



'''simple docstring'''

import argparse
import collections
import importlib.util
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
__lowerCAmelCase		    =     '''src/diffusers'''
__lowerCAmelCase		    =     '''docs/source/en'''
__lowerCAmelCase		    =     '''.'''



def   __lowerCamelCase  (   lowerCAmelCase_		,    lowerCAmelCase_		,    lowerCAmelCase_						)    ->   str:
		with open(lowerCAmelCase_		,    'r'		,    encoding='utf-8'		,    newline='\n'						) as f:
				_a  :   Any				 =							f.readlines()
		# Find the start prompt.
		_a  :   Any				 =							0
		while not lines[start_index].startswith(lowerCAmelCase_						):
				start_index += 1
		start_index += 1

		_a  :   Any				 =							start_index
		while not lines[end_index].startswith(lowerCAmelCase_						):
				end_index += 1
		end_index -= 1

		while len(lines[start_index]						) <= 1:
				start_index += 1
		while len(lines[end_index]						) <= 1:
				end_index -= 1
		end_index += 1
		return "".join(lines[start_index:end_index]						), start_index, end_index, lines


# Add here suffixes that are used to identify models, separated by |
__lowerCAmelCase		    =     '''Model|Encoder|Decoder|ForConditionalGeneration'''
# Regexes that match TF/Flax/PT model names.
__lowerCAmelCase		    =     re.compile(r'''TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')
__lowerCAmelCase		    =     re.compile(r'''Flax(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')
# Will match any TF or Flax model too so need to be in an else branch afterthe two previous regexes.
__lowerCAmelCase		    =     re.compile(r'''(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')


# This is to make sure the diffusers module imported is the one in the repo.
__lowerCAmelCase		    =     importlib.util.spec_from_file_location(
    '''diffusers''',
    os.path.join(TRANSFORMERS_PATH, '''__init__.py'''),
    submodule_search_locations=[TRANSFORMERS_PATH],
)
__lowerCAmelCase		    =     spec.loader.load_module()



def   __lowerCamelCase  (   lowerCAmelCase_						)    ->   str:
		_a  :   List[Any]				 =							re.finditer('.+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)'		,    lowerCAmelCase_						)
		return [m.group(0						) for m in matches]



def   __lowerCamelCase  (   lowerCAmelCase_		,    lowerCAmelCase_						)    ->   str:
		_a  :   Optional[int]				 =							2 if text == '✅' or text == '❌' else len(lowerCAmelCase_						)
		_a  :   int				 =							(width - text_length) // 2
		_a  :   Optional[int]				 =							width - text_length - left_indent
		return " " * left_indent + text + " " * right_indent



def   __lowerCamelCase  (   )    ->   Any:
		_a  :   Dict				 =							diffusers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
		_a  :   Dict				 =							{
		    name: config_mapping_names[code]
		    for code, name in diffusers_module.MODEL_NAMES_MAPPING.items()
		    if code in config_mapping_names
		}
		_a  :   Tuple				 =							{name: config.replace('ConfigMixin'		,    ''						) for name, config in model_name_to_config.items()}

		# Dictionaries flagging if each model prefix has a slow/fast tokenizer, backend in PT/TF/Flax.
		_a  :   int				 =							collections.defaultdict(lowerCAmelCase_						)
		_a  :   int				 =							collections.defaultdict(lowerCAmelCase_						)
		_a  :   List[Any]				 =							collections.defaultdict(lowerCAmelCase_						)
		_a  :   Optional[int]				 =							collections.defaultdict(lowerCAmelCase_						)
		_a  :   Dict				 =							collections.defaultdict(lowerCAmelCase_						)

		# Let's lookup through all diffusers object (once).
		for attr_name in dir(lowerCAmelCase_						):
				_a  :   Dict				 =							None
				if attr_name.endswith('Tokenizer'						):
						_a  :   List[Any]				 =							slow_tokenizers
						_a  :   Tuple				 =							attr_name[:-9]
				elif attr_name.endswith('TokenizerFast'						):
						_a  :   Any				 =							fast_tokenizers
						_a  :   int				 =							attr_name[:-13]
				elif _re_tf_models.match(lowerCAmelCase_						) is not None:
						_a  :   int				 =							tf_models
						_a  :   List[Any]				 =							_re_tf_models.match(lowerCAmelCase_						).groups()[0]
				elif _re_flax_models.match(lowerCAmelCase_						) is not None:
						_a  :   int				 =							flax_models
						_a  :   Optional[Any]				 =							_re_flax_models.match(lowerCAmelCase_						).groups()[0]
				elif _re_pt_models.match(lowerCAmelCase_						) is not None:
						_a  :   Optional[int]				 =							pt_models
						_a  :   Tuple				 =							_re_pt_models.match(lowerCAmelCase_						).groups()[0]

				if lookup_dict is not None:
						while len(lowerCAmelCase_						) > 0:
								if attr_name in model_name_to_prefix.values():
										_a  :   str				 =							True
										break
								# Try again after removing the last word in the name
								_a  :   Tuple				 =							''.join(camel_case_split(lowerCAmelCase_						)[:-1]						)

