
     from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_sew_d import (
             SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
             SEWDForCTC,

src/transformers/models/speech_encoder_decoder/__init__.py

@@ -18,26 +18,46 @@
 
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_flax_available, is_torch_available
+from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
 
 
 _import_structure = {
     "configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"],
 }
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_speech_encoder_decoder"] = ["SpeechEncoderDecoderModel"]
 
-if is_flax_available():
+try:
+    if not is_flax_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_flax_speech_encoder_decoder"] = ["FlaxSpeechEncoderDecoderModel"]
 
 if TYPE_CHECKING:
     from .configuration_speech_encoder_decoder import SpeechEncoderDecoderConfig
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_speech_encoder_decoder import SpeechEncoderDecoderModel
 
-    if is_flax_available():
+    try:
+        if not is_flax_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_flax_speech_encoder_decoder import FlaxSpeechEncoderDecoderModel
 
 else:

src/transformers/models/speech_to_text/__init__.py

@@ -17,7 +17,14 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_sentencepiece_available, is_speech_available, is_tf_available, is_torch_available
+from ...utils import (
+    OptionalDependencyNotAvailable,
+    _LazyModule,
+    is_sentencepiece_available,
+    is_speech_available,
+    is_tf_available,
+    is_torch_available,
+)
 
 
 _import_structure = {
@@ -27,16 +34,31 @@ _import_structure = {
     ],
 }
 
-if is_sentencepiece_available():
+try:
+    if not is_sentencepiece_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["tokenization_speech_to_text"] = ["Speech2TextTokenizer"]
 
-if is_speech_available():
+try:
+    if not is_speech_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["feature_extraction_speech_to_text"] = ["Speech2TextFeatureExtractor"]
 
     if is_sentencepiece_available():
         _import_structure["processing_speech_to_text"] = ["Speech2TextProcessor"]
 
-if is_tf_available():
+try:
+    if not is_tf_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_tf_speech_to_text"] = [
         "TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TFSpeech2TextForConditionalGeneration",
@@ -44,7 +66,12 @@ if is_tf_available():
         "TFSpeech2TextPreTrainedModel",
     ]
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_speech_to_text"] = [
         "SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "Speech2TextForConditionalGeneration",
@@ -56,16 +83,31 @@ if is_torch_available():
 if TYPE_CHECKING:
     from .configuration_speech_to_text import SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, Speech2TextConfig
 
-    if is_sentencepiece_available():
+    try:
+        if not is_sentencepiece_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .tokenization_speech_to_text import Speech2TextTokenizer
 
-    if is_speech_available():
+    try:
+        if not is_speech_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .feature_extraction_speech_to_text import Speech2TextFeatureExtractor
 
         if is_sentencepiece_available():
             from .processing_speech_to_text import Speech2TextProcessor
 
-    if is_tf_available():
+    try:
+        if not is_tf_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_tf_speech_to_text import (
             TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
             TFSpeech2TextForConditionalGeneration,
@@ -73,7 +115,12 @@ if TYPE_CHECKING:
             TFSpeech2TextPreTrainedModel,
         )
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_speech_to_text import (
             SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
             Speech2TextForConditionalGeneration,

src/transformers/models/speech_to_text_2/__init__.py

@@ -17,7 +17,13 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_sentencepiece_available, is_speech_available, is_torch_available
+from ...utils import (
+    OptionalDependencyNotAvailable,
+    _LazyModule,
+    is_sentencepiece_available,
+    is_speech_available,
+    is_torch_available,
+)
 
 
 _import_structure = {
@@ -30,7 +36,12 @@ _import_structure = {
 }
 
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_speech_to_text_2"] = [
         "SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST",
         "Speech2Text2ForCausalLM",
@@ -43,7 +54,12 @@ if TYPE_CHECKING:
     from .processing_speech_to_text_2 import Speech2Text2Processor
     from .tokenization_speech_to_text_2 import Speech2Text2Tokenizer
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_speech_to_text_2 import (
             SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST,
             Speech2Text2ForCausalLM,

src/transformers/models/splinter/__init__.py

@@ -17,7 +17,7 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_tokenizers_available, is_torch_available
+from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
 
