
'''simple docstring'''




from __future__ import annotations

import unittest
from collections.abc import Iterator






class     a__:


			'''simple docstring'''






			def __init__(       self	,   __lowerCAmelCase	,   __lowerCAmelCase):




					"""simple docstring"""


					lowerCAmelCase        =  label
					lowerCAmelCase        =  parent
					lowerCAmelCase        =  None
					lowerCAmelCase        =  None







class     a__:


			'''simple docstring'''






			def __init__(       self):




					"""simple docstring"""


					lowerCAmelCase        =  None



			def 							a_	(       self):




					"""simple docstring"""


					lowerCAmelCase        =  None



			def 							a_	(       self):




					"""simple docstring"""


					return self.root is None



			def 							a_	(       self	,   __lowerCAmelCase):




					"""simple docstring"""


					lowerCAmelCase        =  self._put(self.root	,   SCREAMING_SNAKE_CASE_)



			def 							a_	(       self	,   __lowerCAmelCase	,   __lowerCAmelCase	,   __lowerCAmelCase = None):




					"""simple docstring"""


					if node is None:
							lowerCAmelCase        =  Node(SCREAMING_SNAKE_CASE_	,   SCREAMING_SNAKE_CASE_)
					else:
							if label < node.label:
									lowerCAmelCase        =  self._put(node.left	,   SCREAMING_SNAKE_CASE_	,   SCREAMING_SNAKE_CASE_)
							elif label > node.label:
									lowerCAmelCase        =  self._put(node.right	,   SCREAMING_SNAKE_CASE_	,   SCREAMING_SNAKE_CASE_)
							else:
									lowerCAmelCase        =  f"Node with label {label} already exists"
									raise Exception(SCREAMING_SNAKE_CASE_)

					return node



			def 							a_	(       self	,   __lowerCAmelCase):




					"""simple docstring"""


					return self._search(self.root	,   SCREAMING_SNAKE_CASE_)



			def 							a_	(       self	,   __lowerCAmelCase	,   __lowerCAmelCase):




					"""simple docstring"""


					if node is None:
							lowerCAmelCase        =  f"Node with label {label} does not exist"
							raise Exception(SCREAMING_SNAKE_CASE_)
					else:
							if label < node.label:
									lowerCAmelCase        =  self._search(node.left	,   SCREAMING_SNAKE_CASE_)
							elif label > node.label:
									lowerCAmelCase        =  self._search(node.right	,   SCREAMING_SNAKE_CASE_)

					return node



			def 							a_	(       self	,   __lowerCAmelCase):




					"""simple docstring"""


					lowerCAmelCase        =  self.search(SCREAMING_SNAKE_CASE_)
					if node.right and node.left:
							lowerCAmelCase        =  self._get_lowest_node(node.right)
							lowerCAmelCase        =  node.left
							lowerCAmelCase        =  node.right
							lowerCAmelCase        =  lowest_node
							if node.right:
									lowerCAmelCase        =  lowest_node
							self._reassign_nodes(SCREAMING_SNAKE_CASE_	,   SCREAMING_SNAKE_CASE_)
					elif not node.right and node.left:
							self._reassign_nodes(SCREAMING_SNAKE_CASE_	,   node.left)
					elif node.right and not node.left:
							self._reassign_nodes(SCREAMING_SNAKE_CASE_	,   node.right)
					else:
							self._reassign_nodes(SCREAMING_SNAKE_CASE_	,   SCREAMING_SNAKE_CASE_)



			def 							a_	(       self	,   __lowerCAmelCase	,   __lowerCAmelCase):




					"""simple docstring"""


					if new_children:
							lowerCAmelCase        =  node.parent

					if node.parent:
							if node.parent.right == node:
									lowerCAmelCase        =  new_children
							else:
									lowerCAmelCase        =  new_children
					else:
							lowerCAmelCase        =  new_children



			def 							a_	(       self	,   __lowerCAmelCase):




					"""simple docstring"""


					if node.left:
							lowerCAmelCase        =  self._get_lowest_node(node.left)
					else:
							lowerCAmelCase        =  node
							self._reassign_nodes(SCREAMING_SNAKE_CASE_	,   node.right)

					return lowest_node



			def 							a_	(       self	,   __lowerCAmelCase):




					"""simple docstring"""


					try:
							self.search(SCREAMING_SNAKE_CASE_)
							return True
					except Exception:
							return False



			def 							a_	(       self):




					"""simple docstring"""


					if self.root is None:
							raise Exception("""Binary search tree is empty""")

					lowerCAmelCase        =  self.root
					while node.right is not None:
							lowerCAmelCase        =  node.right

					return node.label



			def 							a_	(       self):




