






import copy
import re







class 	SCREAMING_SNAKE_CASE	:
       snake_case__    :     Tuple   		=			'hp'
       snake_case__    :     List[Any]   		=			{}
       snake_case__    :     Optional[int]   		=			None




       @classmethod
       def 					a_					(					cls      : List[Any]	,    A__      : Tuple	,    A__      : Tuple					):


            """simple docstring"""







            __lowerCamelCase						:       List[str]				   =				prefix
            __lowerCamelCase						:       List[Any]				   =				defaults
            cls.build_naming_info()




       @staticmethod
       def 					a_					(					A__      : Dict	,    A__      : Tuple					):


            """simple docstring"""







            if len(A__					) == 0:
                 return ""
            __lowerCamelCase						:       List[Any]				   =				None
            if any(char.isdigit() for char in word					):
                 raise Exception(f"Parameters should not contain numbers: '{word}' contains a number"					)
            if word in info["short_word"]:
                 return info["short_word"][word]
            for prefix_len in range(1	,    len(A__					) + 1					):
                 __lowerCamelCase						:       List[Any]				   =				word[:prefix_len]
                 if prefix in info["reverse_short_word"]:
                      continue
                 else:
                      __lowerCamelCase						:       str				   =				prefix
                      break

            if short_word is None:
                 # Paranoid fallback
                 def int_to_alphabetic(A__      : Union[str, Any]					):
                      __lowerCamelCase						:       List[Any]				   =				""""""
                      while integer != 0:
                           __lowerCamelCase						:       List[Any]				   =				chr(ord("""A"""					) + integer % 10					) + s
                           integer //= 10
                      return s

                 __lowerCamelCase						:       List[str]				   =				0
                 while True:
                      __lowerCamelCase						:       Any				   =				word + """#""" + int_to_alphabetic(A__					)
                      if sword in info["reverse_short_word"]:
                           continue
                      else:
                           __lowerCamelCase						:       Optional[int]				   =				sword
                           break

            __lowerCamelCase						:       Optional[int]				   =				short_word
            __lowerCamelCase						:       int				   =				word
            return short_word




       @staticmethod
       def 					a_					(					A__      : Optional[Any]	,    A__      : List[str]					):


            """simple docstring"""







            __lowerCamelCase						:       Optional[int]				   =				param_name.split("""_"""					)

            __lowerCamelCase						:       Tuple				   =				[TrialShortNamer.shortname_for_word(A__	,    A__					) for word in words]

            # We try to create a separatorless short name, but if there is a collision we have to fallback
            # to a separated short name
            __lowerCamelCase						:       Any				   =				["""""", """_"""]

            for separator in separators:
                 __lowerCamelCase						:       Any				   =				separator.join(A__					)
                 if shortname not in info["reverse_short_param"]:
                      __lowerCamelCase						:       Tuple				   =				shortname
                      __lowerCamelCase						:       List[str]				   =				param_name
                      return shortname

            return param_name




       @staticmethod
       def 					a_					(					A__      : List[Any]	,    A__      : Optional[Any]					):


            """simple docstring"""







            __lowerCamelCase						:       Tuple				   =				TrialShortNamer.shortname_for_key(A__	,    A__					)
            __lowerCamelCase						:       int				   =				short_name
            __lowerCamelCase						:       List[Any]				   =				param_name




       @classmethod
       def 					a_					(					cls      : str					):


            """simple docstring"""







            if cls.NAMING_INFO is not None:
                 return

            __lowerCamelCase						:       Tuple				   =				{
                """short_word""": {},
                """reverse_short_word""": {},
                """short_param""": {},
                """reverse_short_param""": {},
            }

            __lowerCamelCase						:       Optional[Any]				   =				list(cls.DEFAULTS.keys()					)

            for k in field_keys:
                 cls.add_new_param_name(A__	,    A__					)

            __lowerCamelCase						:       Optional[int]				   =				info




       @classmethod
       def 					a_					(					cls      : int	,    A__      : List[str]					):


            """simple docstring"""







            cls.build_naming_info()
            assert cls.PREFIX is not None
            __lowerCamelCase						:       List[Any]				   =				[copy.copy(cls.PREFIX					)]

            for k, v in params.items():
                 if k not in cls.DEFAULTS:
                      raise Exception(f"You should provide a default value for the param name {k} with value {v}"					)
                 if v == cls.DEFAULTS[k]:
                      # The default value is not added to the name
                      continue

                 __lowerCamelCase						:       Optional[Any]				   =				cls.NAMING_INFO["""short_param"""][k]

                 if isinstance(A__	,    A__					):
                      __lowerCamelCase						:       Tuple				   =				1 if v else 0

                 __lowerCamelCase						:       List[Any]				   =				"""""" if isinstance(A__	,    (int, float)					) else """-"""
                 __lowerCamelCase						:       Optional[Any]				   =				f"{key}{sep}{v}"
                 name.append(A__					)

            return "_".join(A__					)




       @classmethod
       def 					a_					(					cls      : List[Any]	,    A__      : Dict					):


            """simple docstring"""







            __lowerCamelCase						:       Dict				   =				repr[len(cls.PREFIX					) + 1 :]
            if repr == "":
                 __lowerCamelCase						:       List[str]				   =				[]
            else:
                 __lowerCamelCase						:       Optional[int]				   =				repr.split("""_"""					)

