


import os

import pytest
from attr import dataclass


UpperCAmelCase_				:			int				 =	'us-east-1'  # defaults region
@dataclass
class 			SCREAMING_SNAKE_CASE__  :
      snake_case__    :					Union[str, Any]					       =						42
      snake_case__    :					Union[str, Any]					       =						'''arn:aws:iam::558105141721:role/sagemaker_execution_role'''
      snake_case__    :					Tuple					       =						{
          '''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,
      }
      snake_case__    :					Any					       =						{**hyperparameters, '''max_steps''': 1_000}
      @property
      def 	SCREAMING_SNAKE_CASE							(	self    :	Union[str, Any]					)		->      str:
             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    :	List[Any]					)		->      str:
             return F"""{self.framework}-transfromers-test"""
      @property
      def 	SCREAMING_SNAKE_CASE							(	self    :	str					)		->      str:
             return F"""./tests/sagemaker/scripts/{self.framework}"""

      @property
      def 	SCREAMING_SNAKE_CASE							(	self    :	List[str]					)		->      str:
             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_						(      __A			:      Tuple    )     ->		List[Any]:

       """simple docstring"""

       a_ :		Union[str, Any]							=  SageMakerTestEnvironment(framework=request.cls.framework    )






from typing import TYPE_CHECKING

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


UpperCAmelCase_				:			Optional[Any]   =	{'configuration_plbart': ['PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PLBartConfig']}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase_				:			Union[str, Any]   =	['PLBartTokenizer']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase_				:			List[str]   =	[
       'PLBART_PRETRAINED_MODEL_ARCHIVE_LIST',
       'PLBartForCausalLM',
       'PLBartForConditionalGeneration',
       'PLBartForSequenceClassification',
       'PLBartModel',
       'PLBartPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_plbart import PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP, PLBartConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_plbart import PLBartTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_plbart import (
          PLBART_PRETRAINED_MODEL_ARCHIVE_LIST,
          PLBartForCausalLM,
          PLBartForConditionalGeneration,
          PLBartForSequenceClassification,
          PLBartModel,
          PLBartPreTrainedModel,
      )


else:
   import sys

   UpperCAmelCase_				:			Union[str, Any]   =	_LazyModule(__name__, globals()['__file__'], _import_structure)


