





'''simple docstring'''






from __future__ import annotations

import queue




class 					UpperCAmelCase	:




      def __init__(     self     :					Optional[Any]     ,     __snake_case     :					Union[str, Any]    )							-> List[str]:
            _lowerCAmelCase					=				data
            _lowerCAmelCase					=				None
            _lowerCAmelCase					=				None




def   UpperCamelCase__ (						):





      """simple docstring"""


      print("""\n********Press N to stop entering at any point of time********\n"""    )
      _lowerCAmelCase					=				input("""Enter the value of the root node: """    ).strip().lower()
      _lowerCAmelCase					=				queue.Queue()
      _lowerCAmelCase					=				TreeNode(int(lowerCAmelCase    )    )
      q.put(lowerCAmelCase    )
      while not q.empty():
            _lowerCAmelCase					=				q.get()
            _lowerCAmelCase					=				f"Enter the left node of {node_found.data}: "
            _lowerCAmelCase					=				input(lowerCAmelCase    ).strip().lower() or """n"""
            if check == "n":
                  return tree_node
            _lowerCAmelCase					=				TreeNode(int(lowerCAmelCase    )    )
            _lowerCAmelCase					=				left_node
            q.put(lowerCAmelCase    )
            _lowerCAmelCase					=				f"Enter the right node of {node_found.data}: "
            _lowerCAmelCase					=				input(lowerCAmelCase    ).strip().lower() or """n"""
            if check == "n":
                  return tree_node
            _lowerCAmelCase					=				TreeNode(int(lowerCAmelCase    )    )
            _lowerCAmelCase					=				right_node
            q.put(lowerCAmelCase    )
      raise
def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      if not isinstance(lowerCAmelCase				,      lowerCAmelCase    ) or not node:
            return
      print(node.data				,      end=""","""    )
      pre_order(node.left    )
      pre_order(node.right    )
def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      if not isinstance(lowerCAmelCase				,      lowerCAmelCase    ) or not node:
            return
      in_order(node.left    )
      print(node.data				,      end=""","""    )
      in_order(node.right    )
def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      if not isinstance(lowerCAmelCase				,      lowerCAmelCase    ) or not node:
            return
      post_order(node.left    )
      post_order(node.right    )
      print(node.data				,      end=""","""    )
def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      if not isinstance(lowerCAmelCase				,      lowerCAmelCase    ) or not node:
            return
      _lowerCAmelCase					=				queue.Queue()
      q.put(lowerCAmelCase    )
      while not q.empty():
            _lowerCAmelCase					=				q.get()
            print(node_dequeued.data				,      end=""","""    )
            if node_dequeued.left:
                  q.put(node_dequeued.left    )
            if node_dequeued.right:
                  q.put(node_dequeued.right    )
def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      if not isinstance(lowerCAmelCase				,      lowerCAmelCase    ) or not node:
            return
      _lowerCAmelCase					=				queue.Queue()
      q.put(lowerCAmelCase    )
      while not q.empty():
            _lowerCAmelCase					=				[]
            while not q.empty():
                  _lowerCAmelCase					=				q.get()
                  print(node_dequeued.data				,      end=""","""    )
                  if node_dequeued.left:
                        list_.append(node_dequeued.left    )
                  if node_dequeued.right:
                        list_.append(node_dequeued.right    )
            print()
            for node in list_:
                  q.put(lowerCAmelCase    )
def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      if not isinstance(lowerCAmelCase				,      lowerCAmelCase    ) or not node:
            return
      _lowerCAmelCase					=				[]
      _lowerCAmelCase					=				node
      while n or stack:
            while n:  # start from root node, find its left child
                  print(n.data				,      end=""","""    )
                  stack.append(lowerCAmelCase    )
                  _lowerCAmelCase					=				n.left
            # end of while means current node doesn't have left child
            _lowerCAmelCase					=				stack.pop()
            # start to traverse its right child
            _lowerCAmelCase					=				n.right
def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      if not isinstance(lowerCAmelCase				,      lowerCAmelCase    ) or not node:
            return
      _lowerCAmelCase					=				[]
      _lowerCAmelCase					=				node
      while n or stack:
            while n:
                  stack.append(lowerCAmelCase    )
                  _lowerCAmelCase					=				n.left
            _lowerCAmelCase					=				stack.pop()
            print(n.data				,      end=""","""    )
            _lowerCAmelCase					=				n.right
def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      if not isinstance(lowerCAmelCase				,      lowerCAmelCase    ) or not node:
            return
      _lowerCAmelCase	,				_lowerCAmelCase					=				[], []
      _lowerCAmelCase					=				node
      stacka.append(lowerCAmelCase    )
      while stacka:  # to find the reversed order of post order, store it in stack2
            _lowerCAmelCase					=				stacka.pop()
            if n.left:
                  stacka.append(n.left    )
            if n.right:
                  stacka.append(n.right    )
            stacka.append(lowerCAmelCase    )
      while stacka:  # pop up from stack2 will be the post order
            print(stacka.pop().data				,      end=""","""    )
def   UpperCamelCase__ (						lowerCAmelCase = ""				,      lowerCAmelCase=50				,      lowerCAmelCase="*"    ):





