


"""simple docstring"""
from operator import delitem, getitem, setitem

import pytest

from data_structures.hashing.hash_map import HashMap

def 				_snake_case      (   __snake_case							:      List[str]   ):




   """simple docstring"""







   return getitem, k

def 				_snake_case      (   __snake_case							:      List[Any]						, __snake_case							:      int   ):




   """simple docstring"""







   return setitem, k, v

def 				_snake_case      (   __snake_case							:      str   ):




   """simple docstring"""







   return delitem, k

def 				_snake_case      (   __snake_case							:      int						, __snake_case							:      Optional[Any]						, *__snake_case							:      Any   ):




   """simple docstring"""







   try:
      return fun(__snake_case						, *__snake_case   ), None
   except Exception as e:
      return None, e


UpperCAmelCase				=						(
    _set("""key_a""", """val_a"""),
    _set("""key_b""", """val_b"""),
)

UpperCAmelCase				=						[
    _set("""key_a""", """val_a"""),
    _set("""key_a""", """val_b"""),
]

UpperCAmelCase				=						[
    _set("""key_a""", """val_a"""),
    _set("""key_b""", """val_b"""),
    _del("""key_a"""),
    _del("""key_b"""),
    _set("""key_a""", """val_a"""),
    _del("""key_a"""),
]

UpperCAmelCase				=						[
    _get("""key_a"""),
    _del("""key_a"""),
    _set("""key_a""", """val_a"""),
    _del("""key_a"""),
    _del("""key_a"""),
    _get("""key_a"""),
]

UpperCAmelCase				=						[
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
]

UpperCAmelCase				=						[
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
    *[_del(x) for x in range(5)],
    _set("""key_a""", """val_b"""),
]

@pytest.mark.parametrize(
    """operations"""						, (
        pytest.param(_add_items						, id="""add items"""   ),
        pytest.param(_overwrite_items						, id="""overwrite items"""   ),
        pytest.param(_delete_items						, id="""delete items"""   ),
        pytest.param(_access_absent_items						, id="""access absent items"""   ),
        pytest.param(_add_with_resize_up						, id="""add with resize up"""   ),
        pytest.param(_add_with_resize_down						, id="""add with resize down"""   ),
    )						, )
def 				_snake_case      (   __snake_case							:      Any   ):




   """simple docstring"""







   _lowerCamelCase	:					str   =		HashMap(initial_block_size=4   )
   _lowerCamelCase	:					List[Any]   =		{}
   for _, (fun, *args) in enumerate(__snake_case   ):
      _lowerCamelCase   ,    _lowerCamelCase	:					List[str]   =		_run_operation(__snake_case						, __snake_case						, *__snake_case   )
      _lowerCamelCase   ,    _lowerCamelCase	:					Dict   =		_run_operation(__snake_case						, __snake_case						, *__snake_case   )
      assert my_res == py_res
      assert str(__snake_case   ) == str(__snake_case   )
      assert set(__snake_case   ) == set(__snake_case   )
      assert len(__snake_case   ) == len(__snake_case   )
      assert set(my.items()   ) == set(py.items()   )





def 				_snake_case      (   ):




   """simple docstring"""







   def is_public(__snake_case							:      str   ) -> bool:
      return not name.startswith("""_"""   )

   _lowerCamelCase	:					Any   =		{name for name in dir({}   ) if is_public(__snake_case   )}
   _lowerCamelCase	:					Tuple   =		{name for name in dir(HashMap()   ) if is_public(__snake_case   )}

   assert dict_public_names > hash_public_names









import shutil
import tempfile
import unittest

from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio

from .test_feature_extraction_clap import floats_list



@require_torchaudio
@require_sentencepiece
class 				_UpperCamelCase      (unittest.TestCase      ):


      def 			__UpperCAmelCase		(						self						)->						Optional[int]:
           __lowerCAmelCase             =       "laion/clap-htsat-unfused"
           __lowerCAmelCase             =       tempfile.mkdtemp()


      def 			__UpperCAmelCase		(						self       ,    **__UpperCamelCase						)->						Optional[int]:
           return RobertaTokenizer.from_pretrained(self.checkpoint       ,    **__UpperCamelCase						)


      def 			__UpperCAmelCase		(						self       ,    **__UpperCamelCase						)->						List[Any]:
           return ClapFeatureExtractor.from_pretrained(self.checkpoint       ,    **__UpperCamelCase						)


      def 			__UpperCAmelCase		(						self						)->						Union[str, Any]:
           shutil.rmtree(self.tmpdirname						)


      def 			__UpperCAmelCase		(						self						)->						Dict:
           __lowerCAmelCase             =       self.get_tokenizer()
           __lowerCAmelCase             =       self.get_feature_extractor()