    # Let's build that table!
		_a  :   List[Any]				 =							list(model_name_to_config.keys()						)
		model_names.sort(key=str.lower						)
		_a  :   int				 =							['Model', 'Tokenizer slow', 'Tokenizer fast', 'PyTorch support', 'TensorFlow support', 'Flax Support']
		# We'll need widths to properly display everything in the center (+2 is to leave one extra space on each side).
		_a  :   Union[str, Any]				 =							[len(lowerCAmelCase_						) + 2 for c in columns]
		_a  :   Optional[int]				 =							max([len(lowerCAmelCase_						) for name in model_names]						) + 2

		# Build the table per se
		_a  :   int				 =							'|' + '|'.join([_center_text(lowerCAmelCase_		,    lowerCAmelCase_						) for c, w in zip(lowerCAmelCase_		,    lowerCAmelCase_						)]						) + '|\n'
		# Use ":-----:" format to center-aligned table cell texts
		table += "|" + "|".join([':' + '-' * (w - 2) + ':' for w in widths]						) + "|\n"

		_a  :   int				 =							{True: '✅', False: '❌'}
		for name in model_names:
				_a  :   Optional[Any]				 =							model_name_to_prefix[name]
				_a  :   Tuple				 =							[
				    name,
				    check[slow_tokenizers[prefix]],
				    check[fast_tokenizers[prefix]],
				    check[pt_models[prefix]],
				    check[tf_models[prefix]],
				    check[flax_models[prefix]],
				]
				table += "|" + "|".join([_center_text(lowerCAmelCase_		,    lowerCAmelCase_						) for l, w in zip(lowerCAmelCase_		,    lowerCAmelCase_						)]						) + "|\n"
		return table



def   __lowerCamelCase  (   lowerCAmelCase_=False						)    ->   Optional[int]:
		_a ,      _a ,      _a ,      _a  :   List[str]				 =							_find_text_in_file(
		    filename=os.path.join(lowerCAmelCase_		,    'index.mdx'						)		,    start_prompt='<!--This table is updated automatically from the auto modules'		,    end_prompt='<!-- End table-->'		,    )
		_a  :   Union[str, Any]				 =							get_model_table_from_auto_modules()

		if current_table != new_table:
				if overwrite:
						with open(os.path.join(lowerCAmelCase_		,    'index.mdx'						)		,    'w'		,    encoding='utf-8'		,    newline='\n'						) as f:
								f.writelines(lines[:start_index] + [new_table] + lines[end_index:]						)
				else:
						raise ValueError(
						    'The model table in the `index.mdx` has not been updated. Run `make fix-copies` to fix this.'						)


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

							check_model_table(args.fix_and_overwrite)









'''simple docstring'''

from __future__ import annotations

class 			__magic_name__		:







							def __init__(							self      : List[Any]			,_UpperCAmelCase      : int	):
									_a  :   Tuple				 =							value
									_a  :   Node | None				 =							None
									_a  :   Node | None				 =							None

class 			__magic_name__		:
							lowerCAmelCase :					int







							def __init__(							self      : Union[str, Any]	):
									_a  :   Tuple				 =							0







							def 							__lowercase    (							self      : Tuple			,_UpperCAmelCase      : Node | None			,_UpperCAmelCase      : int	):
									if node is None:
											return

									if path_sum == self.target:
											self.paths += 1

									if node.left:
											self.depth_first_search(node.left			,path_sum + node.left.value	)
									if node.right:
											self.depth_first_search(node.right			,path_sum + node.right.value	)







							def 							__lowercase    (							self      : Union[str, Any]			,_UpperCAmelCase      : Node | None			,_UpperCAmelCase      : int | None = None	):
									if node is None:
											return 0
									if target is not None:
											_a  :   Any				 =							target

									self.depth_first_search(_UpperCAmelCase			,node.value	)
									self.path_sum(node.left	)
									self.path_sum(node.right	)

									return self.paths


if __name__ == "__main__":
							import doctest

							doctest.testmod()




