





'''simple docstring'''



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 							__lowercase				(					unittest.TestCase       ,					_A  ):







	'''simple docstring'''

	def   _UpperCAmelCase   (self       )							->							List[str]:







				'''simple docstring'''





				__lowercase   =							load_tool('''translation'''       )
				self.tool.setup()
				__lowercase   =							load_tool('''translation'''   ,remote=snake_case_       )


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







				'''simple docstring'''





				__lowercase   =							self.tool('''Hey, what\'s up?'''   ,src_lang='''English'''   ,tgt_lang='''French'''       )
				self.assertEqual(snake_case_   ,'''- Hé, comment ça va?'''       )


	def   _UpperCAmelCase   (self       )							->							int:







				'''simple docstring'''





				__lowercase   =							self.remote_tool('''Hey, what\'s up?'''   ,src_lang='''English'''   ,tgt_lang='''French'''       )
				self.assertEqual(snake_case_   ,'''- Hé, comment ça va?'''       )


	def   _UpperCAmelCase   (self       )							->							Tuple:







				'''simple docstring'''





				__lowercase   =							self.tool(text='''Hey, what\'s up?'''   ,src_lang='''English'''   ,tgt_lang='''French'''       )
				self.assertEqual(snake_case_   ,'''- Hé, comment ça va?'''       )


	def   _UpperCAmelCase   (self       )							->							List[str]:







				'''simple docstring'''





				__lowercase   =							self.remote_tool(text='''Hey, what\'s up?'''   ,src_lang='''English'''   ,tgt_lang='''French'''       )
				self.assertEqual(snake_case_   ,'''- Hé, comment ça va?'''       )


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







				'''simple docstring'''





				__lowercase   =							["""Hey, what's up?""", """English""", """Spanish"""]
				__lowercase   =							self.tool(*snake_case_       )

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

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


	def   _UpperCAmelCase   (self       )							->							List[str]:







				'''simple docstring'''





				__lowercase   =							["""Hey, what's up?""", """English""", """Spanish"""]
				__lowercase   =							self.tool(*snake_case_       )

				if not isinstance(snake_case_   ,snake_case_       ):
							__lowercase   =							[outputs]

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

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


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







				'''simple docstring'''





				__lowercase   =							["""Hey, what's up?""", """English""", """Spanish"""]

				__lowercase   =							[]

				for _input, input_type in zip(snake_case_   ,self.tool.inputs       ):
							if isinstance(snake_case_   ,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
				__lowercase   =							self.tool(*snake_case_       )

				if not isinstance(snake_case_   ,snake_case_       ):
							__lowercase   =							[outputs]

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







import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


lowerCamelCase_  :       List[Any]					      =     logging.get_logger(__name__)

class 				_UpperCamelCase (    _A     ):






			'''simple docstring'''

			def __init__(				self       :				Dict  ,		*snake_case_       :				Optional[int]  ,		**snake_case_       :				List[Any]					):
							warnings.warn(
							    """The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
							    """ Please use MobileNetV2ImageProcessor instead."""  ,		snake_case_  ,		)
							super().__init__(*snake_case_  ,		**snake_case_					)






