






"""simple docstring"""





from __future__ import annotations

import math
import random
from typing import Any
class    __lowerCamelCase    :

   def __init__(					self      )		->       Union[str, Any]:
       UpperCamelCase__         =    []
       UpperCamelCase__         =    0
       UpperCamelCase__         =    0

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Optional[int]:
       return self.head == self.tail

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       Dict:
       self.data.append(UpperCamelCase_      )
       UpperCamelCase__         =    self.tail + 1

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Any:
       UpperCamelCase__         =    self.data[self.head]
       UpperCamelCase__         =    self.head + 1
       return ret

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Optional[int]:
       return self.tail - self.head







   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       int:
       print(self.data      )
       print('**************'      )
       print(self.data[self.head : self.tail]      )







class    __lowerCamelCase    :

   def __init__(					self ,				snake_case_      )		->       Optional[Any]:
       UpperCamelCase__         =    data
       UpperCamelCase__         =    None
       UpperCamelCase__         =    None
       UpperCamelCase__         =    1

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       List[Any]:
       return self.data

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Dict:
       return self.left

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       List[str]:
       return self.right

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       str:
       return self.height

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       List[Any]:
       UpperCamelCase__         =    data

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       Optional[int]:
       UpperCamelCase__         =    node

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       Dict:
       UpperCamelCase__         =    node







   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       Tuple:
       UpperCamelCase__         =    height







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	int:
    """simple docstring"""

    if node is None:
        return 0
    return node.get_height()







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE					)					->	int:
    """simple docstring"""

    if a > b:
        return a
    return b







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	MyNode:
    """simple docstring"""

    print('left rotation node:' ,	node.get_data()					)
    UpperCamelCase__         =    node.get_left()
    assert ret is not None
    node.set_left(ret.get_right()					)
    ret.set_right(lowerCamelCase__					)
    UpperCamelCase__         =    my_max(get_height(node.get_right()					) ,	get_height(node.get_left()					)					) + 1
    node.set_height(lowerCamelCase__					)
    UpperCamelCase__         =    my_max(get_height(ret.get_right()					) ,	get_height(ret.get_left()					)					) + 1
    ret.set_height(lowerCamelCase__					)
    return ret







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	MyNode:
    """simple docstring"""

    print('right rotation node:' ,	node.get_data()					)
    UpperCamelCase__         =    node.get_right()
    assert ret is not None
    node.set_right(ret.get_left()					)
    ret.set_left(lowerCamelCase__					)
    UpperCamelCase__         =    my_max(get_height(node.get_right()					) ,	get_height(node.get_left()					)					) + 1
    node.set_height(lowerCamelCase__					)
    UpperCamelCase__         =    my_max(get_height(ret.get_right()					) ,	get_height(ret.get_left()					)					) + 1
    ret.set_height(lowerCamelCase__					)
    return ret







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	MyNode:
    """simple docstring"""

    UpperCamelCase__         =    node.get_left()
    assert left_child is not None
    node.set_left(left_rotation(lowerCamelCase__					)					)
    return right_rotation(lowerCamelCase__					)







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	MyNode:
    """simple docstring"""

    UpperCamelCase__         =    node.get_right()
    assert right_child is not None
    node.set_right(right_rotation(lowerCamelCase__					)					)
    return left_rotation(lowerCamelCase__					)







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE					)					->	MyNode | None:
    """simple docstring"""

    if node is None:
        return MyNode(lowerCamelCase__					)
    if data < node.get_data():
        node.set_left(insert_node(node.get_left() ,	lowerCamelCase__					)					)
        if (
            get_height(node.get_left()					) - get_height(node.get_right()					) == 2
        ):  # an unbalance detected
            UpperCamelCase__         =    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
                UpperCamelCase__         =    right_rotation(lowerCamelCase__					)
            else:
                UpperCamelCase__         =    lr_rotation(lowerCamelCase__					)
    else:
        node.set_right(insert_node(node.get_right() ,	lowerCamelCase__					)					)
        if get_height(node.get_right()					) - get_height(node.get_left()					) == 2:
            UpperCamelCase__         =    node.get_right()
            assert right_child is not None
            if data < right_child.get_data():
                UpperCamelCase__         =    rl_rotation(lowerCamelCase__					)
            else:
                UpperCamelCase__         =    left_rotation(lowerCamelCase__					)
    UpperCamelCase__         =    my_max(get_height(node.get_right()					) ,	get_height(node.get_left()					)					) + 1
    node.set_height(lowerCamelCase__					)
    return node







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	Any:
    """simple docstring"""

    while True:
        UpperCamelCase__         =    root.get_right()
        if right_child is None:
            break
        UpperCamelCase__         =    right_child
    return root.get_data()







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	Any:
    """simple docstring"""

    while True:
        UpperCamelCase__         =    root.get_left()
        if left_child is None:
            break
        UpperCamelCase__         =    left_child
    return root.get_data()







