
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		):




							def 			A__				(    self):
												lowercase						     =						'''laion/clap-htsat-unfused'''
												lowercase						     =						tempfile.mkdtemp()




							def 			A__				(    self       ,**A__):
												return RobertaTokenizer.from_pretrained(self.checkpoint       ,**__lowerCamelCase)




							def 			A__				(    self       ,**A__):
												return ClapFeatureExtractor.from_pretrained(self.checkpoint       ,**__lowerCamelCase)




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




							def 			A__				(    self):
												lowercase						     =						self.get_tokenizer()
												lowercase						     =						self.get_feature_extractor()

												lowercase						     =						ClapProcessor(tokenizer=__lowerCamelCase       ,feature_extractor=__lowerCamelCase)

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

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

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




							def 			A__				(    self):
												lowercase						     =						ClapProcessor(tokenizer=self.get_tokenizer()       ,feature_extractor=self.get_feature_extractor())
												processor.save_pretrained(self.tmpdirname)

												lowercase						     =						self.get_tokenizer(bos_token='''(BOS)'''       ,eos_token='''(EOS)''')
												lowercase						     =						self.get_feature_extractor(do_normalize=__lowerCamelCase       ,padding_value=1.0)

												lowercase						     =						ClapProcessor.from_pretrained(
												    self.tmpdirname       ,bos_token='''(BOS)'''       ,eos_token='''(EOS)'''       ,do_normalize=__lowerCamelCase       ,padding_value=1.0)

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

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




							def 			A__				(    self):
												lowercase						     =						self.get_feature_extractor()
												lowercase						     =						self.get_tokenizer()

												lowercase						     =						ClapProcessor(tokenizer=__lowerCamelCase       ,feature_extractor=__lowerCamelCase)

												lowercase						     =						floats_list((3, 1_0_0_0))

												lowercase						     =						feature_extractor(__lowerCamelCase       ,return_tensors='''np''')
												lowercase						     =						processor(audios=__lowerCamelCase       ,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):
												lowercase						     =						self.get_feature_extractor()
												lowercase						     =						self.get_tokenizer()

												lowercase						     =						ClapProcessor(tokenizer=__lowerCamelCase       ,feature_extractor=__lowerCamelCase)

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

												lowercase						     =						processor(text=__lowerCamelCase)

												lowercase						     =						tokenizer(__lowerCamelCase)

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




							def 			A__				(    self):
												lowercase						     =						self.get_feature_extractor()
												lowercase						     =						self.get_tokenizer()

												lowercase						     =						ClapProcessor(tokenizer=__lowerCamelCase       ,feature_extractor=__lowerCamelCase)

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

												lowercase						     =						processor.batch_decode(__lowerCamelCase)
												lowercase						     =						tokenizer.batch_decode(__lowerCamelCase)

												self.assertListEqual(__lowerCamelCase       ,__lowerCamelCase)





							def 			A__				(    self):
												lowercase						     =						self.get_feature_extractor()
												lowercase						     =						self.get_tokenizer()

												lowercase						     =						ClapProcessor(tokenizer=__lowerCamelCase       ,feature_extractor=__lowerCamelCase)

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







from __future__ import annotations

from decimal import Decimal

from numpy import array



def 	UpperCamelCase   (							lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						Decimal

					# Check if the provided matrix has 2 rows and 2 columns
					# since this implementation only works for 2x2 matrices
					if len(lowerCAmelCase__		) == 2 and len(matrix[0]		) == 2 and len(matrix[1]		) == 2:
										# Calculate the determinant of the matrix
										lowercase						     =						float(
										    d(matrix[0][0]		) * d(matrix[1][1]		) - d(matrix[1][0]		) * d(matrix[0][1]		)		)
										if determinant == 0:
															raise ValueError('''This matrix has no inverse.'''		)

