



'''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


SCREAMING_SNAKE_CASE__     : str				=   logging.get_logger(__name__)

if is_vision_available():
							import PIL.Image
							from PIL import Image
							from PIL.Image import Image as ImageType
else:
							SCREAMING_SNAKE_CASE__     : Optional[int]				=   object

if is_torch_available():
							import torch

if is_soundfile_availble():
							import soundfile as sf




class 				__lowerCAmelCase:






			def __init__(   self  :							int      ,       SCREAMING_SNAKE_CASE  :							Any	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Optional[Any]										=      value






			def __str__(   self  :							Optional[Any]	):




					"""simple docstring"""







					return self.to_string()






			def 				_lowercase	(   self  :							Dict	):




					"""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  :							Dict	):




					"""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__      ):






			def 				_lowercase	(   self  :							Union[str, Any]	):




					"""simple docstring"""







					return self._value






			def 				_lowercase	(   self  :							int	):




					"""simple docstring"""







					return self._value




class 				__lowerCAmelCase(							a__		,			a__      ):






			def __init__(   self  :							Tuple      ,       SCREAMING_SNAKE_CASE  :							Dict	):




					"""simple docstring"""







					super().__init__(UpperCamelCase_	)

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

					SCREAMING_SNAKE_CASE_						:List[str]										=      None
					SCREAMING_SNAKE_CASE_						:str										=      None
					SCREAMING_SNAKE_CASE_						:Tuple										=      None

					if isinstance(UpperCamelCase_      ,       UpperCamelCase_	):
							SCREAMING_SNAKE_CASE_						:List[Any]										=      value
					elif isinstance(UpperCamelCase_      ,       (str, pathlib.Path)	):
							SCREAMING_SNAKE_CASE_						:List[str]										=      value
					elif isinstance(UpperCamelCase_      ,       torch.Tensor	):
							SCREAMING_SNAKE_CASE_						:List[str]										=      value
					else:
							raise ValueError(f'Unsupported type for {self.__class__.__name__}: {type(UpperCamelCase_	)}'	)






			def 				_lowercase	(   self  :							Optional[Any]      ,       SCREAMING_SNAKE_CASE  :							Tuple=None      ,       SCREAMING_SNAKE_CASE  :							Optional[Any]=None	):




					"""simple docstring"""







					from IPython.display import Image, display

					display(Image(self.to_string()	)	)






			def 				_lowercase	(   self  :							Any	):




					"""simple docstring"""







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

					if self._path is not None:
							SCREAMING_SNAKE_CASE_						:List[str]										=      Image.open(self._path	)
							return self._raw






			def 				_lowercase	(   self  :							Tuple	):




					"""simple docstring"""







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

					if self._raw is not None:
							SCREAMING_SNAKE_CASE_						:Tuple										=      tempfile.mkdtemp()
							SCREAMING_SNAKE_CASE_						:Optional[Any]										=      os.path.join(UpperCamelCase_      ,       str(uuid.uuida()	) + '.png'	)
							self._raw.save(self._path	)

							return self._path

					if self._tensor is not None:
							SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      self._tensor.cpu().detach().numpy()

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

							SCREAMING_SNAKE_CASE_						:Any										=      tempfile.mkdtemp()
							SCREAMING_SNAKE_CASE_						:Optional[Any]										=      os.path.join(UpperCamelCase_      ,       str(uuid.uuida()	) + '.png'	)

							img.save(self._path	)

							return self._path




class 				__lowerCAmelCase(							a__      ):






			def __init__(   self  :							Dict      ,       SCREAMING_SNAKE_CASE  :							Optional[Any]      ,       SCREAMING_SNAKE_CASE  :							Union[str, Any]=16_000	):




					"""simple docstring"""







					super().__init__(UpperCamelCase_	)

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

					SCREAMING_SNAKE_CASE_						:Any										=      None
					SCREAMING_SNAKE_CASE_						:str										=      None

