



"""simple docstring"""






from dataclasses import dataclass, field
from typing import Tuple

from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments


if is_torch_available():
	import torch

if is_torch_tpu_available(check_device=False):
	import torch_xla.core.xla_model as xm


__snake_case				:  Optional[int] =       logging.get_logger(__name__)



@dataclass
class      A__  (    __SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      [
	    'no_inference',
	    'no_cuda',
	    'no_tpu',
	    'no_speed',
	    'no_memory',
	    'no_env_print',
	    'no_multi_process',
	]

	def __init__(	self:						int			,     **_SCREAMING_SNAKE_CASE:						Optional[Any])							->			List[Any]:

				"""simple docstring"""

				for deprecated_arg in self.deprecated_args:
							if deprecated_arg in kwargs:
										__lowerCAmelCase :    Optional[Any]				=			deprecated_arg[3:]
										setattr(self			,     _SCREAMING_SNAKE_CASE			,     not kwargs.pop(_SCREAMING_SNAKE_CASE))
										logger.warning(
										    F"""{deprecated_arg} is depreciated. Please use --no_{positive_arg} or"""
										    F""" {positive_arg}={kwargs[positive_arg]}""")

				__lowerCAmelCase :    List[Any]				=			kwargs.pop("torchscript"			,     self.torchscript)
				__lowerCAmelCase :    Dict				=			kwargs.pop("torch_xla_tpu_print_metrics"			,     self.torch_xla_tpu_print_metrics)
				__lowerCAmelCase :    Any				=			kwargs.pop("fp16_opt_level"			,     self.fpaa_opt_level)
				super().__init__(**_SCREAMING_SNAKE_CASE)

	SCREAMING_SNAKE_CASE        =      field(default=__SCREAMING_SNAKE_CASE    ,						metadata={'help': 'Trace the models using torchscript'}				)
	SCREAMING_SNAKE_CASE        =      field(default=__SCREAMING_SNAKE_CASE    ,						metadata={'help': 'Print Xla/PyTorch tpu metrics'}				)
	SCREAMING_SNAKE_CASE        =      field(
	    default='O1'    ,						metadata={
	        'help': (
	            'For fp16: Apex AMP optimization level selected in [\'O0\', \'O1\', \'O2\', and \'O3\']. '
	            'See details at https://nvidia.github.io/apex/amp.html'
	        )
	    }    ,						)

	@cached_property
	def 				_SCREAMING_SNAKE_CASE  (	self:						str)							->			Tuple["torch.device", int]:

				"""simple docstring"""

				requires_backends(self			,     ["torch"])
				logger.info("PyTorch: setting up devices")
				if not self.cuda:
							__lowerCAmelCase :    Dict				=			torch.device("cpu")
							__lowerCAmelCase :    Union[str, Any]				=			0
				elif is_torch_tpu_available():
							__lowerCAmelCase :    Optional[int]				=			xm.xla_device()
							__lowerCAmelCase :    Optional[int]				=			0
				else:
							__lowerCAmelCase :    Any				=			torch.device("cuda" if torch.cuda.is_available() else "cpu")
							__lowerCAmelCase :    Union[str, Any]				=			torch.cuda.device_count()
				return device, n_gpu

	@property
	def 				_SCREAMING_SNAKE_CASE  (	self:						Optional[int])							->			Optional[Any]:

				"""simple docstring"""

				return is_torch_tpu_available() and self.tpu

	@property
	def 				_SCREAMING_SNAKE_CASE  (	self:						int)							->			int:

				"""simple docstring"""

				requires_backends(self			,     ["torch"])
				# TODO(PVP): currently only single GPU is supported
				return torch.cuda.current_device()

	@property
	def 				_SCREAMING_SNAKE_CASE  (	self:						Optional[int])							->			"torch.device":

				"""simple docstring"""

				requires_backends(self			,     ["torch"])
				return self._setup_devices[0]

	@property
	def 				_SCREAMING_SNAKE_CASE  (	self:						str)							->			Optional[int]:

