
"""simple docstring"""





import os

import pytest
from attr import dataclass


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


@dataclass
class A_	:




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						str
  SCREAMING_SNAKE_CASE__			:						List[Any]       =		"""arn:aws:iam::558105141721:role/sagemaker_execution_role"""
  SCREAMING_SNAKE_CASE__			:						str       =		{
      """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,
  }
  SCREAMING_SNAKE_CASE__			:						Optional[Any]       =		{**hyperparameters, """max_steps""": 1000}







  @property
  def        UpperCamelCase__					(		self  ):

     """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        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return F"""{self.framework}-transfromers-test"""







  @property
  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return F"""./tests/sagemaker/scripts/{self.framework}"""







  @property
  def        UpperCamelCase__					(		self  ):

     """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     (		__lowerCamelCase  ):
   UpperCAmelCase_					:					Union[str, Any]			     =    SageMakerTestEnvironment(framework=request.cls.framework  )







"""simple docstring"""

import numpy as np




def __lowercase			(							_a    ):
    return (2 / (1 + np.exp(-2 * vector    ))) - 1


if __name__ == "__main__":
     import doctest

     doctest.testmod()





