
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


lowercase__	:Any										=					logging.get_logger(__name__)







@dataclass
class        lowercase	(      _A	):
							lowercase_ : 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:
																						lowercase					=		deprecated_arg[3:]
																						lowercase					=		not kwargs.pop(UpperCamelCase__)
																						logger.warning(
																						    f'{deprecated_arg} is depreciated. Please use --no-{positive_arg} or'
																						    f' {positive_arg}={kwargs[positive_arg]}')
												lowercase					=		kwargs.pop('''tpu_name'''     ,self.tpu_name)
												lowercase					=		kwargs.pop('''device_idx'''     ,self.device_idx)
												lowercase					=		kwargs.pop('''eager_mode'''     ,self.eager_mode)
												lowercase					=		kwargs.pop('''use_xla'''     ,self.use_xla)
												super().__init__(**UpperCamelCase__)

							lowercase_ : Optional[int]       =field(
							    default=_A ,						metadata={'''help''': '''Name of TPU'''} ,						)
							lowercase_ : Optional[Any]       =field(
							    default=0 ,						metadata={'''help''': '''CPU / GPU device index. Defaults to 0.'''} ,						)
							lowercase_ : Tuple       =field(default=_A ,						metadata={'''help''': '''Benchmark models in eager model.'''}	)
							lowercase_ : Optional[Any]       =field(
							    default=_A ,						metadata={
							        '''help''': '''Benchmark models using XLA JIT compilation. Note that `eager_model` has to be set to `False`.'''
							    } ,						)




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




							@cached_property
							def 				A__   (       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)

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

												return strategy




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




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




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




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





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






from __future__ import annotations

from random import random







class        lowercase	:




							def __init__(       self     ,A__ = None):
												lowercase					=		value
												lowercase					=		random()
												lowercase					=		None
												lowercase					=		None




							def __repr__(       self):
												from pprint import pformat

												if self.left is None and self.right is None:
																	return f'\'{self.value}: {self.prior:.5}\''
												else:
																	return pformat(
																	    {f'{self.value}: {self.prior:.5}': (self.left, self.right)}     ,indent=1)





							def __str__(       self):
												lowercase					=		str(self.value) + ''' '''
												lowercase					=		str(self.left or '''''')
												lowercase					=		str(self.right or '''''')
												return value + left + right



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__	):
					'''simple docstring'''
					if root is None:  # None tree is split into 2 Nones
										return None, None
					elif root.value is None:
										return None, None
					else:
										if value < root.value:
															lowercase			,		lowercase					=		split(root.left				,    lowerCAmelCase__	)
															return left, root
										else:
															lowercase			,		lowercase					=		split(root.right				,    lowerCAmelCase__	)
															return root, right



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__	):
					'''simple docstring'''
					if (not left) or (not right):  # If one node is None, return the other
										return left or right
					elif left.prior < right.prior:
										lowercase					=		merge(left.right				,    lowerCAmelCase__	)
										return left
					else:
										lowercase					=		merge(lowerCAmelCase__				,    right.left	)
										return right



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__	):
					'''simple docstring'''
					lowercase					=		Node(lowerCAmelCase__	)
					lowercase			,		lowercase					=		split(lowerCAmelCase__				,    lowerCAmelCase__	)
					return merge(merge(lowerCAmelCase__				,    lowerCAmelCase__	)				,    lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__	):
					'''simple docstring'''
					lowercase			,		lowercase					=		split(lowerCAmelCase__				,    value - 1	)
					lowercase			,		lowercase					=		split(lowerCAmelCase__				,    lowerCAmelCase__	)
					return merge(lowerCAmelCase__				,    lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					if not root:  # None
										return
					else:
										inorder(root.left	)
										print(root.value				,    end=''','''	)
										inorder(root.right	)



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__	):
					'''simple docstring'''
					for arg in args.split():
										if arg[0] == "+":
															lowercase					=		insert(lowerCAmelCase__				,    int(arg[1:]	)	)

										elif arg[0] == "-":
															lowercase					=		erase(lowerCAmelCase__				,    int(arg[1:]	)	)

										else:
															print('''Unknown command'''	)

					return root



def  UpperCamelCase					(							):
					'''simple docstring'''
					lowercase					=		None
					print(
					    '''enter numbers to create a tree, + value to add value into treap, '''
					    '''- value to erase all nodes with value. \'q\' to quit. '''	)

					lowercase					=		input()
					while args != "q":
										lowercase					=		interact_treap(lowerCAmelCase__				,    lowerCAmelCase__	)
										print(lowerCAmelCase__	)
										lowercase					=		input()

					print('''good by!'''	)


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							main()




