



'''simple docstring'''







import warnings

from ...utils import logging
from .image_processing_conditional_detr import ConditionalDetrImageProcessor


SCREAMING_SNAKE_CASE__     : str				=   logging.get_logger(__name__)




class 				__lowerCAmelCase(							lowerCAmelCase__      ):






			def __init__(   self  :							str      ,       *SCREAMING_SNAKE_CASE  :							Dict      ,       **SCREAMING_SNAKE_CASE  :							str	):




					"""simple docstring"""







					warnings.warn(
					    'The class ConditionalDetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
					    ' Please use ConditionalDetrImageProcessor instead.'      ,       SCREAMING_SNAKE_CASE      ,       )
					super().__init__(*SCREAMING_SNAKE_CASE      ,       **SCREAMING_SNAKE_CASE	)





'''simple docstring'''







from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__     : int				=   {"""configuration_bert_generation""": ["""BertGenerationConfig"""]}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__     : List[Any]				=   ["""BertGenerationTokenizer"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__     : Optional[Any]				=   [
							    """BertGenerationDecoder""",
							    """BertGenerationEncoder""",
							    """BertGenerationPreTrainedModel""",
							    """load_tf_weights_in_bert_generation""",
							]


if TYPE_CHECKING:
							from .configuration_bert_generation import BertGenerationConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_bert_generation import BertGenerationTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_bert_generation import (
														    BertGenerationDecoder,
														    BertGenerationEncoder,
														    BertGenerationPreTrainedModel,
														    load_tf_weights_in_bert_generation,
														)

else:
							import sys

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