

'''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    lowerCamelCase_  (					self    :		List[str]      ):
										'''simple docstring'''
										lowercase   :       Any								='''laion/clap-htsat-unfused'''
										lowercase   :       int								=tempfile.mkdtemp()







				def    lowerCamelCase_  (					self    :		Any		,				**UpperCAmelCase__    :		List[str]      ):
										'''simple docstring'''
										return RobertaTokenizer.from_pretrained(self.checkpoint		,				**UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		Any		,				**UpperCAmelCase__    :		List[str]      ):
										'''simple docstring'''
										return ClapFeatureExtractor.from_pretrained(self.checkpoint		,				**UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		Optional[int]      ):
										'''simple docstring'''
										shutil.rmtree(self.tmpdirname      )







				def    lowerCamelCase_  (					self    :		str      ):
										'''simple docstring'''
										lowercase   :       List[Any]								=self.get_tokenizer()
										lowercase   :       str								=self.get_feature_extractor()

										lowercase   :       List[str]								=ClapProcessor(tokenizer=UpperCAmelCase__		,				feature_extractor=UpperCAmelCase__      )

										processor.save_pretrained(self.tmpdirname      )
										lowercase   :       str								=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    lowerCamelCase_  (					self    :		List[Any]      ):
										'''simple docstring'''
										lowercase   :       Tuple								=ClapProcessor(tokenizer=self.get_tokenizer()		,				feature_extractor=self.get_feature_extractor()      )
										processor.save_pretrained(self.tmpdirname      )

										lowercase   :       int								=self.get_tokenizer(bos_token='''(BOS)'''		,				eos_token='''(EOS)'''      )
										lowercase   :       str								=self.get_feature_extractor(do_normalize=UpperCAmelCase__		,				padding_value=1.0      )

										lowercase   :       int								=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    lowerCamelCase_  (					self    :		Optional[Any]      ):
										'''simple docstring'''
										lowercase   :       str								=self.get_feature_extractor()
										lowercase   :       Any								=self.get_tokenizer()

										lowercase   :       List[Any]								=ClapProcessor(tokenizer=UpperCAmelCase__		,				feature_extractor=UpperCAmelCase__      )

										lowercase   :       int								=floats_list((3, 1000)      )

										lowercase   :       str								=feature_extractor(UpperCAmelCase__		,				return_tensors='''np'''      )
										lowercase   :       int								=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    lowerCamelCase_  (					self    :		Optional[Any]      ):
										'''simple docstring'''
										lowercase   :       Optional[int]								=self.get_feature_extractor()
										lowercase   :       Optional[Any]								=self.get_tokenizer()

										lowercase   :       Optional[int]								=ClapProcessor(tokenizer=UpperCAmelCase__		,				feature_extractor=UpperCAmelCase__      )

										lowercase   :       str								='''This is a test string'''

										lowercase   :       Optional[Any]								=processor(text=UpperCAmelCase__      )

										lowercase   :       Optional[Any]								=tokenizer(UpperCAmelCase__      )

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







				def    lowerCamelCase_  (					self    :		int      ):
										'''simple docstring'''
										lowercase   :       Dict								=self.get_feature_extractor()
										lowercase   :       Optional[Any]								=self.get_tokenizer()

										lowercase   :       Any								=ClapProcessor(tokenizer=UpperCAmelCase__		,				feature_extractor=UpperCAmelCase__      )

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

										lowercase   :       str								=processor.batch_decode(UpperCAmelCase__      )
										lowercase   :       Optional[Any]								=tokenizer.batch_decode(UpperCAmelCase__      )

										self.assertListEqual(UpperCAmelCase__		,				UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		Union[str, Any]      ):
										'''simple docstring'''
										lowercase   :       int								=self.get_feature_extractor()
										lowercase   :       str								=self.get_tokenizer()

										lowercase   :       List[str]								=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'''		,				)








'''simple docstring'''





# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# this script dumps information about the environment

import os
import platform
import sys


UpperCamelCase_							=					"""3"""

print("""Python version:""", sys.version)

print("""OS platform:""", platform.platform())
print("""OS architecture:""", platform.machine())

try:
							import torch

							print("""Torch version:""", torch.__version__)
							print("""Cuda available:""", torch.cuda.is_available())
							print("""Cuda version:""", torch.version.cuda)
							print("""CuDNN version:""", torch.backends.cudnn.version())
							print("""Number of GPUs available:""", torch.cuda.device_count())
except ImportError:
							print("""Torch version:""", None)

try:
							import transformers

							print("""transformers version:""", transformers.__version__)
except ImportError:
							print("""transformers version:""", None)





