




'''simple docstring'''

from __future__ import annotations

import math
import random
from typing import Any






class 						a				:


				def __init__(		self    :					Union[str, Any]					):
									snake_case_									=				[]
									snake_case_									=				0
									snake_case_									=				0


				def   A_ (		self    :					Tuple					):
									return self.head == self.tail


				def   A_ (		self    :					int       ,				lowercase_    :					Any					):
									self.data.append(lowercase_					)
									snake_case_									=				self.tail + 1


				def   A_ (		self    :					List[str]					):
									snake_case_									=				self.data[self.head]
									snake_case_									=				self.head + 1
									return ret


				def   A_ (		self    :					Tuple					):
									return self.tail - self.head


				def   A_ (		self    :					Any					):
									print(self.data					)
									print('''**************'''					)
									print(self.data[self.head : self.tail]					)







class 						a				:


				def __init__(		self    :					Optional[int]       ,				lowercase_    :					Any					):
									snake_case_									=				data
									snake_case_									=				None
									snake_case_									=				None
									snake_case_									=				1


				def   A_ (		self    :					List[str]					):
									return self.data


				def   A_ (		self    :					str					):
									return self.left


				def   A_ (		self    :					Any					):
									return self.right


				def   A_ (		self    :					Tuple					):
									return self.height


				def   A_ (		self    :					Any       ,				lowercase_    :					Any					):
									snake_case_									=				data


				def   A_ (		self    :					str       ,				lowercase_    :					MyNode | None					):
									snake_case_									=				node


				def   A_ (		self    :					Dict       ,				lowercase_    :					MyNode | None					):
									snake_case_									=				node


				def   A_ (		self    :					Any       ,				lowercase_    :					int					):
									snake_case_									=				height







def 		__magic_name__    (	__UpperCAmelCase	)		->					int:

					'''simple docstring'''

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


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase	)		->					int:

					'''simple docstring'''

					if a > b:
										return a
					return b


def 		__magic_name__    (	__UpperCAmelCase	)		->					MyNode:

					'''simple docstring'''

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


def 		__magic_name__    (	__UpperCAmelCase	)		->					MyNode:

					'''simple docstring'''

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


def 		__magic_name__    (	__UpperCAmelCase	)		->					MyNode:

					'''simple docstring'''

					snake_case_									=				node.get_left()
					assert left_child is not None
					node.set_left(left_rotation(__UpperCAmelCase	)	)
					return right_rotation(__UpperCAmelCase	)


def 		__magic_name__    (	__UpperCAmelCase	)		->					MyNode:

					'''simple docstring'''

					snake_case_									=				node.get_right()
					assert right_child is not None
					node.set_right(right_rotation(__UpperCAmelCase	)	)
					return left_rotation(__UpperCAmelCase	)


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase	)		->					MyNode | None:

					'''simple docstring'''

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


def 		__magic_name__    (	__UpperCAmelCase	)		->					Any:

					'''simple docstring'''

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


def 		__magic_name__    (	__UpperCAmelCase	)		->					Any:

					'''simple docstring'''

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


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase	)		->					MyNode | None:

					'''simple docstring'''

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

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






class 						a				:


				def __init__(		self    :					Union[str, Any]					):
									snake_case_									=				None


				def   A_ (		self    :					Any					):
									return get_height(self.root					)


				def   A_ (		self    :					Any       ,				lowercase_    :					Any					):
									print('''insert:''' + str(lowercase_					)					)
									snake_case_									=				insert_node(self.root       ,				lowercase_					)


				def   A_ (		self    :					Dict       ,				lowercase_    :					Any					):
									print('''delete:''' + str(lowercase_					)					)
									if self.root is None:
														print('''Tree is empty!'''					)
														return
									snake_case_									=				del_node(self.root       ,				lowercase_					)


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







def 		__magic_name__    (	)		->					None:

					'''simple docstring'''

					import doctest

					doctest.testmod()


if __name__ == "__main__":
							_test()
							a  :				List[Any]									=  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 typing import Optional, Tuple, Union

import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict

from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, FlaxTimesteps
from .modeling_flax_utils import FlaxModelMixin
from .unet_ad_blocks_flax import (
    FlaxCrossAttnDownBlockaD,
    FlaxCrossAttnUpBlockaD,
    FlaxDownBlockaD,
    FlaxUNetMidBlockaDCrossAttn,
    FlaxUpBlockaD,
)






@flax.struct.dataclass
class 						a				(   _lowerCamelCase     ):
				snake_case_      =		42







