

'''simple docstring'''
import os

import pytest
from attr import dataclass


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


@dataclass
class        a__  :
   _SCREAMING_SNAKE_CASE   :					str
   _SCREAMING_SNAKE_CASE   :					Tuple     	=							'arn:aws:iam::558105141721:role/sagemaker_execution_role'
   _SCREAMING_SNAKE_CASE   :					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,
   }
   _SCREAMING_SNAKE_CASE   :					Dict     	=							{**hyperparameters, 'max_steps': 1000}


   @property
   def 						_lowerCamelCase       (			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 						_lowerCamelCase       (			self  ):





      """simple docstring"""





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


   @property
   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





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






   @property
   def 						_lowerCamelCase       (			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  _A		(     snake_case					)      ->     int:
   _lowercase      :				int      					=       SageMakerTestEnvironment(framework=request.cls.framework					)









'''simple docstring'''
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union

import transformers
from transformers.testing_utils import require_tf, require_torch, slow


_snake_case         =  logging.getLogger()


@unittest.skip('Temporarily disable the doc tests.'  )
@require_torch
@require_tf
@slow
class        a__  (							unittest.TestCase  ):


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase = None      ,    _UpperCamelCase = None      ,    _UpperCamelCase = None      ,    _UpperCamelCase = True      ,    ):





      """simple docstring"""





      _lowercase      :				str      					=       [file for file in os.listdir(_UpperCamelCase  ) if os.path.isfile(os.path.join(_UpperCamelCase      ,    _UpperCamelCase  )  )]

      if identifier is not None:
         _lowercase      :				str      					=       [file for file in files if identifier in file]

      if n_identifier is not None:
         if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ):
            for n_ in n_identifier:
               _lowercase      :				Dict      					=       [file for file in files if n_ not in file]
         else:
            _lowercase      :				Optional[Any]      					=       [file for file in files if n_identifier not in file]

      _lowercase      :				Dict      					=       ignore_files or []
      ignore_files.append("__init__.py"  )
      _lowercase      :				List[str]      					=       [file for file in files if file not in ignore_files]

      for file in files:
         # Open all files
         print("Testing"      ,    _UpperCamelCase  )

         if only_modules:
            _lowercase      :				Optional[Any]      					=       file.split("."  )[0]
            try:
               _lowercase      :				Union[str, Any]      					=       getattr(_UpperCamelCase      ,    _UpperCamelCase  )
               _lowercase      :				Optional[int]      					=       doctest.DocTestSuite(_UpperCamelCase  )
               _lowercase      :				Tuple      					=       unittest.TextTestRunner().run(_UpperCamelCase  )
               self.assertIs(len(result.failures  )      ,    0  )
            except AttributeError:
               logger.info(f'''{module_identifier} is not a module.'''  )
         else:
            _lowercase      :				Optional[Any]      					=       doctest.testfile(str(".." / directory / file  )      ,    optionflags=doctest.ELLIPSIS  )
            self.assertIs(result.failed      ,    0  )


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				Tuple      					=       Path("src/transformers"  )
      _lowercase      :				str      					=       "modeling"
      _lowercase      :				Tuple      					=       [
          "modeling_ctrl.py",
          "modeling_tf_ctrl.py",
      ]
      self.analyze_directory(_UpperCamelCase      ,    identifier=_UpperCamelCase      ,    ignore_files=_UpperCamelCase  )


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				Optional[int]      					=       Path("src/transformers"  )
      _lowercase      :				Any      					=       "tokenization"
      self.analyze_directory(_UpperCamelCase      ,    identifier=_UpperCamelCase  )


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				Tuple      					=       Path("src/transformers"  )
      _lowercase      :				Optional[Any]      					=       "configuration"
      self.analyze_directory(_UpperCamelCase      ,    identifier=_UpperCamelCase  )


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				Union[str, Any]      					=       Path("src/transformers"  )
      _lowercase      :				List[Any]      					=       ["configuration", "modeling", "tokenization"]
      self.analyze_directory(_UpperCamelCase      ,    n_identifier=_UpperCamelCase  )






   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				Dict      					=       Path("docs/source"  )
      _lowercase      :				int      					=       ["favicon.ico"]
      self.analyze_directory(_UpperCamelCase      ,    ignore_files=_UpperCamelCase      ,    only_modules=_UpperCamelCase  )






