






from dataclasses import dataclass
from typing import Optional, Tuple, Union

import torch
import torch.nn as nn

from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decoder, DecoderOutput, Encoder, VectorQuantizer





@dataclass
class __lowerCamelCase (      snake_case__):





	"""simple docstring"""






	UpperCamelCase__								=      42





class __lowerCamelCase (      snake_case__     ,       snake_case__):





	"""simple docstring"""






	@register_to_config
	def __init__(							self       ,    UpperCAmelCase = 3       ,    UpperCAmelCase = 3       ,    UpperCAmelCase = ("DownEncoderBlock2D",)       ,    UpperCAmelCase = ("UpDecoderBlock2D",)       ,    UpperCAmelCase = (64,)       ,    UpperCAmelCase = 1       ,    UpperCAmelCase = "silu"       ,    UpperCAmelCase = 3       ,    UpperCAmelCase = 32       ,    UpperCAmelCase = 256       ,    UpperCAmelCase = 32       ,    UpperCAmelCase = None       ,    UpperCAmelCase = 0.1_82_15       ,    UpperCAmelCase = "group"       ,    ):
							"""simple docstring"""







							super().__init__()

							# pass init params to Encoder
							_UpperCAmelCase									=			Encoder(
							    in_channels=UpperCAmelCase       ,    out_channels=UpperCAmelCase       ,    down_block_types=UpperCAmelCase       ,    block_out_channels=UpperCAmelCase       ,    layers_per_block=UpperCAmelCase       ,    act_fn=UpperCAmelCase       ,    norm_num_groups=UpperCAmelCase       ,    double_z=UpperCAmelCase       ,    )

							_UpperCAmelCase									=			vq_embed_dim if vq_embed_dim is not None else latent_channels

							_UpperCAmelCase									=			nn.Convad(UpperCAmelCase       ,    UpperCAmelCase       ,    1    )
							_UpperCAmelCase									=			VectorQuantizer(UpperCAmelCase       ,    UpperCAmelCase       ,    beta=0.25       ,    remap=UpperCAmelCase       ,    sane_index_shape=UpperCAmelCase    )
							_UpperCAmelCase									=			nn.Convad(UpperCAmelCase       ,    UpperCAmelCase       ,    1    )

							# pass init params to Decoder
							_UpperCAmelCase									=			Decoder(
							    in_channels=UpperCAmelCase       ,    out_channels=UpperCAmelCase       ,    up_block_types=UpperCAmelCase       ,    block_out_channels=UpperCAmelCase       ,    layers_per_block=UpperCAmelCase       ,    act_fn=UpperCAmelCase       ,    norm_num_groups=UpperCAmelCase       ,    norm_type=UpperCAmelCase       ,    )

	@apply_forward_hook
	def        UpperCamelCase    (							self       ,    UpperCAmelCase       ,    UpperCAmelCase = True    ):
							"""simple docstring"""







							_UpperCAmelCase									=			self.encoder(UpperCAmelCase    )
							_UpperCAmelCase									=			self.quant_conv(UpperCAmelCase    )

							if not return_dict:
													return (h,)

							return VQEncoderOutput(latents=UpperCAmelCase    )

	@apply_forward_hook
	def        UpperCamelCase    (							self       ,    UpperCAmelCase       ,    UpperCAmelCase = False       ,    UpperCAmelCase = True    ):
							"""simple docstring"""







							if not force_not_quantize:
													_UpperCAmelCase					, _UpperCAmelCase					, _UpperCAmelCase									=			self.quantize(UpperCAmelCase    )
							else:
													_UpperCAmelCase									=			h
							_UpperCAmelCase									=			self.post_quant_conv(UpperCAmelCase    )
							_UpperCAmelCase									=			self.decoder(UpperCAmelCase       ,    quant if self.config.norm_type == 'spatial' else None    )

							if not return_dict:
													return (dec,)

							return DecoderOutput(sample=UpperCAmelCase    )

	def        UpperCamelCase    (							self       ,    UpperCAmelCase       ,    UpperCAmelCase = True    ):
							"""simple docstring"""







							_UpperCAmelCase									=			sample
							_UpperCAmelCase									=			self.encode(UpperCAmelCase    ).latents
							_UpperCAmelCase									=			self.decode(UpperCAmelCase    ).sample

							if not return_dict:
													return (dec,)

							return DecoderOutput(sample=UpperCAmelCase    )








class __lowerCamelCase :





	"""simple docstring"""






	def __init__(							self    ):
							"""simple docstring"""







							_UpperCAmelCase									=			{}  # Mapping from char to TrieNode
							_UpperCAmelCase									=			False

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							for word in words:
													self.insert(UpperCAmelCase    )

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							_UpperCAmelCase									=			self
							for char in word:
													if char not in curr.nodes:
																			_UpperCAmelCase									=			TrieNode()
													_UpperCAmelCase									=			curr.nodes[char]
							_UpperCAmelCase									=			True

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							_UpperCAmelCase									=			self
							for char in word:
													if char not in curr.nodes:
																			return False
													_UpperCAmelCase									=			curr.nodes[char]
							return curr.is_leaf

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							def _delete(UpperCAmelCase       ,    UpperCAmelCase       ,    UpperCAmelCase    ) -> bool:
													if index == len(UpperCAmelCase    ):
																			# If word does not exist
																			if not curr.is_leaf:
																									return False
																			_UpperCAmelCase									=			False
																			return len(curr.nodes    ) == 0
													_UpperCAmelCase									=			word[index]
													_UpperCAmelCase									=			curr.nodes.get(UpperCAmelCase    )
													# If char not in current trie node
													if not char_node:
																			return False
													# Flag to check if node can be deleted
													_UpperCAmelCase									=			_delete(UpperCAmelCase       ,    UpperCAmelCase       ,    index + 1    )
													if delete_curr:
																			del curr.nodes[char]
																			return len(curr.nodes    ) == 0
													return delete_curr

							_delete(self       ,    UpperCAmelCase       ,    0    )



def __A    (      __lowerCAmelCase ,		__lowerCAmelCase	)->  None:





						"""simple docstring"""



						if node.is_leaf:
												print(__lowerCAmelCase ,		end=' '	)

						for key, value in node.nodes.items():
												print_words(__lowerCAmelCase ,		word + key	)


def __A    (      )->  bool:





						"""simple docstring"""



						_UpperCAmelCase									=			'banana bananas bandana band apple all beast'.split()
						_UpperCAmelCase									=			TrieNode()
						root.insert_many(__lowerCAmelCase	)
						# print_words(root, "")
						assert all(root.find(__lowerCAmelCase	) for word in words	)
						assert root.find('banana'	)
						assert not root.find('bandanas'	)
						assert not root.find('apps'	)
						assert root.find('apple'	)
						assert root.find('all'	)
						root.delete('all'	)
						assert not root.find('all'	)
						root.delete('banana'	)
						assert not root.find('banana'	)
						assert root.find('bananas'	)
						return True


def __A    (      __lowerCAmelCase ,		__lowerCAmelCase	)->  None:





						"""simple docstring"""



						print(str(__lowerCAmelCase	) ,		'works!' if passes else 'doesn\'t work :('	)


def __A    (      )->  None:





						"""simple docstring"""



						assert test_trie()


def __A    (      )->  None:





						"""simple docstring"""



						print_results('Testing trie functionality' ,		test_trie()	)


if __name__ == "__main__":
		main()
