


import socket




def 	a_      (    ):
       '''simple docstring'''





       _lowerCamelCase       :		Optional[Any]		=socket.socket(socket.AF_INET		,			socket.SOCK_STREAM     )
       _lowerCamelCase       :		Union[str, Any]		=socket.gethostname()
       _lowerCamelCase       :		int		=12_312

       sock.connect((host, port)     )
       sock.send(b'Hello server!'     )

       with open('Received_file'		,			'wb'     ) as out_file:
              print('File opened'     )
              print('Receiving data...'     )
              while True:
                     _lowerCamelCase       :		Optional[int]		=sock.recv(1_024     )
                     if not data:
                            break
                     out_file.write(SCREAMING_SNAKE_CASE__     )

       print('Successfully received the file'     )
       sock.close()
       print('Connection closed'     )


if __name__ == "__main__":
 main()






import os

import pytest
from attr import dataclass


lowerCamelCase											=       'us-east-1'  # defaults region




@dataclass
class A  :
      UpperCamelCase__							:  str
      UpperCamelCase__							:  Dict      ='arn:aws:iam::558105141721:role/sagemaker_execution_role'
      UpperCamelCase__							:  int      ={
          'task_name': 'mnli',
          'per_device_train_batch_size': 16,
          'per_device_eval_batch_size': 16,
          'do_train': True,
          'do_eval': True,
          'do_predict': True,
          'output_dir': '/opt/ml/model',
          'overwrite_output_dir': True,
          'max_steps': 500,
          'save_steps': 5500,
      }
      UpperCamelCase__							:  Optional[Any]      ={**hyperparameters, 'max_steps': 1000}






      @property
      def        lowerCamelCase       (					self						:     List[Any] )					->						str:
             """simple docstring"""




             if self.framework == "pytorch":
                    return [
                        {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
                        {"Name": "eval_accuracy", "Regex": r"eval_accuracy.*=\D*(.*?)$"},
                        {"Name": "eval_loss", "Regex": r"eval_loss.*=\D*(.*?)$"},
                    ]
             else:
                    return [
                        {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
                        {"Name": "eval_accuracy", "Regex": r"loss.*=\D*(.*?)]?$"},
                        {"Name": "eval_loss", "Regex": r"sparse_categorical_accuracy.*=\D*(.*?)]?$"},
                    ]






      @property
      def        lowerCamelCase       (					self						:     List[Any] )					->						str:
             """simple docstring"""




             return F'''{self.framework}-transfromers-test'''






      @property
      def        lowerCamelCase       (					self						:     Union[str, Any] )					->						str:
             """simple docstring"""




             return F'''./tests/sagemaker/scripts/{self.framework}'''






      @property
      def        lowerCamelCase       (					self						:     Union[str, Any] )					->						str:
             """simple docstring"""




             if self.framework == "pytorch":
                    return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
             else:
                    return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04"




@pytest.fixture(scope='class'     )
def 	a_      (    SCREAMING_SNAKE_CASE__					:      Tuple     ):
       '''simple docstring'''





       _lowerCamelCase       :		List[Any]		=SageMakerTestEnvironment(framework=request.cls.framework     )


