code: 
  
  
  
  
  
  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			,__UpperCAmelCase):
  
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  
  
  							def 						lowercase__     (   self		):
  
  
  
  
  
  
  
  													"""simple docstring"""
  
  
  													a_					=		load_tool("""translation"""		)
  													self.tool.setup()
  													a_					=		load_tool("""translation"""			,    remote=lowercase_		)
  
  
  							def 						lowercase__     (   self		):
  
  
  
  
  
  
  
  													"""simple docstring"""
  
  
  													a_					=		self.tool("""Hey, what\'s up?"""			,    src_lang="""English"""			,    tgt_lang="""French"""		)
  													self.assertEqual(lowercase_			,    """- Hé, comment ça va?"""		)
  
  
  							def 						lowercase__     (   self		):
  
  
  
  
  
  
  
  													"""simple docstring"""
  
  
  													a_					=		self.remote_tool("""Hey, what\'s up?"""			,    src_lang="""English"""			,    tgt_lang="""French"""		)
  													self.assertEqual(lowercase_			,    """- Hé, comment ça va?"""		)
  
  
  							def 						lowercase__     (   self		):
  
  
  
  
  
  
  
  													"""simple docstring"""
  
  
  													a_					=		self.tool(text="""Hey, what\'s up?"""			,    src_lang="""English"""			,    tgt_lang="""French"""		)
  													self.assertEqual(lowercase_			,    """- Hé, comment ça va?"""		)
  
  
  							def 						lowercase__     (   self		):
  
  
  
  
  
  
  
  													"""simple docstring"""
  
  
  													a_					=		self.remote_tool(text="""Hey, what\'s up?"""			,    src_lang="""English"""			,    tgt_lang="""French"""		)
  													self.assertEqual(lowercase_			,    """- Hé, comment ça va?"""		)
  
  
  							def 						lowercase__     (   self		):
  
  
  
  
  
  
  
  													"""simple docstring"""
  
  
  													a_					=		['''Hey, what\'s up?''', '''English''', '''Spanish''']
  													a_					=		self.tool(*lowercase_		)
  
  													# There is a single output
  													if len(self.tool.outputs		) == 1:
  																			a_					=		[outputs]
  
  													self.assertListEqual(output_types(lowercase_		)			,    self.tool.outputs		)
  
  
  							def 						lowercase__     (   self		):
  
  
  
  
  
  
  
  													"""simple docstring"""
  
  
  													a_					=		['''Hey, what\'s up?''', '''English''', '''Spanish''']
  													a_					=		self.tool(*lowercase_		)
  
  													if not isinstance(lowercase_			,    lowercase_		):
  																			a_					=		[outputs]
  
  													self.assertEqual(len(lowercase_		)			,    len(self.tool.outputs		)		)
  
  													for output, output_type in zip(lowercase_			,    self.tool.outputs		):
  																			a_					=		AGENT_TYPE_MAPPING[output_type]
  																			self.assertTrue(isinstance(lowercase_			,    lowercase_		)		)
  
  
  
  
  
  
  							def 						lowercase__     (   self		):
  
  
  
  
  
  
  
  													"""simple docstring"""
  
  
  													a_					=		['''Hey, what\'s up?''', '''English''', '''Spanish''']
  
  													a_					=		[]
  
  													for _input, input_type in zip(lowercase_			,    self.tool.inputs		):
  																			if isinstance(lowercase_			,    lowercase_		):
  																									_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_					=		self.tool(*lowercase_		)
  
  													if not isinstance(lowercase_			,    lowercase_		):
  																			a_					=		[outputs]
  
  													self.assertEqual(len(lowercase_		)			,    len(self.tool.outputs		)		)
style_context: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
  
  
  A_    :					Optional[Any]             ={
      """configuration_wav2vec2_conformer""": [
          """WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
          """Wav2Vec2ConformerConfig""",
      ],
  }
  
  
  try:
  	if not is_torch_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	A_    :					Union[str, Any]             =[
  	    """WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
  	    """Wav2Vec2ConformerForAudioFrameClassification""",
  	    """Wav2Vec2ConformerForCTC""",
  	    """Wav2Vec2ConformerForPreTraining""",
  	    """Wav2Vec2ConformerForSequenceClassification""",
  	    """Wav2Vec2ConformerForXVector""",
  	    """Wav2Vec2ConformerModel""",
  	    """Wav2Vec2ConformerPreTrainedModel""",
  	]
  
  if TYPE_CHECKING:
  	from .configuration_wavaveca_conformer import (
  	    WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
  	    WavaVecaConformerConfig,
  	)
  
  	try:
  		if not is_torch_available():
  			raise OptionalDependencyNotAvailable()
  	except OptionalDependencyNotAvailable:
  		pass
  	else:
  		from .modeling_wavaveca_conformer import (
  		    WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
  		    WavaVecaConformerForAudioFrameClassification,
  		    WavaVecaConformerForCTC,
  		    WavaVecaConformerForPreTraining,
  		    WavaVecaConformerForSequenceClassification,
  		    WavaVecaConformerForXVector,
  		    WavaVecaConformerModel,
  		    WavaVecaConformerPreTrainedModel,
  		)
  
  else:
  	import sys
  
  	A_    :					Union[str, Any]             =_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)