



'''simple docstring'''





from pathlib import Path
from typing import List

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText


if is_torch_available():
  import torch

if is_vision_available():
  from PIL import Image


lowercase_	 =						["text", "image", "audio"]




def lowerCAmelCase						(__A       ):



     """simple docstring"""



     _a											=						[]

     for input_type in input_types:
          if input_type == "text":
               inputs.append('''Text input'''       )
          elif input_type == "image":
               inputs.append(
                   Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''       )       ) / '''000000039769.png'''       ).resize((512, 512)       )       )
          elif input_type == "audio":
               inputs.append(torch.ones(3_000       )       )
          elif isinstance(__snake_case						,			__snake_case       ):
               inputs.append(create_inputs(__snake_case       )       )
          else:
               raise ValueError(F'''Invalid type requested: {input_type}'''       )

     return inputs




def lowerCAmelCase						(__A       ):



     """simple docstring"""



     _a											=						[]

     for output in outputs:
          if isinstance(__snake_case						,			(str, AgentText)       ):
               output_types.append('''text'''       )
          elif isinstance(__snake_case						,			(Image.Image, AgentImage)       ):
               output_types.append('''image'''       )
          elif isinstance(__snake_case						,			(torch.Tensor, AgentAudio)       ):
               output_types.append('''audio'''       )
          else:
               raise ValueError(F'''Invalid output: {output}'''       )

     return output_types






@is_tool_test
class __A    :



 '''simple docstring'''







 def       a__						(self )					->  Any:


      """simple docstring"""



      self.assertTrue(hasattr(self.tool				,     '''inputs''' ) )
      self.assertTrue(hasattr(self.tool				,     '''outputs''' ) )

      _a											=						self.tool.inputs
      for _input in inputs:
           if isinstance(_input				,     __a ):
                for __input in _input:
                     self.assertTrue(__input in authorized_types )
           else:
                self.assertTrue(_input in authorized_types )

      _a											=						self.tool.outputs
      for _output in outputs:
           self.assertTrue(_output in authorized_types )



 def       a__						(self )					->  str:


      """simple docstring"""



      _a											=						create_inputs(self.tool.inputs )
      _a											=						self.tool(*__a )

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

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



 def       a__						(self )					->  int:


      """simple docstring"""



      self.assertTrue(hasattr(self.tool				,     '''description''' ) )
      self.assertTrue(hasattr(self.tool				,     '''default_checkpoint''' ) )
      self.assertTrue(self.tool.description.startswith('''This is a tool that''' ) )



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


      """simple docstring"""



      _a											=						create_inputs(self.tool.inputs )
      _a											=						self.tool(*__a )

      if not isinstance(__a				,     __a ):
           _a											=						[outputs]

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

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



 def       a__						(self )					->  str:


      """simple docstring"""



      _a											=						create_inputs(self.tool.inputs )

      _a											=						[]

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

      if not isinstance(__a				,     __a ):
           _a											=						[outputs]

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








'''simple docstring'''





import pytest

import datasets


# Import fixture modules as plugins
lowercase_	 =						["tests.fixtures.files", "tests.fixtures.hub", "tests.fixtures.fsspec"]




def lowerCAmelCase						(__A						,			__A):



     """simple docstring"""



     for item in items:
          if any(marker in item.keywords for marker in ['''integration''', '''unit''']):
               continue
          item.add_marker(pytest.mark.unit)




def lowerCAmelCase						(__A):



     """simple docstring"""



     config.addinivalue_line('''markers'''						,			'''torchaudio_latest: mark test to run with torchaudio>=0.12''')




@pytest.fixture(autouse=__A)
def lowerCAmelCase						(__A						,			__A):



     """simple docstring"""



     _a											=						tmp_path_factory.getbasetemp() / '''cache'''
     _a											=						test_hf_cache_home / '''datasets'''
     _a											=						test_hf_cache_home / '''metrics'''
     _a											=						test_hf_cache_home / '''modules'''
     monkeypatch.setattr('''datasets.config.HF_DATASETS_CACHE'''						,			str(__A))
     monkeypatch.setattr('''datasets.config.HF_METRICS_CACHE'''						,			str(__A))
     monkeypatch.setattr('''datasets.config.HF_MODULES_CACHE'''						,			str(__A))
     _a											=						test_hf_datasets_cache / '''downloads'''
     monkeypatch.setattr('''datasets.config.DOWNLOADED_DATASETS_PATH'''						,			str(__A))
     _a											=						test_hf_datasets_cache / '''downloads''' / '''extracted'''
     monkeypatch.setattr('''datasets.config.EXTRACTED_DATASETS_PATH'''						,			str(__A))




@pytest.fixture(autouse=__A						,			scope='''session''')
def lowerCAmelCase						():



     """simple docstring"""



     datasets.disable_progress_bar()




@pytest.fixture(autouse=__A)
def lowerCAmelCase						(__A):



     """simple docstring"""



     monkeypatch.setattr('''datasets.config.HF_UPDATE_DOWNLOAD_COUNTS'''						,			__A)




@pytest.fixture
def lowerCAmelCase						(__A):



     """simple docstring"""



     monkeypatch.setattr('''sqlalchemy.util.deprecations.SILENCE_UBER_WARNING'''						,			__A)