 
 _import_structure = {
@@ -25,10 +25,20 @@ _import_structure = {
     "tokenization_splinter": ["SplinterTokenizer"],
 }
 
-if is_tokenizers_available():
+try:
+    if not is_tokenizers_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["tokenization_splinter_fast"] = ["SplinterTokenizerFast"]
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_splinter"] = [
         "SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST",
         "SplinterForQuestionAnswering",
@@ -42,10 +52,20 @@ if TYPE_CHECKING:
     from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
     from .tokenization_splinter import SplinterTokenizer
 
-    if is_tokenizers_available():
+    try:
+        if not is_tokenizers_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .tokenization_splinter_fast import SplinterTokenizerFast
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_splinter import (
             SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
             SplinterForQuestionAnswering,

src/transformers/models/squeezebert/__init__.py

@@ -18,7 +18,7 @@
 
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_tokenizers_available, is_torch_available
+from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
 
 
 _import_structure = {
@@ -26,10 +26,20 @@ _import_structure = {
     "tokenization_squeezebert": ["SqueezeBertTokenizer"],
 }
 
-if is_tokenizers_available():
+try:
+    if not is_tokenizers_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["tokenization_squeezebert_fast"] = ["SqueezeBertTokenizerFast"]
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_squeezebert"] = [
         "SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "SqueezeBertForMaskedLM",
@@ -47,10 +57,20 @@ if TYPE_CHECKING:
     from .configuration_squeezebert import SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, SqueezeBertConfig
     from .tokenization_squeezebert import SqueezeBertTokenizer
 
-    if is_tokenizers_available():
+    try:
+        if not is_tokenizers_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_squeezebert import (
             SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
             SqueezeBertForMaskedLM,

src/transformers/models/swin/__init__.py

@@ -18,7 +18,7 @@
 from typing import TYPE_CHECKING
 
 # rely on isort to merge the imports
-from ...utils import _LazyModule, is_torch_available
+from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
 
 
 _import_structure = {
@@ -26,7 +26,12 @@ _import_structure = {
 }
 
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_swin"] = [
         "SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
         "SwinForImageClassification",
@@ -39,7 +44,12 @@ if is_torch_available():
 if TYPE_CHECKING:
     from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_swin import (
             SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
             SwinForImageClassification,

src/transformers/models/t5/__init__.py

@@ -19,6 +19,7 @@
 from typing import TYPE_CHECKING
 
 from ...utils import (
+    OptionalDependencyNotAvailable,
     _LazyModule,
     is_flax_available,
     is_sentencepiece_available,
@@ -32,13 +33,28 @@ _import_structure = {
     "configuration_t5": ["T5_PRETRAINED_CONFIG_ARCHIVE_MAP", "T5Config", "T5OnnxConfig"],
 }
 
-if is_sentencepiece_available():
+try:
+    if not is_sentencepiece_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["tokenization_t5"] = ["T5Tokenizer"]
 
-if is_tokenizers_available():
+try:
+    if not is_tokenizers_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["tokenization_t5_fast"] = ["T5TokenizerFast"]
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_t5"] = [
         "T5_PRETRAINED_MODEL_ARCHIVE_LIST",
         "T5EncoderModel",
@@ -48,7 +64,12 @@ if is_torch_available():
         "load_tf_weights_in_t5",
     ]
 
-if is_tf_available():
+try:
+    if not is_tf_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_tf_t5"] = [
         "TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TFT5EncoderModel",
@@ -57,7 +78,12 @@ if is_tf_available():
         "TFT5PreTrainedModel",
     ]
 
-if is_flax_available():
+try:
+    if not is_flax_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_flax_t5"] = [
         "FlaxT5ForConditionalGeneration",
         "FlaxT5Model",
@@ -68,13 +94,28 @@ if is_flax_available():
 if TYPE_CHECKING:
     from .configuration_t5 import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, T5Config, T5OnnxConfig
 
-    if is_sentencepiece_available():
+    try:
+        if not is_sentencepiece_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .tokenization_t5 import T5Tokenizer
 
