






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
__snake_case			:			List[Any]			   =   """src/diffusers"""
__snake_case			:			Union[str, Any]			   =   """docs/source/en"""
__snake_case			:			str			   =   """."""







def 		_UpperCamelCase      (			UpperCamelCase_				:    str			,				UpperCamelCase_				:    int			,				UpperCamelCase_				:    List[str]						)     ->      Optional[int]:

						"""simple docstring"""



						with open(UpperCamelCase_			,				'r'			,				encoding='utf-8'			,				newline='\n'						) as f:
												lowerCAmelCase__			  =  f.readlines()
						# Find the start prompt.
						lowerCAmelCase__			  =  0
						while not lines[start_index].startswith(UpperCamelCase_						):
												start_index += 1
						start_index += 1

						lowerCAmelCase__			  =  start_index
						while not lines[end_index].startswith(UpperCamelCase_						):
												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 |
__snake_case			:			int			   =   """Model|Encoder|Decoder|ForConditionalGeneration"""
# Regexes that match TF/Flax/PT model names.
__snake_case			:			Optional[Any]			   =   re.compile(R"""TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")
__snake_case			:			List[Any]			   =   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.
__snake_case			:			Any			   =   re.compile(R"""(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")


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







def 		_UpperCamelCase      (			UpperCamelCase_				:    Tuple						)     ->      Optional[Any]:

						"""simple docstring"""



						lowerCAmelCase__			  =  re.finditer('.+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)'			,				UpperCamelCase_						)
						return [m.group(0						) for m in matches]







def 		_UpperCamelCase      (			UpperCamelCase_				:    List[Any]			,				UpperCamelCase_				:    Tuple						)     ->      Any:

						"""simple docstring"""



						lowerCAmelCase__			  =  2 if text == '✅' or text == '❌' else len(UpperCamelCase_						)
						lowerCAmelCase__			  =  (width - text_length) // 2
						lowerCAmelCase__			  =  width - text_length - left_indent
						return " " * left_indent + text + " " * right_indent







def 		_UpperCamelCase      (			)     ->      str:

						"""simple docstring"""



						lowerCAmelCase__			  =  diffusers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
						lowerCAmelCase__			  =  {
						    name: config_mapping_names[code]
						    for code, name in diffusers_module.MODEL_NAMES_MAPPING.items()
						    if code in config_mapping_names
						}
						lowerCAmelCase__			  =  {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.
						lowerCAmelCase__			  =  collections.defaultdict(UpperCamelCase_						)
						lowerCAmelCase__			  =  collections.defaultdict(UpperCamelCase_						)
						lowerCAmelCase__			  =  collections.defaultdict(UpperCamelCase_						)
						lowerCAmelCase__			  =  collections.defaultdict(UpperCamelCase_						)
						lowerCAmelCase__			  =  collections.defaultdict(UpperCamelCase_						)

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

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

    # Let's build that table!
						lowerCAmelCase__			  =  list(model_name_to_config.keys()						)
						model_names.sort(key=str.lower						)
						lowerCAmelCase__			  =  ['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).
						lowerCAmelCase__			  =  [len(UpperCamelCase_						) + 2 for c in columns]
						lowerCAmelCase__			  =  max([len(UpperCamelCase_						) for name in model_names]						) + 2

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

						lowerCAmelCase__			  =  {True: '✅', False: '❌'}
						for name in model_names:
												lowerCAmelCase__			  =  model_name_to_prefix[name]
												lowerCAmelCase__			  =  [
												    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(UpperCamelCase_			,				UpperCamelCase_						) for l, w in zip(UpperCamelCase_			,				UpperCamelCase_						)]						) + "|\n"
						return table







def 		_UpperCamelCase      (			UpperCamelCase_				:    Any=False						)     ->      int:

						"""simple docstring"""



						lowerCAmelCase__  ,				lowerCAmelCase__  ,				lowerCAmelCase__  ,				lowerCAmelCase__			  =  _find_text_in_file(
						    filename=os.path.join(UpperCamelCase_			,				'index.mdx'						)			,				start_prompt='<!--This table is updated automatically from the auto modules'			,				end_prompt='<!-- End table-->'			,				)
						lowerCAmelCase__			  =  get_model_table_from_auto_modules()

						if current_table != new_table:
												if overwrite:
																		with open(os.path.join(UpperCamelCase_			,				'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__":
					__snake_case			:			Any			   =   argparse.ArgumentParser()
					parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
					__snake_case			:			Tuple			   =   parser.parse_args()

					check_model_table(args.fix_and_overwrite)













def 		_UpperCamelCase      (			UpperCamelCase_				:    str						)     ->      int:

						"""simple docstring"""



						lowerCAmelCase__			  =  len(UpperCamelCase_						)
						lowerCAmelCase__			  =  [0] * length
						lowerCAmelCase__			  =  [[False for i in range(UpperCamelCase_						)] for j in range(UpperCamelCase_						)]
						for i, c in enumerate(UpperCamelCase_						):
												lowerCAmelCase__			  =  i
												for j in range(i + 1						):
																		if c == string[j] and (i - j < 2 or is_palindromic[j + 1][i - 1]):
																								lowerCAmelCase__			  =  True
																								lowerCAmelCase__			  =  min(UpperCamelCase_			,				0 if j == 0 else (cut[j - 1] + 1)						)
												lowerCAmelCase__			  =  mincut
						return cut[length - 1]


if __name__ == "__main__":
					__snake_case			:			Optional[Any]			   =   input("""Enter the string: """).strip()
					__snake_case			:			List[Any]			   =   find_minimum_partitions(s)
					print(f'Minimum number of partitions required for the \'{s}\' is {ans}')





