

"""simple docstring"""





import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
							import torch

							from transformers.generation import DisjunctiveConstraint







@require_torch
class 				SCREAMING_SNAKE_CASE					(		unittest.TestCase       ):






					"""simple docstring"""



					def        __lowerCAmelCase (       self			:				Any		):
						# For consistency across different places the DisjunctiveConstraint is called,
						# dc.token_ids is a list of integers. It is also initialized only by integers.

						lowerCAmelCase__	:						List[str]  				=	[[1, 2, 4], [1, 2, 3, 4]]
						lowerCAmelCase__	:						Optional[int]  				=	DisjunctiveConstraint(lowercase_		)
						self.assertTrue(isinstance(dc.token_ids   ,lowercase_		)		)

						with self.assertRaises(lowercase_		):
							DisjunctiveConstraint(torch.LongTensor([[1, 2, 4], [1, 2, 3]]		)		)

						with self.assertRaises(lowercase_		):
							DisjunctiveConstraint([torch.LongTensor([1, 2, 4]		), torch.LongTensor([1, 2, 3, 4, 5]		)]		)







					def        __lowerCAmelCase (       self			:				Tuple		):
						# We can't have constraints that are complete subsets of another. This leads to a preverse
						# interpretation of "constraint fulfillment": does generating [1,2,3] fulfill the constraint?
						# It would mean that it generated [1,2] which fulfills it, but it's in the middle of potentially
						# fulfilling [1,2,3,4]. If we believe that [1,2,3] does fulfill the constraint, then the algorithm
						# will necessarily never reach [1,2,3,4], giving users a false sense of control (better to just not allow it).
						lowerCAmelCase__	:						List[str]  				=	[[1, 2], [1, 2, 3, 4]]

						with self.assertRaises(lowercase_		):
							DisjunctiveConstraint(lowercase_		)  # fails here







					def        __lowerCAmelCase (       self			:				Optional[int]		):
						lowerCAmelCase__	:						str  				=	[[1, 2, 3], [1, 2, 4]]

						lowerCAmelCase__	:						Optional[int]  				=	DisjunctiveConstraint(lowercase_		)

						lowerCAmelCase__				,lowerCAmelCase__				,lowerCAmelCase__	:						Optional[int]  				=	dc.update(1		)
						lowerCAmelCase__	:						int  				=	stepped is True and completed is False and reset is False
						self.assertTrue(lowercase_		)
						self.assertTrue(not dc.completed		)
						self.assertTrue(dc.current_seq == [1]		)

						lowerCAmelCase__				,lowerCAmelCase__				,lowerCAmelCase__	:						Optional[Any]  				=	dc.update(2		)
						lowerCAmelCase__	:						Optional[Any]  				=	stepped is True and completed is False and reset is False
						self.assertTrue(lowercase_		)
						self.assertTrue(not dc.completed		)
						self.assertTrue(dc.current_seq == [1, 2]		)

						lowerCAmelCase__				,lowerCAmelCase__				,lowerCAmelCase__	:						Union[str, Any]  				=	dc.update(3		)
						lowerCAmelCase__	:						Any  				=	stepped is True and completed is True and reset is False
						self.assertTrue(lowercase_		)
						self.assertTrue(dc.completed		)  # Completed!
						self.assertTrue(dc.current_seq == [1, 2, 3]		)







					def        __lowerCAmelCase (       self			:				Union[str, Any]		):
						lowerCAmelCase__	:						Optional[int]  				=	[[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

						lowerCAmelCase__	:						List[Any]  				=	DisjunctiveConstraint(lowercase_		)

						lowerCAmelCase__				,lowerCAmelCase__				,lowerCAmelCase__	:						Any  				=	dc.update(1		)
						self.assertTrue(not dc.completed		)
						self.assertTrue(dc.current_seq == [1]		)

						lowerCAmelCase__				,lowerCAmelCase__				,lowerCAmelCase__	:						Optional[Any]  				=	dc.update(2		)
						self.assertTrue(not dc.completed		)
						self.assertTrue(dc.current_seq == [1, 2]		)

						lowerCAmelCase__				,lowerCAmelCase__				,lowerCAmelCase__	:						Any  				=	dc.update(4		)
						self.assertTrue(not dc.completed		)
						self.assertTrue(dc.current_seq == [1, 2, 4]		)

						lowerCAmelCase__				,lowerCAmelCase__				,lowerCAmelCase__	:						Dict  				=	dc.update(5		)
						self.assertTrue(dc.completed		)  # Completed!
						self.assertTrue(dc.current_seq == [1, 2, 4, 5]		)

						dc.reset()

						lowerCAmelCase__				,lowerCAmelCase__				,lowerCAmelCase__	:						Optional[int]  				=	dc.update(1		)
						self.assertTrue(not dc.completed		)
						self.assertTrue(dc.remaining() == 3		)
						self.assertTrue(dc.current_seq == [1]		)

						lowerCAmelCase__				,lowerCAmelCase__				,lowerCAmelCase__	:						Dict  				=	dc.update(2		)
						self.assertTrue(not dc.completed		)
						self.assertTrue(dc.remaining() == 2		)
						self.assertTrue(dc.current_seq == [1, 2]		)

						lowerCAmelCase__				,lowerCAmelCase__				,lowerCAmelCase__	:						List[str]  				=	dc.update(5		)
						self.assertTrue(dc.completed		)  # Completed!
						self.assertTrue(dc.remaining() == 0		)
						self.assertTrue(dc.current_seq == [1, 2, 5]		)








"""simple docstring"""
from __future__ import annotations

from scipy.special import comb  # type: ignore



class 			_UpperCAmelCase :






		'''simple docstring'''

		def __init__(self				,       a_					):





			'''simple docstring'''

			__snake_case	:						List[str]						=				list_of_points
			# Degree determines the flexibility of the curve.
			# Degree = 1 will produce a straight line.
			__snake_case	:						Optional[Any]						=				len(a_					) - 1



		def 				SCREAMING_SNAKE_CASE  (self				,       a_					):





			'''simple docstring'''

			assert 0 <= t <= 1, "Time t must be between 0 and 1."
			__snake_case	:						list[float]						=				[]
			for i in range(len(self.list_of_points					)					):
				# basis function for each i
				output_values.append(
				    comb(self.degree				,       a_					) * ((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(a_					)				,       5					) == 1
			return output_values



		def 				SCREAMING_SNAKE_CASE  (self				,       a_					):





			'''simple docstring'''

			assert 0 <= t <= 1, "Time t must be between 0 and 1."

			__snake_case	:						List[str]						=				self.basis_function(a_					)
			__snake_case	:						str						=				0.0
			__snake_case	:						Union[str, Any]						=				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 				SCREAMING_SNAKE_CASE  (self				,       a_ = 0.01					):





			'''simple docstring'''

			from matplotlib import pyplot as plt  # type: ignore

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

			__snake_case	:						int						=				0.0
			while t <= 1:
				__snake_case	:						Union[str, Any]						=				self.bezier_curve_function(a_					)
				to_plot_x.append(value[0]					)
				to_plot_y.append(value[1]					)
				t += step_size

			__snake_case	:						List[Any]						=				[i[0] for i in self.list_of_points]
			__snake_case	:						Any						=				[i[1] for i in self.list_of_points]

			plt.plot(
			    a_				,       a_				,       color='''blue'''				,       label='''Curve of Degree ''' + str(self.degree					)				,       )
			plt.scatter(a_				,       a_				,       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





