






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


A        =			logging.get_logger(__name__)

A        =			{
    'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/config.json',
    # See all XGLM models at https://huggingface.co/models?filter=xglm
}


class 							__a							(  __A						):





		'''simple docstring'''



		UpperCAmelCase__      :				str				    =						"""xglm"""
		UpperCAmelCase__      :				Union[str, Any]				    =						["""past_key_values"""]

		UpperCAmelCase__      :				Union[str, Any]				    =						{
		    """num_attention_heads""": """attention_heads""",
		    """hidden_size""": """d_model""",
		    """num_hidden_layers""": """num_layers""",
		}


		def __init__(						self ,    UpperCamelCase__=256008 ,    UpperCamelCase__=2048 ,    UpperCamelCase__=1024 ,    UpperCamelCase__=4096 ,    UpperCamelCase__=24 ,    UpperCamelCase__=16 ,    UpperCamelCase__="gelu" ,    UpperCamelCase__=0.1 ,    UpperCamelCase__=0.1 ,    UpperCamelCase__=0.0 ,    UpperCamelCase__=0.0 ,    UpperCamelCase__=0.02 ,    UpperCamelCase__=True ,    UpperCamelCase__=True ,    UpperCamelCase__=2 ,    UpperCamelCase__=1 ,    UpperCamelCase__=0 ,    UpperCamelCase__=2 ,    **UpperCamelCase__ ,    ):
						SCREAMING_SNAKE_CASE_   :	Any													=   vocab_size
						SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   max_position_embeddings
						SCREAMING_SNAKE_CASE_   :	Tuple													=   d_model
						SCREAMING_SNAKE_CASE_   :	Dict													=   ffn_dim
						SCREAMING_SNAKE_CASE_   :	Tuple													=   num_layers
						SCREAMING_SNAKE_CASE_   :	Dict													=   attention_heads
						SCREAMING_SNAKE_CASE_   :	str													=   activation_function
						SCREAMING_SNAKE_CASE_   :	List[str]													=   dropout
						SCREAMING_SNAKE_CASE_   :	str													=   attention_dropout
						SCREAMING_SNAKE_CASE_   :	Tuple													=   activation_dropout
						SCREAMING_SNAKE_CASE_   :	List[Any]													=   layerdrop
						SCREAMING_SNAKE_CASE_   :	str													=   init_std
						SCREAMING_SNAKE_CASE_   :	List[str]													=   scale_embedding  # scale factor will be sqrt(d_model) if True
						SCREAMING_SNAKE_CASE_   :	List[str]													=   use_cache

						super().__init__(
						    pad_token_id=UpperCamelCase__ ,    bos_token_id=UpperCamelCase__ ,    eos_token_id=UpperCamelCase__ ,    decoder_start_token_id=UpperCamelCase__ ,    **UpperCamelCase__ ,    )











import importlib
import inspect
import os
import re


# 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
A        =			'src/transformers'


# This is to make sure the transformers module imported is the one in the repo.
A        =			importlib.util.spec_from_file_location(
    'transformers',
    os.path.join(PATH_TO_TRANSFORMERS, '__init__.py'),
    submodule_search_locations=[PATH_TO_TRANSFORMERS],
)
A        =			spec.loader.load_module()

A        =			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)`
A        =			re.compile('\[(.+?)\]\((https://huggingface\.co/.+?)\)')


A        =			{
    'CLIPConfigMixin',
    'DecisionTransformerConfigMixin',
    'EncoderDecoderConfigMixin',
    'RagConfigMixin',
    'SpeechEncoderDecoderConfigMixin',
    'VisionEncoderDecoderConfigMixin',
    'VisionTextDualEncoderConfigMixin',
}



def 					_lowerCamelCase(			):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	Optional[int]													=   []

				for config_class in list(CONFIG_MAPPING.values()      ):
								SCREAMING_SNAKE_CASE_   :	int													=   False

								# source code of `config_class`
								SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   inspect.getsource(lowerCAmelCase__      )
								SCREAMING_SNAKE_CASE_   :	List[Any]													=   _re_checkpoint.findall(lowerCAmelCase__      )

								for checkpoint in checkpoints:
												# Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
												# For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
												SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_   :	Tuple													=   checkpoint

												# verify the checkpoint name corresponds to the checkpoint link
												SCREAMING_SNAKE_CASE_   :	List[str]													=   F'''https://huggingface.co/{ckpt_name}'''
												if ckpt_link == ckpt_link_from_name:
																SCREAMING_SNAKE_CASE_   :	Optional[int]													=   True
																break

								SCREAMING_SNAKE_CASE_   :	Tuple													=   config_class.__name__
								if not checkpoint_found and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
												configs_without_checkpoint.append(lowerCAmelCase__      )

				if len(lowerCAmelCase__      ) > 0:
								SCREAMING_SNAKE_CASE_   :	str													=   '\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()