

import argparse
from collections import defaultdict

import yaml


A_			:					Dict    			=     'docs/source/en/_toctree.yml'

def 		UpperCamelCase   (lowercase_:					Tuple   )	-> List[Any]:
	A__				:       int	  =						defaultdict(lowercase_   )
	A__				:       Tuple	  =						[]
	A__				:       Tuple	  =						[]
	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(lowercase_   )

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

	A__				:       Any	  =						[]
	for duplicate_key in duplicates:
		A__				:       Union[str, Any]	  =						list({doc["""title"""] for doc in doc_list if doc["""local"""] == duplicate_key}   )
		if len(lowercase_   ) > 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]   )
	A__				:       str	  =						sorted(lowercase_       , key=lambda lowercase_   : s["title"].lower()   )

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

	overview_doc.extend(lowercase_   )

	# Sort
	return overview_doc

def 		UpperCamelCase   (lowercase_:					List[Any]=False   )	-> List[Any]:
	with open(lowercase_       , encoding="""utf-8"""   ) as f:
		A__				:       Tuple	  =						yaml.safe_load(f.read()   )

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

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

	A__				:       Optional[Any]	  =						api_doc[scheduler_idx]["""sections"""]
	A__				:       Any	  =						clean_doc_toc(lowercase_   )

	A__				:       Optional[int]	  =						False
	if new_scheduler_doc != scheduler_doc:
		A__				:       Any	  =						True
		if overwrite:
			A__				:       List[Any]	  =						new_scheduler_doc

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

def 		UpperCamelCase   (lowercase_:					List[Any]=False   )	-> int:
	with open(lowercase_       , encoding="""utf-8"""   ) as f:
		A__				:       List[str]	  =						yaml.safe_load(f.read()   )

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

	# Then to the model doc
	A__				:       Optional[int]	  =						0
	while api_doc[pipeline_idx]["title"] != "Pipelines":
		pipeline_idx += 1

	A__				:       Any	  =						False
	A__				:       Tuple	  =						api_doc[pipeline_idx]["""sections"""]
	A__				:       List[Any]	  =						[]

	# sort sub pipeline docs
	for pipeline_doc in pipeline_docs:
		if "section" in pipeline_doc:
			A__				:       List[str]	  =						pipeline_doc["""section"""]
			A__				:       Tuple	  =						clean_doc_toc(lowercase_   )
			if overwrite:
				A__				:       Any	  =						new_sub_pipeline_doc
		new_pipeline_docs.append(lowercase_   )

	# sort overall pipeline doc
	A__				:       Tuple	  =						clean_doc_toc(lowercase_   )

	if new_pipeline_docs != pipeline_docs:
		A__				:       Tuple	  =						True
		if overwrite:
			A__				:       str	  =						new_pipeline_docs

	if diff:
		if overwrite:
			A__				:       Optional[int]	  =						api_doc
			with open(lowercase_       , """w"""       , encoding="""utf-8"""   ) as f:
				f.write(yaml.dump(lowercase_       , allow_unicode=lowercase_   )   )
		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__":
	A_			:					List[Any]    			=     argparse.ArgumentParser()
	parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
	A_			:					Optional[Any]    			=     parser.parse_args()

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






import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


A_			:					Any    			=     logging.get_logger(__name__)



class        _a		:


					'''simple docstring'''






					UpperCAmelCase__:  str    				=			None



@experimental
def 		UpperCamelCase   (lowercase_:					int       , lowercase_:					Any       , lowercase_:					str       , lowercase_:					str       , lowercase_:					List[str]       , lowercase_:					List[Any]       , lowercase_:					Union[str, Any]   )	-> Union[str, Any]:
	if ParallelBackendConfig.backend_name is None:
		return _map_with_multiprocessing_pool(
		    lowercase_       , lowercase_       , lowercase_       , lowercase_       , lowercase_       , lowercase_       , lowercase_   )

	return _map_with_joblib(lowercase_       , lowercase_       , lowercase_       , lowercase_       , lowercase_       , lowercase_       , lowercase_   )

def 		UpperCamelCase   (lowercase_:					Tuple       , lowercase_:					List[Any]       , lowercase_:					Tuple       , lowercase_:					Tuple       , lowercase_:					List[str]       , lowercase_:					Dict       , lowercase_:					Tuple   )	-> Tuple:
	A__				:       Union[str, Any]	  =						num_proc if num_proc <= len(lowercase_   ) else len(lowercase_   )
	A__				:       str	  =						[]  # We organize the splits ourselve (contiguous splits)
	for index in range(lowercase_   ):
		A__				:       Tuple	  =						len(lowercase_   ) // num_proc
		A__				:       Tuple	  =						len(lowercase_   ) % num_proc
		A__				:       Optional[Any]	  =						div * index + min(lowercase_       , lowercase_   )
		A__				:       Union[str, Any]	  =						start + div + (1 if index < mod else 0)
		split_kwds.append((function, iterable[start:end], types, index, disable_tqdm, desc)   )

	if len(lowercase_   ) != sum(len(i[1]   ) for i in split_kwds   ):
		raise ValueError(
		    f"""Error dividing inputs iterable among processes. """
		    f"""Total number of objects {len(lowercase_   )}, """
		    f"""length: {sum(len(i[1]   ) for i in split_kwds   )}"""   )

	logger.info(
	    f"""Spawning {num_proc} processes for {len(lowercase_   )} objects in slices of {[len(i[1]   ) for i in split_kwds]}"""   )
	A__  ,  A__				:       Optional[int]	  =						None, None
	if not disable_tqdm:
		A__  ,  A__				:       List[str]	  =						(RLock(),), tqdm.set_lock
	with Pool(lowercase_       , initargs=lowercase_       , initializer=lowercase_   ) as pool:
		A__				:       Optional[Any]	  =						pool.map(lowercase_       , lowercase_   )
	logger.info(f"""Finished {num_proc} processes"""   )
	A__				:       Tuple	  =						[obj for proc_res in mapped for obj in proc_res]
	logger.info(f"""Unpacked {len(lowercase_   )} objects"""   )

	return mapped

def 		UpperCamelCase   (lowercase_:					Union[str, Any]       , lowercase_:					Dict       , lowercase_:					str       , lowercase_:					Union[str, Any]       , lowercase_:					List[Any]       , lowercase_:					Dict       , lowercase_:					Optional[Any]   )	-> Union[str, Any]:
	# progress bar is not yet supported for _map_with_joblib, because tqdm couldn't accurately be applied to joblib,
	# and it requires monkey-patching joblib internal classes which is subject to change
	import joblib

	with joblib.parallel_backend(ParallelBackendConfig.backend_name       , n_jobs=lowercase_   ):
		return joblib.Parallel()(
		    joblib.delayed(lowercase_   )((function, obj, types, None, True, None)   ) for obj in iterable   )


@experimental
@contextlib.contextmanager
def 		UpperCamelCase   (lowercase_:					str   )	-> str:
	A__				:       int	  =						backend_name

	if backend_name == "spark":
		from joblibspark import register_spark

		register_spark()

		# TODO: call create_cache_and_write_probe if "download" in steps
		# TODO: raise NotImplementedError when Dataset.map etc is called

	try:
		yield
	finally:
		A__				:       Optional[Any]	  =						None



