





from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE							=						{
    'configuration_efficientformer': [
        'EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'EfficientFormerConfig',
    ]
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_SCREAMING_SNAKE_CASE							=						['EfficientFormerImageProcessor']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_SCREAMING_SNAKE_CASE							=						[
						    'EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'EfficientFormerForImageClassification',
						    'EfficientFormerForImageClassificationWithTeacher',
						    'EfficientFormerModel',
						    'EfficientFormerPreTrainedModel',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_SCREAMING_SNAKE_CASE							=						[
						    'TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'TFEfficientFormerForImageClassification',
						    'TFEfficientFormerForImageClassificationWithTeacher',
						    'TFEfficientFormerModel',
						    'TFEfficientFormerPreTrainedModel',
						]

if TYPE_CHECKING:
						from .configuration_efficientformer import EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientFormerConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .image_processing_efficientformer import EfficientFormerImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_efficientformer import (
												    EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    EfficientFormerForImageClassification,
												    EfficientFormerForImageClassificationWithTeacher,
												    EfficientFormerModel,
												    EfficientFormerPreTrainedModel,
												)
						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_efficientformer import (
												    TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFEfficientFormerForImageClassification,
												    TFEfficientFormerForImageClassificationWithTeacher,
												    TFEfficientFormerModel,
												    TFEfficientFormerPreTrainedModel,
												)

else:
						import sys

						_SCREAMING_SNAKE_CASE							=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


SCREAMING_SNAKE_CASE__       :      List[Any]  =   {'processing_layoutxlm': ['LayoutXLMProcessor']}

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

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       SCREAMING_SNAKE_CASE__       :      Dict  =   ['LayoutXLMTokenizerFast']

if TYPE_CHECKING:
       from .processing_layoutxlm import LayoutXLMProcessor

       try:
              if not is_sentencepiece_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_layoutxlm import LayoutXLMTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_layoutxlm_fast import LayoutXLMTokenizerFast

else:
       import sys

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






