

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 					a__						(					unittest.TestCase			):
			"""simple docstring"""







			def      UpperCamelCase		(    self      ,      lowercase      ,      lowercase      ,      lowercase       )  ->						Dict:
							'''simple docstring'''






							self.assertEqual(len(lowercase       )      ,      len(lowercase       )       )
							for a, b in zip(lowercase      ,      lowercase       ):
											self.assertAlmostEqual(lowercase      ,      lowercase      ,      delta=lowercase       )


			def      UpperCamelCase		(    self       )  ->						Any:
							'''simple docstring'''






							A__        =			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(lowercase       ):
											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      UpperCamelCase		(    self       )  ->						int:
							'''simple docstring'''






							A__        =			None
							ops.enable_eager_execution_internal()
							A__        =			tf.config.list_physical_devices("CPU"       )
							if len(lowercase       ) == 1:
											tf.config.set_logical_device_configuration(
											    physical_devices[0]      ,      [tf.config.LogicalDeviceConfiguration(), tf.config.LogicalDeviceConfiguration()]       )
							A__        =			tf.config.list_logical_devices(device_type="CPU"       )
							A__        =			tf.distribute.MirroredStrategy(devices=devices[:2]       )

							with strategy.scope():
											A__        =			GradientAccumulator()
											A__        =			tf.Variable([4.0, 3.0]       )
											A__    ,				A__        =			create_optimizer(5e-5      ,      10      ,      5       )
											A__        =			tf.Variable([0.0, 0.0]      ,      trainable=lowercase       )

							def accumulate_on_replica(lowercase       ):
											accumulator([gradient]       )

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

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

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

							def _check_local_values(lowercase      ,      lowercase       ):
											A__        =			strategy.experimental_local_results(accumulator._gradients[0]       )
											self.assertListAlmostEqual(values[0].value()      ,      lowercase      ,      tol=1e-2       )
											self.assertListAlmostEqual(values[1].value()      ,      lowercase      ,      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]       )




from __future__ import annotations

from collections.abc import Iterator
from typing import Any

class 					a__						:
			"""simple docstring"""







			def __init__(    self      ,      lowercase       )  ->						int:
							'''simple docstring'''






							A__        =			data
							A__        =			None

class 					a__						:
			"""simple docstring"""







			def __init__(    self       )  ->						List[Any]:
							'''simple docstring'''






							A__        =			None
							A__        =			None


			def __iter__(    self       )  ->						Iterator[Any]:
							'''simple docstring'''






							A__        =			self.head
							while self.head:
											yield node.data
											A__        =			node.next
											if node == self.head:
															break


			def __len__(    self       )  ->						int:
							'''simple docstring'''






							return sum(1 for _ in self       )


			def __repr__(    self       )  ->						List[Any]:
							'''simple docstring'''






							return "->".join(str(lowercase       ) for item in iter(self       )       )


			def      UpperCamelCase		(    self      ,      lowercase       )  ->						None:
							'''simple docstring'''






							self.insert_nth(len(self       )      ,      lowercase       )


			def      UpperCamelCase		(    self      ,      lowercase       )  ->						None:
							'''simple docstring'''






							self.insert_nth(0      ,      lowercase       )


			def      UpperCamelCase		(    self      ,      lowercase      ,      lowercase       )  ->						None:
							'''simple docstring'''






							if index < 0 or index > len(self       ):
											raise IndexError("list index out of range."       )
							A__        =			Node(lowercase       )
							if self.head is None:
											A__        =			new_node  # first node points itself
											A__        =			A__        =			new_node
							elif index == 0:  # insert at head
											A__        =			self.head
											A__        =			A__        =			new_node
							else:
											A__        =			self.head
											for _ in range(index - 1       ):
															A__        =			temp.next
											A__        =			temp.next
											A__        =			new_node
											if index == len(self       ) - 1:  # insert at tail
															A__        =			new_node


			def      UpperCamelCase		(    self       )  ->						List[Any]:
							'''simple docstring'''






							return self.delete_nth(0       )


			def      UpperCamelCase		(    self       )  ->						Any:
							'''simple docstring'''






							return self.delete_nth(len(self       ) - 1       )


			def      UpperCamelCase		(    self      ,      lowercase = 0       )  ->						Any:
							'''simple docstring'''






							if not 0 <= index < len(self       ):
											raise IndexError("list index out of range."       )
							A__        =			self.head
							if self.head == self.tail:  # just one node
											A__        =			A__        =			None
							elif index == 0:  # delete head node
											A__        =			self.tail.next.next
											A__        =			self.head.next
							else:
											A__        =			self.head
											for _ in range(index - 1       ):
															A__        =			temp.next
											A__        =			temp.next
											A__        =			temp.next.next
											if index == len(self       ) - 1:  # delete at tail
															A__        =			temp
							return delete_node.data


			def      UpperCamelCase		(    self       )  ->						bool:
							'''simple docstring'''






							return len(self       ) == 0



def 					lowerCAmelCase__							(	)			->      None:




				'''simple docstring'''





				A__        =			CircularLinkedList()
				assert len(SCREAMING_SNAKE_CASE_      ) == 0
				assert circular_linked_list.is_empty() is True
				assert str(SCREAMING_SNAKE_CASE_      ) == ""

				try:
								circular_linked_list.delete_front()
								raise AssertionError  # This should not happen
				except IndexError:
								assert True  # This should happen

				try:
								circular_linked_list.delete_tail()
								raise AssertionError  # This should not happen
				except IndexError:
								assert True  # This should happen

				try:
								circular_linked_list.delete_nth(-1      )
								raise AssertionError
				except IndexError:
								assert True

				try:
								circular_linked_list.delete_nth(0      )
								raise AssertionError
				except IndexError:
								assert True

				assert circular_linked_list.is_empty() is True
				for i in range(5      ):
								assert len(SCREAMING_SNAKE_CASE_      ) == i
								circular_linked_list.insert_nth(SCREAMING_SNAKE_CASE_	,       i + 1      )
				assert str(SCREAMING_SNAKE_CASE_      ) == "->".join(str(SCREAMING_SNAKE_CASE_      ) for i in range(1	,       6      )      )

				circular_linked_list.insert_tail(6      )
				assert str(SCREAMING_SNAKE_CASE_      ) == "->".join(str(SCREAMING_SNAKE_CASE_      ) for i in range(1	,       7      )      )
				circular_linked_list.insert_head(0      )
				assert str(SCREAMING_SNAKE_CASE_      ) == "->".join(str(SCREAMING_SNAKE_CASE_      ) for i in range(0	,       7      )      )

				assert circular_linked_list.delete_front() == 0
				assert circular_linked_list.delete_tail() == 6
				assert str(SCREAMING_SNAKE_CASE_      ) == "->".join(str(SCREAMING_SNAKE_CASE_      ) for i in range(1	,       6      )      )
				assert circular_linked_list.delete_nth(2      ) == 3

				circular_linked_list.insert_nth(2	,       3      )
				assert str(SCREAMING_SNAKE_CASE_      ) == "->".join(str(SCREAMING_SNAKE_CASE_      ) for i in range(1	,       6      )      )

				assert circular_linked_list.is_empty() is False


if __name__ == "__main__":
	import doctest

	doctest.testmod()

