

'''simple docstring'''





def   _UpperCamelCase	(		__UpperCamelCase	)       ->			Dict:
					return [
					    {
					        0: [1, 2],
					        1: [0, 2],
					        2: [0, 1, 3, 5],
					        3: [2, 4],
					        4: [3],
					        5: [2, 6, 8],
					        6: [5, 7],
					        7: [6, 8],
					        8: [5, 7],
					    },
					    {
					        0: [6],
					        1: [9],
					        2: [4, 5],
					        3: [4],
					        4: [2, 3],
					        5: [2],
					        6: [0, 7],
					        7: [6],
					        8: [],
					        9: [1],
					    },
					    {
					        0: [4],
					        1: [6],
					        2: [],
					        3: [5, 6, 7],
					        4: [0, 6],
					        5: [3, 8, 9],
					        6: [1, 3, 4, 7],
					        7: [3, 6, 8, 9],
					        8: [5, 7],
					        9: [5, 7],
					    },
					    {
					        0: [1, 3],
					        1: [0, 2, 4],
					        2: [1, 3, 4],
					        3: [0, 2, 4],
					        4: [1, 2, 3],
					    },
					][index]







def   _UpperCamelCase	(		__UpperCamelCase	)       ->			list[tuple[int, int]]:
					lowerCamelCase_  				=      0
					lowerCamelCase_  				=      len(__UpperCamelCase	)  # No of vertices in graph
					lowerCamelCase_  				=      [0] * n
					lowerCamelCase_  				=      [False] * n

					def dfs(__UpperCamelCase    ,__UpperCamelCase    ,__UpperCamelCase    ,__UpperCamelCase	):
										lowerCamelCase_  				=      True
										lowerCamelCase_  				=      id_
										id_ += 1
										for to in graph[at]:
															if to == parent:
																				pass
															elif not visited[to]:
																				dfs(__UpperCamelCase    ,__UpperCamelCase    ,__UpperCamelCase    ,id_	)
																				lowerCamelCase_  				=      min(low[at]    ,low[to]	)
																				if id_ <= low[to]:
																									bridges.append((at, to) if at < to else (to, at)	)
															else:
																				# This edge is a back edge and cannot be a bridge
																				lowerCamelCase_  				=      min(low[at]    ,low[to]	)

					lowerCamelCase_  				=      []
					for i in range(__UpperCamelCase	):
										if not visited[i]:
															dfs(__UpperCamelCase    ,-1    ,__UpperCamelCase    ,id_	)
					return bridges


if __name__ == "__main__":
				import doctest

				doctest.testmod()






import argparse

import torch

from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging


logging.set_verbosity_info()
def 							__SCREAMING_SNAKE_CASE     (   a__    :   Optional[Any]			,a__    :   Union[str, Any]			,a__    :   Optional[int]       )					->				List[Any]:
	# Initialise PyTorch model
	__A :			Dict		    =			MobileBertConfig.from_json_file(a__       )
	print(f"""Building PyTorch model from configuration: {config}"""       )
	__A :			Tuple		    =			MobileBertForPreTraining(a__       )
	# Load weights from tf checkpoint
	__A :			Dict		    =			load_tf_weights_in_mobilebert(a__			,a__			,a__       )
	# Save pytorch-model
	print(f"""Save PyTorch model to {pytorch_dump_path}"""       )
	torch.save(model.state_dict()			,a__       )


if __name__ == "__main__":
			UpperCAmelCase_							:					Any		 =   argparse.ArgumentParser()
			# Required parameters
			parser.add_argument(
			    '''--tf_checkpoint_path''', default=None, type=str, required=True, help='''Path to the TensorFlow checkpoint path.'''
			)
			parser.add_argument(
			    '''--mobilebert_config_file''',
			    default=None,
			    type=str,
			    required=True,
			    help=(
			        '''The config json file corresponding to the pre-trained MobileBERT model. \n'''
			        '''This specifies the model architecture.'''
			    ),
			)
			parser.add_argument(
			    '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
			)
			UpperCAmelCase_							:					Tuple		 =   parser.parse_args()
			convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.mobilebert_config_file, args.pytorch_dump_path)





