



"""simple docstring"""
from __future__ import annotations

import math
import random
from typing import Any
class 					a	:



  def __init__(						self :					str		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: list[Any]     			=[]
     SCREAMING_SNAKE_CASE_: int     			=0
     SCREAMING_SNAKE_CASE_: int     			=0



  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					bool:


     '''simple docstring'''




     return self.head == self.tail



  def 	lowerCamelCase__       (						self :					Tuple       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     self.data.append(lowerCAmelCase		)
     SCREAMING_SNAKE_CASE_: List[str]     			=self.tail + 1



  def 	lowerCamelCase__       (						self :					int		)     ->					Any:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: int     			=self.data[self.head]
     SCREAMING_SNAKE_CASE_: Optional[int]     			=self.head + 1
     return ret



  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					int:


     '''simple docstring'''




     return self.tail - self.head





  def 	lowerCamelCase__       (						self :					str		)     ->					None:


     '''simple docstring'''




     print(self.data		)
     print("""**************"""		)
     print(self.data[self.head : self.tail]		)







class 					a	:



  def __init__(						self :					Union[str, Any]       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Dict     			=data
     SCREAMING_SNAKE_CASE_: MyNode | None     			=None
     SCREAMING_SNAKE_CASE_: MyNode | None     			=None
     SCREAMING_SNAKE_CASE_: int     			=1



  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					Any:


     '''simple docstring'''




     return self.data



  def 	lowerCamelCase__       (						self :					List[Any]		)     ->					MyNode | None:


     '''simple docstring'''




     return self.left



  def 	lowerCamelCase__       (						self :					Dict		)     ->					MyNode | None:


     '''simple docstring'''




     return self.right



  def 	lowerCamelCase__       (						self :					Any		)     ->					int:


     '''simple docstring'''




     return self.height



  def 	lowerCamelCase__       (						self :					Any       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Optional[Any]     			=data



  def 	lowerCamelCase__       (						self :					Dict       ,		lowerCAmelCase :					MyNode | None		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Tuple     			=node



  def 	lowerCamelCase__       (						self :					List[Any]       ,		lowerCAmelCase :					MyNode | None		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: str     			=node





  def 	lowerCamelCase__       (						self :					int       ,		lowerCAmelCase :					int		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Any     			=height







def      __magic_name__				(							lowercase ):
   if node is None:
      return 0
   return node.get_height()





def      __magic_name__				(							lowercase							,			lowercase ):
   if a > b:
      return a
   return b





def      __magic_name__				(							lowercase ):
   print("""left rotation node:"""							,			node.get_data() )
   SCREAMING_SNAKE_CASE_: List[Any]     			=node.get_left()
   assert ret is not None
   node.set_left(ret.get_right() )
   ret.set_right(lowercase )
   SCREAMING_SNAKE_CASE_: Tuple     			=my_max(get_height(node.get_right() )							,			get_height(node.get_left() ) ) + 1
   node.set_height(lowercase )
   SCREAMING_SNAKE_CASE_: int     			=my_max(get_height(ret.get_right() )							,			get_height(ret.get_left() ) ) + 1
   ret.set_height(lowercase )
   return ret





def      __magic_name__				(							lowercase ):
   print("""right rotation node:"""							,			node.get_data() )
   SCREAMING_SNAKE_CASE_: List[Any]     			=node.get_right()
   assert ret is not None
   node.set_right(ret.get_left() )
   ret.set_left(lowercase )
   SCREAMING_SNAKE_CASE_: List[Any]     			=my_max(get_height(node.get_right() )							,			get_height(node.get_left() ) ) + 1
   node.set_height(lowercase )
   SCREAMING_SNAKE_CASE_: Optional[int]     			=my_max(get_height(ret.get_right() )							,			get_height(ret.get_left() ) ) + 1
   ret.set_height(lowercase )
   return ret





