


"""simple docstring"""
class      _UpperCAmelCase					:






		'''simple docstring'''

		def __init__(self							,			a_   ):





			'''simple docstring'''

			__snake_case      :		List[Any]         =							val
			# Number of nodes in left subtree
			__snake_case      :		Dict         =							0
			__snake_case      :		Optional[Any]         =							None
			__snake_case      :		Dict         =							None
			__snake_case      :		List[Any]         =							None



		def 							SCREAMING_SNAKE_CASE    (self							,			a_   ):





			'''simple docstring'''

			assert self.left_tree_size == other.left_tree_size, "Unequal Sizes of Blocks"

			if self.val < other.val:
				__snake_case      :		str         =							self.right
				__snake_case      :		Union[str, Any]         =							None
				if self.right:
					__snake_case      :		List[Any]         =							other
				__snake_case      :		Optional[int]         =							other
				__snake_case      :		Union[str, Any]         =							self.left_tree_size * 2 + 1
				return self
			else:
				__snake_case      :		Optional[Any]         =							other.right
				__snake_case      :		Any         =							None
				if other.right:
					__snake_case      :		Union[str, Any]         =							self
				__snake_case      :		int         =							self
				__snake_case      :		List[Any]         =							other.left_tree_size * 2 + 1
				return other



class      _UpperCAmelCase					:






		'''simple docstring'''

		def __init__(self							,			a_=None							,			a_=None							,			a_=0   ):





			'''simple docstring'''

			__snake_case      :		str         =							heap_size
			__snake_case      :		Optional[int]         =							bottom_root
			__snake_case      :		Any         =							min_node



		def 							SCREAMING_SNAKE_CASE    (self							,			a_   ):





			'''simple docstring'''

			if other.size == 0:
				return None
			if self.size == 0:
				__snake_case      :		Any         =							other.size
				__snake_case      :		str         =							other.bottom_root
				__snake_case      :		Optional[int]         =							other.min_node
				return None
			# Update size
			__snake_case      :		List[str]         =							self.size + other.size

			# Update min.node
			if self.min_node.val > other.min_node.val:
				__snake_case      :		Dict         =							other.min_node
			# Merge

			# Order roots by left_subtree_size
			__snake_case      :		Optional[int]         =							[]
			__snake_case      ,				__snake_case      :		List[str]         =							self.bottom_root, other.bottom_root
			while i or j:
				if i and ((not j) or i.left_tree_size < j.left_tree_size):
					combined_roots_list.append((i, True)   )
					__snake_case      :		Optional[Any]         =							i.parent
				else:
					combined_roots_list.append((j, False)   )
					__snake_case      :		List[str]         =							j.parent
        # Insert links between them
			for i in range(len(a_   ) - 1   ):
				if combined_roots_list[i][1] != combined_roots_list[i + 1][1]:
					__snake_case      :		List[Any]         =							combined_roots_list[i + 1][0]
					__snake_case      :		Optional[Any]         =							combined_roots_list[i][0]
        # Consecutively merge roots with same left_tree_size
			__snake_case      :		List[Any]         =							combined_roots_list[0][0]
			while i.parent:
				if (
				    (i.left_tree_size == i.parent.left_tree_size) and (not i.parent.parent)
				) or (
				    i.left_tree_size == i.parent.left_tree_size
				    and i.left_tree_size != i.parent.parent.left_tree_size
				):
					# Neighbouring Nodes
					__snake_case      :		Union[str, Any]         =							i.left
					__snake_case      :		int         =							i.parent.parent

					# Merging trees
					__snake_case      :		Optional[Any]         =							i.merge_trees(i.parent   )

					# Updating links
					__snake_case      :		Dict         =							previous_node
					__snake_case      :		Optional[Any]         =							next_node
					if previous_node:
						__snake_case      :		List[str]         =							i
					if next_node:
						__snake_case      :		Any         =							i
				else:
					__snake_case      :		Optional[Any]         =							i.parent
        # Updating self.bottom_root
			while i.left:
				__snake_case      :		Union[str, Any]         =							i.left
			__snake_case      :		int         =							i