      """simple docstring"""


      if not s:
            return "\n" + width * char
      _lowerCAmelCase	,				_lowerCAmelCase					=				divmod(width - len(lowerCAmelCase    ) - 2				,      2    )
      return f"{left * char} {s} {(left + extra) * char}"


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      print(prompt('''Binary Tree Traversals'''))

      A__							:  TreeNode    =build_tree()
      print(prompt('''Pre Order Traversal'''))
      pre_order(node)
      print(prompt() + '''\n''')

      print(prompt('''In Order Traversal'''))
      in_order(node)
      print(prompt() + '''\n''')

      print(prompt('''Post Order Traversal'''))
      post_order(node)
      print(prompt() + '''\n''')

      print(prompt('''Level Order Traversal'''))
      level_order(node)
      print(prompt() + '''\n''')

      print(prompt('''Actual Level Order Traversal'''))
      level_order_actual(node)
      print('''*''' * 50 + '''\n''')

      print(prompt('''Pre Order Traversal - Iteration Version'''))
      pre_order_iter(node)
      print(prompt() + '''\n''')

      print(prompt('''In Order Traversal - Iteration Version'''))
      in_order_iter(node)
      print(prompt() + '''\n''')

      print(prompt('''Post Order Traversal - Iteration Version'''))
      post_order_iter(node)
      print(prompt())













'''simple docstring'''






import argparse

import requests
import torch
from PIL import Image

from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      if "cls_token" in name:
            _lowerCAmelCase					=				name.replace("""cls_token"""				,      """vit.embeddings.cls_token"""    )
      if "mask_token" in name:
            _lowerCAmelCase					=				name.replace("""mask_token"""				,      """decoder.mask_token"""    )
      if "decoder_pos_embed" in name:
            _lowerCAmelCase					=				name.replace("""decoder_pos_embed"""				,      """decoder.decoder_pos_embed"""    )
      if "pos_embed" in name and "decoder" not in name:
            _lowerCAmelCase					=				name.replace("""pos_embed"""				,      """vit.embeddings.position_embeddings"""    )
      if "patch_embed.proj" in name:
            _lowerCAmelCase					=				name.replace("""patch_embed.proj"""				,      """vit.embeddings.patch_embeddings.projection"""    )
      if "patch_embed.norm" in name:
            _lowerCAmelCase					=				name.replace("""patch_embed.norm"""				,      """vit.embeddings.norm"""    )
      if "decoder_blocks" in name:
            _lowerCAmelCase					=				name.replace("""decoder_blocks"""				,      """decoder.decoder_layers"""    )
      if "blocks" in name:
            _lowerCAmelCase					=				name.replace("""blocks"""				,      """vit.encoder.layer"""    )
      if "attn.proj" in name:
            _lowerCAmelCase					=				name.replace("""attn.proj"""				,      """attention.output.dense"""    )
      if "attn" in name:
            _lowerCAmelCase					=				name.replace("""attn"""				,      """attention.self"""    )
      if "norm1" in name:
            _lowerCAmelCase					=				name.replace("""norm1"""				,      """layernorm_before"""    )
      if "norm2" in name:
            _lowerCAmelCase					=				name.replace("""norm2"""				,      """layernorm_after"""    )
      if "mlp.fc1" in name:
            _lowerCAmelCase					=				name.replace("""mlp.fc1"""				,      """intermediate.dense"""    )
      if "mlp.fc2" in name:
            _lowerCAmelCase					=				name.replace("""mlp.fc2"""				,      """output.dense"""    )
      if "decoder_embed" in name:
            _lowerCAmelCase					=				name.replace("""decoder_embed"""				,      """decoder.decoder_embed"""    )
      if "decoder_norm" in name:
            _lowerCAmelCase					=				name.replace("""decoder_norm"""				,      """decoder.decoder_norm"""    )
      if "decoder_pred" in name:
            _lowerCAmelCase					=				name.replace("""decoder_pred"""				,      """decoder.decoder_pred"""    )
      if "norm.weight" in name and "decoder" not in name:
            _lowerCAmelCase					=				name.replace("""norm.weight"""				,      """vit.layernorm.weight"""    )
      if "norm.bias" in name and "decoder" not in name:
            _lowerCAmelCase					=				name.replace("""norm.bias"""				,      """vit.layernorm.bias"""    )

      return name
def   UpperCamelCase__ (						lowerCAmelCase				,      lowerCAmelCase    ):





