




"""simple docstring"""





from __future__ import annotations

from typing import Any

def 					_UpperCamelCase    (			UpperCamelCase							)			->			int:


			"""simple docstring"""
			if not postfix_notation:
						return 0

			__UpperCAmelCase	: Tuple		=					{"+", "-", "*", "/"}
			__UpperCAmelCase	: list[Any]		=					[]

			for token in postfix_notation:
						if token in operations:
									__UpperCAmelCase	,     __UpperCAmelCase	: List[str]		=					stack.pop(), stack.pop()
									if token == "+":
												stack.append(a + b							)
									elif token == "-":
												stack.append(a - b							)
									elif token == "*":
												stack.append(a * b							)
									else:
												if a * b < 0 and a % b != 0:
															stack.append(a // b + 1							)
												else:
															stack.append(a // b							)
						else:
									stack.append(int(UpperCamelCase							)							)

			return stack.pop()


if __name__ == "__main__":
					import doctest

					doctest.testmod()








"""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      a__				(	unittest.TestCase   ):


			def       a_     (      self      :    Any):


						"""simple docstring"""




						__UpperCAmelCase	: Tuple		=					"laion/clap-htsat-unfused"
						__UpperCAmelCase	: List[str]		=					tempfile.mkdtemp()


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


						"""simple docstring"""




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


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


						"""simple docstring"""




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


			def       a_     (      self      :    List[Any]):


						"""simple docstring"""




						shutil.rmtree(self.tmpdirname)


			def       a_     (      self      :    Optional[int]):


						"""simple docstring"""




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

						__UpperCAmelCase	: List[Any]		=					ClapProcessor(tokenizer=UpperCamelCase_      ,  feature_extractor=UpperCamelCase_)

						processor.save_pretrained(self.tmpdirname)
						__UpperCAmelCase	: Union[str, Any]		=					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       a_     (      self      :    Any):


						"""simple docstring"""




						__UpperCAmelCase	: Union[str, Any]		=					ClapProcessor(tokenizer=self.get_tokenizer()      ,  feature_extractor=self.get_feature_extractor())
						processor.save_pretrained(self.tmpdirname)

						__UpperCAmelCase	: int		=					self.get_tokenizer(bos_token="(BOS)"      ,  eos_token="(EOS)")
						__UpperCAmelCase	: Any		=					self.get_feature_extractor(do_normalize=UpperCamelCase_      ,  padding_value=1.0)

						__UpperCAmelCase	: Tuple		=					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       a_     (      self      :    Any):


						"""simple docstring"""




						__UpperCAmelCase	: Tuple		=					self.get_feature_extractor()
						__UpperCAmelCase	: int		=					self.get_tokenizer()

						__UpperCAmelCase	: Any		=					ClapProcessor(tokenizer=UpperCamelCase_      ,  feature_extractor=UpperCamelCase_)

						__UpperCAmelCase	: Optional[int]		=					floats_list((3, 1000))

						__UpperCAmelCase	: Tuple		=					feature_extractor(UpperCamelCase_      ,  return_tensors="np")
						__UpperCAmelCase	: Any		=					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       a_     (      self      :    Optional[Any]):


						"""simple docstring"""




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

						__UpperCAmelCase	: str		=					ClapProcessor(tokenizer=UpperCamelCase_      ,  feature_extractor=UpperCamelCase_)

						__UpperCAmelCase	: Any		=					"This is a test string"

						__UpperCAmelCase	: List[Any]		=					processor(text=UpperCamelCase_)

						__UpperCAmelCase	: Dict		=					tokenizer(UpperCamelCase_)

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


			def       a_     (      self      :    Tuple):


						"""simple docstring"""




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

						__UpperCAmelCase	: List[str]		=					ClapProcessor(tokenizer=UpperCamelCase_      ,  feature_extractor=UpperCamelCase_)

						__UpperCAmelCase	: Tuple		=					[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

						__UpperCAmelCase	: int		=					processor.batch_decode(UpperCamelCase_)
						__UpperCAmelCase	: Tuple		=					tokenizer.batch_decode(UpperCamelCase_)

						self.assertListEqual(UpperCamelCase_      ,  UpperCamelCase_)


			def       a_     (      self      :    Optional[int]):


						"""simple docstring"""




						__UpperCAmelCase	: Any		=					self.get_feature_extractor()
						__UpperCAmelCase	: int		=					self.get_tokenizer()

						__UpperCAmelCase	: int		=					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"      ,  )