			# Update other
			__snake_case      :		Tuple         =							self.size
			__snake_case      :		Optional[int]         =							self.bottom_root
			__snake_case      :		List[str]         =							self.min_node

			# Return the merged heap
			return self



		def 							SCREAMING_SNAKE_CASE    (self							,			a_   ):





			'''simple docstring'''

			if self.size == 0:
				__snake_case      :		str         =							Node(a_   )
				__snake_case      :		List[Any]         =							1
				__snake_case      :		Optional[Any]         =							self.bottom_root
			else:
				# Create new node
				__snake_case      :		List[Any]         =							Node(a_   )

				# Update size
				self.size += 1

				# update min_node
				if val < self.min_node.val:
					__snake_case      :		Union[str, Any]         =							new_node
				# Put new_node as a bottom_root in heap
				__snake_case      :		str         =							new_node
				__snake_case      :		List[str]         =							self.bottom_root
				__snake_case      :		List[Any]         =							new_node

				# Consecutively merge roots with same left_tree_size
				while (
				    self.bottom_root.parent
				    and self.bottom_root.left_tree_size
				    == self.bottom_root.parent.left_tree_size
				):
					# Next node
					__snake_case      :		Optional[int]         =							self.bottom_root.parent.parent

					# Merge
					__snake_case      :		List[Any]         =							self.bottom_root.merge_trees(self.bottom_root.parent   )

					# Update Links
					__snake_case      :		List[Any]         =							next_node
					__snake_case      :		Optional[Any]         =							None
					if next_node:
						__snake_case      :		List[Any]         =							self.bottom_root



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			return self.min_node.val



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			return self.size == 0



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		List[Any]         =							self.min_node.val

			# Last element in heap corner case
			if self.size == 1:
				# Update size
				__snake_case      :		Union[str, Any]         =							0

				# Update bottom root
				__snake_case      :		Tuple         =							None

				# Update min_node
				__snake_case      :		Optional[int]         =							None

				return min_value
			# No right subtree corner case
			# The structure of the tree implies that this should be the bottom root
			# and there is at least one other root
			if self.min_node.right is None:
				# Update size
				self.size -= 1

				# Update bottom root
				__snake_case      :		List[str]         =							self.bottom_root.parent
				__snake_case      :		int         =							None

				# Update min_node
				__snake_case      :		Union[str, Any]         =							self.bottom_root
				__snake_case      :		Any         =							self.bottom_root.parent
				while i:
					if i.val < self.min_node.val:
						__snake_case      :		Dict         =							i
					__snake_case      :		str         =							i.parent
				return min_value
			# General case
			# Find the BinomialHeap of the right subtree of min_node
			__snake_case      :		List[Any]         =							self.min_node.right
			__snake_case      :		str         =							None
			__snake_case      :		Tuple         =							bottom_of_new
			__snake_case      :		Optional[Any]         =							1

			# Size, min_node and bottom_root
			while bottom_of_new.left:
				__snake_case      :		str         =							size_of_new * 2 + 1
				__snake_case      :		Union[str, Any]         =							bottom_of_new.left
				if bottom_of_new.val < min_of_new.val:
					__snake_case      :		Dict         =							bottom_of_new
        # Corner case of single root on top left path
			if (not self.min_node.left) and (not self.min_node.parent):
				__snake_case      :		List[str]         =							size_of_new
				__snake_case      :		str         =							bottom_of_new
				__snake_case      :		Optional[Any]         =							min_of_new
				# print("Single root, multiple nodes case")
				return min_value
			# Remaining cases
			# Construct heap of right subtree
			__snake_case      :		Optional[int]         =							BinomialHeap(
			    bottom_root=a_							,			min_node=a_							,			heap_size=a_   )

			# Update size
			__snake_case      :		List[str]         =							self.size - 1 - size_of_new

			# Neighbour nodes
			__snake_case      :		Dict         =							self.min_node.left
			__snake_case      :		Dict         =							self.min_node.parent

