

import os

import pytest
from attr import dataclass


A_ :				Union[str, Any]						 =    'us-east-1'  # defaults region



@dataclass
class 					_a		:


					'''simple docstring'''






					UpperCAmelCase__:     str
					UpperCAmelCase__:     Any													= '''arn:aws:iam::558105141721:role/sagemaker_execution_role'''
					UpperCAmelCase__:     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''': 5_00,
					    '''save_steps''': 55_00,
					}
					UpperCAmelCase__:     str													= {**hyperparameters, '''max_steps''': 10_00}






					@property
					def 						__A    (				self    ):
						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    ):
						return F"""{self.framework}-transfromers-test"""






					@property
					def 						__A    (				self    ):
						return F"""./tests/sagemaker/scripts/{self.framework}"""






					@property
					def 						__A    (				self    ):
						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 		UpperCamelCase      (lowercase_:				Tuple      )  ->   List[str]:
	A__							:					str       =	SageMakerTestEnvironment(framework=request.cls.framework      )






import os

try:
	from .build_directory_md import good_file_paths
except ImportError:
	from build_directory_md import good_file_paths  # type: ignore

A_ :				Dict						 =    list(good_file_paths())
assert filepaths, "good_file_paths() failed!"

A_ :				Optional[Any]						 =    [file for file in filepaths if file != file.lower()]
if upper_files:
	print(f'''{len(upper_files)} files contain uppercase characters:''')
	print('\n'.join(upper_files) + '\n')

A_ :				Tuple						 =    [file for file in filepaths if ' ' in file]
if space_files:
	print(f'''{len(space_files)} files contain space characters:''')
	print('\n'.join(space_files) + '\n')

A_ :				Any						 =    [file for file in filepaths if '-' in file]
if hyphen_files:
	print(f'''{len(hyphen_files)} files contain hyphen characters:''')
	print('\n'.join(hyphen_files) + '\n')

A_ :				List[str]						 =    [file for file in filepaths if os.sep not in file]
if nodir_files:
	print(f'''{len(nodir_files)} files are not in a directory:''')
	print('\n'.join(nodir_files) + '\n')

A_ :				Any						 =    len(upper_files + space_files + hyphen_files + nodir_files)
if bad_files:
	import sys

	sys.exit(bad_files)



