




import os

import pytest
from attr import dataclass


_lowerCamelCase	:		List[Any]							       =   'us-east-1'  # defaults region


@dataclass
class 				UpperCamelCase_    :

    '''simple docstring'''






    UpperCAmelCase__							  =      42
    UpperCAmelCase__							  =      """arn:aws:iam::558105141721:role/sagemaker_execution_role"""
    UpperCAmelCase__							  =      {
        """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__							  =      {**hyperparameters, """max_steps""": 1000}


    @property
    def        SCREAMING_SNAKE_CASE							(			self      :	Union[str, Any])						->Union[str, Any]:





           '''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        SCREAMING_SNAKE_CASE							(			self      :	Tuple)						->str:





           '''simple docstring'''

           return f"""{self.framework}-transfromers-test"""


    @property
    def        SCREAMING_SNAKE_CASE							(			self      :	Optional[int])						->Optional[Any]:





           '''simple docstring'''

           return f"""./tests/sagemaker/scripts/{self.framework}"""





    @property
    def        SCREAMING_SNAKE_CASE							(			self      :	Union[str, Any])						->Union[str, Any]:





           '''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 SCREAMING_SNAKE_CASE				(       lowercase_						)   ->       Dict:



       """simple docstring"""

       A__       =    SageMakerTestEnvironment(framework=request.cls.framework						)









"""simple docstring"""




from transformers import BertTokenizerFast

from .custom_tokenization import CustomTokenizer

class  _UpperCAmelCase  (   UpperCAmelCase__		):



      '''simple docstring'''
      lowercase_      : List[str]	    =   CustomTokenizer
      pass