




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


SCREAMING_SNAKE_CASE__	:				int  =       {
    'configuration_flaubert': ['FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FlaubertConfig', 'FlaubertOnnxConfig'],
    'tokenization_flaubert': ['FlaubertTokenizer'],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       SCREAMING_SNAKE_CASE__	:				Any  =       [
           'FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
           'FlaubertForMultipleChoice',
           'FlaubertForQuestionAnswering',
           'FlaubertForQuestionAnsweringSimple',
           'FlaubertForSequenceClassification',
           'FlaubertForTokenClassification',
           'FlaubertModel',
           'FlaubertWithLMHeadModel',
           'FlaubertPreTrainedModel',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       SCREAMING_SNAKE_CASE__	:				Optional[Any]  =       [
           'TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
           'TFFlaubertForMultipleChoice',
           'TFFlaubertForQuestionAnsweringSimple',
           'TFFlaubertForSequenceClassification',
           'TFFlaubertForTokenClassification',
           'TFFlaubertModel',
           'TFFlaubertPreTrainedModel',
           'TFFlaubertWithLMHeadModel',
       ]


if TYPE_CHECKING:
       from .configuration_flaubert import FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, FlaubertConfig, FlaubertOnnxConfig
       from .tokenization_flaubert import FlaubertTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flaubert import (
                  FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  FlaubertForMultipleChoice,
                  FlaubertForQuestionAnswering,
                  FlaubertForQuestionAnsweringSimple,
                  FlaubertForSequenceClassification,
                  FlaubertForTokenClassification,
                  FlaubertModel,
                  FlaubertPreTrainedModel,
                  FlaubertWithLMHeadModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_flaubert import (
                  TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFFlaubertForMultipleChoice,
                  TFFlaubertForQuestionAnsweringSimple,
                  TFFlaubertForSequenceClassification,
                  TFFlaubertForTokenClassification,
                  TFFlaubertModel,
                  TFFlaubertPreTrainedModel,
                  TFFlaubertWithLMHeadModel,
              )

else:
       import sys

       SCREAMING_SNAKE_CASE__	:				Any  =       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


SCREAMING_SNAKE_CASE__	:				Dict  =       {
    'configuration_oneformer': ['ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OneFormerConfig'],
    'processing_oneformer': ['OneFormerProcessor'],
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       SCREAMING_SNAKE_CASE__	:				Optional[Any]  =       ['OneFormerImageProcessor']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       SCREAMING_SNAKE_CASE__	:				Optional[int]  =       [
           'ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
           'OneFormerForUniversalSegmentation',
           'OneFormerModel',
           'OneFormerPreTrainedModel',
       ]

if TYPE_CHECKING:
       from .configuration_oneformer import ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, OneFormerConfig
       from .processing_oneformer import OneFormerProcessor

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .image_processing_oneformer import OneFormerImageProcessor
       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_oneformer import (
                  ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  OneFormerForUniversalSegmentation,
                  OneFormerModel,
                  OneFormerPreTrainedModel,
              )


else:
       import sys

       SCREAMING_SNAKE_CASE__	:				str  =       _LazyModule(__name__, globals()['__file__'], _import_structure)






