





'''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
lowercase_					= '''src/transformers'''
lowercase_					= '''docs/source/en'''
lowercase_					= '''.'''





def lowerCamelCase						(     __lowerCamelCase :    List[str]					,       __lowerCamelCase :    Any					,       __lowerCamelCase :    Union[str, Any]    )						->Dict:
    with open(_UpperCAmelCase					,       """r"""					,       encoding="""utf-8"""					,       newline="""\n"""    ) as f:
        _SCREAMING_SNAKE_CASE									=			f.readlines()
    # Find the start prompt.
    _SCREAMING_SNAKE_CASE									=			0
    while not lines[start_index].startswith(_UpperCAmelCase    ):
        start_index += 1
    start_index += 1

    _SCREAMING_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 |
lowercase_					= '''Model|Encoder|Decoder|ForConditionalGeneration'''
# Regexes that match TF/Flax/PT model names.
lowercase_					= re.compile(R"""TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")
lowercase_					= 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.
lowercase_					= re.compile(R"""(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")


# This is to make sure the transformers module imported is the one in the repo.
lowercase_					= direct_transformers_import(TRANSFORMERS_PATH)





def lowerCamelCase						(     __lowerCamelCase :    Union[str, Any]    )						->List[str]:
    _SCREAMING_SNAKE_CASE									=			re.finditer(""".+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)"""					,       _UpperCAmelCase    )
    return [m.group(0    ) for m in matches]





def lowerCamelCase						(     __lowerCamelCase :    Any					,       __lowerCamelCase :    int    )						->List[str]:
    _SCREAMING_SNAKE_CASE									=			2 if text == """✅""" or text == """❌""" else len(_UpperCAmelCase    )
    _SCREAMING_SNAKE_CASE									=			(width - text_length) // 2
    _SCREAMING_SNAKE_CASE									=			width - text_length - left_indent
    return " " * left_indent + text + " " * right_indent





def lowerCamelCase						(     )						->str:
    _SCREAMING_SNAKE_CASE									=			transformers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
    _SCREAMING_SNAKE_CASE									=			{
        name: config_maping_names[code]
        for code, name in transformers_module.MODEL_NAMES_MAPPING.items()
        if code in config_maping_names
    }
    _SCREAMING_SNAKE_CASE									=			{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.
    _SCREAMING_SNAKE_CASE									=			collections.defaultdict(_UpperCAmelCase    )
    _SCREAMING_SNAKE_CASE									=			collections.defaultdict(_UpperCAmelCase    )
    _SCREAMING_SNAKE_CASE									=			collections.defaultdict(_UpperCAmelCase    )
    _SCREAMING_SNAKE_CASE									=			collections.defaultdict(_UpperCAmelCase    )
    _SCREAMING_SNAKE_CASE									=			collections.defaultdict(_UpperCAmelCase    )

    # Let's lookup through all transformers object (once).
    for attr_name in dir(_UpperCAmelCase    ):
        _SCREAMING_SNAKE_CASE									=			None
        if attr_name.endswith("""Tokenizer"""    ):
            _SCREAMING_SNAKE_CASE									=			slow_tokenizers
            _SCREAMING_SNAKE_CASE									=			attr_name[:-9]
        elif attr_name.endswith("""TokenizerFast"""    ):
            _SCREAMING_SNAKE_CASE									=			fast_tokenizers
            _SCREAMING_SNAKE_CASE									=			attr_name[:-13]
        elif _re_tf_models.match(_UpperCAmelCase    ) is not None:
            _SCREAMING_SNAKE_CASE									=			tf_models
            _SCREAMING_SNAKE_CASE									=			_re_tf_models.match(_UpperCAmelCase    ).groups()[0]
        elif _re_flax_models.match(_UpperCAmelCase    ) is not None:
            _SCREAMING_SNAKE_CASE									=			flax_models
            _SCREAMING_SNAKE_CASE									=			_re_flax_models.match(_UpperCAmelCase    ).groups()[0]
        elif _re_pt_models.match(_UpperCAmelCase    ) is not None:
            _SCREAMING_SNAKE_CASE									=			pt_models
            _SCREAMING_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():
                    _SCREAMING_SNAKE_CASE									=			True
                    break
                # Try again after removing the last word in the name
                _SCREAMING_SNAKE_CASE									=			"""""".join(camel_case_split(_UpperCAmelCase    )[:-1]    )

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

    # Build the table per se
    _SCREAMING_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"

    _SCREAMING_SNAKE_CASE									=			{True: """✅""", False: """❌"""}
    for name in model_names:
        _SCREAMING_SNAKE_CASE									=			model_name_to_prefix[name]
        _SCREAMING_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 lowerCamelCase						(     __lowerCamelCase :    Optional[int]=False    )						->str:
    _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE									=			_find_text_in_file(
        filename=os.path.join(_UpperCAmelCase					,       """index.md"""    )					,       start_prompt="""<!--This table is updated automatically from the auto modules"""					,       end_prompt="""<!-- End table-->"""					,       )
    _SCREAMING_SNAKE_CASE									=			get_model_table_from_auto_modules()

    if current_table != new_table:
        if overwrite:
            with open(os.path.join(_UpperCAmelCase					,       """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__":
      lowercase_					= argparse.ArgumentParser()
      parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
      lowercase_					= parser.parse_args()

      check_model_table(args.fix_and_overwrite)








import os

try:
 from .build_directory_md import good_file_paths
except ImportError:
 from build_directory_md import good_file_paths  # type: ignore

__snake_case						:Optional[Any]      		=     list(good_file_paths())
assert filepaths, "good_file_paths() failed!"

__snake_case						:Any      		=     [file for file in filepaths if file != file.lower()]
if upper_files:
 print(f'{len(upper_files)} files contain uppercase characters:')
 print('''\n'''.join(upper_files) + '''\n''')

__snake_case						:Tuple      		=     [file for file in filepaths if ''' ''' in file]
if space_files:
 print(f'{len(space_files)} files contain space characters:')
 print('''\n'''.join(space_files) + '''\n''')

__snake_case						:Optional[int]      		=     [file for file in filepaths if '''-''' in file]
if hyphen_files:
 print(f'{len(hyphen_files)} files contain hyphen characters:')
 print('''\n'''.join(hyphen_files) + '''\n''')

__snake_case						:Optional[int]      		=     [file for file in filepaths if os.sep not in file]
if nodir_files:
 print(f'{len(nodir_files)} files are not in a directory:')
 print('''\n'''.join(nodir_files) + '''\n''')

__snake_case						:int      		=     len(upper_files + space_files + hyphen_files + nodir_files)
if bad_files:
 import sys

 sys.exit(bad_files)





