code: 
  
  
  """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
  UpperCAmelCase   =	"""src/diffusers"""
  UpperCAmelCase   =	"""docs/source/en"""
  UpperCAmelCase   =	"""."""
  
  def 							_snake_case			(      __snake_case       :			List[str]	,   __snake_case       :			Union[str, Any]	,   __snake_case       :			int      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     with open(__snake_case	,   """r"""	,   encoding="""utf-8"""	,   newline="""\n"""      ) as f:
        _lowerCamelCase  :				List[Any]      =		f.readlines()
     # Find the start prompt.
     _lowerCamelCase  :				Tuple      =		0
     while not lines[start_index].startswith(__snake_case      ):
        start_index += 1
     start_index += 1
  
     _lowerCamelCase  :				List[Any]      =		start_index
     while not lines[end_index].startswith(__snake_case      ):
        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 |
  UpperCAmelCase   =	"""Model|Encoder|Decoder|ForConditionalGeneration"""
  # Regexes that match TF/Flax/PT model names.
  UpperCAmelCase   =	re.compile(r"""TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")
  UpperCAmelCase   =	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.
  UpperCAmelCase   =	re.compile(r"""(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")
  
  
  # This is to make sure the diffusers module imported is the one in the repo.
  UpperCAmelCase   =	importlib.util.spec_from_file_location(
      """diffusers""",
      os.path.join(TRANSFORMERS_PATH, """__init__.py"""),
      submodule_search_locations=[TRANSFORMERS_PATH],
  )
  UpperCAmelCase   =	spec.loader.load_module()
  
  def 							_snake_case			(      __snake_case       :			List[Any]      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _lowerCamelCase  :				Union[str, Any]      =		re.finditer(""".+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)"""	,   __snake_case      )
     return [m.group(0      ) for m in matches]
  
  def 							_snake_case			(      __snake_case       :			List[Any]	,   __snake_case       :			Dict      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _lowerCamelCase  :				List[str]      =		2 if text == """✅""" or text == """❌""" else len(__snake_case      )
     _lowerCamelCase  :				List[str]      =		(width - text_length) // 2
     _lowerCamelCase  :				Any      =		width - text_length - left_indent
     return " " * left_indent + text + " " * right_indent
  
  def 							_snake_case			(      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _lowerCamelCase  :				Tuple      =		diffusers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
     _lowerCamelCase  :				Optional[Any]      =		{
         name: config_mapping_names[code]
         for code, name in diffusers_module.MODEL_NAMES_MAPPING.items()
         if code in config_mapping_names
     }
     _lowerCamelCase  :				List[str]      =		{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  :				Union[str, Any]      =		collections.defaultdict(__snake_case      )
     _lowerCamelCase  :				List[str]      =		collections.defaultdict(__snake_case      )
     _lowerCamelCase  :				Dict      =		collections.defaultdict(__snake_case      )
     _lowerCamelCase  :				str      =		collections.defaultdict(__snake_case      )
     _lowerCamelCase  :				Optional[int]      =		collections.defaultdict(__snake_case      )
  
     # Let's lookup through all diffusers object (once).
     for attr_name in dir(__snake_case      ):
        _lowerCamelCase  :				Tuple      =		None
        if attr_name.endswith("""Tokenizer"""      ):
           _lowerCamelCase  :				Any      =		slow_tokenizers
           _lowerCamelCase  :				str      =		attr_name[:-9]
        elif attr_name.endswith("""TokenizerFast"""      ):
           _lowerCamelCase  :				Any      =		fast_tokenizers
           _lowerCamelCase  :				Tuple      =		attr_name[:-13]
        elif _re_tf_models.match(__snake_case      ) is not None:
           _lowerCamelCase  :				str      =		tf_models
           _lowerCamelCase  :				Optional[int]      =		_re_tf_models.match(__snake_case      ).groups()[0]
        elif _re_flax_models.match(__snake_case      ) is not None:
           _lowerCamelCase  :				Tuple      =		flax_models
           _lowerCamelCase  :				List[Any]      =		_re_flax_models.match(__snake_case      ).groups()[0]
        elif _re_pt_models.match(__snake_case      ) is not None:
           _lowerCamelCase  :				Union[str, Any]      =		pt_models
           _lowerCamelCase  :				Any      =		_re_pt_models.match(__snake_case      ).groups()[0]
  
