




'''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
a__         =     '''src/diffusers'''
a__         =     '''docs/source/en'''
a__         =     '''.'''




def    snake_case__     (  a       ,      a       ,      a	)			->       List[Any]:





			'''simple docstring'''






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

			snake_case__          =						start_index
			while not lines[end_index].startswith(a	):
						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 |
a__         =     '''Model|Encoder|Decoder|ForConditionalGeneration'''
# Regexes that match TF/Flax/PT model names.
a__         =     re.compile(R'''TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')
a__         =     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.
a__         =     re.compile(R'''(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')


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




def    snake_case__     (  a	)			->       Any:





			'''simple docstring'''






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




def    snake_case__     (  a       ,      a	)			->       Tuple:





			'''simple docstring'''






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




def    snake_case__     (  )			->       List[str]:





			'''simple docstring'''






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

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

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

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

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

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




def    snake_case__     (  a=False	)			->       str:





			'''simple docstring'''






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

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

		check_model_table(args.fix_and_overwrite)



class     __a     :
 def __init__(  self					)   ->							Tuple:




        '''simple docstring'''
        lowercase__:  str         =  []
        lowercase__:  Any         =  0
        lowercase__:  int         =  0
 def __str__(  self					)   ->							Any:




        '''simple docstring'''
        lowercase__:  str         =  '<' + str(self.entries					)[1:-1] + '>'
        return printed
 def 						SCREAMING_SNAKE_CASE__  (  self							,					lowerCAmelCase__					)   ->							List[str]:




        '''simple docstring'''
        self.entries.append(lowerCAmelCase__					)
        lowercase__:  List[str]         =  self.length + 1
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							str:




        '''simple docstring'''
        lowercase__:  Any         =  self.length - 1
        lowercase__:  Optional[int]         =  self.entries[self.front]
        # self.front-=1
        # self.entries = self.entries[self.front:]
        lowercase__:  int         =  self.entries[1:]
        return dequeued
 def 						SCREAMING_SNAKE_CASE__  (  self							,					lowerCAmelCase__					)   ->							List[str]:




        '''simple docstring'''
        for _ in range(lowerCAmelCase__					):
               self.put(self.get()					)
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							Union[str, Any]:




        '''simple docstring'''
        return self.entries[0]
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							Optional[int]:




        '''simple docstring'''
        return self.length


