

"""simple docstring"""


import argparse
import collections
import os
import re

from transformers.utils import direct_transformers_import


# 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/transformers"
UpperCAmelCase													="docs/source/en"
UpperCAmelCase													="."



def   _A					(	_a	:						Dict     ,   _a	:						Tuple     ,   _a	:						Optional[int]				):



      """simple docstring"""






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

      A				  =		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 |
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 transformers module imported is the one in the repo.
UpperCAmelCase													=direct_transformers_import(TRANSFORMERS_PATH)



def   _A					(	_a	:						Optional[Any]				):



      """simple docstring"""






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



def   _A					(	_a	:						Any     ,   _a	:						int				):



      """simple docstring"""






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



def   _A					(	):



      """simple docstring"""






      A				  =		transformers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
      A				  =		{
          name: config_maping_names[code]
          for code, name in transformers_module.MODEL_NAMES_MAPPING.items()
          if code in config_maping_names
      }
      A				  =		{name: config.replace("""Config"""     ,   """"""				) 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.
      A				  =		collections.defaultdict(_a				)
      A				  =		collections.defaultdict(_a				)
      A				  =		collections.defaultdict(_a				)
      A				  =		collections.defaultdict(_a				)
      A				  =		collections.defaultdict(_a				)

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

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

      # Build the table per se
      A				  =		"""|""" + """|""".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"

      A				  =		{True: """✅""", False: """❌"""}
      for name in model_names:
            A				  =		model_name_to_prefix[name]
            A				  =		[
                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   _A					(	_a	:						int=False				):



      """simple docstring"""






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

      if current_table != new_table:
            if overwrite:
                  with open(os.path.join(_a     ,   """index.md"""				)     ,   """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.md` 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)







"""simple docstring"""


def   _A					(	_a	:						Optional[int]     ,   _a	:						str				):



      """simple docstring"""






      A				  =		0
      A				  =		len(_a				) - 1

      while left <= right:
            # avoid divided by 0 during interpolation
            if sorted_collection[left] == sorted_collection[right]:
                  if sorted_collection[left] == item:
                        return left
                  else:
                        return None

            A				  =		left + ((item - sorted_collection[left]) * (right - left)) // (
                sorted_collection[right] - sorted_collection[left]
            )

            # out of range check
            if point < 0 or point >= len(_a				):
                  return None

            A				  =		sorted_collection[point]
            if current_item == item:
                  return point
            else:
                  if point < left:
                        A				  =		left
                        A				  =		point
                  elif point > right:
                        A				  =		right
                        A				  =		point
                  else:
                        if item < current_item:
                              A				  =		point - 1
                        else:
                              A				  =		point + 1
      return None



def   _A					(	_a	:						Any     ,   _a	:						List[str]     ,   _a	:						Dict     ,   _a	:						List[str]				):



      """simple docstring"""






      if sorted_collection[left] == sorted_collection[right]:
            if sorted_collection[left] == item:
                  return left
            else:
                  return None

      A				  =		left + ((item - sorted_collection[left]) * (right - left)) // (
          sorted_collection[right] - sorted_collection[left]
      )

      # out of range check
      if point < 0 or point >= len(_a				):
            return None

      if sorted_collection[point] == item:
            return point
      elif point < left:
            return interpolation_search_by_recursion(_a     ,   _a     ,   _a     ,   _a				)
      elif point > right:
            return interpolation_search_by_recursion(_a     ,   _a     ,   _a     ,   _a				)
      else:
            if sorted_collection[point] > item:
                  return interpolation_search_by_recursion(
                      _a     ,   _a     ,   _a     ,   point - 1				)
            else:
                  return interpolation_search_by_recursion(
                      _a     ,   _a     ,   point + 1     ,   _a				)



def   _A					(	_a	:						List[Any]				):



      """simple docstring"""






      if collection != sorted(_a				):
            raise ValueError("""Collection must be ascending sorted"""				)
      return True


if __name__ == "__main__":
  import sys
  UpperCAmelCase													=0
  if debug == 1:
    UpperCAmelCase													=[10, 30, 40, 45, 50, 66, 77, 93]
    try:
      __assert_sorted(collection)
    except ValueError:
      sys.exit("Sequence must be ascending sorted to apply interpolation search")
    UpperCAmelCase													=67

  UpperCAmelCase													=interpolation_search(collection, target)
  if result is not None:
    print(f"""{target} found at positions: {result}""")
  else:
    print("Not found")




