





from __future__ import annotations

from scipy.special import comb  # type: ignore

class        __SCREAMING_SNAKE_CASE					:






							def __init__(						self  , __lowerCAmelCase  ):
														UpperCamelCase__				     =			list_of_points
														# Degree determines the flexibility of the curve.
														# Degree = 1 will produce a straight line.
														UpperCamelCase__				     =			len(__lowerCAmelCase  ) - 1






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






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  ):
														assert 0 <= t <= 1, "Time t must be between 0 and 1."

														UpperCamelCase__				     =			self.basis_function(__lowerCAmelCase  )
														UpperCamelCase__				     =			0.0
														UpperCamelCase__				     =			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 				_lowerCamelCase		(						self  , __lowerCAmelCase = 0.01  ):
														from matplotlib import pyplot as plt  # type: ignore

														UpperCamelCase__				     =			[]  # x coordinates of points to plot
														UpperCamelCase__				     =			[]  # y coordinates of points to plot

														UpperCamelCase__				     =			0.0
														while t <= 1:
																					UpperCamelCase__				     =			self.bezier_curve_function(__lowerCAmelCase  )
																					to_plot_x.append(value[0]  )
																					to_plot_y.append(value[1]  )
																					t += step_size

														UpperCamelCase__				     =			[i[0] for i in self.list_of_points]
														UpperCamelCase__				     =			[i[1] for i in self.list_of_points]

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











import unittest

from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow


if is_flax_available():
					import jax

					from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
					from transformers.models.bert.modeling_flax_bert import FlaxBertModel
					from transformers.models.roberta.modeling_flax_roberta import FlaxRobertaModel

@require_flax
class        __SCREAMING_SNAKE_CASE					(     unittest.TestCase       ):






							@slow
							def 				_lowerCamelCase		(						self  ):
														for model_name in ["bert-base-cased", "bert-large-uncased"]:
																					with self.subTest(__lowerCAmelCase  ):
																												UpperCamelCase__				     =			AutoConfig.from_pretrained(__lowerCAmelCase  )
																												self.assertIsNotNone(__lowerCAmelCase  )
																												self.assertIsInstance(__lowerCAmelCase  , __lowerCAmelCase  )

																												UpperCamelCase__				     =			FlaxAutoModel.from_pretrained(__lowerCAmelCase  )
																												self.assertIsNotNone(__lowerCAmelCase  )
																												self.assertIsInstance(__lowerCAmelCase  , __lowerCAmelCase  )






							@slow
							def 				_lowerCamelCase		(						self  ):
														for model_name in ["roberta-base", "roberta-large"]:
																					with self.subTest(__lowerCAmelCase  ):
																												UpperCamelCase__				     =			AutoConfig.from_pretrained(__lowerCAmelCase  )
																												self.assertIsNotNone(__lowerCAmelCase  )
																												self.assertIsInstance(__lowerCAmelCase  , __lowerCAmelCase  )

																												UpperCamelCase__				     =			FlaxAutoModel.from_pretrained(__lowerCAmelCase  )
																												self.assertIsNotNone(__lowerCAmelCase  )
																												self.assertIsInstance(__lowerCAmelCase  , __lowerCAmelCase  )






							@slow
							def 				_lowerCamelCase		(						self  ):
														for model_name in ["bert-base-cased", "bert-large-uncased"]:
																					UpperCamelCase__				     =			AutoTokenizer.from_pretrained(__lowerCAmelCase  )
																					UpperCamelCase__				     =			FlaxBertModel.from_pretrained(__lowerCAmelCase  )
																					UpperCamelCase__				     =			tokenizer("""Do you support jax jitted function?"""  , return_tensors=TensorType.JAX  )

																					@jax.jit
																					def eval(**__lowerCAmelCase  ):
																												return model(**__lowerCAmelCase  )

																					eval(**__lowerCAmelCase  ).block_until_ready()






							@slow
							def 				_lowerCamelCase		(						self  ):
														for model_name in ["roberta-base", "roberta-large"]:
																					UpperCamelCase__				     =			AutoTokenizer.from_pretrained(__lowerCAmelCase  )
																					UpperCamelCase__				     =			FlaxRobertaModel.from_pretrained(__lowerCAmelCase  )
																					UpperCamelCase__				     =			tokenizer("""Do you support jax jitted function?"""  , return_tensors=TensorType.JAX  )

																					@jax.jit
																					def eval(**__lowerCAmelCase  ):
																												return model(**__lowerCAmelCase  )

																					eval(**__lowerCAmelCase  ).block_until_ready()






							def 				_lowerCamelCase		(						self  ):
														with self.assertRaisesRegex(
														    __lowerCAmelCase  , """bert-base is not a local folder and is not a valid model identifier"""  ):
																					UpperCamelCase__				     =			FlaxAutoModel.from_pretrained("""bert-base"""  )






							def 				_lowerCamelCase		(						self  ):
														with self.assertRaisesRegex(
														    __lowerCAmelCase  , r"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""  ):
																					UpperCamelCase__				     =			FlaxAutoModel.from_pretrained(__lowerCAmelCase  , revision="""aaaaaa"""  )






							def 				_lowerCamelCase		(						self  ):
														with self.assertRaisesRegex(
														    __lowerCAmelCase  , """hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack"""  , ):
																					UpperCamelCase__				     =			FlaxAutoModel.from_pretrained("""hf-internal-testing/config-no-model"""  )







							def 				_lowerCamelCase		(						self  ):
														with self.assertRaisesRegex(__lowerCAmelCase  , """Use `from_pt=True` to load this model"""  ):
																					UpperCamelCase__				     =			FlaxAutoModel.from_pretrained("""hf-internal-testing/tiny-bert-pt-only"""  )




