

'''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


_lowerCamelCase    =  logging.get_logger(__name__)

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

if is_torch_available():
							import torch

if is_soundfile_availble():
							import soundfile as sf
class 					__a   :

						def __init__(		self	:						Dict    ,			lowercase__	:						Dict)						->Optional[Any]:

							"""simple docstring"""



							_lowercase							=     value

						def __str__(		self	:						Tuple)						->Tuple:

							"""simple docstring"""



							return self.to_string()

						def 	_UpperCAmelCase							(		self	:						int)						->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 	_UpperCAmelCase							(		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 					__a   (		_snake_case							,_snake_case  ):

						def 	_UpperCAmelCase							(		self	:						int)						->Tuple:

							"""simple docstring"""



							return self._value


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

							"""simple docstring"""



							return self._value






class 					__a   (		_snake_case							,_snake_case  ):

						def __init__(		self	:						List[str]    ,			lowercase__	:						Tuple)						->List[str]:

							"""simple docstring"""



							super().__init__(lowercase__)

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

							_lowercase							=     None
							_lowercase							=     None
							_lowercase							=     None

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

						def 	_UpperCAmelCase							(		self	:						Dict    ,			lowercase__	:						str=None    ,			lowercase__	:						Dict=None)						->Optional[int]:

							"""simple docstring"""



							from IPython.display import Image, display

							display(Image(self.to_string()))

						def 	_UpperCAmelCase							(		self	:						Dict)						->Dict:

							"""simple docstring"""



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

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


						def 	_UpperCAmelCase							(		self	:						Optional[int])						->Union[str, Any]:

							"""simple docstring"""



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

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

								return self._path

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

								# There is likely simpler than load into image into save
								_lowercase							=     Image.fromarray((array * 2_55).astype(np.uinta))

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

								img.save(self._path)

								return self._path






class 					__a   (		_snake_case  ):

						def __init__(		self	:						List[Any]    ,			lowercase__	:						List[Any]    ,			lowercase__	:						Tuple=1_60_00)						->int:

							"""simple docstring"""



							super().__init__(lowercase__)

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

							_lowercase							=     None
							_lowercase							=     None

							_lowercase							=     samplerate

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

						def 	_UpperCAmelCase							(		self	:						int    ,			lowercase__	:						List[Any]=None    ,			lowercase__	:						Optional[Any]=None)						->Any:

							"""simple docstring"""



							from IPython.display import Audio, display

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

						def 	_UpperCAmelCase							(		self	:						Dict)						->Any:

							"""simple docstring"""



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

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


						def 	_UpperCAmelCase							(		self	:						Optional[int])						->str:

							"""simple docstring"""



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

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






_lowerCamelCase    =  {'text': AgentText, 'image': AgentImage, 'audio': AgentAudio}
_lowerCamelCase    =  {str: AgentText}

if is_vision_available():
							_lowerCamelCase    =  AgentImage






def 					_SCREAMING_SNAKE_CASE		(						*snake_case_							,       **snake_case_	):
	_lowercase							=     [(arg.to_raw() if isinstance(snake_case_							,       snake_case_	) else arg) for arg in args]
	_lowercase							=     {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		(						snake_case_							,       snake_case_=None	):
	if isinstance(snake_case_							,       snake_case_	):
		_lowercase							=     {}
		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:
					_lowercase							=     AGENT_TYPE_MAPPING[output_types[i]](snake_case_	)
				else:
					_lowercase							=     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	):
						_lowercase							=     _v(snake_case_	)
				if k not in decoded_outputs:
					_lowercase							=     AgentType[v]

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







from collections import namedtuple

_lowerCamelCase    =  namedtuple('from_to', 'from_ to')

_lowerCamelCase    =  {
    'millimeter': 'mm',
    'centimeter': 'cm',
    'meter': 'm',
    'kilometer': 'km',
    'inch': 'in',
    'inche': 'in',  # Trailing 's' has been stripped off
    'feet': 'ft',
    'foot': 'ft',
    'yard': 'yd',
    'mile': 'mi',
}

_lowerCamelCase    =  {
    'mm': from_to(0.001, 1_0_0_0),
    'cm': from_to(0.01, 1_0_0),
    'm': from_to(1, 1),
    'km': from_to(1_0_0_0, 0.001),
    'in': from_to(0.0254, 39.3701),
    'ft': from_to(0.3048, 3.2_8084),
    'yd': from_to(0.9144, 1.0_9361),
    'mi': from_to(1609.34, 0.0_0062_1371),
}






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_							,       snake_case_	):
	_lowercase							=     from_type.lower().rstrip("""s"""	)
	_lowercase							=     TYPE_CONVERSION.get(snake_case_							,       snake_case_	)
	_lowercase							=     to_type.lower().rstrip("""s"""	)
	_lowercase							=     TYPE_CONVERSION.get(snake_case_							,       snake_case_	)
	if new_from not in METRIC_CONVERSION:
		_lowercase							=     (
		    F"""Invalid 'from_type' value: {from_type!r}.\n"""
		    F"""Conversion abbreviations are: {", ".join(snake_case_	)}"""
		)
		raise ValueError(snake_case_	)
	if new_to not in METRIC_CONVERSION:
		_lowercase							=     (
		    F"""Invalid 'to_type' value: {to_type!r}.\n"""
		    F"""Conversion abbreviations are: {", ".join(snake_case_	)}"""
		)
		raise ValueError(snake_case_	)
	return value * METRIC_CONVERSION[new_from].from_ * METRIC_CONVERSION[new_to].to


if __name__ == "__main__":
							import doctest

							doctest.testmod()




