
'''simple docstring'''







import os

import pytest
from attr import dataclass


_lowercase			:  Any   							=	"us-east-1"  # defaults region






@dataclass
class 			lowerCAmelCase__       :
					lowerCAmelCase_					       =					42
					lowerCAmelCase_					       =					'''arn:aws:iam::558105141721:role/sagemaker_execution_role'''
					lowerCAmelCase_					       =					{
					    '''task_name''': '''mnli''',
					    '''per_device_train_batch_size''': 1_6,
					    '''per_device_eval_batch_size''': 1_6,
					    '''do_train''': True,
					    '''do_eval''': True,
					    '''do_predict''': True,
					    '''output_dir''': '''/opt/ml/model''',
					    '''overwrite_output_dir''': True,
					    '''max_steps''': 5_0_0,
					    '''save_steps''': 5_5_0_0,
					}
					lowerCAmelCase_					       =					{**hyperparameters, '''max_steps''': 1_0_0_0}






					@property
					def      _snake_case   (       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      _snake_case   (       self		):


											"""simple docstring"""





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






					@property
					def      _snake_case   (       self		):


											"""simple docstring"""





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






					@property
					def      _snake_case   (       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  snake_case_		(    __SCREAMING_SNAKE_CASE :			Tuple							):



						"""simple docstring"""





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





'''simple docstring'''







import logging
import os

from .state import PartialState






class 			lowerCAmelCase__       (  logging.LoggerAdapter					):






					@staticmethod
					def      _snake_case   (       __SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											lowercase_     :					Optional[Any]													=	PartialState()
											return not main_process_only or (main_process_only and state.is_main_process)






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											if PartialState._shared_state == {}:
																	raise RuntimeError(
																	    '''You must initialize the accelerate state by calling either `PartialState()` or `Accelerator()` before using the logging utility.'''		)
											lowercase_     :					Tuple													=	kwargs.pop('''main_process_only'''    ,							__SCREAMING_SNAKE_CASE		)
											lowercase_     :					Optional[int]													=	kwargs.pop('''in_order'''    ,							__SCREAMING_SNAKE_CASE		)

											if self.isEnabledFor(__SCREAMING_SNAKE_CASE		):
																	if self._should_log(__SCREAMING_SNAKE_CASE		):
																							lowercase_						,			lowercase_     :					Optional[Any]													=	self.process(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)
																							self.logger.log(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)

																	elif in_order:
																							lowercase_     :					Optional[Any]													=	PartialState()
																							for i in range(state.num_processes		):
																													if i == state.process_index:
																																			lowercase_						,			lowercase_     :					Optional[int]													=	self.process(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)
																																			self.logger.log(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)
																													state.wait_for_everyone()







def  snake_case_		(    __SCREAMING_SNAKE_CASE :			str				,				__SCREAMING_SNAKE_CASE :			str = None							):



						"""simple docstring"""





						if log_level is None:
												lowercase_     :					Any													=	os.environ.get('''ACCELERATE_LOG_LEVEL'''				,				__SCREAMING_SNAKE_CASE							)
						lowercase_     :					List[str]													=	logging.getLogger(__SCREAMING_SNAKE_CASE							)
						if log_level is not None:
												logger.setLevel(log_level.upper()							)
												logger.root.setLevel(log_level.upper()							)
						return MultiProcessAdapter(__SCREAMING_SNAKE_CASE				,				{}							)