-    if is_tokenizers_available():
+    try:
+        if not is_tokenizers_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .tokenization_t5_fast import T5TokenizerFast
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_t5 import (
             T5_PRETRAINED_MODEL_ARCHIVE_LIST,
             T5EncoderModel,
@@ -84,7 +125,12 @@ if TYPE_CHECKING:
             load_tf_weights_in_t5,
         )
 
-    if is_tf_available():
+    try:
+        if not is_tf_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_tf_t5 import (
             TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST,
             TFT5EncoderModel,
@@ -93,7 +139,12 @@ if TYPE_CHECKING:
             TFT5PreTrainedModel,
         )
 
-    if is_flax_available():
+    try:
+        if not is_flax_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_flax_t5 import FlaxT5ForConditionalGeneration, FlaxT5Model, FlaxT5PreTrainedModel
 
 

src/transformers/models/tapas/__init__.py

@@ -18,7 +18,7 @@
 
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_tf_available, is_torch_available
+from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
 
 
 _import_structure = {
@@ -26,7 +26,12 @@ _import_structure = {
     "tokenization_tapas": ["TapasTokenizer"],
 }
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_tapas"] = [
         "TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TapasForMaskedLM",
@@ -36,7 +41,12 @@ if is_torch_available():
         "TapasPreTrainedModel",
         "load_tf_weights_in_tapas",
     ]
-if is_tf_available():
+try:
+    if not is_tf_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_tf_tapas"] = [
         "TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TFTapasForMaskedLM",
@@ -51,7 +61,12 @@ if TYPE_CHECKING:
     from .configuration_tapas import TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP, TapasConfig
     from .tokenization_tapas import TapasTokenizer
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_tapas import (
             TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
             TapasForMaskedLM,
@@ -62,7 +77,12 @@ if TYPE_CHECKING:
             load_tf_weights_in_tapas,
         )
 
-    if is_tf_available():
+    try:
+        if not is_tf_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_tf_tapas import (
             TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
             TFTapasForMaskedLM,

src/transformers/models/transfo_xl/__init__.py

@@ -18,7 +18,7 @@
 
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_tf_available, is_torch_available
+from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
 
 
 _import_structure = {
@@ -26,7 +26,12 @@ _import_structure = {
     "tokenization_transfo_xl": ["TransfoXLCorpus", "TransfoXLTokenizer"],
 }
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_transfo_xl"] = [
         "TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST",
         "AdaptiveEmbedding",
@@ -37,7 +42,12 @@ if is_torch_available():
         "load_tf_weights_in_transfo_xl",
     ]
 
-if is_tf_available():
+try:
+    if not is_tf_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_tf_transfo_xl"] = [
         "TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TFAdaptiveEmbedding",
@@ -53,7 +63,12 @@ if TYPE_CHECKING:
     from .configuration_transfo_xl import TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, TransfoXLConfig
     from .tokenization_transfo_xl import TransfoXLCorpus, TransfoXLTokenizer
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_transfo_xl import (
             TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
             AdaptiveEmbedding,
@@ -64,7 +79,12 @@ if TYPE_CHECKING:
             load_tf_weights_in_transfo_xl,
         )
 
-    if is_tf_available():
+    try:
+        if not is_tf_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_tf_transfo_xl import (
             TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
             TFAdaptiveEmbedding,

src/transformers/models/trocr/__init__.py

@@ -17,7 +17,13 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_sentencepiece_available, is_speech_available, is_torch_available
+from ...utils import (
+    OptionalDependencyNotAvailable,
+    _LazyModule,
+    is_sentencepiece_available,
+    is_speech_available,
+    is_torch_available,
+)
 
 
 _import_structure = {
@@ -29,7 +35,12 @@ _import_structure = {
 }
 
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_trocr"] = [
         "TROCR_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TrOCRForCausalLM",
@@ -41,7 +52,12 @@ if TYPE_CHECKING:
     from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
     from .processing_trocr import TrOCRProcessor
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel
 
 else:

src/transformers/models/unispeech/__init__.py

@@ -17,14 +17,25 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_flax_available, is_tf_available, is_torch_available
+from ...utils import (
+    OptionalDependencyNotAvailable,
+    _LazyModule,
+    is_flax_available,
+    is_tf_available,
+    is_torch_available,
+)
 
