


import logging

from transformers import PretrainedConfig


lowerCamelCase											=       logging.getLogger(__name__)


lowerCamelCase											=       {
    'bertabs-finetuned-cnndm': 'https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json',
}




class A  (   UpperCamelCase_     ):
      UpperCamelCase__							:  Optional[Any]      ='bertabs'






      def __init__(					self						:     Dict			,   lowercase_						:     int=3_0522			,   lowercase_						:     Union[str, Any]=512			,   lowercase_						:     Optional[int]=6			,   lowercase_						:     List[str]=512			,   lowercase_						:     Optional[Any]=8			,   lowercase_						:     Any=512			,   lowercase_						:     Optional[int]=0.2			,   lowercase_						:     Union[str, Any]=6			,   lowercase_						:     Any=768			,   lowercase_						:     List[Any]=8			,   lowercase_						:     Union[str, Any]=2048			,   lowercase_						:     Optional[Any]=0.2			,   **lowercase_						:     Any			,   )					->						Optional[Any]:
             """simple docstring"""




             super().__init__(**lowercase_ )

             _lowerCamelCase       :		Optional[Any]		=vocab_size
             _lowerCamelCase       :		Union[str, Any]		=max_pos

             _lowerCamelCase       :		Union[str, Any]		=enc_layers
             _lowerCamelCase       :		str		=enc_hidden_size
             _lowerCamelCase       :		str		=enc_heads
             _lowerCamelCase       :		List[str]		=enc_ff_size
             _lowerCamelCase       :		str		=enc_dropout

             _lowerCamelCase       :		List[str]		=dec_layers
             _lowerCamelCase       :		Tuple		=dec_hidden_size
             _lowerCamelCase       :		Optional[Any]		=dec_heads
             _lowerCamelCase       :		Dict		=dec_ff_size
             _lowerCamelCase       :		str		=dec_dropout






import os

import pytest
from attr import dataclass


lowerCamelCase											=       'us-east-1'  # defaults region




@dataclass
class A  :
      UpperCamelCase__							:  str
      UpperCamelCase__							:  Dict      ='arn:aws:iam::558105141721:role/sagemaker_execution_role'
      UpperCamelCase__							:  int      ={
          '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__							:  Optional[Any]      ={**hyperparameters, 'max_steps': 1000}






      @property
      def        lowerCamelCase       (					self						:     List[Any] )					->						str:
             """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        lowerCamelCase       (					self						:     List[Any] )					->						str:
             """simple docstring"""




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






      @property
      def        lowerCamelCase       (					self						:     Union[str, Any] )					->						str:
             """simple docstring"""




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






      @property
      def        lowerCamelCase       (					self						:     Union[str, Any] )					->						str:
             """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 	a_      (    SCREAMING_SNAKE_CASE__					:      Tuple     ):
       '''simple docstring'''





       _lowerCamelCase       :		List[Any]		=SageMakerTestEnvironment(framework=request.cls.framework     )