            __lowerCamelCase						:       Tuple				   =				{}

            for value in values:
                 if "-" in value:
                      __lowerCamelCase						:       List[str]				   =				value.split("""-"""					)
                 else:
                      __lowerCamelCase						:       int				   =				re.sub("""[0-9.]"""	,    """"""	,    A__					)
                      __lowerCamelCase						:       Tuple				   =				float(re.sub("""[^0-9.]"""	,    """"""	,    A__					)					)

                 __lowerCamelCase						:       List[Any]				   =				cls.NAMING_INFO["""reverse_short_param"""][p_k]

                 __lowerCamelCase						:       Tuple				   =				p_v

            for k in cls.DEFAULTS:
                 if k not in parameters:
                      __lowerCamelCase						:       Optional[Any]				   =				cls.DEFAULTS[k]

            return parameters











'''simple docstring'''

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 	SCREAMING_SNAKE_CASE	(      unittest.TestCase  ):




       def 					a_					(					self      : str					):


            """simple docstring"""







            __lowerCamelCase						:       Any				   =				"""laion/clap-htsat-unfused"""
            __lowerCamelCase						:       List[Any]				   =				tempfile.mkdtemp()




       def 					a_					(					self      : Optional[int]	,    **A__      : Union[str, Any]					):


            """simple docstring"""







            return RobertaTokenizer.from_pretrained(self.checkpoint	,    **A__					)




       def 					a_					(					self      : str	,    **A__      : Any					):


            """simple docstring"""







            return ClapFeatureExtractor.from_pretrained(self.checkpoint	,    **A__					)




       def 					a_					(					self      : List[str]					):


            """simple docstring"""







            shutil.rmtree(self.tmpdirname					)




       def 					a_					(					self      : str					):


            """simple docstring"""







            __lowerCamelCase						:       Dict				   =				self.get_tokenizer()
            __lowerCamelCase						:       Union[str, Any]				   =				self.get_feature_extractor()

            __lowerCamelCase						:       Dict				   =				ClapProcessor(tokenizer=A__	,    feature_extractor=A__					)

            processor.save_pretrained(self.tmpdirname					)
            __lowerCamelCase						:       Optional[Any]				   =				ClapProcessor.from_pretrained(self.tmpdirname					)

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

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




       def 					a_					(					self      : str					):


            """simple docstring"""







            __lowerCamelCase						:       str				   =				ClapProcessor(tokenizer=self.get_tokenizer()	,    feature_extractor=self.get_feature_extractor()					)
            processor.save_pretrained(self.tmpdirname					)

            __lowerCamelCase						:       Tuple				   =				self.get_tokenizer(bos_token="""(BOS)"""	,    eos_token="""(EOS)"""					)
            __lowerCamelCase						:       Any				   =				self.get_feature_extractor(do_normalize=A__	,    padding_value=1.0					)

            __lowerCamelCase						:       List[Any]				   =				ClapProcessor.from_pretrained(
                self.tmpdirname	,    bos_token="""(BOS)"""	,    eos_token="""(EOS)"""	,    do_normalize=A__	,    padding_value=1.0					)

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

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




       def 					a_					(					self      : Optional[int]					):


            """simple docstring"""







            __lowerCamelCase						:       Dict				   =				self.get_feature_extractor()
            __lowerCamelCase						:       Tuple				   =				self.get_tokenizer()

            __lowerCamelCase						:       Optional[int]				   =				ClapProcessor(tokenizer=A__	,    feature_extractor=A__					)

            __lowerCamelCase						:       Dict				   =				floats_list((3, 1000)					)

            __lowerCamelCase						:       str				   =				feature_extractor(A__	,    return_tensors="""np"""					)
            __lowerCamelCase						:       Any				   =				processor(audios=A__	,    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 					a_					(					self      : Any					):


            """simple docstring"""







            __lowerCamelCase						:       Optional[Any]				   =				self.get_feature_extractor()
            __lowerCamelCase						:       int				   =				self.get_tokenizer()

            __lowerCamelCase						:       str				   =				ClapProcessor(tokenizer=A__	,    feature_extractor=A__					)

            __lowerCamelCase						:       int				   =				"""This is a test string"""

            __lowerCamelCase						:       Any				   =				processor(text=A__					)

            __lowerCamelCase						:       Any				   =				tokenizer(A__					)

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




       def 					a_					(					self      : List[Any]					):


            """simple docstring"""







            __lowerCamelCase						:       Optional[int]				   =				self.get_feature_extractor()
            __lowerCamelCase						:       List[str]				   =				self.get_tokenizer()

            __lowerCamelCase						:       int				   =				ClapProcessor(tokenizer=A__	,    feature_extractor=A__					)

            __lowerCamelCase						:       Union[str, Any]				   =				[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

            __lowerCamelCase						:       int				   =				processor.batch_decode(A__					)
            __lowerCamelCase						:       List[Any]				   =				tokenizer.batch_decode(A__					)

            self.assertListEqual(A__	,    A__					)




       def 					a_					(					self      : str					):


            """simple docstring"""







            __lowerCamelCase						:       Any				   =				self.get_feature_extractor()
            __lowerCamelCase						:       List[Any]				   =				self.get_tokenizer()

            __lowerCamelCase						:       Any				   =				ClapProcessor(tokenizer=A__	,    feature_extractor=A__					)

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



