


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 	lowerCAmelCase__			(							_lowercase):




     '''simple docstring'''
     __SCREAMING_SNAKE_CASE         =					[
         '''no_inference''',
         '''no_cuda''',
         '''no_tpu''',
         '''no_speed''',
         '''no_memory''',
         '''no_env_print''',
         '''no_multi_process''',
     ]


     def __init__(		self					,		**__lowerCamelCase)     ->							str:
            for deprecated_arg in self.deprecated_args:
                   if deprecated_arg in kwargs:
                          _A :			List[Any]							       =					deprecated_arg[3:]
                          _A :			Tuple							       =					not kwargs.pop(A_)
                          logger.warning(
                              F"{deprecated_arg} is depreciated. Please use --no-{positive_arg} or"
                              F" {positive_arg}={kwargs[positive_arg]}")
            _A :			Optional[Any]							       =					kwargs.pop("tpu_name"					,		self.tpu_name)
            _A :			List[str]							       =					kwargs.pop("device_idx"					,		self.device_idx)
            _A :			int							       =					kwargs.pop("eager_mode"					,		self.eager_mode)
            _A :			Any							       =					kwargs.pop("use_xla"					,		self.use_xla)
            super().__init__(**A_)

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


     @cached_property
     def 					_lowerCamelCase					(		self)     ->							Tuple["tf.distribute.cluster_resolver.TPUClusterResolver"]:
            requires_backends(self					,		["tf"])
            _A :			Optional[Any]							       =					None
            if self.tpu:
                   try:
                          if self.tpu_name:
                                 _A :			Optional[int]							       =					tf.distribute.cluster_resolver.TPUClusterResolver(self.tpu_name)
                          else:
                                 _A :			List[str]							       =					tf.distribute.cluster_resolver.TPUClusterResolver()
                   except ValueError:
                          _A :			Optional[int]							       =					None
            return tpu


     @cached_property
     def 					_lowerCamelCase					(		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 :			str							       =					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 :			Union[str, Any]							       =					tf.distribute.OneDeviceStrategy(device=F"/gpu:{self.device_idx}")
                   else:
                          tf.config.set_visible_devices([]					,		"GPU")  # disable GPU
                          _A :			Union[str, Any]							       =					tf.distribute.OneDeviceStrategy(device=F"/cpu:{self.device_idx}")

            return strategy


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


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


     @property
     def 					_lowerCamelCase					(		self)     ->							Dict:
            requires_backends(self					,		["tf"])
            return tf.config.list_physical_devices("GPU")


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


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


"""simple docstring"""


from __future__ import annotations






def    _snake_case					(		snake_case__ :  tuple[int, int]						,   snake_case__ :  int  ):
	A ,   A     = position
	A     = [
	    (y + 1, x + 2),
	    (y - 1, x + 2),
	    (y + 1, x - 2),
	    (y - 1, x - 2),
	    (y + 2, x + 1),
	    (y + 2, x - 1),
	    (y - 2, x + 1),
	    (y - 2, x - 1),
	]
	A     = []

	for position in positions:
		A ,   A     = position
		if 0 <= y_test < n and 0 <= x_test < n:
			permissible_positions.append(snake_case__  )

	return permissible_positions






def    _snake_case					(		snake_case__ :  list[list[int]]  ):
	return not any(elem == 0 for row in board for elem in row  )






def    _snake_case					(		snake_case__ :  list[list[int]]						,   snake_case__ :  tuple[int, int]						,   snake_case__ :  int  ):

	if is_complete(snake_case__  ):
		return True

	for position in get_valid_pos(snake_case__						,   len(snake_case__  )  ):
		A ,   A     = position

		if board[y][x] == 0:
			A     = curr + 1
			if open_knight_tour_helper(snake_case__						,   snake_case__						,   curr + 1  ):
				return True
			A     = 0

	return False






def    _snake_case					(		snake_case__ :  int  ):
	A     = [[0 for i in range(snake_case__  )] for j in range(snake_case__  )]

	for i in range(snake_case__  ):
		for j in range(snake_case__  ):
			A     = 1
			if open_knight_tour_helper(snake_case__						,   (i, j)						,   1  ):
				return board
			A     = 0

	A     = F'Open Kight Tour cannot be performed on a board of size {n}'
	raise ValueError(snake_case__  )


if __name__ == "__main__":
		import doctest

		doctest.testmod()