

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


SCREAMING_SNAKE_CASE_            = logging.get_logger(__name__)

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

class 			a					(		UpperCAmelCase			):
						_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_=0.02  ,   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_  ,   ):







										'''simple docstring'''


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





import inspect
import re

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
SCREAMING_SNAKE_CASE_            = 'src/transformers'


# This is to make sure the transformers module imported is the one in the repo.
SCREAMING_SNAKE_CASE_            = direct_transformers_import(PATH_TO_TRANSFORMERS)

SCREAMING_SNAKE_CASE_            = transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
SCREAMING_SNAKE_CASE_            = re.compile(R'\[(.+?)\]\((https://huggingface\.co/.+?)\)')


SCREAMING_SNAKE_CASE_            = {
    'DecisionTransformerConfig',
    'EncoderDecoderConfig',
    'MusicgenConfig',
    'RagConfig',
    'SpeechEncoderDecoderConfig',
    'TimmBackboneConfig',
    'VisionEncoderDecoderConfig',
    'VisionTextDualEncoderConfig',
    'LlamaConfig',
}

def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					Dict	)				->    Union[str, Any]:
				_UpperCAmelCase    :						List[Any]							=      None

				# source code of `config_class`
				_UpperCAmelCase    :						int							=      inspect.getsource(lowerCAmelCase	)
				_UpperCAmelCase    :						Tuple							=      _re_checkpoint.findall(lowerCAmelCase	)

				# Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
				# For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
				for ckpt_name, ckpt_link in checkpoints:
								# allow the link to end with `/`
								if ckpt_link.endswith("/"	):
												_UpperCAmelCase    :						Dict							=      ckpt_link[:-1]

								# verify the checkpoint name corresponds to the checkpoint link
								_UpperCAmelCase    :						Any							=      F'https://huggingface.co/{ckpt_name}'
								if ckpt_link == ckpt_link_from_name:
												_UpperCAmelCase    :						Union[str, Any]							=      ckpt_name
												break

				return checkpoint

def 							__SCREAMING_SNAKE_CASE							(			)				->    Dict:
				_UpperCAmelCase    :						Any							=      []

				for config_class in list(CONFIG_MAPPING.values()	):
								# Skip deprecated models
								if "models.deprecated" in config_class.__module__:
												continue
								_UpperCAmelCase    :						int							=      get_checkpoint_from_config_class(lowerCAmelCase	)

								_UpperCAmelCase    :						Tuple							=      config_class.__name__
								if checkpoint is None and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
												configs_without_checkpoint.append(lowerCAmelCase	)

				if len(lowerCAmelCase	) > 0:
								_UpperCAmelCase    :						int							=      "\n".join(sorted(lowerCAmelCase	)	)
								raise ValueError(F'The following configurations don\'t contain any valid checkpoint:\n{message}'	)


if __name__ == "__main__":
					check_config_docstrings_have_checkpoints()