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE					)					->	MyNode | None:
    """simple docstring"""

    UpperCamelCase__         =    root.get_left()
    UpperCamelCase__         =    root.get_right()
    if root.get_data() == data:
        if left_child is not None and right_child is not None:
            UpperCamelCase__         =    get_left_most(lowerCamelCase__					)
            root.set_data(lowerCamelCase__					)
            root.set_right(del_node(lowerCamelCase__ ,	lowerCamelCase__					)					)
        elif left_child is not None:
            UpperCamelCase__         =    left_child
        elif right_child is not None:
            UpperCamelCase__         =    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(lowerCamelCase__ ,	lowerCamelCase__					)					)
    else:  # root.get_data() < data
        if right_child is None:
            return root
        else:
            root.set_right(del_node(lowerCamelCase__ ,	lowerCamelCase__					)					)

    if get_height(lowerCamelCase__					) - get_height(lowerCamelCase__					) == 2:
        assert right_child is not None
        if get_height(right_child.get_right()					) > get_height(right_child.get_left()					):
            UpperCamelCase__         =    left_rotation(lowerCamelCase__					)
        else:
            UpperCamelCase__         =    rl_rotation(lowerCamelCase__					)
    elif get_height(lowerCamelCase__					) - get_height(lowerCamelCase__					) == -2:
        assert left_child is not None
        if get_height(left_child.get_left()					) > get_height(left_child.get_right()					):
            UpperCamelCase__         =    right_rotation(lowerCamelCase__					)
        else:
            UpperCamelCase__         =    lr_rotation(lowerCamelCase__					)
    UpperCamelCase__         =    my_max(get_height(root.get_right()					) ,	get_height(root.get_left()					)					) + 1
    root.set_height(lowerCamelCase__					)
    return root
class    __lowerCamelCase    :

   def __init__(					self      )		->       Optional[int]:
       UpperCamelCase__         =    None

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Dict:
       return get_height(self.root      )

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       int:
       print('insert:' + str(UpperCamelCase_      )      )
       UpperCamelCase__         =    insert_node(self.root ,				UpperCamelCase_      )

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       int:
       print('delete:' + str(UpperCamelCase_      )      )
       if self.root is None:
           print('Tree is empty!'      )
           return
       UpperCamelCase__         =    del_node(self.root ,				UpperCamelCase_      )







   def __str__(					self ,				)		->       Dict:  # a level traversale, gives a more intuitive look on the tree
       UpperCamelCase__         =    ""
       UpperCamelCase__         =    MyQueue()
       q.push(self.root      )
       UpperCamelCase__         =    self.get_height()
       if layer == 0:
           return output
       UpperCamelCase__         =    0
       while not q.is_empty():
           UpperCamelCase__         =    q.pop()
           UpperCamelCase__         =    " " * int(math.pow(2 ,				layer - 1      )      )
           output += space
           if node is None:
               output += "*"
               q.push(UpperCamelCase_      )
               q.push(UpperCamelCase_      )
           else:
               output += str(node.get_data()      )
               q.push(node.get_left()      )
               q.push(node.get_right()      )
           output += space
           UpperCamelCase__         =    cnt + 1
           for i in range(100      ):
               if cnt == math.pow(2 ,				UpperCamelCase_      ) - 1:
                   UpperCamelCase__         =    layer - 1
                   if layer == 0:
                       output += "\n*************************************"
                       return output
                   output += "\n"
                   break
       output += "\n*************************************"
       return output







def   lowerCAmelCase_( )					->	None:
    """simple docstring"""

    import doctest

    doctest.testmod()


if __name__ == "__main__":
  _test()
  A__					: Dict=	AVLtree()
  A__					: List[str]=	list(range(10))
  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"""





from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging


if TYPE_CHECKING:
  from ...processing_utils import ProcessorMixin
  from ...utils import TensorType


A__					: Any=	logging.get_logger(__name__)

A__					: str=	{
    """microsoft/layoutlmv3-base""": """https://huggingface.co/microsoft/layoutlmv3-base/resolve/main/config.json""",
}
class    __lowerCamelCase    (  _a  ):
   a      :				List[str] 						="""layoutlmv3"""