			# Initialize new bottom_root and min_node
			__snake_case      :		List[Any]         =							previous_node or next_node
			__snake_case      :		Union[str, Any]         =							next_node

			# Update links of previous_node and search below for new min_node and
			# bottom_root
			if previous_node:
				__snake_case      :		Optional[int]         =							next_node

				# Update bottom_root and search for min_node below
				__snake_case      :		Optional[Any]         =							previous_node
				__snake_case      :		str         =							previous_node
				while self.bottom_root.left:
					__snake_case      :		Any         =							self.bottom_root.left
					if self.bottom_root.val < self.min_node.val:
						__snake_case      :		Tuple         =							self.bottom_root
			if next_node:
				__snake_case      :		Optional[int]         =							previous_node

				# Search for new min_node above min_node
				__snake_case      :		Tuple         =							next_node
				while i:
					if i.val < self.min_node.val:
						__snake_case      :		List[str]         =							i
					__snake_case      :		int         =							i.parent
        # Merge heaps
			self.merge_heaps(a_   )

			return min_value



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Dict         =							self.bottom_root
			while top_root.parent:
				__snake_case      :		Optional[int]         =							top_root.parent
			# preorder
			__snake_case      :		Dict         =							[]
			self.__traversal(a_							,			a_   )
			return heap_pre_order



		def 							SCREAMING_SNAKE_CASE    (self							,			a_							,			a_							,			a_=0   ):





			'''simple docstring'''

			if curr_node:
				preorder.append((curr_node.val, level)   )
				self.__traversal(curr_node.left							,			a_							,			level + 1   )
				self.__traversal(curr_node.right							,			a_							,			level + 1   )
			else:
				preorder.append(('''#''', level)   )



		def __str__(self   ):





			'''simple docstring'''

			if self.is_empty():
				return ""
			__snake_case      :		List[Any]         =							self.pre_order()

			return "\n".join(('''-''' * level + str(a_   )) for value, level in preorder_heap   )


# Unit Tests
if __name__ == "__main__":
			import doctest

			doctest.testmod()










'''simple docstring'''



import os
import pathlib
import tempfile
import uuid

import numpy as np

from ..utils import is_soundfile_availble, is_torch_available, is_vision_available, logging


_lowercase       :						Dict						=logging.get_logger(__name__)

if is_vision_available():
				import PIL.Image
				from PIL import Image
				from PIL.Image import Image as ImageType
else:
				_lowercase       :						List[Any]						=object

if is_torch_available():
				import torch

if is_soundfile_availble():
				import soundfile as sf






class 			_SCREAMING_SNAKE_CASE				:



			def __init__(     self		:						List[str]    ,			__UpperCamelCase		:						Optional[int]			)      ->      List[str]:
							"""simple docstring"""





							snake_case__      :   int      =    value



			def __str__(     self		:						int			)      ->      str:
							"""simple docstring"""





							return self.to_string()



			def 				lowerCAmelCase (     self		:						List[Any]			)      ->      List[str]:
							"""simple docstring"""





							logger.error(
							    '''This is a raw AgentType of unknown type. Display in notebooks and string conversion will be unreliable'''			)
							return self._value







			def 				lowerCAmelCase (     self		:						Optional[Any]			)      ->      str:
							"""simple docstring"""





							logger.error(
							    '''This is a raw AgentType of unknown type. Display in notebooks and string conversion will be unreliable'''			)
							return str(self._value			)






class 			_SCREAMING_SNAKE_CASE				(lowercase__,	lowercase__      ):



			def 				lowerCAmelCase (     self		:						str			)      ->      Tuple:
							"""simple docstring"""





							return self._value







			def 				lowerCAmelCase (     self		:						Optional[int]			)      ->      Union[str, Any]:
							"""simple docstring"""





							return self._value






class 			_SCREAMING_SNAKE_CASE				(lowercase__,	lowercase__      ):



			def __init__(     self		:						str    ,			__UpperCamelCase		:						List[Any]			)      ->      Dict:
							"""simple docstring"""





