


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        __lowerCAmelCase    (SCREAMING_SNAKE_CASE					,					SCREAMING_SNAKE_CASE					,					SCREAMING_SNAKE_CASE					)->  int:




      """simple docstring"""

      with open(SCREAMING_SNAKE_CASE					,					'''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(SCREAMING_SNAKE_CASE					):
            start_index += 1
      start_index += 1

      snake_case_       =      start_index
      while not lines[end_index].startswith(SCREAMING_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        __lowerCAmelCase    (SCREAMING_SNAKE_CASE					)->  str:




      """simple docstring"""

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






def        __lowerCAmelCase    (SCREAMING_SNAKE_CASE					,					SCREAMING_SNAKE_CASE					)->  str:




      """simple docstring"""

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






def        __lowerCAmelCase    ()->  Dict:




      """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(SCREAMING_SNAKE_CASE					)
      snake_case_       =      collections.defaultdict(SCREAMING_SNAKE_CASE					)
      snake_case_       =      collections.defaultdict(SCREAMING_SNAKE_CASE					)
      snake_case_       =      collections.defaultdict(SCREAMING_SNAKE_CASE					)
      snake_case_       =      collections.defaultdict(SCREAMING_SNAKE_CASE					)

      # Let's lookup through all diffusers object (once).
      for attr_name in dir(SCREAMING_SNAKE_CASE					):
            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(SCREAMING_SNAKE_CASE					) is not None:
                  snake_case_       =      tf_models
                  snake_case_       =      _re_tf_models.match(SCREAMING_SNAKE_CASE					).groups()[0]
            elif _re_flax_models.match(SCREAMING_SNAKE_CASE					) is not None:
                  snake_case_       =      flax_models
                  snake_case_       =      _re_flax_models.match(SCREAMING_SNAKE_CASE					).groups()[0]
            elif _re_pt_models.match(SCREAMING_SNAKE_CASE					) is not None:
                  snake_case_       =      pt_models
                  snake_case_       =      _re_pt_models.match(SCREAMING_SNAKE_CASE					).groups()[0]

            if lookup_dict is not None:
                  while len(SCREAMING_SNAKE_CASE					) > 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(SCREAMING_SNAKE_CASE					)[:-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(SCREAMING_SNAKE_CASE					) + 2 for c in columns]
      snake_case_       =      max([len(SCREAMING_SNAKE_CASE					) for name in model_names]					) + 2

      # Build the table per se
      snake_case_       =      '''|''' + '''|'''.join([_center_text(SCREAMING_SNAKE_CASE					,					SCREAMING_SNAKE_CASE					) for c, w in zip(SCREAMING_SNAKE_CASE					,					SCREAMING_SNAKE_CASE					)]					) + '''|\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(SCREAMING_SNAKE_CASE					,					SCREAMING_SNAKE_CASE					) for l, w in zip(SCREAMING_SNAKE_CASE					,					SCREAMING_SNAKE_CASE					)]					) + "|\n"
      return table






def        __lowerCAmelCase    (SCREAMING_SNAKE_CASE=False					)->  Dict:




      """simple docstring"""

      snake_case_       ,    snake_case_       ,    snake_case_       ,    snake_case_       =      _find_text_in_file(
          filename=os.path.join(SCREAMING_SNAKE_CASE					,					'''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(SCREAMING_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)



def        __lowerCAmelCase    (SCREAMING_SNAKE_CASE = 1000					)->  int:




      """simple docstring"""

      snake_case_       =      0
      snake_case_       =      (n - 1) // 3
      total += ((terms) * (6 + (terms - 1) * 3)) // 2  # total of an A.P.
      snake_case_       =      (n - 1) // 5
      total += ((terms) * (10 + (terms - 1) * 5)) // 2
      snake_case_       =      (n - 1) // 15
      total -= ((terms) * (30 + (terms - 1) * 15)) // 2
      return total


if __name__ == "__main__":
   print(f'''{solution() = }''')