



import os

import pytest
from attr import dataclass


__lowerCamelCase     :							List[str]  							=  "us-east-1"  # defaults region





@dataclass
class  __magic_name__   :
		lowercase      :       Tuple          =42
		lowercase      :       int          ='''arn:aws:iam::558105141721:role/sagemaker_execution_role'''
		lowercase      :       List[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,
		}
		lowercase      :       Union[str, Any]          ={**hyperparameters, '''max_steps''': 1000}






		@property
		def SCREAMING_SNAKE_CASE_			(						self      :     int      )				->					Optional[int]:
								'''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      :     Any      )				->					Union[str, Any]:
								'''simple docstring'''







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






		@property
		def SCREAMING_SNAKE_CASE_			(						self      :     Any      )				->					Dict:
								'''simple docstring'''







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







		@property
		def SCREAMING_SNAKE_CASE_			(						self      :     List[Any]      )				->					Dict:
								'''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    lowerCamelCase_(lowerCamelCase_    ) ->       int:
						UpperCAmelCase         =     SageMakerTestEnvironment(framework=request.cls.framework    )








from ..utils import DummyObject, requires_backends





class  __magic_name__   (							metaclass=A__						):
		lowercase      :       int          =['''note_seq''']






		def __init__(						self      :     List[Any]				,		*UpperCamelCase__      :     Tuple				,		**UpperCamelCase__      :     Dict      )				->					int:
								'''simple docstring'''







								requires_backends(self				,		["note_seq"]      )






		@classmethod
		def SCREAMING_SNAKE_CASE_			(						cls      :     List[str]				,		*UpperCamelCase__      :     Dict				,		**UpperCamelCase__      :     str      )				->					Optional[int]:
								'''simple docstring'''







								requires_backends(cls				,		["note_seq"]      )







		@classmethod
		def SCREAMING_SNAKE_CASE_			(						cls      :     List[Any]				,		*UpperCamelCase__      :     Optional[int]				,		**UpperCamelCase__      :     Optional[Any]      )				->					Optional[int]:
								'''simple docstring'''







								requires_backends(cls				,		["note_seq"]      )



