
import argparse

import torch

from transformers import RoFormerConfig, RoFormerForMaskedLM, load_tf_weights_in_roformer
from transformers.utils import logging


logging.set_verbosity_info()


def       a			(   a		,	a		,	a  )    ->Union[str, Any]:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE    	=   RoFormerConfig.from_json_file(a  )
			print(F"""Building PyTorch model from configuration: {config}"""  )
			SCREAMING_SNAKE_CASE    	=   RoFormerForMaskedLM(a  )

			# Load weights from tf checkpoint
			load_tf_weights_in_roformer(a		,	a		,	a  )

			# Save pytorch-model
			print(F"""Save PyTorch model to {pytorch_dump_path}"""  )
			torch.save(model.state_dict()		,	a		,	_use_new_zipfile_serialization=a  )


if __name__ == "__main__":
							__lowerCAmelCase				      =					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(
							    '--bert_config_file',
							    default=None,
							    type=str,
							    required=True,
							    help=(
							        'The config json file corresponding to the pre-trained BERT 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.'
							)
							__lowerCAmelCase				      =					parser.parse_args()
							convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.bert_config_file, args.pytorch_dump_path)

import json

import requests

from .fetch_github_info import AUTHENTICATED_USER_ENDPOINT, fetch_github_info


def       a			(   a  )    ->Tuple:




			'''simple docstring'''


			class 						lowerCamelCase			:







				def __init__(    self			:int      ,    lowercase			:List[str] )		->			None:







							"""simple docstring"""






							assert isinstance(lowercase      ,    (bytes, str) )
							SCREAMING_SNAKE_CASE    	=   content







				def    snake_case__    (    self			:Optional[Any] )		->			Optional[int]:







							"""simple docstring"""






							return json.loads(self.content )

			def mock_response(*a		,	**a  ):
						assert args[0] == AUTHENTICATED_USER_ENDPOINT
						assert "Authorization" in kwargs["headers"]
						assert kwargs["headers"]["Authorization"].startswith('''token '''  )
						assert "Accept" in kwargs["headers"]
						return FakeResponse(B'''{"login":"test","id":1}'''  )

			monkeypatch.setattr(a		,	'''get'''		,	a  )
			SCREAMING_SNAKE_CASE    	=   fetch_github_info('''token'''  )
			assert result["login"] == "test"
			assert result["id"] == 1