




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        _lowerCamelCase  (	unittest.TestCase							,	_SCREAMING_SNAKE_CASE      ):

      """simple docstring"""

      def 					snake_case		(   self    :       int ):
          __UpperCamelCase     						=  load_tool('''translation''' )
          self.tool.setup()
          __UpperCamelCase     						=  load_tool('''translation'''       ,				remote=snake_case )







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







      def 					snake_case		(   self    :       Dict ):
          __UpperCamelCase     						=  self.remote_tool('''Hey, what\'s up?'''       ,				src_lang='''English'''       ,				tgt_lang='''French''' )
          self.assertEqual(snake_case       ,				'''- Hé, comment ça va?''' )







      def 					snake_case		(   self    :       Union[str, Any] ):
          __UpperCamelCase     						=  self.tool(text='''Hey, what\'s up?'''       ,				src_lang='''English'''       ,				tgt_lang='''French''' )
          self.assertEqual(snake_case       ,				'''- Hé, comment ça va?''' )







      def 					snake_case		(   self    :       str ):
          __UpperCamelCase     						=  self.remote_tool(text='''Hey, what\'s up?'''       ,				src_lang='''English'''       ,				tgt_lang='''French''' )
          self.assertEqual(snake_case       ,				'''- Hé, comment ça va?''' )







      def 					snake_case		(   self    :       Optional[Any] ):
          __UpperCamelCase     						=  ['''Hey, what\'s up?''', '''English''', '''Spanish''']
          __UpperCamelCase     						=  self.tool(*snake_case )

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

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







      def 					snake_case		(   self    :       Optional[Any] ):
          __UpperCamelCase     						=  ['''Hey, what\'s up?''', '''English''', '''Spanish''']
          __UpperCamelCase     						=  self.tool(*snake_case )

          if not isinstance(snake_case       ,				snake_case ):
              __UpperCamelCase     						=  [outputs]

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

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







      def 					snake_case		(   self    :       Dict ):
          __UpperCamelCase     						=  ['''Hey, what\'s up?''', '''English''', '''Spanish''']

          __UpperCamelCase     						=  []

          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
          __UpperCamelCase     						=  self.tool(*snake_case )

          if not isinstance(snake_case       ,				snake_case ):
              __UpperCamelCase     						=  [outputs]

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







'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case__     :			Optional[Any]      			=  {'''configuration_nat''': ['''NAT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NatConfig''']}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__     :			Tuple      			=  [
     '''NAT_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''NatForImageClassification''',
     '''NatModel''',
     '''NatPreTrainedModel''',
     '''NatBackbone''',
 ]

if TYPE_CHECKING:
 from .configuration_nat import NAT_PRETRAINED_CONFIG_ARCHIVE_MAP, NatConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_nat import (
      NAT_PRETRAINED_MODEL_ARCHIVE_LIST,
      NatBackbone,
      NatForImageClassification,
      NatModel,
      NatPreTrainedModel,
  )

else:
 import sys

 snake_case__     :			int      			=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






