





import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_tf


if is_tf_available():
			import tensorflow as tf
			from tensorflow.python.eager import context
			from tensorflow.python.framework import ops

			from transformers import GradientAccumulator, create_optimizer


@require_tf
class       __lowerCAmelCase					(       unittest.TestCase      ):


	'''simple docstring'''





	def    snake_case__(						self:						Optional[Any],					lowerCamelCase_:						int,					lowerCamelCase_:						List[Any],					lowerCamelCase_:						int			):
			self.assertEqual(len(lowerCamelCase_			),					len(lowerCamelCase_			)			)
			for a, b in zip(lowerCamelCase_,					lowerCamelCase_			):
					self.assertAlmostEqual(lowerCamelCase_,					lowerCamelCase_,					delta=lowerCamelCase_			)

	def    snake_case__(						self:						List[Any]			):
			lowercase__					:      str      =		GradientAccumulator()
			accumulator([tf.constant([1.0, 2.0]			)]			)
			accumulator([tf.constant([-2.0, 1.0]			)]			)
			accumulator([tf.constant([-1.0, 2.0]			)]			)
			with self.assertRaises(lowerCamelCase_			):
					accumulator([tf.constant([1.0, 1.0]			), tf.constant([2.0, 2.0]			)]			)
			self.assertEqual(accumulator.step,					3			)
			self.assertEqual(len(accumulator.gradients			),					1			)
			self.assertListAlmostEqual(accumulator.gradients[0].numpy().tolist(),					[-2.0, 5.0],					tol=1E-2			)
			accumulator.reset()
			self.assertEqual(accumulator.step,					0			)
			self.assertListAlmostEqual(accumulator.gradients[0].numpy().tolist(),					[0.0, 0.0],					tol=1E-2			)





	def    snake_case__(						self:						Optional[Any]			):
			lowercase__					:      List[Any]      =		None
			ops.enable_eager_execution_internal()
			lowercase__					:      Optional[int]      =		tf.config.list_physical_devices('CPU'			)
			if len(lowerCamelCase_			) == 1:
					tf.config.set_logical_device_configuration(
					    physical_devices[0],					[tf.config.LogicalDeviceConfiguration(), tf.config.LogicalDeviceConfiguration()]			)
			lowercase__					:      Tuple      =		tf.config.list_logical_devices(device_type='CPU'			)
			lowercase__					:      Optional[Any]      =		tf.distribute.MirroredStrategy(devices=devices[:2]			)

			with strategy.scope():
					lowercase__					:      Union[str, Any]      =		GradientAccumulator()
					lowercase__					:      Any      =		tf.Variable([4.0, 3.0]			)
					lowercase__   ,				lowercase__					:      Tuple      =		create_optimizer(5E-5,					10,					5			)
					lowercase__					:      Optional[Any]      =		tf.Variable([0.0, 0.0],					trainable=lowerCamelCase_			)

			def accumulate_on_replica(lowerCamelCase_:						int			):
					accumulator([gradient]			)

			def apply_on_replica():
					optimizer.apply_gradients(list(zip(accumulator.gradients,					[variable]			)			)			)

			@tf.function
			def accumulate(lowerCamelCase_:						Tuple,					lowerCamelCase_:						Any			):
					with strategy.scope():
							lowercase__					:      Any      =		strategy.experimental_local_results(lowerCamelCase_			)
							local_variables[0].assign(lowerCamelCase_			)
							local_variables[1].assign(lowerCamelCase_			)
							strategy.run(lowerCamelCase_,					args=(gradient_placeholder,)			)

			@tf.function
			def apply_grad():
					with strategy.scope():
							strategy.run(lowerCamelCase_			)

			def _check_local_values(lowerCamelCase_:						List[Any],					lowerCamelCase_:						List[Any]			):
					lowercase__					:      Any      =		strategy.experimental_local_results(accumulator._gradients[0]			)
					self.assertListAlmostEqual(values[0].value(),					lowerCamelCase_,					tol=1E-2			)
					self.assertListAlmostEqual(values[1].value(),					lowerCamelCase_,					tol=1E-2			)

			accumulate([1.0, 2.0],					[-1.0, 1.0]			)
			accumulate([3.0, -1.0],					[-1.0, -1.0]			)
			accumulate([-2.0, 2.0],					[3.0, -2.0]			)
			self.assertEqual(accumulator.step,					3			)
			_check_local_values([2.0, 3.0],					[1.0, -2.0]			)
			apply_grad()
			self.assertListAlmostEqual(variable.value(),					[4.0, 3.0],					tol=1E-2			)
			accumulator.reset()
			self.assertEqual(accumulator.step,					0			)
			_check_local_values([0.0, 0.0],					[0.0, 0.0]			)









__UpperCamelCase:	str = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}

__UpperCamelCase:	Tuple = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : dict[int, list[int]]   ,    _lowercase     : int   ,    _lowercase     : list[bool]			)   ->							list[int]:




		'''simple docstring'''
		lowercase__					:      str      =		True
		lowercase__					:      int      =		[]

		for neighbour in graph[vert]:
				if not visited[neighbour]:
						order += topology_sort(_lowercase   ,    _lowercase   ,    _lowercase			)

		order.append(_lowercase			)

		return order


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : dict[int, list[int]]   ,    _lowercase     : int   ,    _lowercase     : list[bool]			)   ->							list[int]:




		'''simple docstring'''
		lowercase__					:      Union[str, Any]      =		True
		lowercase__					:      Optional[Any]      =		[vert]

		for neighbour in reversed_graph[vert]:
				if not visited[neighbour]:
						component += find_components(_lowercase   ,    _lowercase   ,    _lowercase			)

		return component





def       SCREAMING_SNAKE_CASE__  (       _lowercase     : dict[int, list[int]]			)   ->							list[list[int]]:




		'''simple docstring'''
		lowercase__					:      Optional[int]      =		len(_lowercase			) * [False]
		lowercase__					:      dict[int, list[int]]      =		{vert: [] for vert in range(len(_lowercase			)			)}

		for vert, neighbours in graph.items():
				for neighbour in neighbours:
						reversed_graph[neighbour].append(_lowercase			)

		lowercase__					:      Dict      =		[]
		for i, was_visited in enumerate(_lowercase			):
				if not was_visited:
						order += topology_sort(_lowercase   ,    _lowercase   ,    _lowercase			)

		lowercase__					:      Dict      =		[]
		lowercase__					:      Optional[Any]      =		len(_lowercase			) * [False]

		for i in range(len(_lowercase			)			):
				lowercase__					:      List[Any]      =		order[len(_lowercase			) - i - 1]
				if not visited[vert]:
						lowercase__					:      Tuple      =		find_components(_lowercase   ,    _lowercase   ,    _lowercase			)
						components_list.append(_lowercase			)

		return components_list


