






"""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      UpperCamelCase		(unittest.TestCase     ):






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






						def      __snake_case      (		self  :List[str]			, **__magic_name__  :str				)      ->Any:
										return RobertaTokenizer.from_pretrained(self.checkpoint			, **__magic_name__				)






						def      __snake_case      (		self  :Union[str, Any]			, **__magic_name__  :Tuple				)      ->str:
										return ClapFeatureExtractor.from_pretrained(self.checkpoint			, **__magic_name__				)






						def      __snake_case      (		self  :Dict				)      ->Tuple:
										shutil.rmtree(self.tmpdirname				)






						def      __snake_case      (		self  :Dict				)      ->Optional[int]:
										lowercase    :      Tuple       = self.get_tokenizer()
										lowercase    :      Dict       = self.get_feature_extractor()

										lowercase    :      Union[str, Any]       = ClapProcessor(tokenizer=__magic_name__			, feature_extractor=__magic_name__				)

										processor.save_pretrained(self.tmpdirname				)
										lowercase    :      List[Any]       = 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      __snake_case      (		self  :str				)      ->Union[str, Any]:
										lowercase    :      Any       = ClapProcessor(tokenizer=self.get_tokenizer()			, feature_extractor=self.get_feature_extractor()				)
										processor.save_pretrained(self.tmpdirname				)

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

										lowercase    :      List[Any]       = 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      __snake_case      (		self  :Dict				)      ->str:
										lowercase    :      List[str]       = self.get_feature_extractor()
										lowercase    :      Tuple       = self.get_tokenizer()

										lowercase    :      Union[str, Any]       = ClapProcessor(tokenizer=__magic_name__			, feature_extractor=__magic_name__				)

										lowercase    :      List[Any]       = floats_list((3, 1_000)				)

										lowercase    :      int       = feature_extractor(__magic_name__			, return_tensors="""np"""				)
										lowercase    :      str       = 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      __snake_case      (		self  :Optional[Any]				)      ->List[str]:
										lowercase    :      Dict       = self.get_feature_extractor()
										lowercase    :      Tuple       = self.get_tokenizer()

										lowercase    :      int       = ClapProcessor(tokenizer=__magic_name__			, feature_extractor=__magic_name__				)

										lowercase    :      Optional[Any]       = """This is a test string"""

										lowercase    :      List[str]       = processor(text=__magic_name__				)

										lowercase    :      Dict       = tokenizer(__magic_name__				)

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






						def      __snake_case      (		self  :int				)      ->Optional[int]:
										lowercase    :      Tuple       = self.get_feature_extractor()
										lowercase    :      Union[str, Any]       = self.get_tokenizer()

										lowercase    :      Optional[Any]       = ClapProcessor(tokenizer=__magic_name__			, feature_extractor=__magic_name__				)

										lowercase    :      Union[str, Any]       = [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

										lowercase    :      Any       = processor.batch_decode(__magic_name__				)
										lowercase    :      Union[str, Any]       = tokenizer.batch_decode(__magic_name__				)

										self.assertListEqual(__magic_name__			, __magic_name__				)






						def      __snake_case      (		self  :str				)      ->Optional[Any]:
										lowercase    :      Dict       = self.get_feature_extractor()
										lowercase    :      Optional[Any]       = self.get_tokenizer()

										lowercase    :      str       = 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"""			, )








"""simple docstring"""







from __future__ import annotations

from scipy.special import comb  # type: ignore


class      UpperCamelCase		:






						def __init__(		self  :Any			, __magic_name__  :list[tuple[float, float]]				)      ->str:
										lowercase    :      List[Any]       = list_of_points
										# Degree determines the flexibility of the curve.
										# Degree = 1 will produce a straight line.
										lowercase    :      Optional[int]       = len(__magic_name__				) - 1






						def      __snake_case      (		self  :List[str]			, __magic_name__  :float				)      ->list[float]:
										assert 0 <= t <= 1, "Time t must be between 0 and 1."
										lowercase    :      list[float]       = []
										for i in range(len(self.list_of_points				)				):
														# basis function for each i
														output_values.append(
														    comb(self.degree			, __magic_name__				) * ((1 - t) ** (self.degree - i)) * (t**i)				)
										# the basis must sum up to 1 for it to produce a valid Bezier curve.
										assert round(sum(__magic_name__				)			, 5				) == 1
										return output_values






						def      __snake_case      (		self  :List[str]			, __magic_name__  :float				)      ->tuple[float, float]:
										assert 0 <= t <= 1, "Time t must be between 0 and 1."

										lowercase    :      str       = self.basis_function(__magic_name__				)
										lowercase    :      Optional[int]       = 0.0
										lowercase    :      List[str]       = 0.0
										for i in range(len(self.list_of_points				)				):
														# For all points, sum up the product of i-th basis function and i-th point.
														x += basis_function[i] * self.list_of_points[i][0]
														y += basis_function[i] * self.list_of_points[i][1]
										return (x, y)






						def      __snake_case      (		self  :Tuple			, __magic_name__  :float = 0.01				)      ->List[str]:
										from matplotlib import pyplot as plt  # type: ignore

										lowercase    :      list[float]       = []  # x coordinates of points to plot
										lowercase    :      list[float]       = []  # y coordinates of points to plot

										lowercase    :      int       = 0.0
										while t <= 1:
														lowercase    :      List[Any]       = self.bezier_curve_function(__magic_name__				)
														to_plot_x.append(value[0]				)
														to_plot_y.append(value[1]				)
														t += step_size

										lowercase    :      Union[str, Any]       = [i[0] for i in self.list_of_points]
										lowercase    :      Optional[int]       = [i[1] for i in self.list_of_points]

										plt.plot(
										    __magic_name__			, __magic_name__			, color="""blue"""			, label="""Curve of Degree """ + str(self.degree				)			, )
										plt.scatter(__magic_name__			, __magic_name__			, color="""red"""			, label="""Control Points"""				)
										plt.legend()
										plt.show()


if __name__ == "__main__":
				import doctest

				doctest.testmod()

				BezierCurve([(1, 2), (3, 5)]).plot_curve()  # degree 1
				BezierCurve([(0, 0), (5, 5), (5, 0)]).plot_curve()  # degree 2
				BezierCurve([(0, 0), (5, 5), (5, 0), (2.5, -2.5)]).plot_curve()  # degree 3