							super().__init__(__UpperCamelCase			)

							if not is_vision_available():
											raise ImportError('''PIL must be installed in order to handle images.'''			)

							snake_case__      :   str      =    None
							snake_case__      :   List[Any]      =    None
							snake_case__      :   Tuple      =    None

							if isinstance(__UpperCamelCase    ,			__UpperCamelCase			):
											snake_case__      :   List[Any]      =    value
							elif isinstance(__UpperCamelCase    ,			(str, pathlib.Path)			):
											snake_case__      :   int      =    value
							elif isinstance(__UpperCamelCase    ,			torch.Tensor			):
											snake_case__      :   Union[str, Any]      =    value
							else:
											raise ValueError(F'''Unsupported type for {self.__class__.__name__}: {type(__UpperCamelCase			)}'''			)



			def 				lowerCAmelCase (     self		:						str    ,			__UpperCamelCase		:						Dict=None    ,			__UpperCamelCase		:						Any=None			)      ->      List[Any]:
							"""simple docstring"""





							from IPython.display import Image, display

							display(Image(self.to_string()			)			)



			def 				lowerCAmelCase (     self		:						List[str]			)      ->      str:
							"""simple docstring"""





							if self._raw is not None:
											return self._raw

							if self._path is not None:
											snake_case__      :   str      =    Image.open(self._path			)
											return self._raw







			def 				lowerCAmelCase (     self		:						Dict			)      ->      Optional[Any]:
							"""simple docstring"""





							if self._path is not None:
											return self._path

							if self._raw is not None:
											snake_case__      :   Any      =    tempfile.mkdtemp()
											snake_case__      :   Dict      =    os.path.join(__UpperCamelCase    ,			str(uuid.uuida()			) + '''.png'''			)
											self._raw.save(self._path			)

											return self._path

							if self._tensor is not None:
											snake_case__      :   List[str]      =    self._tensor.cpu().detach().numpy()

											# There is likely simpler than load into image into save
											snake_case__      :   List[Any]      =    Image.fromarray((array * 255).astype(np.uinta			)			)

											snake_case__      :   str      =    tempfile.mkdtemp()
											snake_case__      :   Dict      =    os.path.join(__UpperCamelCase    ,			str(uuid.uuida()			) + '''.png'''			)

											img.save(self._path			)

											return self._path






class 			_SCREAMING_SNAKE_CASE				(lowercase__      ):



			def __init__(     self		:						Optional[Any]    ,			__UpperCamelCase		:						List[Any]    ,			__UpperCamelCase		:						str=16000			)      ->      Union[str, Any]:
							"""simple docstring"""





							super().__init__(__UpperCamelCase			)

							if not is_soundfile_availble():
											raise ImportError('''soundfile must be installed in order to handle audio.'''			)

							snake_case__      :   List[str]      =    None
							snake_case__      :   Optional[int]      =    None

							snake_case__      :   Any      =    samplerate

							if isinstance(__UpperCamelCase    ,			(str, pathlib.Path)			):
											snake_case__      :   int      =    value
							elif isinstance(__UpperCamelCase    ,			torch.Tensor			):
											snake_case__      :   int      =    value
							else:
											raise ValueError(F'''Unsupported audio type: {type(__UpperCamelCase			)}'''			)



			def 				lowerCAmelCase (     self		:						Tuple    ,			__UpperCamelCase		:						List[Any]=None    ,			__UpperCamelCase		:						Optional[Any]=None			)      ->      Any:
							"""simple docstring"""





							from IPython.display import Audio, display

							display(Audio(self.to_string()    ,			rate=self.samplerate			)			)



			def 				lowerCAmelCase (     self		:						Union[str, Any]			)      ->      Union[str, Any]:
							"""simple docstring"""





							if self._tensor is not None:
											return self._tensor

							if self._path is not None:
											snake_case__  ,      snake_case__      :   Tuple      =    sf.read(self._path			)
											snake_case__      :   Tuple      =    torch.tensor(__UpperCamelCase			)
											return self._tensor







			def 				lowerCAmelCase (     self		:						Any			)      ->      Dict:
							"""simple docstring"""





							if self._path is not None:
											return self._path

							if self._tensor is not None:
											snake_case__      :   Tuple      =    tempfile.mkdtemp()
											snake_case__      :   int      =    os.path.join(__UpperCamelCase    ,			str(uuid.uuida()			) + '''.wav'''			)
											sf.write(self._path    ,			self._tensor    ,			samplerate=self.samplerate			)
											return self._path