@flax_register_to_config
class 						a				(   nn.Module   ,     _lowerCamelCase   ,     _lowerCamelCase     ):
				snake_case_      =		32
				snake_case_      =		4
				snake_case_      =		4
				snake_case_      =		(
				    "CrossAttnDownBlock2D",
				    "CrossAttnDownBlock2D",
				    "CrossAttnDownBlock2D",
				    "DownBlock2D",
				)
				snake_case_      =		("UpBlock2D", "CrossAttnUpBlock2D", "CrossAttnUpBlock2D", "CrossAttnUpBlock2D")
				snake_case_      =		False
				snake_case_      =		(320, 640, 1_280, 1_280)
				snake_case_      =		2
				snake_case_      =		8
				snake_case_      =		None
				snake_case_      =		1_280
				snake_case_      =		0.0
				snake_case_      =		False
				snake_case_      =		jnp.floataa
				snake_case_      =		True
				snake_case_      =		0
				snake_case_      =		False


				def   A_ (		self    :					Optional[int]       ,				lowercase_    :					jax.random.KeyArray					):
									# init input tensors
									snake_case_									=				(1, self.in_channels, self.sample_size, self.sample_size)
									snake_case_									=				jnp.zeros(lowercase_       ,				dtype=jnp.floataa					)
									snake_case_									=				jnp.ones((1,)       ,				dtype=jnp.intaa					)
									snake_case_									=				jnp.zeros((1, 1, self.cross_attention_dim)       ,				dtype=jnp.floataa					)

									snake_case_			,snake_case_									=				jax.random.split(lowercase_					)
									snake_case_									=				{'''params''': params_rng, '''dropout''': dropout_rng}

									return self.init(lowercase_       ,				lowercase_       ,				lowercase_       ,				lowercase_					)["params"]


				def   A_ (		self    :					List[str]					):
									snake_case_									=				self.block_out_channels
									snake_case_									=				block_out_channels[0] * 4

									if self.num_attention_heads is not None:
														raise ValueError(
														    '''At the moment it is not possible to define the number of attention heads via `num_attention_heads` because of a naming issue as described in https://github.com/huggingface/diffusers/issues/2011#issuecomment-1547958131. Passing `num_attention_heads` will only be supported in diffusers v0.19.'''					)

									# If `num_attention_heads` is not defined (which is the case for most models)
									# it will default to `attention_head_dim`. This looks weird upon first reading it and it is.
									# The reason for this behavior is to correct for incorrectly named variables that were introduced
									# when this library was created. The incorrect naming was only discovered much later in https://github.com/huggingface/diffusers/issues/2011#issuecomment-1547958131
									# Changing `attention_head_dim` to `num_attention_heads` for 40,000+ configurations is too backwards breaking
									# which is why we correct for the naming here.
									snake_case_									=				self.num_attention_heads or self.attention_head_dim

									# input
									snake_case_									=				nn.Conv(
									    block_out_channels[0]       ,				kernel_size=(3, 3)       ,				strides=(1, 1)       ,				padding=((1, 1), (1, 1))       ,				dtype=self.dtype       ,				)

									# time
									snake_case_									=				FlaxTimesteps(
									    block_out_channels[0]       ,				flip_sin_to_cos=self.flip_sin_to_cos       ,				freq_shift=self.config.freq_shift					)
									snake_case_									=				FlaxTimestepEmbedding(lowercase_       ,				dtype=self.dtype					)

									snake_case_									=				self.only_cross_attention
									if isinstance(lowercase_       ,				lowercase_					):
														snake_case_									=				(only_cross_attention,) * len(self.down_block_types					)

									if isinstance(lowercase_       ,				lowercase_					):
														snake_case_									=				(num_attention_heads,) * len(self.down_block_types					)

									# down
									snake_case_									=				[]
									snake_case_									=				block_out_channels[0]
									for i, down_block_type in enumerate(self.down_block_types					):
														snake_case_									=				output_channel
														snake_case_									=				block_out_channels[i]
														snake_case_									=				i == len(lowercase_					) - 1

														if down_block_type == "CrossAttnDownBlock2D":
																			snake_case_									=				FlaxCrossAttnDownBlockaD(
																			    in_channels=lowercase_       ,				out_channels=lowercase_       ,				dropout=self.dropout       ,				num_layers=self.layers_per_block       ,				num_attention_heads=num_attention_heads[i]       ,				add_downsample=not is_final_block       ,				use_linear_projection=self.use_linear_projection       ,				only_cross_attention=only_cross_attention[i]       ,				use_memory_efficient_attention=self.use_memory_efficient_attention       ,				dtype=self.dtype       ,				)
														else:
																			snake_case_									=				FlaxDownBlockaD(
																			    in_channels=lowercase_       ,				out_channels=lowercase_       ,				dropout=self.dropout       ,				num_layers=self.layers_per_block       ,				add_downsample=not is_final_block       ,				dtype=self.dtype       ,				)

														down_blocks.append(lowercase_					)
									snake_case_									=				down_blocks

									# mid
									snake_case_									=				FlaxUNetMidBlockaDCrossAttn(
									    in_channels=block_out_channels[-1]       ,				dropout=self.dropout       ,				num_attention_heads=num_attention_heads[-1]       ,				use_linear_projection=self.use_linear_projection       ,				use_memory_efficient_attention=self.use_memory_efficient_attention       ,				dtype=self.dtype       ,				)