        if lookup_dict is not None:
           while len(__snake_case      ) > 0:
              if attr_name in model_name_to_prefix.values():
                 _lowerCamelCase  :				Dict      =		True
                 break
              # Try again after removing the last word in the name
              _lowerCamelCase  :				Tuple      =		"""""".join(camel_case_split(__snake_case      )[:-1]      )
  
      # Let's build that table!
     _lowerCamelCase  :				Optional[int]      =		list(model_name_to_config.keys()      )
     model_names.sort(key=str.lower      )
     _lowerCamelCase  :				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).
     _lowerCamelCase  :				List[str]      =		[len(__snake_case      ) + 2 for c in columns]
     _lowerCamelCase  :				Tuple      =		max([len(__snake_case      ) for name in model_names]      ) + 2
  
     # Build the table per se
     _lowerCamelCase  :				Optional[int]      =		"""|""" + """|""".join([_center_text(__snake_case	,   __snake_case      ) for c, w in zip(__snake_case	,   __snake_case      )]      ) + """|\n"""
     # Use ":-----:" format to center-aligned table cell texts
     table += "|" + "|".join([""":""" + """-""" * (w - 2) + """:""" for w in widths]      ) + "|\n"
  
     _lowerCamelCase  :				List[Any]      =		{True: """✅""", False: """❌"""}
     for name in model_names:
        _lowerCamelCase  :				Tuple      =		model_name_to_prefix[name]
        _lowerCamelCase  :				Any      =		[
            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(__snake_case	,   __snake_case      ) for l, w in zip(__snake_case	,   __snake_case      )]      ) + "|\n"
     return table
  
  def 							_snake_case			(      __snake_case       :			Optional[Any]=False      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase  :				List[str]      =		_find_text_in_file(
         filename=os.path.join(__snake_case	,   """index.mdx"""      )	,   start_prompt="""<!--This table is updated automatically from the auto modules"""	,   end_prompt="""<!-- End table-->"""	,   )
     _lowerCamelCase  :				Dict      =		get_model_table_from_auto_modules()
  
     if current_table != new_table:
        if overwrite:
           with open(os.path.join(__snake_case	,   """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__":
   UpperCAmelCase   =	argparse.ArgumentParser()
   parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
   UpperCAmelCase   =	parser.parse_args()
  
   check_model_table(args.fix_and_overwrite)
  
  
style_context: 
  
  
  """simple docstring"""
  def 							_snake_case			(      __snake_case       :			str	,   __snake_case       :			str	,   __snake_case       :			int	,   __snake_case       :			int	,   __snake_case       :			int	,   __snake_case       :			int	,   ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _lowerCamelCase  :				Optional[Any]      =		list(__snake_case      )
     _lowerCamelCase  :				Optional[int]      =		list(__snake_case      )
     _lowerCamelCase  :				Union[str, Any]      =		len(__snake_case      )
     _lowerCamelCase  :				Optional[int]      =		len(__snake_case      )
  
     _lowerCamelCase  :				List[str]      =		[
         [0 for _ in range(len_destination_seq + 1      )] for _ in range(len_source_seq + 1      )
     ]
     _lowerCamelCase  :				List[Any]      =		[
         ["""0""" for _ in range(len_destination_seq + 1      )] for _ in range(len_source_seq + 1      )
     ]
  
     for i in range(1	,   len_source_seq + 1      ):
        _lowerCamelCase  :				Optional[Any]      =		i * delete_cost
        _lowerCamelCase  :				Any      =		F'D{source_seq[i - 1]:c}'
  