   def __init__(					self ,				snake_case_=5_0265 ,				snake_case_=768 ,				snake_case_=12 ,				snake_case_=12 ,				snake_case_=3072 ,				snake_case_="gelu" ,				snake_case_=0.1 ,				snake_case_=0.1 ,				snake_case_=512 ,				snake_case_=2 ,				snake_case_=0.02 ,				snake_case_=1E-5 ,				snake_case_=1 ,				snake_case_=0 ,				snake_case_=2 ,				snake_case_=1024 ,				snake_case_=128 ,				snake_case_=128 ,				snake_case_=True ,				snake_case_=32 ,				snake_case_=128 ,				snake_case_=64 ,				snake_case_=256 ,				snake_case_=True ,				snake_case_=True ,				snake_case_=True ,				snake_case_=224 ,				snake_case_=3 ,				snake_case_=16 ,				snake_case_=None ,				**snake_case_ ,				)		->       Union[str, Any]:
       super().__init__(
           vocab_size=snake_case_ ,				hidden_size=snake_case_ ,				num_hidden_layers=snake_case_ ,				num_attention_heads=snake_case_ ,				intermediate_size=snake_case_ ,				hidden_act=snake_case_ ,				hidden_dropout_prob=snake_case_ ,				attention_probs_dropout_prob=snake_case_ ,				max_position_embeddings=snake_case_ ,				type_vocab_size=snake_case_ ,				initializer_range=snake_case_ ,				layer_norm_eps=snake_case_ ,				pad_token_id=snake_case_ ,				bos_token_id=snake_case_ ,				eos_token_id=snake_case_ ,				**snake_case_ ,				)
       UpperCamelCase__         =    max_ad_position_embeddings
       UpperCamelCase__         =    coordinate_size
       UpperCamelCase__         =    shape_size
       UpperCamelCase__         =    has_relative_attention_bias
       UpperCamelCase__         =    rel_pos_bins
       UpperCamelCase__         =    max_rel_pos
       UpperCamelCase__         =    has_spatial_attention_bias
       UpperCamelCase__         =    rel_ad_pos_bins
       UpperCamelCase__         =    max_rel_ad_pos
       UpperCamelCase__         =    text_embed
       UpperCamelCase__         =    visual_embed
       UpperCamelCase__         =    input_size
       UpperCamelCase__         =    num_channels
       UpperCamelCase__         =    patch_size
       UpperCamelCase__         =    classifier_dropout







class    __lowerCamelCase    (  _a  ):
   a      :				Tuple 						=version.parse("""1.12"""  )

   @property
   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Mapping[str, Mapping[int, str]]:
       # The order of inputs is different for question answering and sequence classification
       if self.task in ["question-answering", "sequence-classification"]:
           return OrderedDict(
               [
                   ('input_ids', {0: 'batch', 1: 'sequence'}),
                   ('attention_mask', {0: 'batch', 1: 'sequence'}),
                   ('bbox', {0: 'batch', 1: 'sequence'}),
                   ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
               ]      )
       else:
           return OrderedDict(
               [
                   ('input_ids', {0: 'batch', 1: 'sequence'}),
                   ('bbox', {0: 'batch', 1: 'sequence'}),
                   ('attention_mask', {0: 'batch', 1: 'sequence'}),
                   ('pixel_values', {0: 'batch', 1: 'num_channels'}),
               ]      )

   @property
   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       float:
       return 1E-5

   @property
   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       int:
       return 12







   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_ ,				snake_case_ = -1 ,				snake_case_ = -1 ,				snake_case_ = False ,				snake_case_ = None ,				snake_case_ = 3 ,				snake_case_ = 40 ,				snake_case_ = 40 ,				)		->       Mapping[str, Any]:
       setattr(processor.image_processor ,				'apply_ocr' ,				snake_case_      )

       # If dynamic axis (-1) we forward with a fixed dimension of 2 samples to avoid optimizations made by ONNX
       UpperCamelCase__         =    compute_effective_axis_dimension(
           snake_case_ ,				fixed_dimension=OnnxConfig.default_fixed_batch ,				num_token_to_add=0      )
       # If dynamic axis (-1) we forward with a fixed dimension of 8 tokens to avoid optimizations made by ONNX
       UpperCamelCase__         =    processor.tokenizer.num_special_tokens_to_add(snake_case_      )
       UpperCamelCase__         =    compute_effective_axis_dimension(
           snake_case_ ,				fixed_dimension=OnnxConfig.default_fixed_sequence ,				num_token_to_add=snake_case_      )
       # Generate dummy inputs according to compute batch and sequence
       UpperCamelCase__         =    [[' '.join([processor.tokenizer.unk_token]      ) * seq_length]] * batch_size

       # Generate dummy bounding boxes
       UpperCamelCase__         =    [[[48, 84, 73, 128]]] * batch_size

       # If dynamic axis (-1) we forward with a fixed dimension of 2 samples to avoid optimizations made by ONNX
       # batch_size = compute_effective_axis_dimension(batch_size, fixed_dimension=OnnxConfig.default_fixed_batch)
       UpperCamelCase__         =    self._generate_dummy_images(snake_case_ ,				snake_case_ ,				snake_case_ ,				snake_case_      )

       UpperCamelCase__         =    dict(
           processor(
               snake_case_ ,				text=snake_case_ ,				boxes=snake_case_ ,				return_tensors=snake_case_ ,				)      )

       return inputs




