



import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


_UpperCAmelCase     =			pytest.mark.integration





@pytest.mark.parametrize("""path"""							,			["""paws""", """csv"""] )
def      __magic_name__				(							lowercase							,			lowercase ):
   inspect_dataset(lowercase							,			lowercase )
   SCREAMING_SNAKE_CASE_: List[str]     			=path + """.py"""
   assert script_name in os.listdir(lowercase )
   assert "__pycache__" not in os.listdir(lowercase )





@pytest.mark.filterwarnings("""ignore:inspect_metric is deprecated:FutureWarning""" )
@pytest.mark.filterwarnings("""ignore:metric_module_factory is deprecated:FutureWarning""" )
@pytest.mark.parametrize("""path"""							,			["""accuracy"""] )
def      __magic_name__				(							lowercase							,			lowercase ):
   inspect_metric(lowercase							,			lowercase )
   SCREAMING_SNAKE_CASE_: str     			=path + """.py"""
   assert script_name in os.listdir(lowercase )
   assert "__pycache__" not in os.listdir(lowercase )





@pytest.mark.parametrize(
    """path, config_name, expected_splits"""							,			[
        ("""squad""", """plain_text""", ["""train""", """validation"""]),
        ("""dalle-mini/wit""", """dalle-mini--wit""", ["""train"""]),
        ("""paws""", """labeled_final""", ["""train""", """test""", """validation"""]),
    ]							,			)
def      __magic_name__				(							lowercase							,			lowercase							,			lowercase ):
   SCREAMING_SNAKE_CASE_: Optional[Any]     			=get_dataset_config_info(lowercase							,			config_name=lowercase )
   assert info.config_name == config_name
   assert list(info.splits.keys() ) == expected_splits





@pytest.mark.parametrize(
    """path, config_name, expected_exception"""							,			[
        ("""paws""", None, ValueError),
    ]							,			)
def      __magic_name__				(							lowercase							,			lowercase							,			lowercase ):
   with pytest.raises(lowercase ):
      get_dataset_config_info(lowercase							,			config_name=lowercase )





@pytest.mark.parametrize(
    """path, expected"""							,			[
        ("""squad""", """plain_text"""),
        ("""acronym_identification""", """default"""),
        ("""lhoestq/squad""", """plain_text"""),
        ("""lhoestq/test""", """default"""),
        ("""lhoestq/demo1""", """lhoestq--demo1"""),
        ("""dalle-mini/wit""", """dalle-mini--wit"""),
    ]							,			)
def      __magic_name__				(							lowercase							,			lowercase ):
   SCREAMING_SNAKE_CASE_: Any     			=get_dataset_config_names(lowercase )
   assert expected in config_names





@pytest.mark.parametrize(
    """path, expected_configs, expected_splits_in_first_config"""							,			[
        ("""squad""", ["""plain_text"""], ["""train""", """validation"""]),
        ("""dalle-mini/wit""", ["""dalle-mini--wit"""], ["""train"""]),
        ("""paws""", ["""labeled_final""", """labeled_swap""", """unlabeled_final"""], ["""train""", """test""", """validation"""]),
    ]							,			)
def      __magic_name__				(							lowercase							,			lowercase							,			lowercase ):
   SCREAMING_SNAKE_CASE_: List[Any]     			=get_dataset_infos(lowercase )
   assert list(infos.keys() ) == expected_configs
   SCREAMING_SNAKE_CASE_: Dict     			=expected_configs[0]
   assert expected_config in infos
   SCREAMING_SNAKE_CASE_: List[str]     			=infos[expected_config]
   assert info.config_name == expected_config
   assert list(info.splits.keys() ) == expected_splits_in_first_config





@pytest.mark.parametrize(
    """path, expected_config, expected_splits"""							,			[
        ("""squad""", """plain_text""", ["""train""", """validation"""]),
        ("""dalle-mini/wit""", """dalle-mini--wit""", ["""train"""]),
        ("""paws""", """labeled_final""", ["""train""", """test""", """validation"""]),
    ]							,			)
def      __magic_name__				(							lowercase							,			lowercase							,			lowercase ):
   SCREAMING_SNAKE_CASE_: Optional[int]     			=get_dataset_infos(lowercase )
   assert expected_config in infos
   SCREAMING_SNAKE_CASE_: Optional[int]     			=infos[expected_config]
   assert info.config_name == expected_config
   assert list(info.splits.keys() ) == expected_splits





@pytest.mark.parametrize(
    """path, config_name, expected_exception"""							,			[
        ("""paws""", None, ValueError),
    ]							,			)
def      __magic_name__				(							lowercase							,			lowercase							,			lowercase ):
   with pytest.raises(lowercase ):
      get_dataset_split_names(lowercase							,			config_name=lowercase )








"""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


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





def      __magic_name__				(							lowercase ):
   SCREAMING_SNAKE_CASE_: str     			=[]

   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(3000 ) )
      elif isinstance(lowercase							,			lowercase ):
         inputs.append(create_inputs(lowercase ) )
      else:
         raise ValueError(f'''Invalid type requested: {input_type}''' )

   return inputs





def      __magic_name__				(							lowercase ):
   SCREAMING_SNAKE_CASE_: int     			=[]

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

   return output_types
@is_tool_test
class 					a	:



  def 	lowerCamelCase__       (						self :					Tuple		)     ->					List[Any]:


     '''simple docstring'''




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

     SCREAMING_SNAKE_CASE_: Optional[int]     			=self.tool.inputs
     for _input in inputs:
        if isinstance(_input       ,		lowerCAmelCase		):
           for __input in _input:
              self.assertTrue(__input in authorized_types		)
        else:
           self.assertTrue(_input in authorized_types		)

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



  def 	lowerCamelCase__       (						self :					str		)     ->					List[Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Dict     			=create_inputs(self.tool.inputs		)
     SCREAMING_SNAKE_CASE_: List[Any]     			=self.tool(*lowerCAmelCase		)

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

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



  def 	lowerCamelCase__       (						self :					str		)     ->					Optional[Any]:


     '''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 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					List[Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: str     			=create_inputs(self.tool.inputs		)
     SCREAMING_SNAKE_CASE_: Tuple     			=self.tool(*lowerCAmelCase		)

     if not isinstance(lowerCAmelCase       ,		lowerCAmelCase		):
        SCREAMING_SNAKE_CASE_: int     			=[outputs]

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

     for output, output_type in zip(lowerCAmelCase       ,		self.tool.outputs		):
        SCREAMING_SNAKE_CASE_: int     			=AGENT_TYPE_MAPPING[output_type]
        self.assertTrue(isinstance(lowerCAmelCase       ,		lowerCAmelCase		)		)





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


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Tuple     			=create_inputs(self.tool.inputs		)

     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=[]

     for _input, input_type in zip(lowerCAmelCase       ,		self.tool.inputs		):
        if isinstance(lowerCAmelCase       ,		lowerCAmelCase		):
           _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
     SCREAMING_SNAKE_CASE_: Dict     			=self.tool(*lowerCAmelCase		)

     if not isinstance(lowerCAmelCase       ,		lowerCAmelCase		):
        SCREAMING_SNAKE_CASE_: List[str]     			=[outputs]

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



