


import unittest
from dataclasses import dataclass
from typing import List, Union

import numpy as np
import PIL.Image

from diffusers.utils.outputs import BaseOutput

@dataclass
class 	__a   (       UpperCAmelCase    ):
		_a			:						Union[List[PIL.Image.Image], np.ndarray]



class 	__a   (       unittest.TestCase    ):
		def 			UpperCAmelCase__       (    self		)				-> List[Any]:




									"""simple docstring"""





									_UpperCAmelCase					=    CustomOutput(images=np.random.rand(1    ,					3    ,					4    ,					4		)		)

									# check every way of getting the attribute
									assert isinstance(outputs.images    ,					np.ndarray		)
									assert outputs.images.shape == (1, 3, 4, 4)
									assert isinstance(outputs['images']    ,					np.ndarray		)
									assert outputs["images"].shape == (1, 3, 4, 4)
									assert isinstance(outputs[0]    ,					np.ndarray		)
									assert outputs[0].shape == (1, 3, 4, 4)

									# test with a non-tensor attribute
									_UpperCAmelCase					=    CustomOutput(images=[PIL.Image.new('RGB'    ,					(4, 4)		)]		)

									# check every way of getting the attribute
									assert isinstance(outputs.images    ,					_SCREAMING_SNAKE_CASE		)
									assert isinstance(outputs.images[0]    ,					PIL.Image.Image		)
									assert isinstance(outputs['images']    ,					_SCREAMING_SNAKE_CASE		)
									assert isinstance(outputs['images'][0]    ,					PIL.Image.Image		)
									assert isinstance(outputs[0]    ,					_SCREAMING_SNAKE_CASE		)
									assert isinstance(outputs[0][0]    ,					PIL.Image.Image		)






		def 			UpperCAmelCase__       (    self		)				-> List[Any]:




									"""simple docstring"""





									_UpperCAmelCase					=    CustomOutput({'images': np.random.rand(1    ,					3    ,					4    ,					4		)}		)

									# check every way of getting the attribute
									assert isinstance(outputs.images    ,					np.ndarray		)
									assert outputs.images.shape == (1, 3, 4, 4)
									assert isinstance(outputs['images']    ,					np.ndarray		)
									assert outputs["images"].shape == (1, 3, 4, 4)
									assert isinstance(outputs[0]    ,					np.ndarray		)
									assert outputs[0].shape == (1, 3, 4, 4)

									# test with a non-tensor attribute
									_UpperCAmelCase					=    CustomOutput({'images': [PIL.Image.new('RGB'    ,					(4, 4)		)]}		)

									# check every way of getting the attribute
									assert isinstance(outputs.images    ,					_SCREAMING_SNAKE_CASE		)
									assert isinstance(outputs.images[0]    ,					PIL.Image.Image		)
									assert isinstance(outputs['images']    ,					_SCREAMING_SNAKE_CASE		)
									assert isinstance(outputs['images'][0]    ,					PIL.Image.Image		)
									assert isinstance(outputs[0]    ,					_SCREAMING_SNAKE_CASE		)
									assert isinstance(outputs[0][0]    ,					PIL.Image.Image		)




import unittest

from transformers import load_tool
from transformers.tools.agent_types import AGENT_TYPE_MAPPING

from .test_tools_common import ToolTesterMixin, output_types

class 	__a   (       unittest.TestCase					,   UpperCAmelCase    ):
		def 			UpperCAmelCase__       (    self		)				-> str:




									"""simple docstring"""





									_UpperCAmelCase					=    load_tool('translation'		)
									self.tool.setup()
									_UpperCAmelCase					=    load_tool('translation'    ,					remote=_SCREAMING_SNAKE_CASE		)
		def 			UpperCAmelCase__       (    self		)				-> Optional[int]:




									"""simple docstring"""





									_UpperCAmelCase					=    self.tool('Hey, what\'s up?'    ,					src_lang='English'    ,					tgt_lang='French'		)
									self.assertEqual(_SCREAMING_SNAKE_CASE    ,					'- Hé, comment ça va?'		)
		def 			UpperCAmelCase__       (    self		)				-> Tuple:




									"""simple docstring"""





									_UpperCAmelCase					=    self.remote_tool('Hey, what\'s up?'    ,					src_lang='English'    ,					tgt_lang='French'		)
									self.assertEqual(_SCREAMING_SNAKE_CASE    ,					'- Hé, comment ça va?'		)
		def 			UpperCAmelCase__       (    self		)				-> Optional[int]:




									"""simple docstring"""





									_UpperCAmelCase					=    self.tool(text='Hey, what\'s up?'    ,					src_lang='English'    ,					tgt_lang='French'		)
									self.assertEqual(_SCREAMING_SNAKE_CASE    ,					'- Hé, comment ça va?'		)
		def 			UpperCAmelCase__       (    self		)				-> int:




									"""simple docstring"""





									_UpperCAmelCase					=    self.remote_tool(text='Hey, what\'s up?'    ,					src_lang='English'    ,					tgt_lang='French'		)
									self.assertEqual(_SCREAMING_SNAKE_CASE    ,					'- Hé, comment ça va?'		)
		def 			UpperCAmelCase__       (    self		)				-> Tuple:




									"""simple docstring"""





									_UpperCAmelCase					=    ['Hey, what\'s up?', 'English', 'Spanish']
									_UpperCAmelCase					=    self.tool(*_SCREAMING_SNAKE_CASE		)

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

									self.assertListEqual(output_types(_SCREAMING_SNAKE_CASE		)    ,					self.tool.outputs		)
		def 			UpperCAmelCase__       (    self		)				-> Union[str, Any]:




									"""simple docstring"""





									_UpperCAmelCase					=    ['Hey, what\'s up?', 'English', 'Spanish']
									_UpperCAmelCase					=    self.tool(*_SCREAMING_SNAKE_CASE		)

									if not isinstance(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE		):
																_UpperCAmelCase					=    [outputs]

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

									for output, output_type in zip(_SCREAMING_SNAKE_CASE    ,					self.tool.outputs		):
																_UpperCAmelCase					=    AGENT_TYPE_MAPPING[output_type]
																self.assertTrue(isinstance(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE		)		)






		def 			UpperCAmelCase__       (    self		)				-> Optional[int]:




									"""simple docstring"""





									_UpperCAmelCase					=    ['Hey, what\'s up?', 'English', 'Spanish']

									_UpperCAmelCase					=    []

									for _input, input_type in zip(_SCREAMING_SNAKE_CASE    ,					self.tool.inputs		):
																if isinstance(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE		):
																							_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
									_UpperCAmelCase					=    self.tool(*_SCREAMING_SNAKE_CASE		)

									if not isinstance(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE		):
																_UpperCAmelCase					=    [outputs]

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