





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


UpperCAmelCase_							=				logging.get_logger(__name__)

UpperCAmelCase_							=				{
    """weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json""",
}
class     UpperCamelCase__					(     lowerCamelCase__				):






		'''simple docstring'''






		__a       :       Tuple       =	"""roc_bert"""






		def __init__(							self,   snake_case__=3_05_22,   snake_case__=7_68,   snake_case__=12,   snake_case__=12,   snake_case__=30_72,   snake_case__="gelu",   snake_case__=0.1,   snake_case__=0.1,   snake_case__=5_12,   snake_case__=2,   snake_case__=0.02,   snake_case__=1E-12,   snake_case__=True,   snake_case__=0,   snake_case__="absolute",   snake_case__=None,   snake_case__=True,   snake_case__=True,   snake_case__=7_68,   snake_case__=9_10,   snake_case__=5_12,   snake_case__=2_48_58,   snake_case__=True,   **snake_case__,   )       -> Tuple:






									"""simple docstring"""
									lowercase_	:   Optional[int]  				=     vocab_size
									lowercase_	:   str  				=     max_position_embeddings
									lowercase_	:   List[Any]  				=     hidden_size
									lowercase_	:   Tuple  				=     num_hidden_layers
									lowercase_	:   str  				=     num_attention_heads
									lowercase_	:   Dict  				=     intermediate_size
									lowercase_	:   str  				=     hidden_act
									lowercase_	:   Any  				=     hidden_dropout_prob
									lowercase_	:   Union[str, Any]  				=     attention_probs_dropout_prob
									lowercase_	:   Any  				=     initializer_range
									lowercase_	:   int  				=     type_vocab_size
									lowercase_	:   Union[str, Any]  				=     layer_norm_eps
									lowercase_	:   Any  				=     use_cache
									lowercase_	:   Any  				=     enable_pronunciation
									lowercase_	:   List[str]  				=     enable_shape
									lowercase_	:   Optional[Any]  				=     pronunciation_embed_dim
									lowercase_	:   Any  				=     pronunciation_vocab_size
									lowercase_	:   Dict  				=     shape_embed_dim
									lowercase_	:   List[str]  				=     shape_vocab_size
									lowercase_	:   List[Any]  				=     concat_input
									lowercase_	:   Optional[int]  				=     position_embedding_type
									lowercase_	:   int  				=     classifier_dropout
									super().__init__(pad_token_id=snake_case__,   **snake_case__  )






from typing import TYPE_CHECKING

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


UpperCAmelCase_							=				{
    """configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxConfig"""],
    """tokenization_m2m_100""": ["""M2M100Tokenizer"""],
}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase_							=				[
							    """M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """M2M100ForConditionalGeneration""",
							    """M2M100Model""",
							    """M2M100PreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_mam_aaa import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, MaMaaaConfig, MaMaaaOnnxConfig
							from .tokenization_mam_aaa import MaMaaaTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mam_aaa import (
														    M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MaMaaaForConditionalGeneration,
														    MaMaaaModel,
														    MaMaaaPreTrainedModel,
														)


else:
							import sys

							UpperCAmelCase_							=				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)