




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       ):




							'''simple docstring'''



							def    _UpperCAmelCase     (					self       :	Union[str, Any]			)			->					List[str]:
										SCREAMING_SNAKE_CASE           =					"""laion/clap-htsat-unfused"""
										SCREAMING_SNAKE_CASE           =					tempfile.mkdtemp()





							def    _UpperCAmelCase     (					self       :	Union[str, Any]       ,     **a       :	Dict			)			->					Optional[Any]:
										return RobertaTokenizer.from_pretrained(self.checkpoint       ,     **a			)





							def    _UpperCAmelCase     (					self       :	List[str]       ,     **a       :	Dict			)			->					int:
										return ClapFeatureExtractor.from_pretrained(self.checkpoint       ,     **a			)





							def    _UpperCAmelCase     (					self       :	Tuple			)			->					List[str]:
										shutil.rmtree(self.tmpdirname			)





							def    _UpperCAmelCase     (					self       :	List[str]			)			->					str:
										SCREAMING_SNAKE_CASE           =					self.get_tokenizer()
										SCREAMING_SNAKE_CASE           =					self.get_feature_extractor()

										SCREAMING_SNAKE_CASE           =					ClapProcessor(tokenizer=a       ,     feature_extractor=a			)

										processor.save_pretrained(self.tmpdirname			)
										SCREAMING_SNAKE_CASE           =					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    _UpperCAmelCase     (					self       :	Optional[int]			)			->					Tuple:
										SCREAMING_SNAKE_CASE           =					ClapProcessor(tokenizer=self.get_tokenizer()       ,     feature_extractor=self.get_feature_extractor()			)
										processor.save_pretrained(self.tmpdirname			)

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

										SCREAMING_SNAKE_CASE           =					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    _UpperCAmelCase     (					self       :	Union[str, Any]			)			->					Dict:
										SCREAMING_SNAKE_CASE           =					self.get_feature_extractor()
										SCREAMING_SNAKE_CASE           =					self.get_tokenizer()

										SCREAMING_SNAKE_CASE           =					ClapProcessor(tokenizer=a       ,     feature_extractor=a			)

										SCREAMING_SNAKE_CASE           =					floats_list((3, 1_000)			)

										SCREAMING_SNAKE_CASE           =					feature_extractor(a       ,     return_tensors="""np"""			)
										SCREAMING_SNAKE_CASE           =					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    _UpperCAmelCase     (					self       :	List[str]			)			->					Optional[int]:
										SCREAMING_SNAKE_CASE           =					self.get_feature_extractor()
										SCREAMING_SNAKE_CASE           =					self.get_tokenizer()

										SCREAMING_SNAKE_CASE           =					ClapProcessor(tokenizer=a       ,     feature_extractor=a			)

										SCREAMING_SNAKE_CASE           =					"""This is a test string"""

										SCREAMING_SNAKE_CASE           =					processor(text=a			)

										SCREAMING_SNAKE_CASE           =					tokenizer(a			)

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





							def    _UpperCAmelCase     (					self       :	Tuple			)			->					Tuple:
										SCREAMING_SNAKE_CASE           =					self.get_feature_extractor()
										SCREAMING_SNAKE_CASE           =					self.get_tokenizer()

										SCREAMING_SNAKE_CASE           =					ClapProcessor(tokenizer=a       ,     feature_extractor=a			)

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

										SCREAMING_SNAKE_CASE           =					processor.batch_decode(a			)
										SCREAMING_SNAKE_CASE           =					tokenizer.batch_decode(a			)

										self.assertListEqual(a       ,     a			)







							def    _UpperCAmelCase     (					self       :	List[Any]			)			->					int:
										SCREAMING_SNAKE_CASE           =					self.get_feature_extractor()
										SCREAMING_SNAKE_CASE           =					self.get_tokenizer()

										SCREAMING_SNAKE_CASE           =					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"""       ,     )












import importlib
import shutil
import threading
import warnings
from typing import List

import fsspec
import fsspec.asyn

from . import compression
from .hffilesystem import HfFileSystem


__A						:							Tuple							=  importlib.util.find_spec("""s3fs""") is not None

if _has_safs:
		from .safilesystem import SaFileSystem  # noqa: F401

__A						:							List[compression.BaseCompressedFileFileSystem]							=  [
    compression.BzaFileSystem,
    compression.GzipFileSystem,
    compression.LzaFileSystem,
    compression.XzFileSystem,
    compression.ZstdFileSystem,
]

# Register custom filesystems
for fs_class in COMPRESSION_FILESYSTEMS + [HfFileSystem]:
		if fs_class.protocol in fsspec.registry and fsspec.registry[fs_class.protocol] is not fs_class:
				warnings.warn(f'''A filesystem protocol was already set for {fs_class.protocol} and will be overwritten.''')
		fsspec.register_implementation(fs_class.protocol, fs_class, clobber=True)
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			if "://" in dataset_path:
						SCREAMING_SNAKE_CASE           =					dataset_path.split("""://"""   )[1]
			return dataset_path
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			if fs is not None and fs.protocol != "file":
						return True
			else:
						return False
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE           =					not is_remote_filesystem(SCREAMING_SNAKE_CASE   )
			if is_local:
						# LocalFileSystem.mv does copy + rm, it is more efficient to simply move a local directory
						shutil.move(fs._strip_protocol(SCREAMING_SNAKE_CASE   )					,	fs._strip_protocol(SCREAMING_SNAKE_CASE   )   )
			else:
						fs.mv(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	recursive=SCREAMING_SNAKE_CASE   )




def 					lowerCamelCase_    (    ):
			'''simple docstring'''
			if hasattr(fsspec.asyn					,	"""reset_lock"""   ):
						# for future fsspec>2022.05.0
						fsspec.asyn.reset_lock()
			else:
						SCREAMING_SNAKE_CASE           =					None
						SCREAMING_SNAKE_CASE           =					None
						SCREAMING_SNAKE_CASE           =					threading.Lock()