					"""simple docstring"""


					if self.root is None:
							raise Exception("""Binary search tree is empty""")

					lowerCAmelCase        =  self.root
					while node.left is not None:
							lowerCAmelCase        =  node.left

					return node.label



			def 							a_	(       self):




					"""simple docstring"""


					return self._inorder_traversal(self.root)



			def 							a_	(       self	,   __lowerCAmelCase):




					"""simple docstring"""


					if node is not None:
							yield from self._inorder_traversal(node.left)
							yield node
							yield from self._inorder_traversal(node.right)



			def 							a_	(       self):




					"""simple docstring"""


					return self._preorder_traversal(self.root)







			def 							a_	(       self	,   __lowerCAmelCase):




					"""simple docstring"""


					if node is not None:
							yield node
							yield from self._preorder_traversal(node.left)
							yield from self._preorder_traversal(node.right)







class     a__( unittest.TestCase     ):


			'''simple docstring'''






			@staticmethod
			def 							a_	(       ):




					"""simple docstring"""


					lowerCAmelCase        =  BinarySearchTree()
					t.put(8)
					t.put(3)
					t.put(6)
					t.put(1)
					t.put(10)
					t.put(14)
					t.put(13)
					t.put(4)
					t.put(7)
					t.put(5)

					return t



			def 							a_	(       self):




					"""simple docstring"""


					lowerCAmelCase        =  BinarySearchTree()
					assert t.is_empty()

					t.put(8)
					assert t.root is not None
					assert t.root.parent is None
					assert t.root.label == 8

					t.put(10)
					assert t.root.right is not None
					assert t.root.right.parent == t.root
					assert t.root.right.label == 10

					t.put(3)
					assert t.root.left is not None
					assert t.root.left.parent == t.root
					assert t.root.left.label == 3

					t.put(6)
					assert t.root.left.right is not None
					assert t.root.left.right.parent == t.root.left
					assert t.root.left.right.label == 6

					t.put(1)
					assert t.root.left.left is not None
					assert t.root.left.left.parent == t.root.left
					assert t.root.left.left.label == 1

					with self.assertRaises(SCREAMING_SNAKE_CASE_):  # noqa: B017
							t.put(1)



			def 							a_	(       self):




					"""simple docstring"""


					lowerCAmelCase        =  self._get_binary_search_tree()

					lowerCAmelCase        =  t.search(6)
					assert node.label == 6

					lowerCAmelCase        =  t.search(13)
					assert node.label == 13

					with self.assertRaises(SCREAMING_SNAKE_CASE_):  # noqa: B017
							t.search(2)



			def 							a_	(       self):




					"""simple docstring"""


					lowerCAmelCase        =  self._get_binary_search_tree()

					t.remove(13)
					assert t.root is not None
					assert t.root.right is not None
					assert t.root.right.right is not None
					assert t.root.right.right.right is None
					assert t.root.right.right.left is None

					t.remove(7)
					assert t.root.left is not None
					assert t.root.left.right is not None
					assert t.root.left.right.left is not None
					assert t.root.left.right.right is None
					assert t.root.left.right.left.label == 4

					t.remove(6)
					assert t.root.left.left is not None
					assert t.root.left.right.right is not None
					assert t.root.left.left.label == 1
					assert t.root.left.right.label == 4
					assert t.root.left.right.right.label == 5
					assert t.root.left.right.left is None
					assert t.root.left.left.parent == t.root.left
					assert t.root.left.right.parent == t.root.left

					t.remove(3)
					assert t.root is not None
					assert t.root.left.label == 4
					assert t.root.left.right.label == 5
					assert t.root.left.left.label == 1
					assert t.root.left.parent == t.root
					assert t.root.left.left.parent == t.root.left
					assert t.root.left.right.parent == t.root.left

					t.remove(4)
					assert t.root.left is not None
					assert t.root.left.left is not None
					assert t.root.left.label == 5
					assert t.root.left.right is None
					assert t.root.left.left.label == 1
					assert t.root.left.parent == t.root
					assert t.root.left.left.parent == t.root.left



			def 							a_	(       self):




					"""simple docstring"""


					lowerCAmelCase        =  self._get_binary_search_tree()

					t.remove(3)
					assert t.root is not None
					assert t.root.left is not None
					assert t.root.left.left is not None
					assert t.root.left.right is not None
					assert t.root.left.right.left is not None
					assert t.root.left.right.right is not None
					assert t.root.left.label == 4
					assert t.root.left.right.label == 6
					assert t.root.left.left.label == 1
					assert t.root.left.right.right.label == 7
					assert t.root.left.right.left.label == 5
					assert t.root.left.parent == t.root
					assert t.root.left.right.parent == t.root.left
					assert t.root.left.left.parent == t.root.left
					assert t.root.left.right.left.parent == t.root.left.right



			def 							a_	(       self):




