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


SCREAMING_SNAKE_CASE			:						Optional[int]				  =		logging.get_logger(__name__)

SCREAMING_SNAKE_CASE			:						Union[str, Any]				  =		{
    """google/realm-cc-news-pretrained-embedder""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-encoder""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-scorer""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-openqa""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/config.json"""
    ),
    """google/realm-orqa-nq-openqa""": """https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/config.json""",
    """google/realm-orqa-nq-reader""": """https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/config.json""",
    """google/realm-orqa-wq-openqa""": """https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/config.json""",
    """google/realm-orqa-wq-reader""": """https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/config.json""",
    # See all REALM models at https://huggingface.co/models?filter=realm
}
class  A_			(							lowerCAmelCase__			):
  _SCREAMING_SNAKE_CASE     					=      '''realm'''

  def __init__(		self			:   Optional[Any]  ,				__SCREAMING_SNAKE_CASE			:   int=3_05_22  ,				__SCREAMING_SNAKE_CASE			:   List[str]=7_68  ,				__SCREAMING_SNAKE_CASE			:   Any=1_28  ,				__SCREAMING_SNAKE_CASE			:   List[Any]=12  ,				__SCREAMING_SNAKE_CASE			:   Any=12  ,				__SCREAMING_SNAKE_CASE			:   Tuple=8  ,				__SCREAMING_SNAKE_CASE			:   List[str]=30_72  ,				__SCREAMING_SNAKE_CASE			:   Any="gelu_new"  ,				__SCREAMING_SNAKE_CASE			:   Optional[int]=0.1  ,				__SCREAMING_SNAKE_CASE			:   Optional[Any]=0.1  ,				__SCREAMING_SNAKE_CASE			:   Optional[Any]=5_12  ,				__SCREAMING_SNAKE_CASE			:   List[str]=2  ,				__SCREAMING_SNAKE_CASE			:   Optional[Any]=0.02  ,				__SCREAMING_SNAKE_CASE			:   Any=1E-12  ,				__SCREAMING_SNAKE_CASE			:   str=2_56  ,				__SCREAMING_SNAKE_CASE			:   Tuple=10  ,				__SCREAMING_SNAKE_CASE			:   Any=1E-3  ,				__SCREAMING_SNAKE_CASE			:   Tuple=5  ,				__SCREAMING_SNAKE_CASE			:   Any=3_20  ,				__SCREAMING_SNAKE_CASE			:   Tuple=13_35_37_18  ,				__SCREAMING_SNAKE_CASE			:   int=50_00  ,				__SCREAMING_SNAKE_CASE			:   int=1  ,				__SCREAMING_SNAKE_CASE			:   Tuple=0  ,				__SCREAMING_SNAKE_CASE			:   Dict=2  ,				**__SCREAMING_SNAKE_CASE			:   Union[str, Any]  ,				):
   super().__init__(pad_token_id=__lowerCAmelCase  ,				bos_token_id=__lowerCAmelCase  ,				eos_token_id=__lowerCAmelCase  ,				**__lowerCAmelCase							)

   # Common config
   __a							=	vocab_size
   __a							=	max_position_embeddings
   __a							=	hidden_size
   __a							=	retriever_proj_size
   __a							=	num_hidden_layers
   __a							=	num_attention_heads
   __a							=	num_candidates
   __a							=	intermediate_size
   __a							=	hidden_act
   __a							=	hidden_dropout_prob
   __a							=	attention_probs_dropout_prob
   __a							=	initializer_range
   __a							=	type_vocab_size
   __a							=	layer_norm_eps

   # Reader config
   __a							=	span_hidden_size
   __a							=	max_span_width
   __a							=	reader_layer_norm_eps
   __a							=	reader_beam_size
   __a							=	reader_seq_len

   # Retrieval config
   __a							=	num_block_records
   __a							=	searcher_beam_size



'''simple docstring'''




from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__lowercase        =    logging.get_logger(__name__)

__lowercase        =    {
    '''google/mobilenet_v1_1.0_224''': '''https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json''',
    '''google/mobilenet_v1_0.75_192''': '''https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json''',
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}






class 							a__(   lowerCAmelCase__      ):


			'''simple docstring'''






			UpperCAmelCase_     :	List[str]						=			'''mobilenet_v1'''



			def __init__(  self			,       __lowerCAmelCase=3			,       __lowerCAmelCase=224			,       __lowerCAmelCase=1.0			,       __lowerCAmelCase=8			,       __lowerCAmelCase="relu6"			,       __lowerCAmelCase=True			,       __lowerCAmelCase=0.999			,       __lowerCAmelCase=0.02			,       __lowerCAmelCase=0.001			,       **__lowerCAmelCase			,       ):




					"""simple docstring"""


					super().__init__(**__lowerCAmelCase)

					if depth_multiplier <= 0:
							raise ValueError("""depth_multiplier must be greater than zero.""")

					lowerCAmelCase     =    num_channels
					lowerCAmelCase     =    image_size
					lowerCAmelCase     =    depth_multiplier
					lowerCAmelCase     =    min_depth
					lowerCAmelCase     =    hidden_act
					lowerCAmelCase     =    tf_padding
					lowerCAmelCase     =    classifier_dropout_prob
					lowerCAmelCase     =    initializer_range
					lowerCAmelCase     =    layer_norm_eps







class 							a__(   lowerCAmelCase__      ):


			'''simple docstring'''






			UpperCAmelCase_     :	Dict						=			version.parse('''1.11'''      )



			@property
			def 				a_			(  self):




					"""simple docstring"""


					return OrderedDict([("""pixel_values""", {0: """batch"""})])



			@property
			def 				a_			(  self):




					"""simple docstring"""


					if self.task == "image-classification":
							return OrderedDict([("""logits""", {0: """batch"""})])
					else:
							return OrderedDict([("""last_hidden_state""", {0: """batch"""}), ("""pooler_output""", {0: """batch"""})])







			@property
			def 				a_			(  self):




					"""simple docstring"""


					return 1E-4




