
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__							:							Optional[int]									=			"src/transformers"
lowercase__							:							List[str]									=			"docs/source/en"
lowercase__							:							Any									=			"."







def 	A_ (							snake_case							:   Any ,      snake_case							:   Optional[Any] ,      snake_case							:   List[Any] )      ->    Optional[Any]:



						'''simple docstring'''

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

						__UpperCamelCase       =			start_index
						while not lines[end_index].startswith(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 |
lowercase__							:							Optional[Any]									=			"Model|Encoder|Decoder|ForConditionalGeneration"
# Regexes that match TF/Flax/PT model names.
lowercase__							:							Any									=			re.compile(R"TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)")
lowercase__							:							int									=			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__							:							Any									=			re.compile(R"(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)")


# This is to make sure the transformers module imported is the one in the repo.
lowercase__							:							List[str]									=			direct_transformers_import(TRANSFORMERS_PATH)







def 	A_ (							snake_case							:   List[str] )      ->    Union[str, Any]:



						'''simple docstring'''

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







def 	A_ (							snake_case							:   Tuple ,      snake_case							:   Optional[Any] )      ->    Dict:



						'''simple docstring'''

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







def 	A_ (							)      ->    Dict:



						'''simple docstring'''

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

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

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

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







def 	A_ (							snake_case							:   Optional[int]=False )      ->    Tuple:



						'''simple docstring'''

						__UpperCamelCase  ,							__UpperCamelCase  ,							__UpperCamelCase  ,							__UpperCamelCase       =			_find_text_in_file(
						    filename=os.path.join(snake_case ,      '''index.md''' ) ,      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(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__":
				lowercase__							:							Tuple									=			argparse.ArgumentParser()
				parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
				lowercase__							:							List[str]									=			parser.parse_args()

				check_model_table(args.fix_and_overwrite)






def 	A_ (							snake_case							:   int = 10 ,      snake_case							:   int = 1000 ,      snake_case							:   bool = True )      ->    int:



						'''simple docstring'''

						assert (
						    isinstance(snake_case ,      snake_case )
						    and isinstance(snake_case ,      snake_case )
						    and isinstance(snake_case ,      snake_case )
						), "Invalid type of value(s) specified to function!"

						if min_val > max_val:
												raise ValueError('''Invalid value for min_val or max_val (min_value < max_value)''' )
						return min_val if option else max_val




def 	A_ (							snake_case							:   int ,      snake_case							:   int )      ->    int:



						'''simple docstring'''

						return int((number_a + number_a) / 2 )




def 	A_ (							snake_case							:   int ,      snake_case							:   int ,      snake_case							:   int )      ->    None:



						'''simple docstring'''

						assert (
						    isinstance(snake_case ,      snake_case ) and isinstance(snake_case ,      snake_case ) and isinstance(snake_case ,      snake_case )
						), 'argument values must be type of "int"'

						if lower > higher:
												raise ValueError('''argument value for lower and higher must be(lower > higher)''' )

						if not lower < to_guess < higher:
												raise ValueError(
												    '''guess value must be within the range of lower and higher value''' )

						def answer(snake_case							:   int ) -> str:
												if number > to_guess:
																		return "high"
												elif number < to_guess:
																		return "low"
												else:
																		return "same"

						print('''started...''' )

						__UpperCamelCase       =			lower
						__UpperCamelCase       =			higher

						__UpperCamelCase       =			[]

						while True:
												__UpperCamelCase       =			get_avg(snake_case ,      snake_case )
												last_numbers.append(snake_case )

												if answer(snake_case ) == "low":
																		__UpperCamelCase       =			number
												elif answer(snake_case ) == "high":
																		__UpperCamelCase       =			number
												else:
																		break

						print(f"guess the number : {last_numbers[-1]}" )
						print(f"details : {last_numbers!s}" )




def 	A_ (							)      ->    None:



						'''simple docstring'''

						__UpperCamelCase       =			int(input('''Enter lower value : ''' ).strip() )
						__UpperCamelCase       =			int(input('''Enter high value : ''' ).strip() )
						__UpperCamelCase       =			int(input('''Enter value to guess : ''' ).strip() )
						guess_the_number(snake_case ,      snake_case ,      snake_case )


if __name__ == "__main__":
				main()