					"""simple docstring"""


					lowerCAmelCase        =  self._get_binary_search_tree()
					t.empty()
					assert t.root is None



			def 							a_	(       self):




					"""simple docstring"""


					lowerCAmelCase        =  self._get_binary_search_tree()
					assert not t.is_empty()

					t.empty()
					assert t.is_empty()



			def 							a_	(       self):




					"""simple docstring"""


					lowerCAmelCase        =  self._get_binary_search_tree()

					assert t.exists(6)
					assert not t.exists(-1)



			def 							a_	(       self):




					"""simple docstring"""


					lowerCAmelCase        =  self._get_binary_search_tree()

					assert t.get_max_label() == 14

					t.empty()
					with self.assertRaises(SCREAMING_SNAKE_CASE_):  # noqa: B017
							t.get_max_label()



			def 							a_	(       self):




					"""simple docstring"""


					lowerCAmelCase        =  self._get_binary_search_tree()

					assert t.get_min_label() == 1

					t.empty()
					with self.assertRaises(SCREAMING_SNAKE_CASE_):  # noqa: B017
							t.get_min_label()



			def 							a_	(       self):




					"""simple docstring"""


					lowerCAmelCase        =  self._get_binary_search_tree()

					lowerCAmelCase        =  [i.label for i in t.inorder_traversal()]
					assert inorder_traversal_nodes == [1, 3, 4, 5, 6, 7, 8, 10, 13, 14]







			def 							a_	(       self):




					"""simple docstring"""


					lowerCAmelCase        =  self._get_binary_search_tree()

					lowerCAmelCase        =  [i.label for i in t.preorder_traversal()]
					assert preorder_traversal_nodes == [8, 3, 1, 6, 4, 5, 7, 10, 14, 13]







def     snake_case__							(      )   ->     None:

		'''simple docstring'''


		lowerCAmelCase        =  BinarySearchTree()
		t.put(8			)
		t.put(3			)
		t.put(6			)
		t.put(1			)
		t.put(10			)
		t.put(14			)
		t.put(13			)
		t.put(4			)
		t.put(7			)
		t.put(5			)

		print(
		    """
            8
           / \\
          3   10
         / \\    \\
        1   6    14
           / \\   /
          4   7 13
           \\
            5
        """			)

		print("""Label 6 exists:"""				,       t.exists(6			)			)
		print("""Label 13 exists:"""				,       t.exists(13			)			)
		print("""Label -1 exists:"""				,       t.exists(-1			)			)
		print("""Label 12 exists:"""				,       t.exists(12			)			)

		# Prints all the elements of the list in inorder traversal
		lowerCAmelCase        =  [i.label for i in t.inorder_traversal()]
		print("""Inorder traversal:"""				,       _A			)

		# Prints all the elements of the list in preorder traversal
		lowerCAmelCase        =  [i.label for i in t.preorder_traversal()]
		print("""Preorder traversal:"""				,       _A			)

		print("""Max. label:"""				,       t.get_max_label()			)
		print("""Min. label:"""				,       t.get_min_label()			)

		# Delete elements
		print("""\nDeleting elements 13, 10, 8, 3, 6, 14"""			)
		print(
		    """
          4
         / \\
        1   7
             \\
              5
        """			)
		t.remove(13			)
		t.remove(10			)
		t.remove(8			)
		t.remove(3			)
		t.remove(6			)
		t.remove(14			)

		# Prints all the elements of the list in inorder traversal after delete
		lowerCAmelCase        =  [i.label for i in t.inorder_traversal()]
		print("""Inorder traversal after delete:"""				,       _A			)

		# Prints all the elements of the list in preorder traversal after delete
		lowerCAmelCase        =  [i.label for i in t.preorder_traversal()]
		print("""Preorder traversal after delete:"""				,       _A			)

		print("""Max. label:"""				,       t.get_max_label()			)
		print("""Min. label:"""				,       t.get_min_label()			)


if __name__ == "__main__":
						binary_search_tree_example()





'''simple docstring'''




import argparse

import torch
from flax.training.checkpoints import restore_checkpoint

from transformers import FNetConfig, FNetForPreTraining
from transformers.utils import logging


logging.set_verbosity_info()






def     snake_case__							(      _A: Dict				,       _A: str				,       _A: int			)   ->     Any:

		'''simple docstring'''


		lowerCAmelCase        =  FNetConfig.from_json_file(_A			)
		print(f"Building PyTorch model from configuration: {config}"			)
		lowerCAmelCase        =  FNetForPreTraining(_A			)

		lowerCAmelCase        =  restore_checkpoint(_A				,       _A			)
		lowerCAmelCase        =  checkpoint_dict["""target"""]

