



'''simple docstring'''





from typing import List

import numpy as np

def 			a_	(				_lowerCAmelCase			) -> int:
  __lowerCamelCase			:			List[Any]       			=					{key: len(_lowerCAmelCase			) for key, value in gen_kwargs.items() if isinstance(_lowerCAmelCase			,_lowerCAmelCase			)}
  if len(set(lists_lengths.values()			)			) > 1:
    raise RuntimeError(
        (
            'Sharding is ambiguous for this dataset: '
            + 'we found several data sources lists of different lengths, and we don\'t know over which list we should parallelize:\n'
            + '\n'.join(F'\t- key {key} has length {length}' for key, length in lists_lengths.items()			)
            + '\nTo fix this, check the \'gen_kwargs\' and make sure to use lists only for data sources, '
            + 'and use tuples otherwise. In the end there should only be one single list, or several lists with the same length.'
        )			)
  __lowerCamelCase			:			Optional[Any]       			=					max(lists_lengths.values()			,default=0			)
  return max(1			,_lowerCAmelCase			)

def 			a_	(				_lowerCAmelCase			,_lowerCAmelCase			) -> List[range]:
  __lowerCamelCase			:			List[str]       			=					[]
  for group_idx in range(_lowerCAmelCase			):
    __lowerCamelCase			:			Dict       			=					num_shards // max_num_jobs + (group_idx < (num_shards % max_num_jobs))
    if num_shards_to_add == 0:
      break
    __lowerCamelCase			:			Optional[Any]       			=					shards_indices_per_group[-1].stop if shards_indices_per_group else 0
    __lowerCamelCase			:			int       			=					range(_lowerCAmelCase			,start + num_shards_to_add			)
    shards_indices_per_group.append(_lowerCAmelCase			)
  return shards_indices_per_group

def 			a_	(				_lowerCAmelCase			,_lowerCAmelCase			) -> List[dict]:
  __lowerCamelCase			:			Optional[Any]       			=					_number_of_shards_in_gen_kwargs(_lowerCAmelCase			)
  if num_shards == 1:
    return [dict(_lowerCAmelCase			)]
  else:
    __lowerCamelCase			:			Optional[int]       			=					_distribute_shards(num_shards=_lowerCAmelCase			,max_num_jobs=_lowerCAmelCase			)
    return [
        {
            key: [value[shard_idx] for shard_idx in shard_indices_per_group[group_idx]]
            if isinstance(_lowerCAmelCase			,_lowerCAmelCase			)
            else value
            for key, value in gen_kwargs.items()
        }
        for group_idx in range(len(_lowerCAmelCase			)			)
    ]

def 			a_	(				_lowerCAmelCase			) -> dict:
  return {
      key: [value for gen_kwargs in gen_kwargs_list for value in gen_kwargs[key]]
      if isinstance(gen_kwargs_list[0][key]			,_lowerCAmelCase			)
      else gen_kwargs_list[0][key]
      for key in gen_kwargs_list[0]
  }


def 			a_	(				_lowerCAmelCase			,_lowerCAmelCase			) -> dict:
  __lowerCamelCase			:			Any       			=					{len(_lowerCAmelCase			) for value in gen_kwargs.values() if isinstance(_lowerCAmelCase			,_lowerCAmelCase			)}
  __lowerCamelCase			:			int       			=					{}
  for size in list_sizes:
    __lowerCamelCase			:			List[Any]       			=					list(range(_lowerCAmelCase			)			)
    rng.shuffle(indices_per_size[size]			)
  # Now let's copy the gen_kwargs and shuffle the lists based on their sizes
  __lowerCamelCase			:			List[Any]       			=					dict(_lowerCAmelCase			)
  for key, value in shuffled_kwargs.items():
    if isinstance(_lowerCAmelCase			,_lowerCAmelCase			):
      __lowerCamelCase			:			List[str]       			=					[value[i] for i in indices_per_size[len(_lowerCAmelCase			)]]
  return shuffled_kwargs











