



'''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


_UpperCamelCase  						=			logging.get_logger(__name__)

if is_vision_available():
		import PIL.Image
		from PIL import Image
		from PIL.Image import Image as ImageType
else:
		_UpperCamelCase  						=			object

if is_torch_available():
		import torch

if is_soundfile_availble():
		import soundfile as sf

class      lowerCamelCase__     :






	'''simple docstring'''

	def __init__(  self		:  Union[str, Any]   ,		__A		:  Optional[Any]					)     ->			Union[str, Any]:




								'''simple docstring'''





								lowerCAmelCase__  =   value




	def __str__(  self		:  List[Any]					)     ->			List[str]:




								'''simple docstring'''





								return self.to_string()




	def      lowercase__							(  self		:  Optional[int]					)     ->			Tuple:




								'''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      lowercase__							(  self		:  List[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      lowerCamelCase__     (     _A,     _A				):






	'''simple docstring'''

	def      lowercase__							(  self		:  Any					)     ->			Dict:




								'''simple docstring'''





								return self._value




	def      lowercase__							(  self		:  str					)     ->			int:




								'''simple docstring'''





								return self._value





class      lowerCamelCase__     (     _A,     _A				):






	'''simple docstring'''

	def __init__(  self		:  Optional[Any]   ,		__A		:  int					)     ->			Optional[Any]:




								'''simple docstring'''





								super().__init__(__A					)

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

								lowerCAmelCase__  =   None
								lowerCAmelCase__  =   None
								lowerCAmelCase__  =   None

								if isinstance(__A   ,		__A					):
															lowerCAmelCase__  =   value
								elif isinstance(__A   ,		(str, pathlib.Path)					):
															lowerCAmelCase__  =   value
								elif isinstance(__A   ,		torch.Tensor					):
															lowerCAmelCase__  =   value
								else:
															raise ValueError(f'''Unsupported type for {self.__class__.__name__}: {type(__A					)}'''					)




	def      lowercase__							(  self		:  List[str]   ,		__A		:  Any=None   ,		__A		:  Optional[Any]=None					)     ->			Union[str, Any]:




								'''simple docstring'''





								from IPython.display import Image, display

								display(Image(self.to_string()					)					)




	def      lowercase__							(  self		:  int					)     ->			List[str]:




								'''simple docstring'''





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

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




	def      lowercase__							(  self		:  Union[str, Any]					)     ->			List[str]:




								'''simple docstring'''





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

								if self._raw is not None:
															lowerCAmelCase__  =   tempfile.mkdtemp()
															lowerCAmelCase__  =   os.path.join(__A   ,		str(uuid.uuida()					) + """.png"""					)
															self._raw.save(self._path					)

															return self._path

								if self._tensor is not None:
															lowerCAmelCase__  =   self._tensor.cpu().detach().numpy()

															# There is likely simpler than load into image into save
															lowerCAmelCase__  =   Image.fromarray((array * 255).astype(np.uinta					)					)

															lowerCAmelCase__  =   tempfile.mkdtemp()
															lowerCAmelCase__  =   os.path.join(__A   ,		str(uuid.uuida()					) + """.png"""					)

															img.save(self._path					)

															return self._path





class      lowerCamelCase__     (     _A				):






	'''simple docstring'''

	def __init__(  self		:  Dict   ,		__A		:  Optional[int]   ,		__A		:  Optional[Any]=1_6000					)     ->			Optional[Any]:




								'''simple docstring'''





								super().__init__(__A					)

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

								lowerCAmelCase__  =   None
								lowerCAmelCase__  =   None

								lowerCAmelCase__  =   samplerate

								if isinstance(__A   ,		(str, pathlib.Path)					):
															lowerCAmelCase__  =   value
								elif isinstance(__A   ,		torch.Tensor					):
															lowerCAmelCase__  =   value
								else:
															raise ValueError(f'''Unsupported audio type: {type(__A					)}'''					)




	def      lowercase__							(  self		:  Union[str, Any]   ,		__A		:  List[Any]=None   ,		__A		:  Tuple=None					)     ->			Optional[Any]:




								'''simple docstring'''





								from IPython.display import Audio, display

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




	def      lowercase__							(  self		:  List[Any]					)     ->			Tuple:




								'''simple docstring'''





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

								if self._path is not None:
															lowerCAmelCase__  ,lowerCAmelCase__  =   sf.read(self._path					)
															lowerCAmelCase__  =   torch.tensor(__A					)
															return self._tensor




	def      lowercase__							(  self		:  Optional[Any]					)     ->			str:




								'''simple docstring'''





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

								if self._tensor is not None:
															lowerCAmelCase__  =   tempfile.mkdtemp()
															lowerCAmelCase__  =   os.path.join(__A   ,		str(uuid.uuida()					) + """.wav"""					)
															sf.write(self._path   ,		self._tensor   ,		samplerate=self.samplerate					)
															return self._path





_UpperCamelCase  						=			{"""text""": AgentText, """image""": AgentImage, """audio""": AgentAudio}
_UpperCamelCase  						=			{str: AgentText}

if is_vision_available():
		_UpperCamelCase  						=			AgentImage
def 			_lowerCAmelCase(      *UpperCAmelCase_      :	int					, **UpperCAmelCase_      :	Any						) ->							str:
							lowerCAmelCase__  =   [(arg.to_raw() if isinstance(UpperCAmelCase_					, UpperCAmelCase_						) else arg) for arg in args]
							lowerCAmelCase__  =   {k: (v.to_raw() if isinstance(UpperCAmelCase_					, UpperCAmelCase_						) else v) for k, v in kwargs.items()}
							return args, kwargs






def 			_lowerCAmelCase(      UpperCAmelCase_      :	Union[str, Any]					, UpperCAmelCase_      :	Union[str, Any]=None						) ->							Optional[int]:
							if isinstance(UpperCAmelCase_					, UpperCAmelCase_						):
														lowerCAmelCase__  =   {}
														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:
																																			lowerCAmelCase__  =   AGENT_TYPE_MAPPING[output_types[i]](UpperCAmelCase_						)
																												else:
																																			lowerCAmelCase__  =   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						):
																																										lowerCAmelCase__  =   _v(UpperCAmelCase_						)
																												if k not in decoded_outputs:
																																			lowerCAmelCase__  =   AgentType[v]

							elif isinstance(UpperCAmelCase_					, (list, tuple)						):
														lowerCAmelCase__  =   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
																												lowerCAmelCase__  =   False
																												for _k, _v in INSTANCE_TYPE_MAPPING.items():
																																			if isinstance(UpperCAmelCase_					, _k						):
																																										decoded_outputs.append(_v(UpperCAmelCase_						)						)
																																										lowerCAmelCase__  =   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
																					lowerCAmelCase__  =   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










'''simple docstring'''







def 			_lowerCAmelCase(      UpperCAmelCase_      :	str					, UpperCAmelCase_      :	str					, UpperCAmelCase_      :	int					, UpperCAmelCase_      :	int					, UpperCAmelCase_      :	int					, UpperCAmelCase_      :	int					, ) ->							tuple[list[list[int]], list[list[str]]]:
							lowerCAmelCase__  =   list(UpperCAmelCase_						)
							lowerCAmelCase__  =   list(UpperCAmelCase_						)
							lowerCAmelCase__  =   len(UpperCAmelCase_						)
							lowerCAmelCase__  =   len(UpperCAmelCase_						)

							lowerCAmelCase__  =   [
							    [0 for _ in range(len_destination_seq + 1						)] for _ in range(len_source_seq + 1						)
							]
							lowerCAmelCase__  =   [
							    ["""0""" for _ in range(len_destination_seq + 1						)] for _ in range(len_source_seq + 1						)
							]

							for i in range(1					, len_source_seq + 1						):
														lowerCAmelCase__  =   i * delete_cost
														lowerCAmelCase__  =   F'''D{source_seq[i - 1]:c}'''