     for i in range(1	,   len_destination_seq + 1      ):
        _lowerCamelCase  :				Dict      =		i * insert_cost
        _lowerCamelCase  :				List[str]      =		F'I{destination_seq[i - 1]:c}'
  
     for i in range(1	,   len_source_seq + 1      ):
        for j in range(1	,   len_destination_seq + 1      ):
           if source_seq[i - 1] == destination_seq[j - 1]:
              _lowerCamelCase  :				Union[str, Any]      =		costs[i - 1][j - 1] + copy_cost
              _lowerCamelCase  :				Tuple      =		F'C{source_seq[i - 1]:c}'
           else:
              _lowerCamelCase  :				Tuple      =		costs[i - 1][j - 1] + replace_cost
              _lowerCamelCase  :				List[str]      =		F'R{source_seq[i - 1]:c}' + str(destination_seq[j - 1]      )
  
           if costs[i - 1][j] + delete_cost < costs[i][j]:
              _lowerCamelCase  :				Any      =		costs[i - 1][j] + delete_cost
              _lowerCamelCase  :				Any      =		F'D{source_seq[i - 1]:c}'
  
           if costs[i][j - 1] + insert_cost < costs[i][j]:
              _lowerCamelCase  :				Dict      =		costs[i][j - 1] + insert_cost
              _lowerCamelCase  :				Union[str, Any]      =		F'I{destination_seq[j - 1]:c}'
  
     return costs, ops
  
  def 							_snake_case			(      __snake_case       :			list[list[str]]	,   __snake_case       :			int	,   __snake_case       :			int      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     if i == 0 and j == 0:
        return []
     else:
        if ops[i][j][0] == "C" or ops[i][j][0] == "R":
           _lowerCamelCase  :				List[Any]      =		assemble_transformation(__snake_case	,   i - 1	,   j - 1      )
           seq.append(ops[i][j]      )
           return seq
        elif ops[i][j][0] == "D":
           _lowerCamelCase  :				Optional[Any]      =		assemble_transformation(__snake_case	,   i - 1	,   __snake_case      )
           seq.append(ops[i][j]      )
           return seq
        else:
           _lowerCamelCase  :				str      =		assemble_transformation(__snake_case	,   __snake_case	,   j - 1      )
           seq.append(ops[i][j]      )
           return seq
  
  
  if __name__ == "__main__":
   UpperCAmelCase ,     UpperCAmelCase   =	compute_transform_tables("""Python""", """Algorithms""", -1, 1, 2, 2)
  
   UpperCAmelCase   =	len(operations)
   UpperCAmelCase   =	len(operations[0])
   UpperCAmelCase   =	assemble_transformation(operations, m - 1, n - 1)
  
   UpperCAmelCase   =	list("""Python""")
   UpperCAmelCase   =	0
   UpperCAmelCase   =	0
  
   with open("""min_cost.txt""", """w""") as file:
    for op in sequence:
     print("""""".join(string))
  
     if op[0] == "C":
      file.write("""%-16s""" % """Copy %c""" % op[1])
      file.write("""\t\t\t""" + """""".join(string))
      file.write("""\r\n""")
  
      cost -= 1
     elif op[0] == "R":
      UpperCAmelCase   =	op[2]
  
      file.write("""%-16s""" % ("""Replace %c""" % op[1] + """ with """ + str(op[2])))
      file.write("""\t\t""" + """""".join(string))
      file.write("""\r\n""")
  
      cost += 1
     elif op[0] == "D":
      string.pop(i)
  
      file.write("""%-16s""" % """Delete %c""" % op[1])
      file.write("""\t\t\t""" + """""".join(string))
      file.write("""\r\n""")
  
      cost += 2
     else:
      string.insert(i, op[1])
  
      file.write("""%-16s""" % """Insert %c""" % op[1])
      file.write("""\t\t\t""" + """""".join(string))
      file.write("""\r\n""")
  
      cost += 2
  
     i += 1
  
    print("""""".join(string))
    print("""Cost: """, cost)
  
    file.write("""\r\nMinimum cost: """ + str(cost))
  
  