






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


__lowerCAmelCase       		=      logging.get_logger(__name__)

# TODO: upload to AWS
__lowerCAmelCase       		=      {
    'yjernite/retribert-base-uncased': (
        'https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json'
    ),
}





class 	SCREAMING_SNAKE_CASE					(					lowercase__       ):
			snake_case__  =				'retribert'






			def __init__( self      :			List[Any]  ,						__SCREAMING_SNAKE_CASE      :			List[str]=3_0522  ,						__SCREAMING_SNAKE_CASE      :			str=768  ,						__SCREAMING_SNAKE_CASE      :			Tuple=8  ,						__SCREAMING_SNAKE_CASE      :			Any=12  ,						__SCREAMING_SNAKE_CASE      :			Optional[int]=3072  ,						__SCREAMING_SNAKE_CASE      :			List[str]="gelu"  ,						__SCREAMING_SNAKE_CASE      :			Dict=0.1  ,						__SCREAMING_SNAKE_CASE      :			Optional[Any]=0.1  ,						__SCREAMING_SNAKE_CASE      :			Dict=512  ,						__SCREAMING_SNAKE_CASE      :			Optional[Any]=2  ,						__SCREAMING_SNAKE_CASE      :			Union[str, Any]=0.02  ,						__SCREAMING_SNAKE_CASE      :			Dict=1e-12  ,						__SCREAMING_SNAKE_CASE      :			Optional[Any]=True  ,						__SCREAMING_SNAKE_CASE      :			Dict=128  ,						__SCREAMING_SNAKE_CASE      :			List[str]=0  ,						**__SCREAMING_SNAKE_CASE      :			Optional[Any]  ,						)			->			int:
							super().__init__(pad_token_id=__SCREAMING_SNAKE_CASE  ,						**__SCREAMING_SNAKE_CASE					)

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












'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCAmelCase       		=      {
    'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
    'processing_git': ['GitProcessor'],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase       		=      [
		    'GIT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'GitForCausalLM',
		    'GitModel',
		    'GitPreTrainedModel',
		    'GitVisionModel',
		]

if TYPE_CHECKING:
		from .configuration_git import GIT_PRETRAINED_CONFIG_ARCHIVE_MAP, GitConfig, GitVisionConfig
		from .processing_git import GitProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_git import (
				    GIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    GitForCausalLM,
				    GitModel,
				    GitPreTrainedModel,
				    GitVisionModel,
				)

else:
		import sys

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