							for i in range(1					, len_destination_seq + 1						):
														lowerCAmelCase__  =   i * insert_cost
														lowerCAmelCase__  =   F'''I{destination_seq[i - 1]:c}'''

							for i in range(1					, len_source_seq + 1						):
														for j in range(1					, len_destination_seq + 1						):
																					if source_seq[i - 1] == destination_seq[j - 1]:
																												lowerCAmelCase__  =   costs[i - 1][j - 1] + copy_cost
																												lowerCAmelCase__  =   F'''C{source_seq[i - 1]:c}'''
																					else:
																												lowerCAmelCase__  =   costs[i - 1][j - 1] + replace_cost
																												lowerCAmelCase__  =   F'''R{source_seq[i - 1]:c}''' + str(destination_seq[j - 1]						)

																					if costs[i - 1][j] + delete_cost < costs[i][j]:
																												lowerCAmelCase__  =   costs[i - 1][j] + delete_cost
																												lowerCAmelCase__  =   F'''D{source_seq[i - 1]:c}'''

																					if costs[i][j - 1] + insert_cost < costs[i][j]:
																												lowerCAmelCase__  =   costs[i][j - 1] + insert_cost
																												lowerCAmelCase__  =   F'''I{destination_seq[j - 1]:c}'''

							return costs, ops
def 			_lowerCAmelCase(      UpperCAmelCase_      :	list[list[str]]					, UpperCAmelCase_      :	int					, UpperCAmelCase_      :	int						) ->							list[str]:
							if i == 0 and j == 0:
														return []
							else:
														if ops[i][j][0] == "C" or ops[i][j][0] == "R":
																					lowerCAmelCase__  =   assemble_transformation(UpperCAmelCase_					, i - 1					, j - 1						)
																					seq.append(ops[i][j]						)
																					return seq
														elif ops[i][j][0] == "D":
																					lowerCAmelCase__  =   assemble_transformation(UpperCAmelCase_					, i - 1					, UpperCAmelCase_						)
																					seq.append(ops[i][j]						)
																					return seq
														else:
																					lowerCAmelCase__  =   assemble_transformation(UpperCAmelCase_					, UpperCAmelCase_					, j - 1						)
																					seq.append(ops[i][j]						)
																					return seq


if __name__ == "__main__":
		_UpperCamelCase						, _UpperCamelCase  						=			compute_transform_tables("""Python""", """Algorithms""", -1, 1, 2, 2)

		_UpperCamelCase  						=			len(operations)
		_UpperCamelCase  						=			len(operations[0])
		_UpperCamelCase  						=			assemble_transformation(operations, m - 1, n - 1)

		_UpperCamelCase  						=			list("""Python""")
		_UpperCamelCase  						=			0
		_UpperCamelCase  						=			0

		with open("""min_cost.txt""", """w""") as file:
				for op in sequence:
						print("""""".join(string))

						if op[0] == "C":
								file.write("""%-16s""" % """Copy %c""" % op[1])
								file.write("""\t\t\t""" + """""".join(string))
								file.write("""\r\n""")

								cost -= 1
						elif op[0] == "R":
								_UpperCamelCase  						=			op[2]

								file.write("""%-16s""" % ("""Replace %c""" % op[1] + """ with """ + str(op[2])))
								file.write("""\t\t""" + """""".join(string))
								file.write("""\r\n""")

								cost += 1
						elif op[0] == "D":
								string.pop(i)

								file.write("""%-16s""" % """Delete %c""" % op[1])
								file.write("""\t\t\t""" + """""".join(string))
								file.write("""\r\n""")

								cost += 2
						else:
								string.insert(i, op[1])

								file.write("""%-16s""" % """Insert %c""" % op[1])
								file.write("""\t\t\t""" + """""".join(string))
								file.write("""\r\n""")

								cost += 2

						i += 1

				print("""""".join(string))
				print("""Cost: """, cost)

				file.write("""\r\nMinimum cost: """ + str(cost))