      """simple docstring"""


      for key in orig_state_dict.copy().keys():
            _lowerCAmelCase					=				orig_state_dict.pop(lowerCAmelCase    )

            if "qkv" in key:
                  _lowerCAmelCase					=				key.split("""."""    )
                  _lowerCAmelCase					=				int(key_split[1]    )
                  if "decoder_blocks" in key:
                        _lowerCAmelCase					=				config.decoder_hidden_size
                        _lowerCAmelCase					=				"""decoder.decoder_layers."""
                        if "weight" in key:
                              _lowerCAmelCase					=				val[:dim, :]
                              _lowerCAmelCase					=				val[dim : dim * 2, :]
                              _lowerCAmelCase					=				val[-dim:, :]
                        elif "bias" in key:
                              _lowerCAmelCase					=				val[:dim]
                              _lowerCAmelCase					=				val[dim : dim * 2]
                              _lowerCAmelCase					=				val[-dim:]
                  else:
                        _lowerCAmelCase					=				config.hidden_size
                        _lowerCAmelCase					=				"""vit.encoder.layer."""
                        if "weight" in key:
                              _lowerCAmelCase					=				val[:dim, :]
                              _lowerCAmelCase					=				val[dim : dim * 2, :]
                              _lowerCAmelCase					=				val[-dim:, :]
                        elif "bias" in key:
                              _lowerCAmelCase					=				val[:dim]
                              _lowerCAmelCase					=				val[dim : dim * 2]
                              _lowerCAmelCase					=				val[-dim:]

            else:
                  _lowerCAmelCase					=				val

      return orig_state_dict
def   UpperCamelCase__ (						lowerCAmelCase				,      lowerCAmelCase    ):





      """simple docstring"""


      _lowerCAmelCase					=				ViTMAEConfig()
      if "large" in checkpoint_url:
            _lowerCAmelCase					=				10_24
            _lowerCAmelCase					=				40_96
            _lowerCAmelCase					=				24
            _lowerCAmelCase					=				16
      elif "huge" in checkpoint_url:
            _lowerCAmelCase					=				14
            _lowerCAmelCase					=				12_80
            _lowerCAmelCase					=				51_20
            _lowerCAmelCase					=				32
            _lowerCAmelCase					=				16

      _lowerCAmelCase					=				ViTMAEForPreTraining(lowerCAmelCase    )

      _lowerCAmelCase					=				torch.hub.load_state_dict_from_url(lowerCAmelCase				,      map_location="""cpu"""    )["""model"""]

      _lowerCAmelCase					=				ViTMAEImageProcessor(size=config.image_size    )

      _lowerCAmelCase					=				convert_state_dict(lowerCAmelCase				,      lowerCAmelCase    )

      model.load_state_dict(lowerCAmelCase    )
      model.eval()

      _lowerCAmelCase					=				"""https://user-images.githubusercontent.com/11435359/147738734-196fd92f-9260-48d5-ba7e-bf103d29364d.jpg"""

      _lowerCAmelCase					=				Image.open(requests.get(lowerCAmelCase				,      stream=lowerCAmelCase    ).raw    )
      _lowerCAmelCase					=				ViTMAEImageProcessor(size=config.image_size    )
      _lowerCAmelCase					=				image_processor(images=lowerCAmelCase				,      return_tensors="""pt"""    )

      # forward pass
      torch.manual_seed(2    )
      _lowerCAmelCase					=				model(**lowerCAmelCase    )
      _lowerCAmelCase					=				outputs.logits

      if "large" in checkpoint_url:
            _lowerCAmelCase					=				torch.tensor(
                [[-0.7_309, -0.7_128, -1.0_169], [-1.0_161, -0.9_058, -1.1_878], [-1.0_478, -0.9_411, -1.1_911]]    )
      elif "huge" in checkpoint_url:
            _lowerCAmelCase					=				torch.tensor(
                [[-1.1_599, -0.9_199, -1.2_221], [-1.1_952, -0.9_269, -1.2_307], [-1.2_143, -0.9_337, -1.2_262]]    )
      else:
            _lowerCAmelCase					=				torch.tensor(
                [[-0.9_192, -0.8_481, -1.1_259], [-1.1_349, -1.0_034, -1.2_599], [-1.1_757, -1.0_429, -1.2_726]]    )

      # verify logits
      assert torch.allclose(logits[0, :3, :3]				,      lowerCAmelCase				,      atol=1e-4    )

      print(f"Saving model to {pytorch_dump_folder_path}"    )
      model.save_pretrained(lowerCAmelCase    )

      print(f"Saving image processor to {pytorch_dump_folder_path}"    )
      image_processor.save_pretrained(lowerCAmelCase    )


if __name__ == "__main__":
      A__							:  Dict    =argparse.ArgumentParser()
      # Required parameters
      parser.add_argument(
          '''--checkpoint_url''',
          default='''https://dl.fbaipublicfiles.com/mae/visualize/mae_visualize_vit_base.pth''',
          type=str,
          help='''URL of the checkpoint you\'d like to convert.''',
      )
      parser.add_argument(
          '''--pytorch_dump_folder_path''', default=None, type=str, help='''Path to the output PyTorch model directory.'''
      )

      A__							:  List[Any]    =parser.parse_args()
      convert_vit_mae_checkpoint(args.checkpoint_url, args.pytorch_dump_folder_path)






