# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING

import numpy as np
import pyarrow as pa

from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter


if TYPE_CHECKING:
				import torch



class        lowerCamelCase__				(   TensorFormatter[Mapping, "torch.Tensor", Mapping]				):





			def __init__(       self	:	Optional[int]  ,  lowercase__	:	Dict=None  ,  **lowercase__	:	List[Any]						):
										super().__init__(features=lowercase__						)
										_lowerCAmelCase							=							torch_tensor_kwargs
										import torch  # noqa import torch at initialization





			def   SCREAMING_SNAKE_CASE__     (       self	:	Union[str, Any]  ,  lowercase__	:	Union[str, Any]						):
										import torch

										if isinstance(lowercase__  ,  lowercase__						) and column:
																	if all(
																	    isinstance(lowercase__  ,  torch.Tensor						) and x.shape == column[0].shape and x.dtype == column[0].dtype
																	    for x in column						):
																								return torch.stack(lowercase__						)
										return column





			def   SCREAMING_SNAKE_CASE__     (       self	:	List[Any]  ,  lowercase__	:	Union[str, Any]						):
										import torch

										if isinstance(lowercase__  ,  (str, bytes, type(lowercase__						))						):
																	return value
										elif isinstance(lowercase__  ,  (np.character, np.ndarray)						) and np.issubdtype(value.dtype  ,  np.character						):
																	return value.tolist()

										_lowerCAmelCase							=							{}

										if isinstance(lowercase__  ,  (np.number, np.ndarray)						) and np.issubdtype(value.dtype  ,  np.integer						):
																	_lowerCAmelCase							=							{'dtype': torch.intaa}
										elif isinstance(lowercase__  ,  (np.number, np.ndarray)						) and np.issubdtype(value.dtype  ,  np.floating						):
																	_lowerCAmelCase							=							{'dtype': torch.floataa}
										elif config.PIL_AVAILABLE and "PIL" in sys.modules:
																	import PIL.Image

																	if isinstance(lowercase__  ,  PIL.Image.Image						):
																								_lowerCAmelCase							=							np.asarray(lowercase__						)
										return torch.tensor(lowercase__  ,  **{**default_dtype, **self.torch_tensor_kwargs}						)





			def   SCREAMING_SNAKE_CASE__     (       self	:	Optional[int]  ,  lowercase__	:	List[str]						):
										import torch

										# support for torch, tf, jax etc.
										if hasattr(lowercase__  ,  '__array__'						) and not isinstance(lowercase__  ,  torch.Tensor						):
																	_lowerCAmelCase							=							data_struct.__array__()
										# support for nested types like struct of list of struct
										if isinstance(lowercase__  ,  np.ndarray						):
																	if data_struct.dtype == object:  # torch tensors cannot be instantied from an array of objects
																								return self._consolidate([self.recursive_tensorize(lowercase__						) for substruct in data_struct]						)
										elif isinstance(lowercase__  ,  (list, tuple)						):
																	return self._consolidate([self.recursive_tensorize(lowercase__						) for substruct in data_struct]						)
										return self._tensorize(lowercase__						)





			def   SCREAMING_SNAKE_CASE__     (       self	:	List[Any]  ,  lowercase__	:	dict						):
										return map_nested(self._recursive_tensorize  ,  lowercase__  ,  map_list=lowercase__						)





			def   SCREAMING_SNAKE_CASE__     (       self	:	int  ,  lowercase__	:	pa.Table						):
										_lowerCAmelCase							=							self.numpy_arrow_extractor().extract_row(lowercase__						)
										_lowerCAmelCase							=							self.python_features_decoder.decode_row(lowercase__						)
										return self.recursive_tensorize(lowercase__						)





			def   SCREAMING_SNAKE_CASE__     (       self	:	List[Any]  ,  lowercase__	:	pa.Table						):
										_lowerCAmelCase							=							self.numpy_arrow_extractor().extract_column(lowercase__						)
										_lowerCAmelCase							=							self.python_features_decoder.decode_column(lowercase__  ,  pa_table.column_names[0]						)
										_lowerCAmelCase							=							self.recursive_tensorize(lowercase__						)
										_lowerCAmelCase							=							self._consolidate(lowercase__						)
										return column





			def   SCREAMING_SNAKE_CASE__     (       self	:	Optional[int]  ,  lowercase__	:	pa.Table						):
										_lowerCAmelCase							=							self.numpy_arrow_extractor().extract_batch(lowercase__						)
										_lowerCAmelCase							=							self.python_features_decoder.decode_batch(lowercase__						)
										_lowerCAmelCase							=							self.recursive_tensorize(lowercase__						)
										for column_name in batch:
																	_lowerCAmelCase							=							self._consolidate(batch[column_name]						)
										return batch







import argparse
from collections import defaultdict

import yaml


_lowercase:	List[Any]       			=		'''docs/source/en/_toctree.yml'''






def _lowerCamelCase  (		snake_case  ):
							_lowerCAmelCase							=							defaultdict(snake_case  )
							_lowerCAmelCase							=							[]
							_lowerCAmelCase							=							[]
							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(snake_case  )

							_lowerCAmelCase							=							new_doc_list
							_lowerCAmelCase							=							[key for key, value in counts.items() if value > 1]

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

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

							overview_doc.extend(snake_case  )

							# Sort
							return overview_doc






def _lowerCamelCase  (		snake_case=False  ):
							with open(snake_case     , encoding='utf-8'  ) as f:
														_lowerCAmelCase							=							yaml.safe_load(f.read()  )

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

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

							_lowerCAmelCase							=							api_doc[scheduler_idx]['sections']
							_lowerCAmelCase							=							clean_doc_toc(snake_case  )

							_lowerCAmelCase							=							False
							if new_scheduler_doc != scheduler_doc:
														_lowerCAmelCase							=							True
														if overwrite:
																					_lowerCAmelCase							=							new_scheduler_doc

							if diff:
														if overwrite:
																					_lowerCAmelCase							=							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.'  )






def _lowerCamelCase  (		snake_case=False  ):
							with open(snake_case     , encoding='utf-8'  ) as f:
														_lowerCAmelCase							=							yaml.safe_load(f.read()  )

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

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

							_lowerCAmelCase							=							False
							_lowerCAmelCase							=							api_doc[pipeline_idx]['sections']
							_lowerCAmelCase							=							[]

							# sort sub pipeline docs
							for pipeline_doc in pipeline_docs:
														if "section" in pipeline_doc:
																					_lowerCAmelCase							=							pipeline_doc['section']
																					_lowerCAmelCase							=							clean_doc_toc(snake_case  )
																					if overwrite:
																												_lowerCAmelCase							=							new_sub_pipeline_doc
														new_pipeline_docs.append(snake_case  )

							# sort overall pipeline doc
							_lowerCAmelCase							=							clean_doc_toc(snake_case  )

							if new_pipeline_docs != pipeline_docs:
														_lowerCAmelCase							=							True
														if overwrite:
																					_lowerCAmelCase							=							new_pipeline_docs

							if diff:
														if overwrite:
																					_lowerCAmelCase							=							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__":
				_lowercase:	Tuple       			=		argparse.ArgumentParser()
				parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
				_lowercase:	Optional[Any]       			=		parser.parse_args()

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






