



'''simple docstring'''




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


a   :			Dict					  =    logging.get_logger(__name__)

a   :			Any					  =    {
    """weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json""",
}

class 			UpperCamelCase_ (							__magic_name__			):
	lowercase          = 'roc_bert'





	def __init__(  self		,		A=30522		,		A=768		,		A=12		,		A=12		,		A=3072		,		A="gelu"		,		A=0.1		,		A=0.1		,		A=512		,		A=2		,		A=0.0_2		,		A=1e-12		,		A=True		,		A=0		,		A="absolute"		,		A=None		,		A=True		,		A=True		,		A=768		,		A=910		,		A=512		,		A=24858		,		A=True		,		**A		,		)			->			Tuple:
								UpperCAmelCase     :		Any							     =		vocab_size
								UpperCAmelCase     :		int							     =		max_position_embeddings
								UpperCAmelCase     :		Optional[int]							     =		hidden_size
								UpperCAmelCase     :		Optional[Any]							     =		num_hidden_layers
								UpperCAmelCase     :		Optional[int]							     =		num_attention_heads
								UpperCAmelCase     :		List[str]							     =		intermediate_size
								UpperCAmelCase     :		Dict							     =		hidden_act
								UpperCAmelCase     :		List[Any]							     =		hidden_dropout_prob
								UpperCAmelCase     :		str							     =		attention_probs_dropout_prob
								UpperCAmelCase     :		Union[str, Any]							     =		initializer_range
								UpperCAmelCase     :		Optional[Any]							     =		type_vocab_size
								UpperCAmelCase     :		Any							     =		layer_norm_eps
								UpperCAmelCase     :		str							     =		use_cache
								UpperCAmelCase     :		List[Any]							     =		enable_pronunciation
								UpperCAmelCase     :		Any							     =		enable_shape
								UpperCAmelCase     :		int							     =		pronunciation_embed_dim
								UpperCAmelCase     :		List[str]							     =		pronunciation_vocab_size
								UpperCAmelCase     :		List[str]							     =		shape_embed_dim
								UpperCAmelCase     :		Tuple							     =		shape_vocab_size
								UpperCAmelCase     :		List[str]							     =		concat_input
								UpperCAmelCase     :		Optional[Any]							     =		position_embedding_type
								UpperCAmelCase     :		Optional[Any]							     =		classifier_dropout
								super().__init__(pad_token_id=A		,		**A    )






'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a   :			Optional[int]					  =    {
    """configuration_git""": ["""GIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GitConfig""", """GitVisionConfig"""],
    """processing_git""": ["""GitProcessor"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a   :			Tuple					  =    [
							    """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

							a   :			Tuple					  =    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

