




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      (						SCREAMING_SNAKE_CASE_							:				Tuple      ,      SCREAMING_SNAKE_CASE_							:				List[str]      ,      SCREAMING_SNAKE_CASE_							:				Union[str, Any]     ):
					with open(SCREAMING_SNAKE_CASE_      ,      "r"      ,      encoding="utf-8"      ,      newline="\n"     ) as f:
										__lowerCAmelCase				   =       f.readlines()
					# Find the start prompt.
					__lowerCAmelCase				   =       0
					while not lines[start_index].startswith(SCREAMING_SNAKE_CASE_     ):
										start_index += 1
					start_index += 1

					__lowerCAmelCase				   =       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 transformers module imported is the one in the repo.
UpperCamelCase__    			=			direct_transformers_import(TRANSFORMERS_PATH)







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







def 	_a      (						SCREAMING_SNAKE_CASE_							:				List[Any]      ,      SCREAMING_SNAKE_CASE_							:				Union[str, Any]     ):
					__lowerCAmelCase				   =       2 if text == "✅" or text == "❌" else len(SCREAMING_SNAKE_CASE_     )
					__lowerCAmelCase				   =       (width - text_length) // 2
					__lowerCAmelCase				   =       width - text_length - left_indent
					return " " * left_indent + text + " " * right_indent







def 	_a      (						):
					__lowerCAmelCase				   =       transformers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
					__lowerCAmelCase				   =       {
					    name: config_maping_names[code]
					    for code, name in transformers_module.MODEL_NAMES_MAPPING.items()
					    if code in config_maping_names
					}
					__lowerCAmelCase				   =       {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.
					__lowerCAmelCase				   =       collections.defaultdict(SCREAMING_SNAKE_CASE_     )
					__lowerCAmelCase				   =       collections.defaultdict(SCREAMING_SNAKE_CASE_     )
					__lowerCAmelCase				   =       collections.defaultdict(SCREAMING_SNAKE_CASE_     )
					__lowerCAmelCase				   =       collections.defaultdict(SCREAMING_SNAKE_CASE_     )
					__lowerCAmelCase				   =       collections.defaultdict(SCREAMING_SNAKE_CASE_     )

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

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

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

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

					if current_table != new_table:
										if overwrite:
															with open(os.path.join(SCREAMING_SNAKE_CASE_      ,      "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)










from typing import TYPE_CHECKING

from ...utils import _LazyModule


UpperCamelCase__    			=			{"""tokenization_wav2vec2_phoneme""": ["""Wav2Vec2PhonemeCTCTokenizer"""]}


if TYPE_CHECKING:
					from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
					import sys

					UpperCamelCase__    			=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