					SCREAMING_SNAKE_CASE_						:str										=      samplerate

					if isinstance(UpperCamelCase_      ,       (str, pathlib.Path)	):
							SCREAMING_SNAKE_CASE_						:Dict										=      value
					elif isinstance(UpperCamelCase_      ,       torch.Tensor	):
							SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      value
					else:
							raise ValueError(f'Unsupported audio type: {type(UpperCamelCase_	)}'	)






			def 				_lowercase	(   self  :							Tuple      ,       SCREAMING_SNAKE_CASE  :							str=None      ,       SCREAMING_SNAKE_CASE  :							Dict=None	):




					"""simple docstring"""







					from IPython.display import Audio, display

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






			def 				_lowercase	(   self  :							Dict	):




					"""simple docstring"""







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

					if self._path is not None:
							SCREAMING_SNAKE_CASE_						:List[str]										=      sf.read(self._path	)
							SCREAMING_SNAKE_CASE_						:Tuple										=      torch.tensor(UpperCamelCase_	)
							return self._tensor






			def 				_lowercase	(   self  :							Union[str, Any]	):




					"""simple docstring"""







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

					if self._tensor is not None:
							SCREAMING_SNAKE_CASE_						:Optional[Any]										=      tempfile.mkdtemp()
							SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      os.path.join(UpperCamelCase_      ,       str(uuid.uuida()	) + '.wav'	)
							sf.write(self._path      ,       self._tensor      ,       samplerate=self.samplerate	)
							return self._path


SCREAMING_SNAKE_CASE__     : int				=   {'''text''': AgentText, '''image''': AgentImage, '''audio''': AgentAudio}
SCREAMING_SNAKE_CASE__     : Union[str, Any]				=   {str: AgentText}

if is_vision_available():
							SCREAMING_SNAKE_CASE__     : List[str]				=   AgentImage







def  SCREAMING_SNAKE_CASE__ (				*SCREAMING_SNAKE_CASE ,		**SCREAMING_SNAKE_CASE     ):
		SCREAMING_SNAKE_CASE_						:int										=      [(arg.to_raw() if isinstance(_snake_case ,		_snake_case     ) else arg) for arg in args]
		SCREAMING_SNAKE_CASE_						:int										=      {k: (v.to_raw() if isinstance(_snake_case ,		_snake_case     ) else v) for k, v in kwargs.items()}
		return args, kwargs







def  SCREAMING_SNAKE_CASE__ (				SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE=None     ):
		if isinstance(_snake_case ,		_snake_case     ):
				SCREAMING_SNAKE_CASE_						:int										=      {}
				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:
										SCREAMING_SNAKE_CASE_						:Tuple										=      AGENT_TYPE_MAPPING[output_types[i]](_snake_case     )
								else:
										SCREAMING_SNAKE_CASE_						:Tuple										=      AgentType(_snake_case     )

						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(_snake_case ,		_k     ):
												SCREAMING_SNAKE_CASE_						:Tuple										=      _v(_snake_case     )
								if k not in decoded_outputs:
										SCREAMING_SNAKE_CASE_						:List[str]										=      AgentType[v]

		elif isinstance(_snake_case ,		(list, tuple)     ):
				SCREAMING_SNAKE_CASE_						:List[str]										=      type(_snake_case     )()
				for i, v in enumerate(_snake_case     ):
						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]](_snake_case     )     )
								else:
										decoded_outputs.append(AgentType(_snake_case     )     )
						else:
								# If the class does not have defined output, then we map according to the type
								SCREAMING_SNAKE_CASE_						:Optional[int]										=      False
								for _k, _v in INSTANCE_TYPE_MAPPING.items():
										if isinstance(_snake_case ,		_k     ):
												decoded_outputs.append(_v(_snake_case     )     )
												SCREAMING_SNAKE_CASE_						:Any										=      True

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

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

				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(_snake_case ,		_k     ):
										return _v(_snake_case     )
						return AgentType(_snake_case     )

		return decoded_outputs




"""simple docstring"""





def   _snake_case    (    _snake_case					:      int      ):
      if not isinstance(_snake_case			, _snake_case      ):
            lowerCAmelCase       :						int							= f'''Input value of [number={number}] must be an integer'''
            raise TypeError(_snake_case      )
      if number < 0 or number % 2 == 1:
            return False
      lowerCAmelCase       :						int							= int(number**0.5      )
      return number == number_sqrt * (number_sqrt + 1)


if __name__ == "__main__":
 import doctest

 doctest.testmod()