           __lowerCAmelCase             =       ClapProcessor(tokenizer=__UpperCamelCase       ,    feature_extractor=__UpperCamelCase						)

           processor.save_pretrained(self.tmpdirname						)
           __lowerCAmelCase             =       ClapProcessor.from_pretrained(self.tmpdirname						)

           self.assertEqual(processor.tokenizer.get_vocab()       ,    tokenizer.get_vocab()						)
           self.assertIsInstance(processor.tokenizer       ,    __UpperCamelCase						)

           self.assertEqual(processor.feature_extractor.to_json_string()       ,    feature_extractor.to_json_string()						)
           self.assertIsInstance(processor.feature_extractor       ,    __UpperCamelCase						)


      def 			__UpperCAmelCase		(						self						)->						List[str]:
           __lowerCAmelCase             =       ClapProcessor(tokenizer=self.get_tokenizer()       ,    feature_extractor=self.get_feature_extractor()						)
           processor.save_pretrained(self.tmpdirname						)

           __lowerCAmelCase             =       self.get_tokenizer(bos_token="(BOS)"       ,    eos_token="(EOS)"						)
           __lowerCAmelCase             =       self.get_feature_extractor(do_normalize=__UpperCamelCase       ,    padding_value=1.0						)

           __lowerCAmelCase             =       ClapProcessor.from_pretrained(
               self.tmpdirname       ,    bos_token="(BOS)"       ,    eos_token="(EOS)"       ,    do_normalize=__UpperCamelCase       ,    padding_value=1.0						)

           self.assertEqual(processor.tokenizer.get_vocab()       ,    tokenizer_add_kwargs.get_vocab()						)
           self.assertIsInstance(processor.tokenizer       ,    __UpperCamelCase						)

           self.assertEqual(processor.feature_extractor.to_json_string()       ,    feature_extractor_add_kwargs.to_json_string()						)
           self.assertIsInstance(processor.feature_extractor       ,    __UpperCamelCase						)


      def 			__UpperCAmelCase		(						self						)->						List[str]:
           __lowerCAmelCase             =       self.get_feature_extractor()
           __lowerCAmelCase             =       self.get_tokenizer()

           __lowerCAmelCase             =       ClapProcessor(tokenizer=__UpperCamelCase       ,    feature_extractor=__UpperCamelCase						)

           __lowerCAmelCase             =       floats_list((3, 1_0_0_0)						)

           __lowerCAmelCase             =       feature_extractor(__UpperCamelCase       ,    return_tensors="np"						)
           __lowerCAmelCase             =       processor(audios=__UpperCamelCase       ,    return_tensors="np"						)

           for key in input_feat_extract.keys():
                self.assertAlmostEqual(input_feat_extract[key].sum()       ,    input_processor[key].sum()       ,    delta=1e-2						)


      def 			__UpperCAmelCase		(						self						)->						Dict:
           __lowerCAmelCase             =       self.get_feature_extractor()
           __lowerCAmelCase             =       self.get_tokenizer()

           __lowerCAmelCase             =       ClapProcessor(tokenizer=__UpperCamelCase       ,    feature_extractor=__UpperCamelCase						)

           __lowerCAmelCase             =       "This is a test string"

           __lowerCAmelCase             =       processor(text=__UpperCamelCase						)

           __lowerCAmelCase             =       tokenizer(__UpperCamelCase						)

           for key in encoded_tok.keys():
                self.assertListEqual(encoded_tok[key]       ,    encoded_processor[key]						)


      def 			__UpperCAmelCase		(						self						)->						int:
           __lowerCAmelCase             =       self.get_feature_extractor()
           __lowerCAmelCase             =       self.get_tokenizer()

           __lowerCAmelCase             =       ClapProcessor(tokenizer=__UpperCamelCase       ,    feature_extractor=__UpperCamelCase						)

           __lowerCAmelCase             =       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

           __lowerCAmelCase             =       processor.batch_decode(__UpperCamelCase						)
           __lowerCAmelCase             =       tokenizer.batch_decode(__UpperCamelCase						)

           self.assertListEqual(__UpperCamelCase       ,    __UpperCamelCase						)


      def 			__UpperCAmelCase		(						self						)->						Dict:
           __lowerCAmelCase             =       self.get_feature_extractor()
           __lowerCAmelCase             =       self.get_tokenizer()

           __lowerCAmelCase             =       ClapProcessor(tokenizer=__UpperCamelCase       ,    feature_extractor=__UpperCamelCase						)

           self.assertListEqual(
               processor.model_input_names[2:]       ,    feature_extractor.model_input_names       ,    msg="`processor` and `feature_extractor` model input names do not match"       ,    )






