

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


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



@dataclass
class 					_a		(__magic_name__       ):


					'''simple docstring'''






					UpperCAmelCase__:     Optional[Any]													= [
					    '''no_inference''',
					    '''no_cuda''',
					    '''no_tpu''',
					    '''no_speed''',
					    '''no_memory''',
					    '''no_env_print''',
					    '''no_multi_process''',
					]






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

						A__							:					Union[str, Any]       =	kwargs.pop("""torchscript"""					, self.torchscript    )
						A__							:					Union[str, Any]       =	kwargs.pop("""torch_xla_tpu_print_metrics"""					, self.torch_xla_tpu_print_metrics    )
						A__							:					Optional[int]       =	kwargs.pop("""fp16_opt_level"""					, self.fpaa_opt_level    )
						super().__init__(**A__    )

					UpperCAmelCase__:     bool													= field(default=__magic_name__	,     metadata={'''help''': '''Trace the models using torchscript'''}       )
					UpperCAmelCase__:     bool													= field(default=__magic_name__	,     metadata={'''help''': '''Print Xla/PyTorch tpu metrics'''}       )
					UpperCAmelCase__:     str													= 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 						__A    (				self    ):
						requires_backends(self					, ["""torch"""]    )
						logger.info("""PyTorch: setting up devices"""    )
						if not self.cuda:
							A__							:					int       =	torch.device("""cpu"""    )
							A__							:					Dict       =	0
						elif is_torch_tpu_available():
							A__							:					Union[str, Any]       =	xm.xla_device()
							A__							:					str       =	0
						else:
							A__							:					Optional[int]       =	torch.device("""cuda""" if torch.cuda.is_available() else """cpu"""    )
							A__							:					str       =	torch.cuda.device_count()
						return device, n_gpu






					@property
					def 						__A    (				self    ):
						return is_torch_tpu_available() and self.tpu






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






					@property
					def 						__A    (				self    ):
						requires_backends(self					, ["""torch"""]    )
						return self._setup_devices[0]






					@property
					def 						__A    (				self    ):
						requires_backends(self					, ["""torch"""]    )
						return self._setup_devices[1]






					@property
					def 						__A    (				self    ):
						return self.n_gpu > 0






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)