										# Creates a copy of the matrix with swapped positions of the elements
										lowercase						     =						[[0.0, 0.0], [0.0, 0.0]]
										lowercase     ,						lowercase						     =						matrix[1][1], matrix[0][0]
										lowercase     ,						lowercase						     =						-matrix[1][0], -matrix[0][1]

										# Calculate the inverse of the matrix
										return [
										    [(float(d(lowerCAmelCase__		)		) / determinant) or 0.0 for n in row] for row in swapped_matrix
										]
					elif (
					    len(lowerCAmelCase__		) == 3
					    and len(matrix[0]		) == 3
					    and len(matrix[1]		) == 3
					    and len(matrix[2]		) == 3
					):
										# Calculate the determinant of the matrix using Sarrus rule
										lowercase						     =						float(
										    (
										        (d(matrix[0][0]		) * d(matrix[1][1]		) * d(matrix[2][2]		))
										        + (d(matrix[0][1]		) * d(matrix[1][2]		) * d(matrix[2][0]		))
										        + (d(matrix[0][2]		) * d(matrix[1][0]		) * d(matrix[2][1]		))
										    )
										    - (
										        (d(matrix[0][2]		) * d(matrix[1][1]		) * d(matrix[2][0]		))
										        + (d(matrix[0][1]		) * d(matrix[1][0]		) * d(matrix[2][2]		))
										        + (d(matrix[0][0]		) * d(matrix[1][2]		) * d(matrix[2][1]		))
										    )		)
										if determinant == 0:
															raise ValueError('''This matrix has no inverse.'''		)

										# Creating cofactor matrix
										lowercase						     =						[
										    [d(0.0		), d(0.0		), d(0.0		)],
										    [d(0.0		), d(0.0		), d(0.0		)],
										    [d(0.0		), d(0.0		), d(0.0		)],
										]
										lowercase						     =						(d(matrix[1][1]		) * d(matrix[2][2]		)) - (
										    d(matrix[1][2]		) * d(matrix[2][1]		)
										)
										lowercase						     =						-(
										    (d(matrix[1][0]		) * d(matrix[2][2]		)) - (d(matrix[1][2]		) * d(matrix[2][0]		))
										)
										lowercase						     =						(d(matrix[1][0]		) * d(matrix[2][1]		)) - (
										    d(matrix[1][1]		) * d(matrix[2][0]		)
										)
										lowercase						     =						-(
										    (d(matrix[0][1]		) * d(matrix[2][2]		)) - (d(matrix[0][2]		) * d(matrix[2][1]		))
										)
										lowercase						     =						(d(matrix[0][0]		) * d(matrix[2][2]		)) - (
										    d(matrix[0][2]		) * d(matrix[2][0]		)
										)
										lowercase						     =						-(
										    (d(matrix[0][0]		) * d(matrix[2][1]		)) - (d(matrix[0][1]		) * d(matrix[2][0]		))
										)
										lowercase						     =						(d(matrix[0][1]		) * d(matrix[1][2]		)) - (
										    d(matrix[0][2]		) * d(matrix[1][1]		)
										)
										lowercase						     =						-(
										    (d(matrix[0][0]		) * d(matrix[1][2]		)) - (d(matrix[0][2]		) * d(matrix[1][0]		))
										)
										lowercase						     =						(d(matrix[0][0]		) * d(matrix[1][1]		)) - (
										    d(matrix[0][1]		) * d(matrix[1][0]		)
										)

										# Transpose the cofactor matrix (Adjoint matrix)
										lowercase						     =						array(lowerCAmelCase__		)
										for i in range(3		):
															for j in range(3		):
																				lowercase						     =						cofactor_matrix[j][i]

        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix
										lowercase						     =						array(lowerCAmelCase__		)
										for i in range(3		):
															for j in range(3		):
																				inverse_matrix[i][j] /= d(lowerCAmelCase__		)

        # Calculate the inverse of the matrix
										return [[float(d(lowerCAmelCase__		)		) or 0.0 for n in row] for row in inverse_matrix]
					raise ValueError('''Please provide a matrix of size 2x2 or 3x3.'''		)




