



'''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						(__A						,			__A						,			__A):



					"""simple docstring"""



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

					_a											=						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 |
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						(__A):



					"""simple docstring"""



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




def lowerCAmelCase						(__A						,			__A):



					"""simple docstring"""



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




def lowerCAmelCase						():



					"""simple docstring"""



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

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

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

					# Build the table per se
					_a											=						'''|''' + '''|'''.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"

					_a											=						{True: '''✅''', False: '''❌'''}
					for name in model_names:
										_a											=						model_name_to_prefix[name]
										_a											=						[
										    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 lowerCAmelCase						(__A=False):



					"""simple docstring"""



					_a						,					_a						,					_a						,					_a											=						_find_text_in_file(
					    filename=os.path.join(__A						,			'''index.md''')						,			start_prompt='''<!--This table is updated automatically from the auto modules'''						,			end_prompt='''<!-- End table-->'''						,			)
					_a											=						get_model_table_from_auto_modules()

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








'''simple docstring'''





def lowerCAmelCase						(__A = 1_000):



     """simple docstring"""



     _a											=						2**power
     _a											=						str(__A)
     _a											=						list(__A)
     _a											=						0

     for i in list_num:
          sum_of_num += int(__A)

     return sum_of_num


if __name__ == "__main__":
  lowercase_	 =						int(input("Enter the power of 2: ").strip())
  print("2 ^ ", power, " = ", 2**power)
  lowercase_	 =						solution(power)
  print("Sum of the digits is: ", result)



