



from pathlib import Path
from typing import List

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText


if is_torch_available():
     import torch

if is_vision_available():
     from PIL import Image


SCREAMING_SNAKE_CASE_:Tuple             =						["""text""", """image""", """audio"""]




def 	__UpperCamelCase	(  _lowerCAmelCase		)       ->  List[Any]:



    """simple docstring"""






    A :       List[Any]          =   []

    for input_type in input_types:
        if input_type == "text":
            inputs.append("""Text input"""		)
        elif input_type == "image":
            inputs.append(
                Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""		)		) / """000000039769.png"""		).resize((512, 512)		)		)
        elif input_type == "audio":
            inputs.append(torch.ones(3000		)		)
        elif isinstance(_lowerCAmelCase      ,     _lowerCAmelCase		):
            inputs.append(create_inputs(_lowerCAmelCase		)		)
        else:
            raise ValueError(f'''Invalid type requested: {input_type}'''		)

    return inputs




def 	__UpperCamelCase	(  _lowerCAmelCase		)       ->  str:



    """simple docstring"""






    A :       int          =   []

    for output in outputs:
        if isinstance(_lowerCAmelCase      ,     (str, AgentText)		):
            output_types.append("""text"""		)
        elif isinstance(_lowerCAmelCase      ,     (Image.Image, AgentImage)		):
            output_types.append("""image"""		)
        elif isinstance(_lowerCAmelCase      ,     (torch.Tensor, AgentAudio)		):
            output_types.append("""audio"""		)
        else:
            raise ValueError(f'''Invalid output: {output}'''		)

    return output_types






@is_tool_test
class SCREAMING_SNAKE_CASE__     :




    '''simple docstring'''






    def 			_lowerCAmelCase					(       self		):
        self.assertTrue(hasattr(self.tool,		"""inputs"""		)		)
        self.assertTrue(hasattr(self.tool,		"""outputs"""		)		)

        A :       Union[str, Any]          =   self.tool.inputs
        for _input in inputs:
            if isinstance(_input,		lowerCamelCase__		):
                for __input in _input:
                    self.assertTrue(__input in authorized_types		)
            else:
                self.assertTrue(_input in authorized_types		)

        A :       Union[str, Any]          =   self.tool.outputs
        for _output in outputs:
            self.assertTrue(_output in authorized_types		)






    def 			_lowerCAmelCase					(       self		):
        A :       Dict          =   create_inputs(self.tool.inputs		)
        A :       str          =   self.tool(*lowerCamelCase__		)

        # There is a single output
        if len(self.tool.outputs		) == 1:
            A :       Optional[int]          =   [outputs]

        self.assertListEqual(output_types(lowerCamelCase__		),		self.tool.outputs		)






    def 			_lowerCAmelCase					(       self		):
        self.assertTrue(hasattr(self.tool,		"""description"""		)		)
        self.assertTrue(hasattr(self.tool,		"""default_checkpoint"""		)		)
        self.assertTrue(self.tool.description.startswith("""This is a tool that"""		)		)






    def 			_lowerCAmelCase					(       self		):
        A :       Union[str, Any]          =   create_inputs(self.tool.inputs		)
        A :       str          =   self.tool(*lowerCamelCase__		)

        if not isinstance(lowerCamelCase__,		lowerCamelCase__		):
            A :       str          =   [outputs]

        self.assertEqual(len(lowerCamelCase__		),		len(self.tool.outputs		)		)

        for output, output_type in zip(lowerCamelCase__,		self.tool.outputs		):
            A :       Optional[Any]          =   AGENT_TYPE_MAPPING[output_type]
            self.assertTrue(isinstance(lowerCamelCase__,		lowerCamelCase__		)		)






    def 			_lowerCAmelCase					(       self		):
        A :       int          =   create_inputs(self.tool.inputs		)

