"""simple docstring"""




from dataclasses import dataclass, field
from typing import Tuple

from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments


if is_tf_available():
				import tensorflow as tf


__lowerCamelCase											=  logging.get_logger(__name__)
@dataclass
class     UpperCamelCase__(			__A ):
						lowerCAmelCase__  :						int													=		[
						    'no_inference',
						    'no_cuda',
						    'no_tpu',
						    'no_speed',
						    'no_memory',
						    'no_env_print',
						    'no_multi_process',
						]





						def __init__(       self		,**__UpperCAmelCase     )					->				List[Any]:
													for deprecated_arg in self.deprecated_args:
																				if deprecated_arg in kwargs:
																											A__	     =							deprecated_arg[3:]
																											A__	     =							not kwargs.pop(__UpperCAmelCase     )
																											logger.warning(
																											    f'''{deprecated_arg} is depreciated. Please use --no-{positive_arg} or'''
																											    f''' {positive_arg}={kwargs[positive_arg]}'''     )
													A__	     =							kwargs.pop('tpu_name'		,self.tpu_name     )
													A__	     =							kwargs.pop('device_idx'		,self.device_idx     )
													A__	     =							kwargs.pop('eager_mode'		,self.eager_mode     )
													A__	     =							kwargs.pop('use_xla'		,self.use_xla     )
													super().__init__(**__UpperCAmelCase     )

						lowerCAmelCase__  :						str													=		field(
						    default=__A		,						metadata={'help': 'Name of TPU'}		,						)
						lowerCAmelCase__  :						int													=		field(
						    default=0		,						metadata={'help': 'CPU / GPU device index. Defaults to 0.'}		,						)
						lowerCAmelCase__  :						bool													=		field(default=__A		,						metadata={'help': 'Benchmark models in eager model.'} )
						lowerCAmelCase__  :						bool													=		field(
						    default=__A		,						metadata={
						        'help': 'Benchmark models using XLA JIT compilation. Note that `eager_model` has to be set to `False`.'
						    }		,						)





						@cached_property
						def 				snake_case__	(       self     )					->				Tuple["tf.distribute.cluster_resolver.TPUClusterResolver"]:
													requires_backends(self		,['tf']     )
													A__	     =							None
													if self.tpu:
																				try:
																											if self.tpu_name:
																																		A__	     =							tf.distribute.cluster_resolver.TPUClusterResolver(self.tpu_name     )
																											else:
																																		A__	     =							tf.distribute.cluster_resolver.TPUClusterResolver()
																				except ValueError:
																											A__	     =							None
													return tpu





						@cached_property
						def 				snake_case__	(       self     )					->				Tuple["tf.distribute.Strategy", "tf.distribute.cluster_resolver.TPUClusterResolver"]:
													requires_backends(self		,['tf']     )
													if self.is_tpu:
																				tf.config.experimental_connect_to_cluster(self._setup_tpu     )
																				tf.tpu.experimental.initialize_tpu_system(self._setup_tpu     )

																				A__	     =							tf.distribute.TPUStrategy(self._setup_tpu     )
													else:
																				# currently no multi gpu is allowed
																				if self.is_gpu:
																											# TODO: Currently only single GPU is supported
																											tf.config.set_visible_devices(self.gpu_list[self.device_idx]		,'GPU'     )
																											A__	     =							tf.distribute.OneDeviceStrategy(device=f'''/gpu:{self.device_idx}'''     )
																				else:
																											tf.config.set_visible_devices([]		,'GPU'     )  # disable GPU
																											A__	     =							tf.distribute.OneDeviceStrategy(device=f'''/cpu:{self.device_idx}'''     )

													return strategy





						@property
						def 				snake_case__	(       self     )					->				bool:
													requires_backends(self		,['tf']     )
													return self._setup_tpu is not None





						@property
						def 				snake_case__	(       self     )					->				"tf.distribute.Strategy":
													requires_backends(self		,['tf']     )
													return self._setup_strategy





						@property
						def 				snake_case__	(       self     )					->				Any:
													requires_backends(self		,['tf']     )
													return tf.config.list_physical_devices('GPU'     )





						@property
						def 				snake_case__	(       self     )					->				int:
													requires_backends(self		,['tf']     )
													if self.cuda:
																				return len(self.gpu_list     )
													return 0





						@property
						def 				snake_case__	(       self     )					->				bool:
													return self.n_gpu > 0






"""simple docstring"""




import os


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
__lowerCamelCase											=  "."


if __name__ == "__main__":
				__lowerCamelCase											=  os.path.join(REPO_PATH, "utils/documentation_tests.txt")
				__lowerCamelCase											=  []
				__lowerCamelCase											=  []
				with open(doctest_file_path) as fp:
								for line in fp:
												__lowerCamelCase											=  line.strip()
												__lowerCamelCase											=  os.path.join(REPO_PATH, line)
												if not (os.path.isfile(path) or os.path.isdir(path)):
																non_existent_paths.append(line)
												all_paths.append(path)
				if len(non_existent_paths) > 0:
								__lowerCamelCase											=  "\n".join(non_existent_paths)
								raise ValueError(F'''`utils/documentation_tests.txt` contains non-existent paths:\n{non_existent_paths}''')
				if all_paths != sorted(all_paths):
								raise ValueError("Files in `utils/documentation_tests.txt` are not in alphabetical order.")