def      __magic_name__				(							lowercase ):
   SCREAMING_SNAKE_CASE_: Any     			=node.get_left()
   assert left_child is not None
   node.set_left(left_rotation(lowercase ) )
   return right_rotation(lowercase )





def      __magic_name__				(							lowercase ):
   SCREAMING_SNAKE_CASE_: Dict     			=node.get_right()
   assert right_child is not None
   node.set_right(right_rotation(lowercase ) )
   return left_rotation(lowercase )





def      __magic_name__				(							lowercase							,			lowercase ):
   if node is None:
      return MyNode(lowercase )
   if data < node.get_data():
      node.set_left(insert_node(node.get_left()							,			lowercase ) )
      if (
          get_height(node.get_left() ) - get_height(node.get_right() ) == 2
      ):  # an unbalance detected
         SCREAMING_SNAKE_CASE_: Union[str, Any]     			=node.get_left()
         assert left_child is not None
         if (
             data < left_child.get_data()
         ):  # new node is the left child of the left child
            SCREAMING_SNAKE_CASE_: Any     			=right_rotation(lowercase )
         else:
            SCREAMING_SNAKE_CASE_: List[Any]     			=lr_rotation(lowercase )
   else:
      node.set_right(insert_node(node.get_right()							,			lowercase ) )
      if get_height(node.get_right() ) - get_height(node.get_left() ) == 2:
         SCREAMING_SNAKE_CASE_: Tuple     			=node.get_right()
         assert right_child is not None
         if data < right_child.get_data():
            SCREAMING_SNAKE_CASE_: Optional[Any]     			=rl_rotation(lowercase )
         else:
            SCREAMING_SNAKE_CASE_: Optional[int]     			=left_rotation(lowercase )
   SCREAMING_SNAKE_CASE_: Tuple     			=my_max(get_height(node.get_right() )							,			get_height(node.get_left() ) ) + 1
   node.set_height(lowercase )
   return node





def      __magic_name__				(							lowercase ):
   while True:
      SCREAMING_SNAKE_CASE_: Dict     			=root.get_right()
      if right_child is None:
         break
      SCREAMING_SNAKE_CASE_: str     			=right_child
   return root.get_data()





def      __magic_name__				(							lowercase ):
   while True:
      SCREAMING_SNAKE_CASE_: str     			=root.get_left()
      if left_child is None:
         break
      SCREAMING_SNAKE_CASE_: Dict     			=left_child
   return root.get_data()





def      __magic_name__				(							lowercase							,			lowercase ):
   SCREAMING_SNAKE_CASE_: str     			=root.get_left()
   SCREAMING_SNAKE_CASE_: List[Any]     			=root.get_right()
   if root.get_data() == data:
      if left_child is not None and right_child is not None:
         SCREAMING_SNAKE_CASE_: Union[str, Any]     			=get_left_most(lowercase )
         root.set_data(lowercase )
         root.set_right(del_node(lowercase							,			lowercase ) )
      elif left_child is not None:
         SCREAMING_SNAKE_CASE_: Optional[int]     			=left_child
      elif right_child is not None:
         SCREAMING_SNAKE_CASE_: Any     			=right_child
      else:
         return None
   elif root.get_data() > data:
      if left_child is None:
         print("""No such data""" )
         return root
      else:
         root.set_left(del_node(lowercase							,			lowercase ) )
   else:  # root.get_data() < data
      if right_child is None:
         return root
      else:
         root.set_right(del_node(lowercase							,			lowercase ) )

