

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							,     snake_case__ ):


     def   UpperCAmelCase  (							self      :		List[Any] )							->     int:
      __lowerCAmelCase:       Dict            =				load_tool('translation' )
      self.tool.setup()
      __lowerCAmelCase:       str            =				load_tool('translation'      ,  remote=UpperCAmelCase )


     def   UpperCAmelCase  (							self      :		str )							->     Tuple:
      __lowerCAmelCase:       Optional[int]            =				self.tool('Hey, what\'s up?'      ,  src_lang='English'      ,  tgt_lang='French' )
      self.assertEqual(UpperCAmelCase      ,  '- Hé, comment ça va?' )


     def   UpperCAmelCase  (							self      :		int )							->     Union[str, Any]:
      __lowerCAmelCase:       Any            =				self.remote_tool('Hey, what\'s up?'      ,  src_lang='English'      ,  tgt_lang='French' )
      self.assertEqual(UpperCAmelCase      ,  '- Hé, comment ça va?' )


     def   UpperCAmelCase  (							self      :		List[str] )							->     Dict:
      __lowerCAmelCase:       int            =				self.tool(text='Hey, what\'s up?'      ,  src_lang='English'      ,  tgt_lang='French' )
      self.assertEqual(UpperCAmelCase      ,  '- Hé, comment ça va?' )


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


     def   UpperCAmelCase  (							self      :		int )							->     Tuple:
      __lowerCAmelCase:       Tuple            =				['Hey, what\'s up?', 'English', 'Spanish']
      __lowerCAmelCase:       Union[str, Any]            =				self.tool(*UpperCAmelCase )

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

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


     def   UpperCAmelCase  (							self      :		List[Any] )							->     List[Any]:
      __lowerCAmelCase:       List[str]            =				['Hey, what\'s up?', 'English', 'Spanish']
      __lowerCAmelCase:       str            =				self.tool(*UpperCAmelCase )

      if not isinstance(UpperCAmelCase      ,  UpperCAmelCase ):
       __lowerCAmelCase:       Optional[Any]            =				[outputs]

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

      for output, output_type in zip(UpperCAmelCase      ,  self.tool.outputs ):
       __lowerCAmelCase:       List[Any]            =				AGENT_TYPE_MAPPING[output_type]
       self.assertTrue(isinstance(UpperCAmelCase      ,  UpperCAmelCase ) )


     def   UpperCAmelCase  (							self      :		Any )							->     Union[str, Any]:
      __lowerCAmelCase:       Union[str, Any]            =				['Hey, what\'s up?', 'English', 'Spanish']

      __lowerCAmelCase:       Optional[int]            =				[]

      for _input, input_type in zip(UpperCAmelCase      ,  self.tool.inputs ):
       if isinstance(UpperCAmelCase      ,  UpperCAmelCase ):
        _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
      __lowerCAmelCase:       str            =				self.tool(*UpperCAmelCase )

      if not isinstance(UpperCAmelCase      ,  UpperCAmelCase ):
       __lowerCAmelCase:       Union[str, Any]            =				[outputs]

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








import torch

from transformers import PreTrainedModel

from .custom_configuration import CustomConfig, NoSuperInitConfig






class 							A_			(		snake_case__ ):
     _lowercase      :					Any       =     CustomConfig


     def __init__(							self      :		List[Any]      ,  UpperCAmelCase      :		Optional[Any] )							->     int:
      super().__init__(UpperCAmelCase )
      __lowerCAmelCase:       Tuple            =				torch.nn.Linear(config.hidden_size      ,  config.hidden_size )


     def   UpperCAmelCase  (							self      :		Optional[int]      ,  UpperCAmelCase      :		Tuple )							->     Union[str, Any]:
      return self.linear(UpperCAmelCase )


     def   UpperCAmelCase  (							self      :		str      ,  UpperCAmelCase      :		str )							->     Optional[int]:
      pass







class 							A_			(		snake_case__ ):
     _lowercase      :					str       =     NoSuperInitConfig


     def __init__(							self      :		List[Any]      ,  UpperCAmelCase      :		Union[str, Any] )							->     int:
      super().__init__(UpperCAmelCase )
      __lowerCAmelCase:       int            =				torch.nn.Linear(config.attribute      ,  config.attribute )


     def   UpperCAmelCase  (							self      :		Tuple      ,  UpperCAmelCase      :		Tuple )							->     Tuple:
      return self.linear(UpperCAmelCase )


     def   UpperCAmelCase  (							self      :		Optional[Any]      ,  UpperCAmelCase      :		Any )							->     str:
      pass