'''simple docstring'''





import argparse
from collections import defaultdict

import yaml


_UpperCamelCase											=		'docs/source/en/_toctree.yml'

def 			a_	(				_lowerCAmelCase			) -> Any:
  __lowerCamelCase			:			Optional[int]       			=					defaultdict(_lowerCAmelCase			)
  __lowerCamelCase			:			Optional[Any]       			=					[]
  __lowerCamelCase			:			Union[str, Any]       			=					[]
  for doc in doc_list:
    if "local" in doc:
      counts[doc["local"]] += 1

    if doc["title"].lower() == "overview":
      overview_doc.append({'local': doc['local'], 'title': doc['title']}			)
    else:
      new_doc_list.append(_lowerCAmelCase			)

  __lowerCamelCase			:			Dict       			=					new_doc_list
  __lowerCamelCase			:			Optional[Any]       			=					[key for key, value in counts.items() if value > 1]

  __lowerCamelCase			:			int       			=					[]
  for duplicate_key in duplicates:
    __lowerCamelCase			:			int       			=					list({doc['title'] for doc in doc_list 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 doc_list if 'local' not in counts or counts[doc['local']] == 1]			)
  __lowerCamelCase			:			Dict       			=					sorted(_lowerCAmelCase			,key=lambda _lowerCAmelCase			: s["title"].lower()			)

  # "overview" gets special treatment and is always first
  if len(_lowerCAmelCase			) > 1:
    raise ValueError('{doc_list} has two \'overview\' docs which is not allowed.'			)

  overview_doc.extend(_lowerCAmelCase			)

  # Sort
  return overview_doc

def 			a_	(				_lowerCAmelCase=False			) -> Optional[Any]:
  with open(_lowerCAmelCase			,encoding='utf-8'			) as f:
    __lowerCamelCase			:			str       			=					yaml.safe_load(f.read()			)

  # Get to the API doc
  __lowerCamelCase			:			Union[str, Any]       			=					0
  while content[api_idx]["title"] != "API":
    api_idx += 1
  __lowerCamelCase			:			List[str]       			=					content[api_idx]['sections']

  # Then to the model doc
  __lowerCamelCase			:			List[Any]       			=					0
  while api_doc[scheduler_idx]["title"] != "Schedulers":
    scheduler_idx += 1

  __lowerCamelCase			:			List[Any]       			=					api_doc[scheduler_idx]['sections']
  __lowerCamelCase			:			Optional[Any]       			=					clean_doc_toc(_lowerCAmelCase			)

  __lowerCamelCase			:			str       			=					False
  if new_scheduler_doc != scheduler_doc:
    __lowerCamelCase			:			int       			=					True
    if overwrite:
      __lowerCamelCase			:			Any       			=					new_scheduler_doc

  if diff:
    if overwrite:
      __lowerCamelCase			:			Tuple       			=					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.'			)

def 			a_	(				_lowerCAmelCase=False			) -> List[Any]:
  with open(_lowerCAmelCase			,encoding='utf-8'			) as f:
    __lowerCamelCase			:			List[str]       			=					yaml.safe_load(f.read()			)

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

  # Then to the model doc
  __lowerCamelCase			:			List[Any]       			=					0
  while api_doc[pipeline_idx]["title"] != "Pipelines":
    pipeline_idx += 1

  __lowerCamelCase			:			int       			=					False
  __lowerCamelCase			:			str       			=					api_doc[pipeline_idx]['sections']
  __lowerCamelCase			:			Optional[Any]       			=					[]

  # sort sub pipeline docs
  for pipeline_doc in pipeline_docs:
    if "section" in pipeline_doc:
      __lowerCamelCase			:			str       			=					pipeline_doc['section']
      __lowerCamelCase			:			Optional[Any]       			=					clean_doc_toc(_lowerCAmelCase			)
      if overwrite:
        __lowerCamelCase			:			Union[str, Any]       			=					new_sub_pipeline_doc
    new_pipeline_docs.append(_lowerCAmelCase			)

  # sort overall pipeline doc
  __lowerCamelCase			:			int       			=					clean_doc_toc(_lowerCAmelCase			)

  if new_pipeline_docs != pipeline_docs:
    __lowerCamelCase			:			Tuple       			=					True
    if overwrite:
      __lowerCamelCase			:			int       			=					new_pipeline_docs

  if diff:
    if overwrite:
      __lowerCamelCase			:			Tuple       			=					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__":
   _UpperCamelCase											=		argparse.ArgumentParser()
   parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
   _UpperCamelCase											=		parser.parse_args()

   check_scheduler_doc(args.fix_and_overwrite)
   check_pipeline_doc(args.fix_and_overwrite)






