






"""simple docstring"""







import io
import json
import unittest

from parameterized import parameterized

from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu


_lowerCAmelCase            =	get_tests_dir() + '/test_data/fsmt/fsmt_val_data.json'
with io.open(filename, 'r', encoding='utf-8') as f:
				_lowerCAmelCase            =	json.load(f)


@require_torch
class      UpperCamelCase		(unittest.TestCase     ):






						def      __snake_case      (		self  :int			, __magic_name__  :List[str]				)      ->Any:
										return FSMTTokenizer.from_pretrained(__magic_name__				)






						def      __snake_case      (		self  :List[Any]			, __magic_name__  :Optional[int]				)      ->int:
										lowercase    :      Union[str, Any]       = FSMTForConditionalGeneration.from_pretrained(__magic_name__				).to(__magic_name__				)
										if torch_device == "cuda":
														model.half()
										return model






						@parameterized.expand(
						    [
						        ["""en-ru""", 26.0],
						        ["""ru-en""", 22.0],
						        ["""en-de""", 22.0],
						        ["""de-en""", 29.0],
						    ]				)
						@slow
						def      __snake_case      (		self  :Union[str, Any]			, __magic_name__  :Dict			, __magic_name__  :Union[str, Any]				)      ->Union[str, Any]:
										# note: this test is not testing the best performance since it only evals a small batch
										# but it should be enough to detect a regression in the output quality
										lowercase    :      Tuple       = f"""facebook/wmt19-{pair}"""
										lowercase    :      List[Any]       = self.get_tokenizer(__magic_name__				)
										lowercase    :      List[Any]       = self.get_model(__magic_name__				)

										lowercase    :      List[Any]       = bleu_data[pair]["""src"""]
										lowercase    :      Tuple       = bleu_data[pair]["""tgt"""]

										lowercase    :      Dict       = tokenizer(__magic_name__			, return_tensors="""pt"""			, truncation=__magic_name__			, padding="""longest"""				).to(__magic_name__				)
										lowercase    :      Tuple       = model.generate(
										    input_ids=batch.input_ids			, num_beams=8			, )
										lowercase    :      Dict       = tokenizer.batch_decode(
										    __magic_name__			, skip_special_tokens=__magic_name__			, clean_up_tokenization_spaces=__magic_name__				)
										lowercase    :      Dict       = calculate_bleu(__magic_name__			, __magic_name__				)
										print(__magic_name__				)
										self.assertGreaterEqual(scores["""bleu"""]			, __magic_name__				)








"""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
