

import os

import pytest
from attr import dataclass


_a:    Tuple 							=			"""us-east-1"""  # defaults region

@dataclass
class 						__UpperCamelCase    :
	SCREAMING_SNAKE_CASE__    				=     42
	SCREAMING_SNAKE_CASE__    				=     'arn:aws:iam::558105141721:role/sagemaker_execution_role'
	SCREAMING_SNAKE_CASE__    				=     {
	    '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': 5_00,
	    'save_steps': 55_00,
	}
	SCREAMING_SNAKE_CASE__    				=     {**hyperparameters, 'max_steps': 10_00}




	@property
	def       __A					(		self	:						List[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       __A					(		self	:						List[Any]							):


		'''simple docstring'''







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




	@property
	def       __A					(		self	:						Tuple							):


		'''simple docstring'''







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




	@property
	def       __A					(		self	:						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      (						A    ):
	UpperCAmelCase_       				=			SageMakerTestEnvironment(framework=request.cls.framework    )


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_a:    List[str] 							=			{
    """configuration_encodec""": [
        """ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """EncodecConfig""",
    ],
    """feature_extraction_encodec""": ["""EncodecFeatureExtractor"""],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_a:    List[Any] 							=			[
				    """ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """EncodecModel""",
				    """EncodecPreTrainedModel""",
				]

if TYPE_CHECKING:
				from .configuration_encodec import (
				    ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    EncodecConfig,
				)
				from .feature_extraction_encodec import EncodecFeatureExtractor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_encodec import (
								    ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST,
								    EncodecModel,
								    EncodecPreTrainedModel,
								)

else:
				import sys

				_a:    int 							=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)