 
 _import_structure = {
     "configuration_unispeech": ["UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP", "UniSpeechConfig"],
 }
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_unispeech"] = [
         "UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST",
         "UniSpeechForCTC",
@@ -37,7 +48,12 @@ if is_torch_available():
 if TYPE_CHECKING:
     from .configuration_unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_unispeech import (
             UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST,
             UniSpeechForCTC,

src/transformers/models/unispeech_sat/__init__.py

@@ -17,14 +17,25 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_flax_available, is_tf_available, is_torch_available
+from ...utils import (
+    OptionalDependencyNotAvailable,
+    _LazyModule,
+    is_flax_available,
+    is_tf_available,
+    is_torch_available,
+)
 
 
 _import_structure = {
     "configuration_unispeech_sat": ["UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP", "UniSpeechSatConfig"],
 }
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_unispeech_sat"] = [
         "UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "UniSpeechSatForAudioFrameClassification",
@@ -39,7 +50,12 @@ if is_torch_available():
 if TYPE_CHECKING:
     from .configuration_unispeech_sat import UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechSatConfig
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_unispeech_sat import (
             UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST,
             UniSpeechSatForAudioFrameClassification,

src/transformers/models/van/__init__.py

@@ -18,7 +18,7 @@
 from typing import TYPE_CHECKING
 
 # rely on isort to merge the imports
-from ...utils import _LazyModule, is_torch_available, is_vision_available
+from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
 
 
 _import_structure = {
@@ -26,7 +26,12 @@ _import_structure = {
 }
 
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_van"] = [
         "VAN_PRETRAINED_MODEL_ARCHIVE_LIST",
         "VanForImageClassification",
@@ -37,7 +42,12 @@ if is_torch_available():
 if TYPE_CHECKING:
     from .configuration_van import VAN_PRETRAINED_CONFIG_ARCHIVE_MAP, VanConfig
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_van import (
             VAN_PRETRAINED_MODEL_ARCHIVE_LIST,
             VanForImageClassification,

src/transformers/models/vilt/__init__.py

@@ -18,18 +18,28 @@
 from typing import TYPE_CHECKING
 
 # rely on isort to merge the imports
-from ...utils import _LazyModule, is_torch_available, is_vision_available
+from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
 
 
 _import_structure = {
     "configuration_vilt": ["VILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViltConfig"],
 }
 
-if is_vision_available():
+try:
+    if not is_vision_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["feature_extraction_vilt"] = ["ViltFeatureExtractor"]
     _import_structure["processing_vilt"] = ["ViltProcessor"]
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_vilt"] = [
         "VILT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "ViltForImageAndTextRetrieval",
@@ -45,11 +55,21 @@ if is_torch_available():
 if TYPE_CHECKING:
     from .configuration_vilt import VILT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViltConfig
 
-    if is_vision_available():
+    try:
+        if not is_vision_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .feature_extraction_vilt import ViltFeatureExtractor
         from .processing_vilt import ViltProcessor
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_vilt import (
             VILT_PRETRAINED_MODEL_ARCHIVE_LIST,
             ViltForImageAndTextRetrieval,

src/transformers/models/vision_encoder_decoder/__init__.py

@@ -18,32 +18,68 @@
 
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_flax_available, is_tf_available, is_torch_available
+from ...utils import (
+    OptionalDependencyNotAvailable,
+    _LazyModule,
+    is_flax_available,
+    is_tf_available,
+    is_torch_available,
+)
 
 
 _import_structure = {
     "configuration_vision_encoder_decoder": ["VisionEncoderDecoderConfig"],
 }
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_vision_encoder_decoder"] = ["VisionEncoderDecoderModel"]
 
-if is_tf_available():
+try:
+    if not is_tf_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_tf_vision_encoder_decoder"] = ["TFVisionEncoderDecoderModel"]
 
-if is_flax_available():
+try:
+    if not is_flax_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_flax_vision_encoder_decoder"] = ["FlaxVisionEncoderDecoderModel"]
 
 if TYPE_CHECKING:
     from .configuration_vision_encoder_decoder import VisionEncoderDecoderConfig
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_vision_encoder_decoder import VisionEncoderDecoderModel
 
-    if is_tf_available():
+    try:
+        if not is_tf_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_tf_vision_encoder_decoder import TFVisionEncoderDecoderModel
 
