



"""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


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


@dataclass
class 							lowerCamelCase_(   A__    ):





					'''simple docstring'''



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

					def __init__(    self				,       **lowerCamelCase__   ):
									for deprecated_arg in self.deprecated_args:
													if deprecated_arg in kwargs:
																	_lowerCamelCase        =				deprecated_arg[3:]
																	_lowerCamelCase        =				not kwargs.pop(lowerCamelCase__   )
																	logger.warning(
																	    F"""{deprecated_arg} is depreciated. Please use --no-{positive_arg} or"""
																	    F""" {positive_arg}={kwargs[positive_arg]}"""   )
									_lowerCamelCase        =				kwargs.pop('''tpu_name'''				,       self.tpu_name   )
									_lowerCamelCase        =				kwargs.pop('''device_idx'''				,       self.device_idx   )
									_lowerCamelCase        =				kwargs.pop('''eager_mode'''				,       self.eager_mode   )
									_lowerCamelCase        =				kwargs.pop('''use_xla'''				,       self.use_xla   )
									super().__init__(**lowerCamelCase__   )

					lowercase__   :       str										= field(
					    default=A__,				metadata={'help': 'Name of TPU'},				)
					lowercase__   :       int										= field(
					    default=0,				metadata={'help': 'CPU / GPU device index. Defaults to 0.'},				)
					lowercase__   :       bool										= field(default=A__,				metadata={'help': 'Benchmark models in eager model.'}    )
					lowercase__   :       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   ):
									requires_backends(self				,       ['''tf''']   )
									_lowerCamelCase        =				None
									if self.tpu:
													try:
																	if self.tpu_name:
																					_lowerCamelCase        =				tf.distribute.cluster_resolver.TPUClusterResolver(self.tpu_name   )
																	else:
																					_lowerCamelCase        =				tf.distribute.cluster_resolver.TPUClusterResolver()
													except ValueError:
																	_lowerCamelCase        =				None
									return tpu

					@cached_property
					def 			snake_case__      (    self   ):
									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   )

													_lowerCamelCase        =				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'''   )
																	_lowerCamelCase        =				tf.distribute.OneDeviceStrategy(device=F"""/gpu:{self.device_idx}"""   )
													else:
																	tf.config.set_visible_devices([]				,       '''GPU'''   )  # disable GPU
																	_lowerCamelCase        =				tf.distribute.OneDeviceStrategy(device=F"""/cpu:{self.device_idx}"""   )

									return strategy

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

					@property
					def 			snake_case__      (    self   ):
									requires_backends(self				,       ['''tf''']   )
									return self._setup_strategy

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

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





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





"""simple docstring"""
def        lowerCAmelCase_(   lowercase_     :							str						,   lowercase_     :							str							)	->       bool:
				_lowerCamelCase        =				len(lowercase_							)
				_lowerCamelCase        =				len(lowercase_							)
				_lowerCamelCase        =				[[False for _ in range(m + 1							)] for _ in range(n + 1							)]
				_lowerCamelCase        =				True
				for i in range(lowercase_							):
								for j in range(m + 1							):
												if dp[i][j]:
																if j < m and a[i].upper() == b[j]:
																				_lowerCamelCase        =				True
																if a[i].islower():
																				_lowerCamelCase        =				True
				return dp[n][m]


if __name__ == "__main__":
			import doctest

			doctest.testmod()