				"""simple docstring"""

				requires_backends(self			,     ["torch"])
				return self._setup_devices[1]







	@property
	def 				_SCREAMING_SNAKE_CASE  (	self:						str)							->			Tuple:

				"""simple docstring"""

				return self.n_gpu > 0




"""simple docstring"""






import argparse
from collections import defaultdict


def      _lowercase							(    __snake_case   ,__snake_case   ,__snake_case   ,__snake_case   ,__snake_case      )		->  Optional[int]:
			__lowerCAmelCase :    str				=			F"""{file}_{class_name}_{test_name}"""
			done_test[_id] += 1

			with open(__snake_case   ,"r"      ) as f:
						__lowerCAmelCase :    List[str]				=			f.readlines()

			__lowerCAmelCase :    Tuple				=			F"""class {class_name}("""
			__lowerCAmelCase :    Tuple				=			F"""{4 * ' '}def {test_name}("""
			__lowerCAmelCase :    List[str]				=			F"""{8 * ' '}{correct_line.split()[0]}"""
			__lowerCAmelCase :    List[Any]				=			F"""{16 * ' '}{correct_line.split()[0]}"""
			__lowerCAmelCase :    Any				=			False
			__lowerCAmelCase :    List[Any]				=			False
			__lowerCAmelCase :    Optional[Any]				=			False
			__lowerCAmelCase :    str				=			False
			__lowerCAmelCase :    Optional[int]				=			0
			__lowerCAmelCase :    Dict				=			0

			__lowerCAmelCase :    int				=			[]
			for line in lines:
						if line.startswith(__snake_case      ):
									__lowerCAmelCase :    Any				=			True
						elif in_class and line.startswith(__snake_case      ):
									__lowerCAmelCase :    str				=			True
						elif in_class and in_func and (line.startswith(__snake_case      ) or line.startswith(__snake_case      )):
									__lowerCAmelCase :    Optional[Any]				=			len(line.split(correct_line.split()[0]      )[0]      )
									count += 1

									if count == done_test[_id]:
												__lowerCAmelCase :    Optional[int]				=			True

						if in_class and in_func and in_line:
									if ")" not in line:
												continue
									else:
												__lowerCAmelCase :    Dict				=			True

						if in_class and in_func and in_line and insert_line:
									new_lines.append(F"""{spaces * ' '}{correct_line}"""      )
									__lowerCAmelCase :    Union[str, Any]				=			False
						else:
									new_lines.append(__snake_case      )

			with open(__snake_case   ,"w"      ) as f:
						for line in new_lines:
									f.write(__snake_case      )


def      _lowercase							(    __snake_case   ,__snake_case=None      )		->  int:
			if fail is not None:
						with open(__snake_case   ,"r"      ) as f:
									__lowerCAmelCase :    Union[str, Any]				=			{l.strip() for l in f.readlines()}
			else:
						__lowerCAmelCase :    Optional[Any]				=			None

			with open(__snake_case   ,"r"      ) as f:
						__lowerCAmelCase :    Union[str, Any]				=			f.readlines()

			__lowerCAmelCase :    Optional[Any]				=			defaultdict(__snake_case      )
			for line in correct_lines:
						__lowerCAmelCase		,      __lowerCAmelCase		,      __lowerCAmelCase		,      __lowerCAmelCase :    List[str]				=			line.split(";"      )
						if test_failures is None or "::".join([file, class_name, test_name]      ) in test_failures:
									overwrite_file(__snake_case   ,__snake_case   ,__snake_case   ,__snake_case   ,__snake_case      )


if __name__ == "__main__":
	__snake_case				:  Union[str, Any] =       argparse.ArgumentParser()
	parser.add_argument('--correct_filename', help='filename of tests with expected result')
	parser.add_argument('--fail_filename', help='filename of test failures', type=str, default=None)
	__snake_case				:  int =       parser.parse_args()

	main(args.correct_filename, args.fail_filename)