   if get_height(lowercase ) - get_height(lowercase ) == 2:
      assert right_child is not None
      if get_height(right_child.get_right() ) > get_height(right_child.get_left() ):
         SCREAMING_SNAKE_CASE_: Tuple     			=left_rotation(lowercase )
      else:
         SCREAMING_SNAKE_CASE_: Optional[Any]     			=rl_rotation(lowercase )
   elif get_height(lowercase ) - get_height(lowercase ) == -2:
      assert left_child is not None
      if get_height(left_child.get_left() ) > get_height(left_child.get_right() ):
         SCREAMING_SNAKE_CASE_: Optional[Any]     			=right_rotation(lowercase )
      else:
         SCREAMING_SNAKE_CASE_: str     			=lr_rotation(lowercase )
   SCREAMING_SNAKE_CASE_: str     			=my_max(get_height(root.get_right() )							,			get_height(root.get_left() ) ) + 1
   root.set_height(lowercase )
   return root
class 					a	:



  def __init__(						self :					int		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: MyNode | None     			=None



  def 	lowerCamelCase__       (						self :					List[Any]		)     ->					int:


     '''simple docstring'''




     return get_height(self.root		)



  def 	lowerCamelCase__       (						self :					Optional[int]       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     print("""insert:""" + str(lowerCAmelCase		)		)
     SCREAMING_SNAKE_CASE_: Tuple     			=insert_node(self.root       ,		lowerCAmelCase		)



  def 	lowerCamelCase__       (						self :					List[Any]       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     print("""delete:""" + str(lowerCAmelCase		)		)
     if self.root is None:
        print("""Tree is empty!"""		)
        return
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=del_node(self.root       ,		lowerCAmelCase		)





  def __str__(						self :					List[str]       ,		)     ->					str:  # a level traversale, gives a more intuitive look on the tree


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: List[Any]     			=""""""
     SCREAMING_SNAKE_CASE_: str     			=MyQueue()
     q.push(self.root		)
     SCREAMING_SNAKE_CASE_: List[str]     			=self.get_height()
     if layer == 0:
        return output
     SCREAMING_SNAKE_CASE_: int     			=0
     while not q.is_empty():
        SCREAMING_SNAKE_CASE_: int     			=q.pop()
        SCREAMING_SNAKE_CASE_: List[Any]     			=""" """ * int(math.pow(2       ,		layer - 1		)		)
        output += space
        if node is None:
           output += "*"
           q.push(lowerCAmelCase		)
           q.push(lowerCAmelCase		)
        else:
           output += str(node.get_data()		)
           q.push(node.get_left()		)
           q.push(node.get_right()		)
        output += space
        SCREAMING_SNAKE_CASE_: List[Any]     			=cnt + 1
        for i in range(100		):
           if cnt == math.pow(2       ,		lowerCAmelCase		) - 1:
              SCREAMING_SNAKE_CASE_: int     			=layer - 1
              if layer == 0:
                 output += "\n*************************************"
                 return output
              output += "\n"
              break
     output += "\n*************************************"
     return output







def      __magic_name__				(							):
   import doctest

   doctest.testmod()


if __name__ == "__main__":
   _test()
   _UpperCAmelCase     =			AVLtree()
   _UpperCAmelCase     =			list(range(1_0))
   random.shuffle(lst)
   for i in lst:
      t.insert(i)
      print(str(t))
   random.shuffle(lst)
   for i in lst:
      t.del_node(i)
      print(str(t))