        A :       Union[str, Any]          =   []

        for _input, input_type in zip(lowerCamelCase__,		self.tool.inputs		):
            if isinstance(lowerCamelCase__,		lowerCamelCase__		):
                _inputs.append([AGENT_TYPE_MAPPING[_input_type](_input		) for _input_type in input_type]		)
            else:
                _inputs.append(AGENT_TYPE_MAPPING[input_type](_input		)		)

        # Should not raise an error
        A :       Optional[Any]          =   self.tool(*lowerCamelCase__		)

        if not isinstance(lowerCamelCase__,		lowerCamelCase__		):
            A :       Optional[int]          =   [outputs]

        self.assertEqual(len(lowerCamelCase__		),		len(self.tool.outputs		)		)







from ..utils import DummyObject, requires_backends






class SCREAMING_SNAKE_CASE__     (		metaclass=SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






    __lowerCamelCase			: List[str]					=      ["torch", "transformers", "onnx"]






    def __init__(       self,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(self,		["""torch""", """transformers""", """onnx"""]		)






    @classmethod
    def 			_lowerCAmelCase					(       cls,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(cls,		["""torch""", """transformers""", """onnx"""]		)






    @classmethod
    def 			_lowerCAmelCase					(       cls,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(cls,		["""torch""", """transformers""", """onnx"""]		)






class SCREAMING_SNAKE_CASE__     (		metaclass=SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






    __lowerCamelCase			: Dict					=      ["torch", "transformers", "onnx"]






    def __init__(       self,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(self,		["""torch""", """transformers""", """onnx"""]		)






    @classmethod
    def 			_lowerCAmelCase					(       cls,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(cls,		["""torch""", """transformers""", """onnx"""]		)






    @classmethod
    def 			_lowerCAmelCase					(       cls,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(cls,		["""torch""", """transformers""", """onnx"""]		)






class SCREAMING_SNAKE_CASE__     (		metaclass=SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






    __lowerCamelCase			: Any					=      ["torch", "transformers", "onnx"]






    def __init__(       self,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(self,		["""torch""", """transformers""", """onnx"""]		)






    @classmethod
    def 			_lowerCAmelCase					(       cls,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(cls,		["""torch""", """transformers""", """onnx"""]		)






    @classmethod
    def 			_lowerCAmelCase					(       cls,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(cls,		["""torch""", """transformers""", """onnx"""]		)






class SCREAMING_SNAKE_CASE__     (		metaclass=SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






    __lowerCamelCase			: Optional[int]					=      ["torch", "transformers", "onnx"]






    def __init__(       self,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(self,		["""torch""", """transformers""", """onnx"""]		)






    @classmethod
    def 			_lowerCAmelCase					(       cls,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(cls,		["""torch""", """transformers""", """onnx"""]		)






    @classmethod
    def 			_lowerCAmelCase					(       cls,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(cls,		["""torch""", """transformers""", """onnx"""]		)






class SCREAMING_SNAKE_CASE__     (		metaclass=SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






    __lowerCamelCase			: Optional[int]					=      ["torch", "transformers", "onnx"]






    def __init__(       self,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(self,		["""torch""", """transformers""", """onnx"""]		)






    @classmethod
    def 			_lowerCAmelCase					(       cls,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(cls,		["""torch""", """transformers""", """onnx"""]		)






    @classmethod
    def 			_lowerCAmelCase					(       cls,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(cls,		["""torch""", """transformers""", """onnx"""]		)






class SCREAMING_SNAKE_CASE__     (		metaclass=SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






    __lowerCamelCase			: Optional[int]					=      ["torch", "transformers", "onnx"]






    def __init__(       self,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(self,		["""torch""", """transformers""", """onnx"""]		)






    @classmethod
    def 			_lowerCAmelCase					(       cls,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(cls,		["""torch""", """transformers""", """onnx"""]		)






    @classmethod
    def 			_lowerCAmelCase					(       cls,		*lowerCamelCase__,		**lowerCamelCase__		):
        requires_backends(cls,		["""torch""", """transformers""", """onnx"""]		)


