



import argparse

from transformers import CanineConfig, CanineModel, CanineTokenizer, load_tf_weights_in_canine
from transformers.utils import logging


logging.set_verbosity_info()






def        a( A			:       Any					,	A			:       Tuple			)						->			Tuple:
					"""simple docstring"""





					a   	=  CanineConfig()
					a   	=  CanineModel(A			)
					model.eval()

					print(f'''Building PyTorch model from configuration: {config}'''			)

					# Load weights from tf checkpoint
					load_tf_weights_in_canine(A					,	A					,	A			)

					# Save pytorch-model (weights and configuration)
					print(f'''Save PyTorch model to {pytorch_dump_path}'''			)
					model.save_pretrained(A			)

					# Save tokenizer files
					a   	=  CanineTokenizer()
					print(f'''Save tokenizer files to {pytorch_dump_path}'''			)
					tokenizer.save_pretrained(A			)


if __name__ == "__main__":
				_lowercase:					List[str]      =						argparse.ArgumentParser()
				# Required parameters
				parser.add_argument(
				    "--tf_checkpoint_path",
				    default=None,
				    type=str,
				    required=True,
				    help="Path to the TensorFlow checkpoint. Should end with model.ckpt",
				)
				parser.add_argument(
				    "--pytorch_dump_path",
				    default=None,
				    type=str,
				    required=True,
				    help="Path to a folder where the PyTorch model will be placed.",
				)
				_lowercase:					Union[str, Any]      =						parser.parse_args()
				convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.pytorch_dump_path)





from __future__ import annotations

from collections import defaultdict
from dataclasses import dataclass



@dataclass
class       _lowercase				:





	"""simple docstring"""
	__A		      =				42
	__A		      =				None
	__A		      =				None






def        a( )						->			TreeNode:
					"""simple docstring"""





					return TreeNode(3					,	TreeNode(9			)					,	TreeNode(20					,	TreeNode(15			)					,	TreeNode(7			)			)			)






def        a( A			:       TreeNode			)						->			list[int]:
					"""simple docstring"""





					def depth_first_search(
					    A			:       TreeNode | None					,	A			:       int					,	A			:       list[int]			) -> None:
										if not root:
															return

										if depth == len(A			):
															right_view.append(root.val			)

										depth_first_search(root.right					,	depth + 1					,	A			)
										depth_first_search(root.left					,	depth + 1					,	A			)

					a   	=  []
					if not root:
										return right_view

					depth_first_search(A					,	0					,	A			)
					return right_view






def        a( A			:       TreeNode			)						->			list[int]:
					"""simple docstring"""





					def depth_first_search(
					    A			:       TreeNode | None					,	A			:       int					,	A			:       list[int]			) -> None:
										if not root:
															return

										if depth == len(A			):
															left_view.append(root.val			)

										depth_first_search(root.left					,	depth + 1					,	A			)
										depth_first_search(root.right					,	depth + 1					,	A			)

					a   	=  []
					if not root:
										return left_view

					depth_first_search(A					,	0					,	A			)
					return left_view






def        a( A			:       TreeNode			)						->			list[int]:
					"""simple docstring"""





					def breadth_first_search(A			:       TreeNode					,	A			:       list[int]			) -> None:
										a   	=  [(root, 0)]
										a   	=  defaultdict(A			)

										while queue:
															a   	=  queue.pop(0			)
															a	,							a   	=  first

															lookup[hd].append(node.val			)

															if node.left:
																				queue.append((node.left, hd - 1)			)
															if node.right:
																				queue.append((node.right, hd + 1)			)

										for pair in sorted(lookup.items()					,	key=lambda A			: each[0]			):
															top_view.append(pair[1][0]			)

					a   	=  []
					if not root:
										return top_view

					breadth_first_search(A					,	A			)
					return top_view






def        a( A			:       TreeNode			)						->			list[int]:
					"""simple docstring"""





					from collections import defaultdict

					def breadth_first_search(A			:       TreeNode					,	A			:       list[int]			) -> None:
										a   	=  [(root, 0)]
										a   	=  defaultdict(A			)

										while queue:
															a   	=  queue.pop(0			)
															a	,							a   	=  first
															lookup[hd].append(node.val			)

															if node.left:
																				queue.append((node.left, hd - 1)			)
															if node.right:
																				queue.append((node.right, hd + 1)			)

										for pair in sorted(lookup.items()					,	key=lambda A			: each[0]			):
															bottom_view.append(pair[1][-1]			)

					a   	=  []
					if not root:
										return bottom_view

					breadth_first_search(A					,	A			)
					return bottom_view


if __name__ == "__main__":
				import doctest

				doctest.testmod()
