"""simple docstring"""



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 SCREAMING_SNAKE_CASE     (    unittest.TestCase   ,      a	):







	"""simple docstring"""


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




				'''simple docstring'''






				a__     				=		load_tool('translation'				)
				self.tool.setup()
				a__     				=		load_tool('translation'					,   remote=_snake_case				)


	def        _lowerCAmelCase				(   self		:      Dict				)				->			Tuple:




				'''simple docstring'''






				a__     				=		self.tool('Hey, what\'s up?'					,   src_lang='English'					,   tgt_lang='French'				)
				self.assertEqual(_snake_case					,   '- Hé, comment ça va?'				)


	def        _lowerCAmelCase				(   self		:      str				)				->			Dict:




				'''simple docstring'''






				a__     				=		self.remote_tool('Hey, what\'s up?'					,   src_lang='English'					,   tgt_lang='French'				)
				self.assertEqual(_snake_case					,   '- Hé, comment ça va?'				)


	def        _lowerCAmelCase				(   self		:      Tuple				)				->			Union[str, Any]:




				'''simple docstring'''






				a__     				=		self.tool(text='Hey, what\'s up?'					,   src_lang='English'					,   tgt_lang='French'				)
				self.assertEqual(_snake_case					,   '- Hé, comment ça va?'				)


	def        _lowerCAmelCase				(   self		:      Tuple				)				->			Any:




				'''simple docstring'''






				a__     				=		self.remote_tool(text='Hey, what\'s up?'					,   src_lang='English'					,   tgt_lang='French'				)
				self.assertEqual(_snake_case					,   '- Hé, comment ça va?'				)


	def        _lowerCAmelCase				(   self		:      Optional[Any]				)				->			int:




				'''simple docstring'''






				a__     				=		['Hey, what\'s up?', 'English', 'Spanish']
				a__     				=		self.tool(*_snake_case				)

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

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


	def        _lowerCAmelCase				(   self		:      Optional[int]				)				->			Union[str, Any]:




				'''simple docstring'''






				a__     				=		['Hey, what\'s up?', 'English', 'Spanish']
				a__     				=		self.tool(*_snake_case				)

				if not isinstance(_snake_case					,   _snake_case				):
							a__     				=		[outputs]

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

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



	def        _lowerCAmelCase				(   self		:      List[Any]				)				->			Optional[Any]:




				'''simple docstring'''






				a__     				=		['Hey, what\'s up?', 'English', 'Spanish']

				a__     				=		[]

				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
				a__     				=		self.tool(*_snake_case				)

				if not isinstance(_snake_case					,   _snake_case				):
							a__     				=		[outputs]

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



"""simple docstring"""



import re
import tempfile
import unittest
from pathlib import Path

from datasets.utils.metadata import DatasetMetadata





def   _lowerCamelCase ( UpperCAmelCase__					)							->     str:


   '''simple docstring'''


   a__     				=		min(re.search('^ +',UpperCAmelCase__					).end() if t.startswith(' '					) else 0 for t in string.splitlines()					)
   return "\n".join([line[indent_level:] for line in string.splitlines() if indent_level < len(UpperCAmelCase__					)]					)


__magic_name__    				=					"\\n---\nlanguage:\n- zh\n- en\ntask_ids:\n- sentiment-classification\n---\n# Begin of markdown\n\nSome cool dataset card\n"

__magic_name__    				=					"\\n---\n---\n# Begin of markdown\n\nSome cool dataset card\n"


__magic_name__    				=					"\\n# Begin of markdown\n\nSome cool dataset card\n"




class SCREAMING_SNAKE_CASE     (    unittest.TestCase	):







 """simple docstring"""


 def        _lowerCAmelCase				(   self		:      Tuple				)				->			Dict:




    '''simple docstring'''






    with tempfile.TemporaryDirectory() as tmp_dir:
       a__     				=		Path(_snake_case				) / 'README.md'
       with open(_snake_case					,   'w+'				) as readme_file:
          readme_file.write(_snake_case				)
       a__     				=		DatasetMetadata.from_readme(_snake_case				)
       self.assertDictEqual(_snake_case					,   {'language': ['zh', 'en'], 'task_ids': ['sentiment-classification']}				)

       with open(_snake_case					,   'w+'				) as readme_file:
          readme_file.write(_snake_case				)
       a__     				=		DatasetMetadata.from_readme(_snake_case				)
       self.assertDictEqual(_snake_case					,   {}				)

       with open(_snake_case					,   'w+'				) as readme_file:
          readme_file.write(_snake_case				)
       a__     				=		DatasetMetadata.from_readme(_snake_case				)
       self.assertEqual(_snake_case					,   {}				)



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




    '''simple docstring'''






    a__     				=		_dedent(
        '\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            '				)
    assert DatasetMetadata.from_yaml_string(_snake_case				)

    a__     				=		_dedent(
        '\\n            annotations_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            task_ids:\n            - open-domain-qa\n            '				)
    with self.assertRaises(_snake_case				):
       DatasetMetadata.from_yaml_string(_snake_case				)

    a__     				=		_dedent(
        '\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - text-classification\n            task_ids:\n            - multi-class-classification\n            paperswithcode_id:\n            - squad\n            configs:\n            - en\n            train-eval-index:\n            - config: en\n              task: text-classification\n              task_id: multi_class_classification\n              splits:\n                train_split: train\n                eval_split: test\n              col_mapping:\n                text: text\n                label: target\n              metrics:\n                - type: accuracy\n                  name: Accuracy\n            extra_gated_prompt: |\n              By clicking on “Access repository” below, you also agree to ImageNet Terms of Access:\n              [RESEARCHER_FULLNAME] (the "Researcher") has requested permission to use the ImageNet database (the "Database") at Princeton University and Stanford University. In exchange for such permission, Researcher hereby agrees to the following terms and conditions:\n              1. Researcher shall use the Database only for non-commercial research and educational purposes.\n            extra_gated_fields:\n              Company: text\n              Country: text\n              I agree to use this model for non-commerical use ONLY: checkbox\n            '				)
    assert DatasetMetadata.from_yaml_string(_snake_case				)