-    if is_flax_available():
+    try:
+        if not is_flax_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_flax_vision_encoder_decoder import FlaxVisionEncoderDecoderModel
 
 else:

src/transformers/models/vision_text_dual_encoder/__init__.py

@@ -18,7 +18,7 @@
 from typing import TYPE_CHECKING
 
 # rely on isort to merge the imports
-from ...utils import _LazyModule, is_flax_available, is_torch_available
+from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
 
 
 _import_structure = {
@@ -27,11 +27,21 @@ _import_structure = {
 }
 
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_vision_text_dual_encoder"] = ["VisionTextDualEncoderModel"]
 
 
-if is_flax_available():
+try:
+    if not is_flax_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_flax_vision_text_dual_encoder"] = ["FlaxVisionTextDualEncoderModel"]
 
 
@@ -39,10 +49,20 @@ if TYPE_CHECKING:
     from .configuration_vision_text_dual_encoder import VisionTextDualEncoderConfig
     from .processing_visiotn_text_dual_encoder import VisionTextDualEncoderProcessor
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_vision_text_dual_encoder import VisionTextDualEncoderModel
 
-    if is_flax_available():
+    try:
+        if not is_flax_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_vision_text_dual_encoder import FlaxVisionTextDualEncoderModel
 
 

src/transformers/models/visual_bert/__init__.py

@@ -17,14 +17,19 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_torch_available
+from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
 
 
 _import_structure = {
     "configuration_visual_bert": ["VISUAL_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "VisualBertConfig"],
 }
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_visual_bert"] = [
         "VISUAL_BERT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "VisualBertForMultipleChoice",
@@ -41,7 +46,12 @@ if is_torch_available():
 if TYPE_CHECKING:
     from .configuration_visual_bert import VISUAL_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, VisualBertConfig
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_visual_bert import (
             VISUAL_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
             VisualBertForMultipleChoice,

src/transformers/models/vit/__init__.py

@@ -17,17 +17,34 @@
 # limitations under the License.
 from typing import TYPE_CHECKING
 
-from ...utils import _LazyModule, is_flax_available, is_tf_available, is_torch_available, is_vision_available
+from ...utils import (
+    OptionalDependencyNotAvailable,
+    _LazyModule,
+    is_flax_available,
+    is_tf_available,
+    is_torch_available,
+    is_vision_available,
+)
 
 
 _import_structure = {
     "configuration_vit": ["VIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTConfig", "ViTOnnxConfig"],
 }
 
-if is_vision_available():
+try:
+    if not is_vision_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["feature_extraction_vit"] = ["ViTFeatureExtractor"]
 
-if is_torch_available():
+try:
+    if not is_torch_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_vit"] = [
         "VIT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "ViTForImageClassification",
@@ -36,14 +53,24 @@ if is_torch_available():
         "ViTPreTrainedModel",
     ]
 
-if is_tf_available():
+try:
+    if not is_tf_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_tf_vit"] = [
         "TFViTForImageClassification",
         "TFViTModel",
         "TFViTPreTrainedModel",
     ]
 
-if is_flax_available():
+try:
+    if not is_flax_available():
+        raise OptionalDependencyNotAvailable()
+except OptionalDependencyNotAvailable:
+    pass
+else:
     _import_structure["modeling_flax_vit"] = [
         "FlaxViTForImageClassification",
         "FlaxViTModel",
@@ -53,10 +80,20 @@ if is_flax_available():
 if TYPE_CHECKING:
     from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig
 
-    if is_vision_available():
+    try:
+        if not is_vision_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .feature_extraction_vit import ViTFeatureExtractor
 
-    if is_torch_available():
+    try:
+        if not is_torch_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_vit import (
             VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
             ViTForImageClassification,
@@ -65,10 +102,20 @@ if TYPE_CHECKING:
             ViTPreTrainedModel,
         )
 
-    if is_tf_available():
+    try:
+        if not is_tf_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel
 
-    if is_flax_available():
+    try:
+        if not is_flax_available():
+            raise OptionalDependencyNotAvailable()
+    except OptionalDependencyNotAvailable:
+        pass
+    else:
         from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel