





'''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
_SCREAMING_SNAKE_CASE    =			"""src/diffusers"""
_SCREAMING_SNAKE_CASE    =			"""docs/source/en"""
_SCREAMING_SNAKE_CASE    =			"""."""




def       _lowerCAmelCase  ( lowerCamelCase_	:     str						,				lowerCamelCase_	:     int						,				lowerCamelCase_	:     List[str] ):



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

			__lowercase   =							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 |
_SCREAMING_SNAKE_CASE    =			"""Model|Encoder|Decoder|ForConditionalGeneration"""
# Regexes that match TF/Flax/PT model names.
_SCREAMING_SNAKE_CASE    =			re.compile(R'''TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')
_SCREAMING_SNAKE_CASE    =			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.
_SCREAMING_SNAKE_CASE    =			re.compile(R'''(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')


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




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




def       _lowerCAmelCase  ( lowerCamelCase_	:     List[Any]						,				lowerCamelCase_	:     Tuple ):
			__lowercase   =							2 if text == '''✅''' or text == '''❌''' else len(UpperCamelCase_ )
			__lowercase   =							(width - text_length) // 2
			__lowercase   =							width - text_length - left_indent
			return " " * left_indent + text + " " * right_indent




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

			# Let's lookup through all diffusers object (once).
			for attr_name in dir(UpperCamelCase_ ):
						__lowercase   =							None
						if attr_name.endswith('''Tokenizer''' ):
									__lowercase   =							slow_tokenizers
									__lowercase   =							attr_name[:-9]
						elif attr_name.endswith('''TokenizerFast''' ):
									__lowercase   =							fast_tokenizers
									__lowercase   =							attr_name[:-1_3]
						elif _re_tf_models.match(UpperCamelCase_ ) is not None:
									__lowercase   =							tf_models
									__lowercase   =							_re_tf_models.match(UpperCamelCase_ ).groups()[0]
						elif _re_flax_models.match(UpperCamelCase_ ) is not None:
									__lowercase   =							flax_models
									__lowercase   =							_re_flax_models.match(UpperCamelCase_ ).groups()[0]
						elif _re_pt_models.match(UpperCamelCase_ ) is not None:
									__lowercase   =							pt_models
									__lowercase   =							_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():
															__lowercase   =							True
															break
												# Try again after removing the last word in the name
												__lowercase   =							''''''.join(camel_case_split(UpperCamelCase_ )[:-1] )

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

			# Build the table per se
			__lowercase   =							'''|''' + '''|'''.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"

			__lowercase   =							{True: '''✅''', False: '''❌'''}
			for name in model_names:
						__lowercase   =							model_name_to_prefix[name]
						__lowercase   =							[
						    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       _lowerCAmelCase  ( lowerCamelCase_	:     Any=False ):
			__lowercase  ,						__lowercase  ,						__lowercase  ,						__lowercase   =							_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-->'''						,				)
			__lowercase   =							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__":
	_SCREAMING_SNAKE_CASE    =			argparse.ArgumentParser()
	parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
	_SCREAMING_SNAKE_CASE    =			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}')





