




'''simple docstring'''





import fire
from torch.utils.data import DataLoader
from tqdm import tqdm

from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save


def 					UpperCamelCase_(     snake_case							:	int							,    snake_case							:	List[Any]							,    snake_case							:	Tuple=1_0_2_4							,    snake_case							:	List[Any]=1_0_2_4							,    snake_case							:	Optional[int]=False							,    **snake_case							:	Optional[Any]					):

							'''simple docstring'''






							snake_case_      =				AutoTokenizer.from_pretrained(A__					)
							snake_case_      =				SeqaSeqDataset(A__							,    A__							,    A__							,    A__							,    type_path="train"							,    **A__					)
							snake_case_      =				tok.pad_token_id

							def get_lens(snake_case							:	Dict					):
														snake_case_      =				tqdm(
														    DataLoader(A__							,    batch_size=5_1_2							,    num_workers=8							,    shuffle=A__							,    collate_fn=ds.collate_fn					)							,    desc=str(ds.len_file					)							,    )
														snake_case_      =				[]
														for batch in dl:
																					snake_case_      =				batch["""input_ids"""].ne(A__					).sum(1					).tolist()
																					snake_case_      =				batch["""labels"""].ne(A__					).sum(1					).tolist()
																					if consider_target:
																												for src, tgt in zip(A__							,    A__					):
																																			max_lens.append(max(A__							,    A__					)					)
																					else:
																												max_lens.extend(A__					)
														return max_lens

							snake_case_      =				get_lens(A__					)
							snake_case_      =				SeqaSeqDataset(A__							,    A__							,    A__							,    A__							,    type_path="val"							,    **A__					)
							snake_case_      =				get_lens(A__					)
							pickle_save(A__							,    train_ds.len_file					)
							pickle_save(A__							,    val_ds.len_file					)


if __name__ == "__main__":
		fire.Fire(save_len_file)











'''simple docstring'''





import argparse
from collections import defaultdict

import yaml


_SCREAMING_SNAKE_CASE							:       Optional[Any]						=			"docs/source/en/_toctree.yml"


def 					UpperCamelCase_(     snake_case							:	Optional[Any]					):

							'''simple docstring'''






							snake_case_      =				defaultdict(snake_case					)
							for doc in model_doc:
														counts[doc["local"]] += 1
							snake_case_      =				[key for key, value in counts.items() if value > 1]

							snake_case_      =				[]
							for duplicate_key in duplicates:
														snake_case_      =				list({doc["title"] for doc in model_doc if doc["local"] == duplicate_key}					)
														if len(snake_case					) > 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(snake_case							,    key=lambda snake_case					: s["title"].lower()					)


def 					UpperCamelCase_(     snake_case							:	Optional[int]=False					):

							'''simple docstring'''






							with open(snake_case							,    encoding="utf-8"					) as f:
														snake_case_      =				yaml.safe_load(f.read()					)

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

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

							snake_case_      =				api_doc[model_idx]["sections"]

							snake_case_      =				[(idx, section) for idx, section in enumerate(snake_case					) if "sections" in section]
							snake_case_      =				False
							for idx, modality_doc in modalities_docs:
														snake_case_      =				modality_doc["sections"]
														snake_case_      =				clean_model_doc_toc(snake_case					)

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

							if diff:
														if overwrite:
																					snake_case_      =				model_doc
																					snake_case_      =				api_doc
																					with open(snake_case							,    "w"							,    encoding="utf-8"					) as f:
																												f.write(yaml.dump(snake_case							,    allow_unicode=snake_case					)					)
														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__":
		_SCREAMING_SNAKE_CASE							:       List[str]						=			argparse.ArgumentParser()
		parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
		_SCREAMING_SNAKE_CASE							:       Any						=			parser.parse_args()

		check_model_doc(args.fix_and_overwrite)