"""simple docstring"""
import argparse

import requests
import torch
from PIL import Image

from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor





def      __magic_name__				(							lowercase ):
   if "cls_token" in name:
      SCREAMING_SNAKE_CASE_: Optional[int]     			=name.replace("""cls_token"""							,			"""vit.embeddings.cls_token""" )
   if "mask_token" in name:
      SCREAMING_SNAKE_CASE_: Optional[int]     			=name.replace("""mask_token"""							,			"""decoder.mask_token""" )
   if "decoder_pos_embed" in name:
      SCREAMING_SNAKE_CASE_: int     			=name.replace("""decoder_pos_embed"""							,			"""decoder.decoder_pos_embed""" )
   if "pos_embed" in name and "decoder" not in name:
      SCREAMING_SNAKE_CASE_: str     			=name.replace("""pos_embed"""							,			"""vit.embeddings.position_embeddings""" )
   if "patch_embed.proj" in name:
      SCREAMING_SNAKE_CASE_: str     			=name.replace("""patch_embed.proj"""							,			"""vit.embeddings.patch_embeddings.projection""" )
   if "patch_embed.norm" in name:
      SCREAMING_SNAKE_CASE_: int     			=name.replace("""patch_embed.norm"""							,			"""vit.embeddings.norm""" )
   if "decoder_blocks" in name:
      SCREAMING_SNAKE_CASE_: List[Any]     			=name.replace("""decoder_blocks"""							,			"""decoder.decoder_layers""" )
   if "blocks" in name:
      SCREAMING_SNAKE_CASE_: str     			=name.replace("""blocks"""							,			"""vit.encoder.layer""" )
   if "attn.proj" in name:
      SCREAMING_SNAKE_CASE_: Optional[Any]     			=name.replace("""attn.proj"""							,			"""attention.output.dense""" )
   if "attn" in name:
      SCREAMING_SNAKE_CASE_: Union[str, Any]     			=name.replace("""attn"""							,			"""attention.self""" )
   if "norm1" in name:
      SCREAMING_SNAKE_CASE_: Optional[Any]     			=name.replace("""norm1"""							,			"""layernorm_before""" )
   if "norm2" in name:
      SCREAMING_SNAKE_CASE_: int     			=name.replace("""norm2"""							,			"""layernorm_after""" )
   if "mlp.fc1" in name:
      SCREAMING_SNAKE_CASE_: int     			=name.replace("""mlp.fc1"""							,			"""intermediate.dense""" )
   if "mlp.fc2" in name:
      SCREAMING_SNAKE_CASE_: Dict     			=name.replace("""mlp.fc2"""							,			"""output.dense""" )
   if "decoder_embed" in name:
      SCREAMING_SNAKE_CASE_: List[str]     			=name.replace("""decoder_embed"""							,			"""decoder.decoder_embed""" )
   if "decoder_norm" in name:
      SCREAMING_SNAKE_CASE_: Tuple     			=name.replace("""decoder_norm"""							,			"""decoder.decoder_norm""" )
   if "decoder_pred" in name:
      SCREAMING_SNAKE_CASE_: Any     			=name.replace("""decoder_pred"""							,			"""decoder.decoder_pred""" )
   if "norm.weight" in name and "decoder" not in name:
      SCREAMING_SNAKE_CASE_: List[str]     			=name.replace("""norm.weight"""							,			"""vit.layernorm.weight""" )
   if "norm.bias" in name and "decoder" not in name:
      SCREAMING_SNAKE_CASE_: List[str]     			=name.replace("""norm.bias"""							,			"""vit.layernorm.bias""" )

   return name





def      __magic_name__				(							lowercase							,			lowercase ):
   for key in orig_state_dict.copy().keys():
      SCREAMING_SNAKE_CASE_: Optional[int]     			=orig_state_dict.pop(lowercase )

      if "qkv" in key:
         SCREAMING_SNAKE_CASE_: Dict     			=key.split(""".""" )
         SCREAMING_SNAKE_CASE_: Optional[Any]     			=int(key_split[1] )
         if "decoder_blocks" in key:
            SCREAMING_SNAKE_CASE_: int     			=config.decoder_hidden_size
            SCREAMING_SNAKE_CASE_: Optional[int]     			="""decoder.decoder_layers."""
            if "weight" in key:
               SCREAMING_SNAKE_CASE_: Dict     			=val[:dim, :]
               SCREAMING_SNAKE_CASE_: Tuple     			=val[dim : dim * 2, :]
               SCREAMING_SNAKE_CASE_: str     			=val[-dim:, :]
            elif "bias" in key:
               SCREAMING_SNAKE_CASE_: List[Any]     			=val[:dim]
               SCREAMING_SNAKE_CASE_: Tuple     			=val[dim : dim * 2]
               SCREAMING_SNAKE_CASE_: List[Any]     			=val[-dim:]
         else:
            SCREAMING_SNAKE_CASE_: Any     			=config.hidden_size
            SCREAMING_SNAKE_CASE_: Union[str, Any]     			="""vit.encoder.layer."""
            if "weight" in key:
               SCREAMING_SNAKE_CASE_: Optional[Any]     			=val[:dim, :]
               SCREAMING_SNAKE_CASE_: Optional[Any]     			=val[dim : dim * 2, :]
               SCREAMING_SNAKE_CASE_: Dict     			=val[-dim:, :]
            elif "bias" in key:
               SCREAMING_SNAKE_CASE_: Optional[Any]     			=val[:dim]
               SCREAMING_SNAKE_CASE_: Any     			=val[dim : dim * 2]
               SCREAMING_SNAKE_CASE_: Optional[Any]     			=val[-dim:]

