


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   lowerCamelCase_					(						self							:		Dict						):







						"""simple docstring"""







						UpperCamelCase         =					"""laion/clap-htsat-unfused"""
						UpperCamelCase         =					tempfile.mkdtemp()




			def   lowerCamelCase_					(						self							:		int       ,       **__magic_name__							:		Dict						):







						"""simple docstring"""







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




			def   lowerCamelCase_					(						self							:		Union[str, Any]       ,       **__magic_name__							:		List[Any]						):







						"""simple docstring"""







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




			def   lowerCamelCase_					(						self							:		List[Any]						):







						"""simple docstring"""







						shutil.rmtree(self.tmpdirname						)




			def   lowerCamelCase_					(						self							:		Tuple						):







						"""simple docstring"""







						UpperCamelCase         =					self.get_tokenizer()
						UpperCamelCase         =					self.get_feature_extractor()

						UpperCamelCase         =					ClapProcessor(tokenizer=__magic_name__       ,       feature_extractor=__magic_name__						)

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

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

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




			def   lowerCamelCase_					(						self							:		str						):







						"""simple docstring"""







						UpperCamelCase         =					ClapProcessor(tokenizer=self.get_tokenizer()       ,       feature_extractor=self.get_feature_extractor()						)
						processor.save_pretrained(self.tmpdirname						)

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

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

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

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




			def   lowerCamelCase_					(						self							:		Optional[Any]						):







						"""simple docstring"""







						UpperCamelCase         =					self.get_feature_extractor()
						UpperCamelCase         =					self.get_tokenizer()

						UpperCamelCase         =					ClapProcessor(tokenizer=__magic_name__       ,       feature_extractor=__magic_name__						)

						UpperCamelCase         =					floats_list((3, 1_0_0_0)						)

						UpperCamelCase         =					feature_extractor(__magic_name__       ,       return_tensors="""np"""						)
						UpperCamelCase         =					processor(audios=__magic_name__       ,       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   lowerCamelCase_					(						self							:		List[Any]						):







						"""simple docstring"""







						UpperCamelCase         =					self.get_feature_extractor()
						UpperCamelCase         =					self.get_tokenizer()

						UpperCamelCase         =					ClapProcessor(tokenizer=__magic_name__       ,       feature_extractor=__magic_name__						)

						UpperCamelCase         =					"""This is a test string"""

						UpperCamelCase         =					processor(text=__magic_name__						)

						UpperCamelCase         =					tokenizer(__magic_name__						)

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




			def   lowerCamelCase_					(						self							:		List[str]						):







						"""simple docstring"""







						UpperCamelCase         =					self.get_feature_extractor()
						UpperCamelCase         =					self.get_tokenizer()

						UpperCamelCase         =					ClapProcessor(tokenizer=__magic_name__       ,       feature_extractor=__magic_name__						)

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

						UpperCamelCase         =					processor.batch_decode(__magic_name__						)
						UpperCamelCase         =					tokenizer.batch_decode(__magic_name__						)

						self.assertListEqual(__magic_name__       ,       __magic_name__						)





			def   lowerCamelCase_					(						self							:		Dict						):







						"""simple docstring"""







						UpperCamelCase         =					self.get_feature_extractor()
						UpperCamelCase         =					self.get_tokenizer()

						UpperCamelCase         =					ClapProcessor(tokenizer=__magic_name__       ,       feature_extractor=__magic_name__						)

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








from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case            =   logging.get_logger(__name__)

__snake_case            =   {
    "SCUT-DLVCLab/lilt-roberta-en-base": (
        "https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"
    ),
}




class    UpperCAmelCase					(       __snake_case    ):
			lowercase						= """lilt"""




			def __init__(						self							:		Tuple       ,       __magic_name__							:		Tuple=3_0_5_2_2       ,       __magic_name__							:		List[str]=7_6_8       ,       __magic_name__							:		Optional[Any]=1_2       ,       __magic_name__							:		str=1_2       ,       __magic_name__							:		Tuple=3_0_7_2       ,       __magic_name__							:		List[Any]="gelu"       ,       __magic_name__							:		Dict=0.1       ,       __magic_name__							:		str=0.1       ,       __magic_name__							:		Dict=5_1_2       ,       __magic_name__							:		Any=2       ,       __magic_name__							:		Optional[int]=0.02       ,       __magic_name__							:		Optional[int]=1e-12       ,       __magic_name__							:		Optional[int]=0       ,       __magic_name__							:		List[str]="absolute"       ,       __magic_name__							:		List[Any]=None       ,       __magic_name__							:		str=4       ,       __magic_name__							:		Any=1_0_2_4       ,       **__magic_name__							:		List[str]       ,       ):







						"""simple docstring"""







						super().__init__(pad_token_id=__magic_name__       ,       **__magic_name__						)

						UpperCamelCase         =					vocab_size
						UpperCamelCase         =					hidden_size
						UpperCamelCase         =					num_hidden_layers
						UpperCamelCase         =					num_attention_heads
						UpperCamelCase         =					hidden_act
						UpperCamelCase         =					intermediate_size
						UpperCamelCase         =					hidden_dropout_prob
						UpperCamelCase         =					attention_probs_dropout_prob
						UpperCamelCase         =					max_position_embeddings
						UpperCamelCase         =					type_vocab_size
						UpperCamelCase         =					initializer_range
						UpperCamelCase         =					layer_norm_eps
						UpperCamelCase         =					position_embedding_type
						UpperCamelCase         =					classifier_dropout
						UpperCamelCase         =					channel_shrink_ratio
						UpperCamelCase         =					max_ad_position_embeddings




