



"""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    __lowercase     (					unittest.TestCase):







						"""simple docstring"""







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Optional[Any] 					=					"""laion/clap-htsat-unfused"""
											snake_case_					:		Any 					=					tempfile.mkdtemp()







						def 						__UpperCamelCase							(self   ,		**lowercase__       ):
											return RobertaTokenizer.from_pretrained(self.checkpoint   ,		**lowercase__       )







						def 						__UpperCamelCase							(self   ,		**lowercase__       ):
											return ClapFeatureExtractor.from_pretrained(self.checkpoint   ,		**lowercase__       )







						def 						__UpperCamelCase							(self       ):
											shutil.rmtree(self.tmpdirname       )







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Optional[int] 					=					self.get_tokenizer()
											snake_case_					:		Union[str, Any] 					=					self.get_feature_extractor()

											snake_case_					:		List[str] 					=					ClapProcessor(tokenizer=lowercase__   ,		feature_extractor=lowercase__       )

											processor.save_pretrained(self.tmpdirname       )
											snake_case_					:		Tuple 					=					ClapProcessor.from_pretrained(self.tmpdirname       )

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

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







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Optional[Any] 					=					ClapProcessor(tokenizer=self.get_tokenizer()   ,		feature_extractor=self.get_feature_extractor()       )
											processor.save_pretrained(self.tmpdirname       )

											snake_case_					:		List[str] 					=					self.get_tokenizer(bos_token="""(BOS)"""   ,		eos_token="""(EOS)"""       )
											snake_case_					:		List[str] 					=					self.get_feature_extractor(do_normalize=lowercase__   ,		padding_value=1.0       )

											snake_case_					:		Tuple 					=					ClapProcessor.from_pretrained(
											    self.tmpdirname   ,		bos_token="""(BOS)"""   ,		eos_token="""(EOS)"""   ,		do_normalize=lowercase__   ,		padding_value=1.0       )

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

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







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		List[str] 					=					self.get_feature_extractor()
											snake_case_					:		Dict 					=					self.get_tokenizer()

											snake_case_					:		Union[str, Any] 					=					ClapProcessor(tokenizer=lowercase__   ,		feature_extractor=lowercase__       )

											snake_case_					:		int 					=					floats_list((3, 10_00)       )

											snake_case_					:		List[str] 					=					feature_extractor(lowercase__   ,		return_tensors="""np"""       )
											snake_case_					:		List[str] 					=					processor(audios=lowercase__   ,		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       ):
											snake_case_					:		int 					=					self.get_feature_extractor()
											snake_case_					:		Tuple 					=					self.get_tokenizer()

											snake_case_					:		int 					=					ClapProcessor(tokenizer=lowercase__   ,		feature_extractor=lowercase__       )

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

											snake_case_					:		Tuple 					=					processor(text=lowercase__       )

											snake_case_					:		Optional[int] 					=					tokenizer(lowercase__       )

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







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Tuple 					=					self.get_feature_extractor()
											snake_case_					:		str 					=					self.get_tokenizer()

											snake_case_					:		Any 					=					ClapProcessor(tokenizer=lowercase__   ,		feature_extractor=lowercase__       )

											snake_case_					:		int 					=					[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

											snake_case_					:		Optional[int] 					=					processor.batch_decode(lowercase__       )
											snake_case_					:		Tuple 					=					tokenizer.batch_decode(lowercase__       )

											self.assertListEqual(lowercase__   ,		lowercase__       )







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Tuple 					=					self.get_feature_extractor()
											snake_case_					:		List[str] 					=					self.get_tokenizer()

											snake_case_					:		List[Any] 					=					ClapProcessor(tokenizer=lowercase__   ,		feature_extractor=lowercase__       )

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









"""simple docstring"""

import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Audio, Features, Value
from .base import TaskTemplate







@dataclass(frozen=_UpperCAmelCase)
class    __lowercase     (					_UpperCAmelCase):







						"""simple docstring"""







						_A		:							str							       =		field(default="""automatic-speech-recognition"""					,    metadata={"""include_in_asdict_even_if_is_default""": True})
						_A		:							ClassVar[Features]							       =		Features({"""audio""": Audio()})
						_A		:							ClassVar[Features]							       =		Features({"""transcription""": Value("""string""")})
						_A		:							str							       =		"audio"
						_A		:							str							       =		"transcription"







						def 						__UpperCamelCase							(self   ,		lowercase__       ):
											if self.audio_column not in features:
																raise ValueError(f'Column {self.audio_column} is not present in features.'       )
											if not isinstance(features[self.audio_column]   ,		lowercase__       ):
																raise ValueError(f'Column {self.audio_column} is not an Audio type.'       )
											snake_case_					:		Optional[int] 					=					copy.deepcopy(self       )
											snake_case_					:		Tuple 					=					self.input_schema.copy()
											snake_case_					:		List[str] 					=					features[self.audio_column]
											snake_case_					:		Any 					=					input_schema
											return task_template







						@property
						def 						__UpperCamelCase							(self       ):
											return {self.audio_column: "audio", self.transcription_column: "transcription"}




