


'''simple docstring'''



from __future__ import annotations

from scipy.special import comb  # type: ignore





class    UpperCAmelCase_  :





    """simple docstring"""






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







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







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

         __lowerCamelCase   :	Union[str, Any]								=		self.basis_function(SCREAMING_SNAKE_CASE_	)
         __lowerCamelCase   :	Union[str, Any]								=		0.0
         __lowerCamelCase   :	List[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       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_ = 0.0_1	)				->     Optional[int]:
         from matplotlib import pyplot as plt  # type: ignore

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

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

         __lowerCamelCase   :	Union[str, Any]								=		[i[0] for i in self.list_of_points]
         __lowerCamelCase   :	Tuple								=		[i[1] for i in self.list_of_points]

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










'''simple docstring'''



import gc
import unittest

from parameterized import parameterized

from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow


if is_flax_available():
      import jax
      import jax.numpy as jnp





@slow
@require_flax
class    UpperCAmelCase_  (unittest.TestCase  ):





    """simple docstring"""






    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_	)				->     Optional[int]:
         return f'gaussian_noise_s={seed}_shape={"_".join([str(SCREAMING_SNAKE_CASE_	) for s in shape]	)}.npy'







    def       lowercase_				(							self	)				->     Optional[Any]:
         # clean up the VRAM after each test
         super().tearDown()
         gc.collect()







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_=0			,     SCREAMING_SNAKE_CASE_=(4, 4, 64, 64)			,     SCREAMING_SNAKE_CASE_=False	)				->     str:
         __lowerCamelCase   :	List[str]								=		jnp.bfloataa if fpaa else jnp.floataa
         __lowerCamelCase   :	Tuple								=		jnp.array(load_hf_numpy(self.get_file_format(SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_	)	)			,     dtype=SCREAMING_SNAKE_CASE_	)
         return image







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_=False			,     SCREAMING_SNAKE_CASE_="CompVis/stable-diffusion-v1-4"	)				->     Dict:
         __lowerCamelCase   :	Union[str, Any]								=		jnp.bfloataa if fpaa else jnp.floataa
         __lowerCamelCase   :	Optional[Any]								=		'bf16' if fpaa else None

         __lowerCamelCase				,       __lowerCamelCase   :	str								=		FlaxUNetaDConditionModel.from_pretrained(
             SCREAMING_SNAKE_CASE_			,     subfolder='unet'			,     dtype=SCREAMING_SNAKE_CASE_			,     revision=SCREAMING_SNAKE_CASE_	)
         return model, params







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_=0			,     SCREAMING_SNAKE_CASE_=(4, 77, 7_68)			,     SCREAMING_SNAKE_CASE_=False	)				->     Union[str, Any]:
         __lowerCamelCase   :	Any								=		jnp.bfloataa if fpaa else jnp.floataa
         __lowerCamelCase   :	Optional[Any]								=		jnp.array(load_hf_numpy(self.get_file_format(SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_	)	)			,     dtype=SCREAMING_SNAKE_CASE_	)
         return hidden_states







    @parameterized.expand(
        [
            # fmt: off
            [83, 4, [-0.2_3_2_3, -0.1_3_0_4, 0.0_8_1_3, -0.3_0_9_3, -0.0_9_1_9, -0.1_5_7_1, -0.1_1_2_5, -0.5_8_0_6]],
            [17, 0.5_5, [-0.0_8_3_1, -0.2_4_4_3, 0.0_9_0_1, -0.0_9_1_9, 0.3_3_9_6, 0.0_1_0_3, -0.3_7_4_3, 0.0_7_0_1]],
            [8, 0.8_9, [-0.4_8_6_3, 0.0_8_5_9, 0.0_8_7_5, -0.1_6_5_8, 0.9_1_9_9, -0.0_1_1_4, 0.4_8_3_9, 0.4_6_3_9]],
            [3, 10_00, [-0.5_6_4_9, 0.2_4_0_2, -0.5_5_1_8, 0.1_2_4_8, 1.1_3_2_8, -0.2_4_4_3, -0.0_3_2_5, -1.0_0_7_8]],
            # fmt: on
        ]	)
    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_	)				->     Any:
         __lowerCamelCase				,       __lowerCamelCase   :	Tuple								=		self.get_unet_model(model_id='CompVis/stable-diffusion-v1-4'			,     fpaa=SCREAMING_SNAKE_CASE_	)
         __lowerCamelCase   :	Any								=		self.get_latents(SCREAMING_SNAKE_CASE_			,     fpaa=SCREAMING_SNAKE_CASE_	)
         __lowerCamelCase   :	int								=		self.get_encoder_hidden_states(SCREAMING_SNAKE_CASE_			,     fpaa=SCREAMING_SNAKE_CASE_	)

