import os

import pytest
from attr import dataclass


SCREAMING_SNAKE_CASE__		:					int						=					"us-east-1"  # defaults region

@dataclass
class       snake_case					:
  lowercase_			=     42
  lowercase_			=     'arn:aws:iam::558105141721:role/sagemaker_execution_role'
  lowercase_			=     {
      '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': 5_500,
  }
  lowercase_			=     {**hyperparameters, 'max_steps': 1_000}




  @property
  def 	__lowercase(      self     :	Optional[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 	__lowercase(      self     :	int				)->       str:




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




  @property
  def 	__lowercase(      self     :	Optional[int]				)->       str:




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




  @property
  def 	__lowercase(      self     :	Optional[int]				)->       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				(      lowercase__  :			Tuple ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				List[str]			=		SageMakerTestEnvironment(framework=request.cls.framework )




from packaging import version

from .import_utils import is_accelerate_available


if is_accelerate_available():
      import accelerate







def     _a				(      lowercase__  :			List[str] ):







     '''simple docstring'''


     if not is_accelerate_available():
          return method
     SCREAMING_SNAKE_CASE__				:				str			=		version.parse(accelerate.__version__ ).base_version
     if version.parse(lowercase__ ) < version.parse('0.17.0' ):
          return method

     def wrapper(self  :			Optional[int]     ,  *lowercase__  :			int     ,  **lowercase__  :			Tuple ):
          if hasattr(self     ,  '_hf_hook' ) and hasattr(self._hf_hook     ,  'pre_forward' ):
               self._hf_hook.pre_forward(self )
          return method(self     ,  *lowercase__     ,  **lowercase__ )

     return wrapper