_lowercase       :						Union[str, Any]						={"text": AgentText, "image": AgentImage, "audio": AgentAudio}
_lowercase       :						List[Any]						={str: AgentText}

if is_vision_available():
				_lowercase       :						Optional[Any]						=AgentImage


def 							__UpperCAmelCase				(				*UpperCamelCase__				:Optional[int]   ,				**UpperCamelCase__				:List[Any]			)		->						Optional[Any]:
				snake_case__      :   List[str]      =    [(arg.to_raw() if isinstance(UpperCamelCase__   ,				UpperCamelCase__			) else arg) for arg in args]
				snake_case__      :   Any      =    {k: (v.to_raw() if isinstance(UpperCamelCase__   ,				UpperCamelCase__			) else v) for k, v in kwargs.items()}
				return args, kwargs



def 							__UpperCAmelCase				(				UpperCamelCase__				:Optional[Any]   ,				UpperCamelCase__				:Tuple=None			)		->						Dict:
				if isinstance(UpperCamelCase__   ,				UpperCamelCase__			):
								snake_case__      :   Any      =    {}
								for i, (k, v) in enumerate(outputs.items()			):
												if output_types is not None:
																# If the class has defined outputs, we can map directly according to the class definition
																if output_types[i] in AGENT_TYPE_MAPPING:
																				snake_case__      :   List[Any]      =    AGENT_TYPE_MAPPING[output_types[i]](UpperCamelCase__			)
																else:
																				snake_case__      :   Optional[int]      =    AgentType(UpperCamelCase__			)

												else:
																# If the class does not have defined output, then we map according to the type
																for _k, _v in INSTANCE_TYPE_MAPPING.items():
																				if isinstance(UpperCamelCase__   ,				_k			):
																								snake_case__      :   str      =    _v(UpperCamelCase__			)
																if k not in decoded_outputs:
																				snake_case__      :   Any      =    AgentType[v]

				elif isinstance(UpperCamelCase__   ,				(list, tuple)			):
								snake_case__      :   List[str]      =    type(UpperCamelCase__			)()
								for i, v in enumerate(UpperCamelCase__			):
												if output_types is not None:
																# If the class has defined outputs, we can map directly according to the class definition
																if output_types[i] in AGENT_TYPE_MAPPING:
																				decoded_outputs.append(AGENT_TYPE_MAPPING[output_types[i]](UpperCamelCase__			)			)
																else:
																				decoded_outputs.append(AgentType(UpperCamelCase__			)			)
												else:
																# If the class does not have defined output, then we map according to the type
																snake_case__      :   Any      =    False
																for _k, _v in INSTANCE_TYPE_MAPPING.items():
																				if isinstance(UpperCamelCase__   ,				_k			):
																								decoded_outputs.append(_v(UpperCamelCase__			)			)
																								snake_case__      :   str      =    True

																if not found:
																				decoded_outputs.append(AgentType(UpperCamelCase__			)			)

				else:
								if output_types[0] in AGENT_TYPE_MAPPING:
												# If the class has defined outputs, we can map directly according to the class definition
												snake_case__      :   Tuple      =    AGENT_TYPE_MAPPING[output_types[0]](UpperCamelCase__			)

								else:
												# If the class does not have defined output, then we map according to the type
												for _k, _v in INSTANCE_TYPE_MAPPING.items():
																if isinstance(UpperCamelCase__   ,				_k			):
																				return _v(UpperCamelCase__			)
												return AgentType(UpperCamelCase__			)

				return decoded_outputs