         __lowerCamelCase   :	List[Any]								=		model.apply(
             {'params': params}			,     SCREAMING_SNAKE_CASE_			,     jnp.array(SCREAMING_SNAKE_CASE_			,     dtype=jnp.intaa	)			,     encoder_hidden_states=SCREAMING_SNAKE_CASE_			,     ).sample

         assert sample.shape == latents.shape

         __lowerCamelCase   :	Any								=		jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())	)			,     dtype=jnp.floataa	)
         __lowerCamelCase   :	Optional[Any]								=		jnp.array(SCREAMING_SNAKE_CASE_			,     dtype=jnp.floataa	)

         # Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, in the same hardware
         assert jnp.allclose(SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_			,     atol=1E-2	)







    @parameterized.expand(
        [
            # fmt: off
            [83, 4, [0.1_5_1_4, 0.0_8_0_7, 0.1_6_2_4, 0.1_0_1_6, -0.1_8_9_6, 0.0_2_6_3, 0.0_6_7_7, 0.2_3_1_0]],
            [17, 0.5_5, [0.1_1_6_4, -0.0_2_1_6, 0.0_1_7_0, 0.1_5_8_9, -0.3_1_2_0, 0.1_0_0_5, -0.0_5_8_1, -0.1_4_5_8]],
            [8, 0.8_9, [-0.1_7_5_8, -0.0_1_6_9, 0.1_0_0_4, -0.1_4_1_1, 0.1_3_1_2, 0.1_1_0_3, -0.1_9_9_6, 0.2_1_3_9]],
            [3, 10_00, [0.1_2_1_4, 0.0_3_5_2, -0.0_7_3_1, -0.1_5_6_2, -0.0_9_9_4, -0.0_9_0_6, -0.2_3_4_0, -0.0_5_3_9]],
            # fmt: on
        ]	)
    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_	)				->     Optional[int]:
         __lowerCamelCase				,       __lowerCamelCase   :	List[str]								=		self.get_unet_model(model_id='stabilityai/stable-diffusion-2'			,     fpaa=SCREAMING_SNAKE_CASE_	)
         __lowerCamelCase   :	int								=		self.get_latents(SCREAMING_SNAKE_CASE_			,     shape=(4, 4, 96, 96)			,     fpaa=SCREAMING_SNAKE_CASE_	)
         __lowerCamelCase   :	Optional[int]								=		self.get_encoder_hidden_states(SCREAMING_SNAKE_CASE_			,     shape=(4, 77, 10_24)			,     fpaa=SCREAMING_SNAKE_CASE_	)

         __lowerCamelCase   :	List[str]								=		model.apply(
             {'params': params}			,     SCREAMING_SNAKE_CASE_			,     jnp.array(SCREAMING_SNAKE_CASE_			,     dtype=jnp.intaa	)			,     encoder_hidden_states=SCREAMING_SNAKE_CASE_			,     ).sample

         assert sample.shape == latents.shape

         __lowerCamelCase   :	Optional[int]								=		jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())	)			,     dtype=jnp.floataa	)
         __lowerCamelCase   :	Tuple								=		jnp.array(SCREAMING_SNAKE_CASE_			,     dtype=jnp.floataa	)

         # Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, on the same hardware
         assert jnp.allclose(SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_			,     atol=1E-2	)






