code: 
  """simple docstring"""
  
  
  
  
  
  
  
  from __future__ import annotations
  def 			__UpperCAmelCase		(		a_			:		Optional[Any]				)     ->       set[int]:
     _UpperCAmelCase   	=					{1}
     _UpperCAmelCase   	=					[1]
     for _ in range(2    ,  depth + 1				):
        _UpperCAmelCase   	=					[*previous_coefficients, 0]
        _UpperCAmelCase   	=					[0, *previous_coefficients]
        _UpperCAmelCase   	=					[]
        for x, y in zip(_UpperCAmelCase    ,  _UpperCAmelCase				):
           coefficients.add(x + y				)
           previous_coefficients.append(x + y				)
     return coefficients
  def 			__UpperCAmelCase		(		a_			:		List[Any]				)     ->       set[int]:
     _UpperCAmelCase   	=					set()
     for number in unique_coefficients:
        _UpperCAmelCase   	=					2
        _UpperCAmelCase   	=					number
        while divisor**2 <= copy_number:
           _UpperCAmelCase   	=					0
           while copy_number % divisor == 0:
              copy_number //= divisor
              multiplicity += 1
           if multiplicity >= 2:
              non_squarefrees.add(_UpperCAmelCase				)
              break
           divisor += 1
  
     return unique_coefficients.difference(_UpperCAmelCase				)
  def 			__UpperCAmelCase		(		a_			:		int = 51				)     ->       int:
     _UpperCAmelCase   	=					get_pascal_triangle_unique_coefficients(_UpperCAmelCase				)
     _UpperCAmelCase   	=					get_squarefrees(_UpperCAmelCase				)
     return sum(_UpperCAmelCase				)
  
  
  if __name__ == "__main__":
    print(f'''{solution() = }''')
  
  
  
style_context: 
  """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 			__UpperCAmelCase		(		a_			:		Optional[Any]    ,  a_			:		Any    ,  a_			:		List[Any]				)     ->       Optional[int]:
     with open(a_    ,  "r"    ,  encoding="utf-8"    ,  newline="\n"				) as f:
        _UpperCAmelCase   	=					f.readlines()
     # Find the start prompt.
     _UpperCAmelCase   	=					0
     while not lines[start_index].startswith(a_				):
        start_index += 1
     start_index += 1
  
     _UpperCAmelCase   	=					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 |
  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 			__UpperCAmelCase		(		a_			:		List[Any]				)     ->       Dict:
     _UpperCAmelCase   	=					re.finditer(".+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)"    ,  a_				)
     return [m.group(0				) for m in matches]
  def 			__UpperCAmelCase		(		a_			:		Any    ,  a_			:		List[Any]				)     ->       Optional[int]:
     _UpperCAmelCase   	=					2 if text == "✅" or text == "❌" else len(a_				)
     _UpperCAmelCase   	=					(width - text_length) // 2
     _UpperCAmelCase   	=					width - text_length - left_indent
     return " " * left_indent + text + " " * right_indent
  def 			__UpperCAmelCase		(		)     ->       List[Any]:
     _UpperCAmelCase   	=					diffusers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
     _UpperCAmelCase   	=					{
         name: config_mapping_names[code]
         for code, name in diffusers_module.MODEL_NAMES_MAPPING.items()
         if code in config_mapping_names
     }
     _UpperCAmelCase   	=					{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.
     _UpperCAmelCase   	=					collections.defaultdict(a_				)
     _UpperCAmelCase   	=					collections.defaultdict(a_				)
     _UpperCAmelCase   	=					collections.defaultdict(a_				)
     _UpperCAmelCase   	=					collections.defaultdict(a_				)
     _UpperCAmelCase   	=					collections.defaultdict(a_				)
  
     # Let's lookup through all diffusers object (once).
     for attr_name in dir(a_				):
        _UpperCAmelCase   	=					None
        if attr_name.endswith("Tokenizer"				):
           _UpperCAmelCase   	=					slow_tokenizers
           _UpperCAmelCase   	=					attr_name[:-9]
        elif attr_name.endswith("TokenizerFast"				):
           _UpperCAmelCase   	=					fast_tokenizers
           _UpperCAmelCase   	=					attr_name[:-13]
        elif _re_tf_models.match(a_				) is not None:
           _UpperCAmelCase   	=					tf_models
           _UpperCAmelCase   	=					_re_tf_models.match(a_				).groups()[0]
        elif _re_flax_models.match(a_				) is not None:
           _UpperCAmelCase   	=					flax_models
           _UpperCAmelCase   	=					_re_flax_models.match(a_				).groups()[0]
        elif _re_pt_models.match(a_				) is not None:
           _UpperCAmelCase   	=					pt_models
           _UpperCAmelCase   	=					_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():
                 _UpperCAmelCase   	=					True
                 break
              # Try again after removing the last word in the name
              _UpperCAmelCase   	=					"".join(camel_case_split(a_				)[:-1]				)
  
      # Let's build that table!
     _UpperCAmelCase   	=					list(model_name_to_config.keys()				)
     model_names.sort(key=str.lower				)
     _UpperCAmelCase   	=					["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).
     _UpperCAmelCase   	=					[len(a_				) + 2 for c in columns]
     _UpperCAmelCase   	=					max([len(a_				) for name in model_names]				) + 2
  
     # Build the table per se
     _UpperCAmelCase   	=					"|" + "|".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"
  
     _UpperCAmelCase   	=					{True: "✅", False: "❌"}
     for name in model_names:
        _UpperCAmelCase   	=					model_name_to_prefix[name]
        _UpperCAmelCase   	=					[
            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 			__UpperCAmelCase		(		a_			:		Union[str, Any]=False				)     ->       int:
     _UpperCAmelCase	,							_UpperCAmelCase	,							_UpperCAmelCase	,							_UpperCAmelCase   	=					_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-->"    ,  )
     _UpperCAmelCase   	=					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__":
    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)
  
  