




'''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_		:    Optional[int]									=		'''src/diffusers'''
UpperCamelCase_		:    List[Any]									=		'''docs/source/en'''
UpperCamelCase_		:    str									=		'''.'''





def 			__a			(     _UpperCamelCase:					Dict      ,		_UpperCamelCase:					Optional[int]      ,		_UpperCamelCase:					Any					)		->				int:

     """simple docstring"""




     with open(_UpperCamelCase      ,		"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(_UpperCamelCase					):
          start_index += 1
     start_index += 1

     _snake_case							=   start_index
     while not lines[end_index].startswith(_UpperCamelCase					):
          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_		:    Any									=		'''Model|Encoder|Decoder|ForConditionalGeneration'''
# Regexes that match TF/Flax/PT model names.
UpperCamelCase_		:    Optional[int]									=		re.compile(R'''TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')
UpperCamelCase_		:    Union[str, Any]									=		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_		:    Tuple									=		re.compile(R'''(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)''')


# This is to make sure the diffusers module imported is the one in the repo.
UpperCamelCase_		:    Optional[Any]									=		importlib.util.spec_from_file_location(
    '''diffusers''',
    os.path.join(TRANSFORMERS_PATH, '''__init__.py'''),
    submodule_search_locations=[TRANSFORMERS_PATH],
)
UpperCamelCase_		:    List[Any]									=		spec.loader.load_module()





def 			__a			(     _UpperCamelCase:					int					)		->				str:

     """simple docstring"""




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





def 			__a			(     _UpperCamelCase:					str      ,		_UpperCamelCase:					int					)		->				List[str]:

     """simple docstring"""




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





def 			__a			(     )		->				Tuple:

     """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(_UpperCamelCase					)
     _snake_case							=   collections.defaultdict(_UpperCamelCase					)
     _snake_case							=   collections.defaultdict(_UpperCamelCase					)
     _snake_case							=   collections.defaultdict(_UpperCamelCase					)
     _snake_case							=   collections.defaultdict(_UpperCamelCase					)

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

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

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





def 			__a			(     _UpperCamelCase:					Tuple=False					)		->				Dict:

     """simple docstring"""




     _snake_case							,      _snake_case							,      _snake_case							,      _snake_case							=   _find_text_in_file(
         filename=os.path.join(_UpperCamelCase      ,		"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(_UpperCamelCase      ,		"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_		:    Union[str, Any]									=		argparse.ArgumentParser()
   parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
   UpperCamelCase_		:    Optional[int]									=		parser.parse_args()

   check_model_table(args.fix_and_overwrite)








'''simple docstring'''





import io
import json
import subprocess


UpperCamelCase_		:    Any									=		[
    ['''en''', '''ru'''],
    ['''ru''', '''en'''],
    ['''en''', '''de'''],
    ['''de''', '''en'''],
]

UpperCamelCase_		:    Union[str, Any]									=		8





def 			__a			(     _UpperCamelCase:					int      ,		_UpperCamelCase:					Optional[Any]					)		->				Optional[int]:

     """simple docstring"""




     _snake_case							=   {}
     for src, tgt in pairs:
          _snake_case							=   F"""{src}-{tgt}"""
          _snake_case							=   F"""sacrebleu -t wmt19 -l {pair} --echo src""".split()
          _snake_case							=   subprocess.run(_UpperCamelCase      ,		stdout=subprocess.PIPE					).stdout.decode("utf-8"					).splitlines()
          _snake_case							=   F"""sacrebleu -t wmt19 -l {pair} --echo ref""".split()
          _snake_case							=   subprocess.run(_UpperCamelCase      ,		stdout=subprocess.PIPE					).stdout.decode("utf-8"					).splitlines()
          _snake_case							=   {"src": src_lines[:n_objs], "tgt": tgt_lines[:n_objs]}
     return text


UpperCamelCase_		:    Tuple									=		get_all_data(pairs, n_objs)
UpperCamelCase_		:    Optional[Any]									=		'''./fsmt_val_data.json'''
with io.open(filename, '''w''', encoding='''utf-8''') as f:
   UpperCamelCase_		:    List[str]									=		json.dump(text, f, indent=2, ensure_ascii=False)