		# Embeddings
		# Position IDs
		lowerCAmelCase        =  fnet_pretraining_model.state_dict()

		lowerCAmelCase        =  state_dict["""fnet.embeddings.position_ids"""]
		lowerCAmelCase        =  {"""fnet.embeddings.position_ids""": position_ids}
		# Embedding Layers
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""encoder"""]["""embedder"""]["""word"""]["""embedding"""]			)
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""encoder"""]["""embedder"""]["""position"""]["""embedding"""][0]			)
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""encoder"""]["""embedder"""]["""type"""]["""embedding"""]			)
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""encoder"""]["""embedder"""]["""hidden_mapping_in"""]["""kernel"""]			).T
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""encoder"""]["""embedder"""]["""hidden_mapping_in"""]["""bias"""]			)
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""encoder"""]["""embedder"""]["""layer_norm"""]["""scale"""]			)
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""encoder"""]["""embedder"""]["""layer_norm"""]["""bias"""]			)

		# Encoder Layers
		for layer in range(config.num_hidden_layers			):
				lowerCAmelCase        =  torch.tensor(
				    pretrained_model_params["""encoder"""][f"encoder_{layer}"]["""mixing_layer_norm"""]["""scale"""]			)
				lowerCAmelCase        =  torch.tensor(
				    pretrained_model_params["""encoder"""][f"encoder_{layer}"]["""mixing_layer_norm"""]["""bias"""]			)

				lowerCAmelCase        =  torch.tensor(
				    pretrained_model_params["""encoder"""][f"feed_forward_{layer}"]["""intermediate"""]["""kernel"""]			).T
				lowerCAmelCase        =  torch.tensor(
				    pretrained_model_params["""encoder"""][f"feed_forward_{layer}"]["""intermediate"""]["""bias"""]			)

				lowerCAmelCase        =  torch.tensor(
				    pretrained_model_params["""encoder"""][f"feed_forward_{layer}"]["""output"""]["""kernel"""]			).T
				lowerCAmelCase        =  torch.tensor(
				    pretrained_model_params["""encoder"""][f"feed_forward_{layer}"]["""output"""]["""bias"""]			)

				lowerCAmelCase        =  torch.tensor(
				    pretrained_model_params["""encoder"""][f"encoder_{layer}"]["""output_layer_norm"""]["""scale"""]			)
				lowerCAmelCase        =  torch.tensor(
				    pretrained_model_params["""encoder"""][f"encoder_{layer}"]["""output_layer_norm"""]["""bias"""]			)

		# Pooler Layers
		lowerCAmelCase        =  torch.tensor(pretrained_model_params["""encoder"""]["""pooler"""]["""kernel"""]			).T
		lowerCAmelCase        =  torch.tensor(pretrained_model_params["""encoder"""]["""pooler"""]["""bias"""]			)

		# Masked LM Layers
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""predictions_dense"""]["""kernel"""]			).T
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""predictions_dense"""]["""bias"""]			)
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""predictions_layer_norm"""]["""scale"""]			)
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""predictions_layer_norm"""]["""bias"""]			)
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""encoder"""]["""embedder"""]["""word"""]["""embedding"""]			)
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""predictions_output"""]["""output_bias"""]			)
		lowerCAmelCase        =  torch.tensor(pretrained_model_params["""predictions_output"""]["""output_bias"""]			)

		# Seq Relationship Layers
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""classification"""]["""output_kernel"""]			)
		lowerCAmelCase        =  torch.tensor(
		    pretrained_model_params["""classification"""]["""output_bias"""]			)

		# Load State Dict
		fnet_pretraining_model.load_state_dict(_A			)

		# Save PreTrained
		print(f"Saving pretrained model to {save_path}"			)
		fnet_pretraining_model.save_pretrained(_A			)


if __name__ == "__main__":
						__lowercase				   =  argparse.ArgumentParser()
						# Required parameters
						parser.add_argument(
						    '''--flax_checkpoint_path''', default=None, type=str, required=True, help='''Path to the TensorFlow checkpoint path.'''
						)
						parser.add_argument(
						    '''--fnet_config_file''',
						    default=None,
						    type=str,
						    required=True,
						    help=(
						        '''The config json file corresponding to the pre-trained FNet model. \n'''
						        '''This specifies the model architecture.'''
						    ),
						)
						parser.add_argument('''--save_path''', default=None, type=str, required=True, help='''Path to the output model.''')
						__lowercase				   =  parser.parse_args()
						convert_flax_checkpoint_to_pytorch(args.flax_checkpoint_path, args.fnet_config_file, args.save_path)




