


from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase_	   =     logging.get_logger(__name__)

lowercase_	   =     {
    'facebook/dpr-ctx_encoder-single-nq-base': (
        'https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json'
    ),
    'facebook/dpr-question_encoder-single-nq-base': (
        'https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json'
    ),
    'facebook/dpr-reader-single-nq-base': (
        'https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json'
    ),
    'facebook/dpr-ctx_encoder-multiset-base': (
        'https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json'
    ),
    'facebook/dpr-question_encoder-multiset-base': (
        'https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json'
    ),
    'facebook/dpr-reader-multiset-base': (
        'https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json'
    ),
}


class 	A_ (	_lowerCAmelCase   ):




      '''simple docstring'''


      __snake_case 	=       """dpr"""




      def __init__(    self:	Dict						,				a:	str=3_0522						,				a:	Optional[Any]=768						,				a:	Tuple=12						,				a:	Optional[int]=12						,				a:	List[str]=3072						,				a:	int="gelu"						,				a:	str=0.1						,				a:	Any=0.1						,				a:	Union[str, Any]=512						,				a:	Any=2						,				a:	Optional[int]=0.0_2						,				a:	List[Any]=1e-12						,				a:	List[str]=0						,				a:	Optional[int]="absolute"						,				a:	Dict = 0						,				**a:	Dict						,				):
       super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_						,				**SCREAMING_SNAKE_CASE_    )

       __lowerCamelCase		:							List[Any]		 =						vocab_size
       __lowerCamelCase		:							Any		 =						hidden_size
       __lowerCamelCase		:							int		 =						num_hidden_layers
       __lowerCamelCase		:							str		 =						num_attention_heads
       __lowerCamelCase		:							Optional[int]		 =						hidden_act
       __lowerCamelCase		:							Union[str, Any]		 =						intermediate_size
       __lowerCamelCase		:							Tuple		 =						hidden_dropout_prob
       __lowerCamelCase		:							Optional[Any]		 =						attention_probs_dropout_prob
       __lowerCamelCase		:							str		 =						max_position_embeddings
       __lowerCamelCase		:							List[str]		 =						type_vocab_size
       __lowerCamelCase		:							Tuple		 =						initializer_range
       __lowerCamelCase		:							Optional[int]		 =						layer_norm_eps
       __lowerCamelCase		:							Tuple		 =						projection_dim
       __lowerCamelCase		:							Tuple		 =						position_embedding_type





from typing import TYPE_CHECKING

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


lowercase_	   =     {
    'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvNextConfig', 'ConvNextOnnxConfig']
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_	   =     ['ConvNextFeatureExtractor']
       lowercase_	   =     ['ConvNextImageProcessor']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_	   =     [
           'CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST',
           'ConvNextForImageClassification',
           'ConvNextModel',
           'ConvNextPreTrainedModel',
           'ConvNextBackbone',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_	   =     [
           'TFConvNextForImageClassification',
           'TFConvNextModel',
           'TFConvNextPreTrainedModel',
       ]

if TYPE_CHECKING:
       from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_convnext import ConvNextFeatureExtractor
              from .image_processing_convnext import ConvNextImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_convnext import (
                  CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  ConvNextBackbone,
                  ConvNextForImageClassification,
                  ConvNextModel,
                  ConvNextPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
       import sys

       lowercase_	   =     _LazyModule(__name__, globals()['__file__'], _import_structure)