      else:
         SCREAMING_SNAKE_CASE_: Tuple     			=val

   return orig_state_dict





def      __magic_name__				(							lowercase							,			lowercase ):
   SCREAMING_SNAKE_CASE_: Dict     			=ViTMAEConfig()
   if "large" in checkpoint_url:
      SCREAMING_SNAKE_CASE_: List[Any]     			=1024
      SCREAMING_SNAKE_CASE_: Dict     			=4096
      SCREAMING_SNAKE_CASE_: Tuple     			=24
      SCREAMING_SNAKE_CASE_: int     			=16
   elif "huge" in checkpoint_url:
      SCREAMING_SNAKE_CASE_: Union[str, Any]     			=14
      SCREAMING_SNAKE_CASE_: Any     			=1280
      SCREAMING_SNAKE_CASE_: Dict     			=5120
      SCREAMING_SNAKE_CASE_: Optional[int]     			=32
      SCREAMING_SNAKE_CASE_: Optional[Any]     			=16

   SCREAMING_SNAKE_CASE_: Tuple     			=ViTMAEForPreTraining(lowercase )

   SCREAMING_SNAKE_CASE_: Optional[int]     			=torch.hub.load_state_dict_from_url(lowercase							,			map_location="""cpu""" )["""model"""]

   SCREAMING_SNAKE_CASE_: Optional[Any]     			=ViTMAEImageProcessor(size=config.image_size )

   SCREAMING_SNAKE_CASE_: str     			=convert_state_dict(lowercase							,			lowercase )

   model.load_state_dict(lowercase )
   model.eval()

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

   SCREAMING_SNAKE_CASE_: List[Any]     			=Image.open(requests.get(lowercase							,			stream=lowercase ).raw )
   SCREAMING_SNAKE_CASE_: int     			=ViTMAEImageProcessor(size=config.image_size )
   SCREAMING_SNAKE_CASE_: int     			=image_processor(images=lowercase							,			return_tensors="""pt""" )

   # forward pass
   torch.manual_seed(2 )
   SCREAMING_SNAKE_CASE_: Optional[Any]     			=model(**lowercase )
   SCREAMING_SNAKE_CASE_: Optional[int]     			=outputs.logits

   if "large" in checkpoint_url:
      SCREAMING_SNAKE_CASE_: Dict     			=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:
      SCREAMING_SNAKE_CASE_: Tuple     			=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:
      SCREAMING_SNAKE_CASE_: Any     			=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]							,			lowercase							,			atol=1e-4 )

   print(f'''Saving model to {pytorch_dump_folder_path}''' )
   model.save_pretrained(lowercase )

   print(f'''Saving image processor to {pytorch_dump_folder_path}''' )
   image_processor.save_pretrained(lowercase )


if __name__ == "__main__":
   _UpperCAmelCase     =			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."""
   )

   _UpperCAmelCase     =			parser.parse_args()
   convert_vit_mae_checkpoint(args.checkpoint_url, args.pytorch_dump_folder_path)



