

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowerCamelCase									= {
    '''configuration_sam''': [
        '''SAM_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SamConfig''',
        '''SamMaskDecoderConfig''',
        '''SamPromptEncoderConfig''',
        '''SamVisionConfig''',
    ],
    '''processing_sam''': ['''SamProcessor'''],
}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase									= [
           '''SAM_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''SamModel''',
           '''SamPreTrainedModel''',
       ]
try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase									= [
           '''TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''TFSamModel''',
           '''TFSamPreTrainedModel''',
       ]
try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase									= ['''SamImageProcessor''']


if TYPE_CHECKING:
       from .configuration_sam import (
           SAM_PRETRAINED_CONFIG_ARCHIVE_MAP,
           SamConfig,
           SamMaskDecoderConfig,
           SamPromptEncoderConfig,
           SamVisionConfig,
       )
       from .processing_sam import SamProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_sam import SAM_PRETRAINED_MODEL_ARCHIVE_LIST, SamModel, SamPreTrainedModel

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_sam import TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, TFSamModel, TFSamPreTrainedModel

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .image_processing_sam import SamImageProcessor

else:
       import sys

       lowerCamelCase									= _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



from typing import TYPE_CHECKING

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


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

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase									= [
           '''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:
       lowerCamelCase									= [
           '''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

       lowerCamelCase									= _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
