
"""simple docstring"""







from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE_     				=   logging.get_logger(__name__)






class     __a			(					lowerCAmelCase_			):
       _lowerCamelCase							:							Optional[int]       =			['input_ids', 'attention_mask']







       def __init__(					self							,lowerCamelCase_="[PAD]"							,lowerCamelCase_="[BOS]"							,lowerCamelCase_="[EOS]"							,lowerCamelCase_="[MASK]"							,lowerCamelCase_="[CLS]"							,lowerCamelCase_="[SEP]"							,lowerCamelCase_=2048							,**lowerCamelCase_							,):



          '''simple docstring'''

          _UpperCAmelCase   	=					AddedToken(lowerCamelCase_							,lstrip=lowerCamelCase_							,rstrip=lowerCamelCase_		) if isinstance(lowerCamelCase_							,lowerCamelCase_		) else pad_token
          _UpperCAmelCase   	=					AddedToken(lowerCamelCase_							,lstrip=lowerCamelCase_							,rstrip=lowerCamelCase_		) if isinstance(lowerCamelCase_							,lowerCamelCase_		) else bos_token
          _UpperCAmelCase   	=					AddedToken(lowerCamelCase_							,lstrip=lowerCamelCase_							,rstrip=lowerCamelCase_		) if isinstance(lowerCamelCase_							,lowerCamelCase_		) else eos_token
          _UpperCAmelCase   	=					AddedToken(lowerCamelCase_							,lstrip=lowerCamelCase_							,rstrip=lowerCamelCase_		) if isinstance(lowerCamelCase_							,lowerCamelCase_		) else mask_token
          _UpperCAmelCase   	=					AddedToken(lowerCamelCase_							,lstrip=lowerCamelCase_							,rstrip=lowerCamelCase_		) if isinstance(lowerCamelCase_							,lowerCamelCase_		) else cls_token
          _UpperCAmelCase   	=					AddedToken(lowerCamelCase_							,lstrip=lowerCamelCase_							,rstrip=lowerCamelCase_		) if isinstance(lowerCamelCase_							,lowerCamelCase_		) else sep_token

          super().__init__(
              pad_token=lowerCamelCase_							,bos_token=lowerCamelCase_							,eos_token=lowerCamelCase_							,mask_token=lowerCamelCase_							,cls_token=lowerCamelCase_							,sep_token=lowerCamelCase_							,model_max_length=lowerCamelCase_							,**lowerCamelCase_							,)

          _UpperCAmelCase   	=					2**8  # utf is 8 bits

          # define special tokens dict
          _UpperCAmelCase   	=					{
              self.pad_token: 0,
              self.bos_token: 1,
              self.eos_token: 2,
              self.mask_token: 3,
              self.cls_token: 4,
              self.sep_token: 5,
          }
          _UpperCAmelCase   	=					len(self.special_tokens_encoder		)
          _UpperCAmelCase   	=					{v: k for k, v in self.special_tokens_encoder.items()}







       def    _snake_case			(					self		):



          '''simple docstring'''

          _UpperCAmelCase   	=					self.special_tokens_encoder.copy()
          vocab.update(self.added_tokens_encoder		)
          for i in range(self._utf_vocab_size		):
             _UpperCAmelCase   	=					chr(lowerCamelCase_		)
             _UpperCAmelCase   	=					i + len(self.special_tokens_encoder		)
          return vocab







       @property
       def    _snake_case			(					self		):



          '''simple docstring'''

          return self._utf_vocab_size + self._num_special_tokens







       def    _snake_case			(					self							,lowerCamelCase_							,lowerCamelCase_ = None							,lowerCamelCase_ = False		):



          '''simple docstring'''

          if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=lowerCamelCase_							,token_ids_a=lowerCamelCase_							,already_has_special_tokens=lowerCamelCase_		)

          # normal case: some special tokens
          if token_ids_a is None:
             return [1] + [0] * len(lowerCamelCase_		) + [1]
          return [1] + ([0] * len(lowerCamelCase_		)) + [1] + ([0] * len(lowerCamelCase_		)) + [1]







       def    _snake_case			(					self							,lowerCamelCase_							,lowerCamelCase_ = None		):



          '''simple docstring'''

          if token_ids_a is None:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          else:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id] + token_ids_a + [self.sep_token_id]







       def    _snake_case			(					self							,lowerCamelCase_		):



          '''simple docstring'''

          _UpperCAmelCase   	=					[chr(lowerCamelCase_		) for i in text.encode("utf-8"		)]
          return tokens







       def    _snake_case			(					self							,lowerCamelCase_		):



          '''simple docstring'''

          if token in self.special_tokens_encoder:
             _UpperCAmelCase   	=					self.special_tokens_encoder[token]
          elif token in self.added_tokens_encoder:
             _UpperCAmelCase   	=					self.added_tokens_encoder[token]
          elif len(lowerCamelCase_		) != 1:
             _UpperCAmelCase   	=					self.unk_token_id
          else:
             _UpperCAmelCase   	=					ord(lowerCamelCase_		) + self._num_special_tokens
          return token_id







       def    _snake_case			(					self							,lowerCamelCase_		):



          '''simple docstring'''

          if index in self.special_tokens_decoder:
             _UpperCAmelCase   	=					self.special_tokens_decoder[index]
          elif index in self.added_tokens_decoder:
             _UpperCAmelCase   	=					self.added_tokens_decoder[index]
          else:
             _UpperCAmelCase   	=					chr(index - self._num_special_tokens		)
          return token







       def    _snake_case			(					self							,lowerCamelCase_		):



          '''simple docstring'''

          _UpperCAmelCase   	=					b""
          for token in tokens:
             if token in self.special_tokens_decoder:
                _UpperCAmelCase   	=					self.special_tokens_decoder[token].encode("utf-8"		)
             elif token in self.added_tokens_decoder:
                _UpperCAmelCase   	=					self.special_tokens_decoder[token].encode("utf-8"		)
             elif token in self.special_tokens_encoder:
                _UpperCAmelCase   	=					token.encode("utf-8"		)
             elif token in self.added_tokens_encoder:
                _UpperCAmelCase   	=					token.encode("utf-8"		)
             else:
                _UpperCAmelCase   	=					bytes([ord(lowerCamelCase_		)]		)
             bstring += tok_string
          _UpperCAmelCase   	=					bstring.decode("utf-8"							,errors="replace"		)
          return string







       def    _snake_case			(					self							,lowerCamelCase_							,lowerCamelCase_ = None		):



          '''simple docstring'''

          return ()



"""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)