									# up
									snake_case_									=				[]
									snake_case_									=				list(reversed(lowercase_					)					)
									snake_case_									=				list(reversed(lowercase_					)					)
									snake_case_									=				list(reversed(lowercase_					)					)
									snake_case_									=				reversed_block_out_channels[0]
									for i, up_block_type in enumerate(self.up_block_types					):
														snake_case_									=				output_channel
														snake_case_									=				reversed_block_out_channels[i]
														snake_case_									=				reversed_block_out_channels[min(i + 1       ,				len(lowercase_					) - 1					)]

														snake_case_									=				i == len(lowercase_					) - 1

														if up_block_type == "CrossAttnUpBlock2D":
																			snake_case_									=				FlaxCrossAttnUpBlockaD(
																			    in_channels=lowercase_       ,				out_channels=lowercase_       ,				prev_output_channel=lowercase_       ,				num_layers=self.layers_per_block + 1       ,				num_attention_heads=reversed_num_attention_heads[i]       ,				add_upsample=not is_final_block       ,				dropout=self.dropout       ,				use_linear_projection=self.use_linear_projection       ,				only_cross_attention=only_cross_attention[i]       ,				use_memory_efficient_attention=self.use_memory_efficient_attention       ,				dtype=self.dtype       ,				)
														else:
																			snake_case_									=				FlaxUpBlockaD(
																			    in_channels=lowercase_       ,				out_channels=lowercase_       ,				prev_output_channel=lowercase_       ,				num_layers=self.layers_per_block + 1       ,				add_upsample=not is_final_block       ,				dropout=self.dropout       ,				dtype=self.dtype       ,				)

														up_blocks.append(lowercase_					)
														snake_case_									=				output_channel
									snake_case_									=				up_blocks

									# out
									snake_case_									=				nn.GroupNorm(num_groups=32       ,				epsilon=1e-5					)
									snake_case_									=				nn.Conv(
									    self.out_channels       ,				kernel_size=(3, 3)       ,				strides=(1, 1)       ,				padding=((1, 1), (1, 1))       ,				dtype=self.dtype       ,				)


				def __call__(		self    :					Union[str, Any]       ,				lowercase_    :					Union[str, Any]       ,				lowercase_    :					int       ,				lowercase_    :					Any       ,				lowercase_    :					int=None       ,				lowercase_    :					Any=None       ,				lowercase_    :					bool = True       ,				lowercase_    :					bool = False       ,				):
									# 1. time
									if not isinstance(lowercase_       ,				jnp.ndarray					):
														snake_case_									=				jnp.array([timesteps]       ,				dtype=jnp.intaa					)
									elif isinstance(lowercase_       ,				jnp.ndarray					) and len(timesteps.shape					) == 0:
														snake_case_									=				timesteps.astype(dtype=jnp.floataa					)
														snake_case_									=				jnp.expand_dims(lowercase_       ,				0					)

									snake_case_									=				self.time_proj(lowercase_					)
									snake_case_									=				self.time_embedding(lowercase_					)

									# 2. pre-process
									snake_case_									=				jnp.transpose(lowercase_       ,				(0, 2, 3, 1)					)
									snake_case_									=				self.conv_in(lowercase_					)

									# 3. down
									snake_case_									=				(sample,)
									for down_block in self.down_blocks:
														if isinstance(lowercase_       ,				lowercase_					):
																			snake_case_			,snake_case_									=				down_block(lowercase_       ,				lowercase_       ,				lowercase_       ,				deterministic=not train					)
														else:
																			snake_case_			,snake_case_									=				down_block(lowercase_       ,				lowercase_       ,				deterministic=not train					)
														down_block_res_samples += res_samples

									if down_block_additional_residuals is not None:
														snake_case_									=				()

														for down_block_res_sample, down_block_additional_residual in zip(
														    lowercase_       ,				lowercase_					):
																			down_block_res_sample += down_block_additional_residual
																			new_down_block_res_samples += (down_block_res_sample,)

														snake_case_									=				new_down_block_res_samples

									# 4. mid
									snake_case_									=				self.mid_block(lowercase_       ,				lowercase_       ,				lowercase_       ,				deterministic=not train					)

									if mid_block_additional_residual is not None:
														sample += mid_block_additional_residual

									# 5. up
									for up_block in self.up_blocks:
														snake_case_									=				down_block_res_samples[-(self.layers_per_block + 1) :]
														snake_case_									=				down_block_res_samples[: -(self.layers_per_block + 1)]
														if isinstance(lowercase_       ,				lowercase_					):
																			snake_case_									=				up_block(
																			    lowercase_       ,				temb=lowercase_       ,				encoder_hidden_states=lowercase_       ,				res_hidden_states_tuple=lowercase_       ,				deterministic=not train       ,				)
														else:
																			snake_case_									=				up_block(lowercase_       ,				temb=lowercase_       ,				res_hidden_states_tuple=lowercase_       ,				deterministic=not train					)

        # 6. post-process
									snake_case_									=				self.conv_norm_out(lowercase_					)
									snake_case_									=				nn.silu(lowercase_					)
									snake_case_									=				self.conv_out(lowercase_					)
									snake_case_									=				jnp.transpose(lowercase_       ,				(0, 3, 1, 2)					)

									if not return_dict:
														return (sample,)

									return FlaxUNetaDConditionOutput(sample=lowercase_					)

