
import warnings

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


lowercase__	:Union[str, Any]										=					logging.get_logger(__name__)

lowercase__	:Dict										=					{
    "xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/config.json",
    "xlnet-large-cased": "https://huggingface.co/xlnet-large-cased/resolve/main/config.json",
}







class        lowercase	(      SCREAMING_SNAKE_CASE__	):
							lowercase_ : int       ='''xlnet'''
							lowercase_ : List[str]       =['''mems''']
							lowercase_ : Union[str, Any]       ={
							    '''n_token''': '''vocab_size''',  # Backward compatibility
							    '''hidden_size''': '''d_model''',
							    '''num_attention_heads''': '''n_head''',
							    '''num_hidden_layers''': '''n_layer''',
							}




							def __init__(       self     ,A__=3_2_0_0_0     ,A__=1_0_2_4     ,A__=2_4     ,A__=1_6     ,A__=4_0_9_6     ,A__="gelu"     ,A__=True     ,A__="bi"     ,A__=0.02     ,A__=1E-12     ,A__=0.1     ,A__=5_1_2     ,A__=None     ,A__=True     ,A__=False     ,A__=False     ,A__=-1     ,A__=False     ,A__="last"     ,A__=True     ,A__="tanh"     ,A__=0.1     ,A__=5     ,A__=5     ,A__=5     ,A__=1     ,A__=2     ,**A__     ,):
												lowercase					=		vocab_size
												lowercase					=		d_model
												lowercase					=		n_layer
												lowercase					=		n_head
												if d_model % n_head != 0:
																	raise ValueError(f'\'d_model % n_head\' ({d_model % n_head}) should be equal to 0')
												if "d_head" in kwargs:
																	if kwargs["d_head"] != d_model // n_head:
																						raise ValueError(
																						    f'`d_head` ({kwargs["d_head"]}) should be equal to `d_model // n_head` ({d_model // n_head})')
												lowercase					=		d_model // n_head
												lowercase					=		ff_activation
												lowercase					=		d_inner
												lowercase					=		untie_r
												lowercase					=		attn_type

												lowercase					=		initializer_range
												lowercase					=		layer_norm_eps

												lowercase					=		dropout
												lowercase					=		mem_len
												lowercase					=		reuse_len
												lowercase					=		bi_data
												lowercase					=		clamp_len
												lowercase					=		same_length

												lowercase					=		summary_type
												lowercase					=		summary_use_proj
												lowercase					=		summary_activation
												lowercase					=		summary_last_dropout
												lowercase					=		start_n_top
												lowercase					=		end_n_top

												lowercase					=		bos_token_id
												lowercase					=		pad_token_id
												lowercase					=		eos_token_id

												if "use_cache" in kwargs:
																	warnings.warn(
																	    '''The `use_cache` argument is deprecated and will be removed in a future version, use `use_mems_eval`'''
																	    ''' instead.'''     ,A__     ,)
																	lowercase					=		kwargs['''use_cache''']

												lowercase					=		use_mems_eval
												lowercase					=		use_mems_train
												super().__init__(pad_token_id=A__     ,bos_token_id=A__     ,eos_token_id=A__     ,**A__)




							@property
							def 				A__   (       self):
												logger.info(f'The model {self.model_type} is one of the few models that has no sequence length limit.')
												return -1





							@max_position_embeddings.setter
							def 				A__   (       self     ,A__):
												# Message copied from Transformer-XL documentation
												raise NotImplementedError(
												    f'The model {self.model_type} is one of the few models that has no sequence length limit.')






import argparse
from collections import defaultdict

import yaml


lowercase__	:Optional[int]										=					"docs/source/en/_toctree.yml"



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					lowercase					=		defaultdict(lowerCAmelCase__	)
					for doc in model_doc:
										counts[doc["local"]] += 1
					lowercase					=		[key for key, value in counts.items() if value > 1]

					lowercase					=		[]
					for duplicate_key in duplicates:
										lowercase					=		list({doc['''title'''] for doc in model_doc if doc['''local'''] == duplicate_key}	)
										if len(lowerCAmelCase__	) > 1:
															raise ValueError(
															    f'{duplicate_key} is present several times in the documentation table of content at '
															    '''`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the '''
															    '''others.'''	)
										# Only add this once
										new_doc.append({'''local''': duplicate_key, '''title''': titles[0]}	)

					# Add none duplicate-keys
					new_doc.extend([doc for doc in model_doc if counts[doc['''local''']] == 1]	)

					# Sort
					return sorted(lowerCAmelCase__				,    key=lambda lowerCAmelCase__	: s["title"].lower()	)



def  UpperCamelCase					(							lowerCAmelCase__=False	):
					'''simple docstring'''
					with open(lowerCAmelCase__				,    encoding='''utf-8'''	) as f:
										lowercase					=		yaml.safe_load(f.read()	)

					# Get to the API doc
					lowercase					=		0
					while content[api_idx]["title"] != "API":
										api_idx += 1
					lowercase					=		content[api_idx]['''sections''']

					# Then to the model doc
					lowercase					=		0
					while api_doc[model_idx]["title"] != "Models":
										model_idx += 1

					lowercase					=		api_doc[model_idx]['''sections''']

					lowercase					=		[(idx, section) for idx, section in enumerate(lowerCAmelCase__	) if '''sections''' in section]
					lowercase					=		False
					for idx, modality_doc in modalities_docs:
										lowercase					=		modality_doc['''sections''']
										lowercase					=		clean_model_doc_toc(lowerCAmelCase__	)

										if old_modality_doc != new_modality_doc:
															lowercase					=		True
															if overwrite:
																				lowercase					=		new_modality_doc

					if diff:
										if overwrite:
															lowercase					=		model_doc
															lowercase					=		api_doc
															with open(lowerCAmelCase__				,    '''w'''				,    encoding='''utf-8'''	) as f:
																				f.write(yaml.dump(lowerCAmelCase__				,    allow_unicode=lowerCAmelCase__	)	)
										else:
															raise ValueError(
															    '''The model doc part of the table of content is not properly sorted, run `make style` to fix this.'''	)


if __name__ == "__main__":
							lowercase__	:Any										=					argparse.ArgumentParser()
							parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
							lowercase__	:int										=					parser.parse_args()

							check_model_doc(args.fix_and_overwrite)




