


'''simple docstring'''

from __future__ import annotations

from scipy.special import comb  # type: ignore





class      snake_case    :





  """simple docstring"""




  def __init__(    self			,  UpperCamelCase     ):







   """simple docstring"""
   lowerCamelCase_      =  list_of_points
   # Degree determines the flexibility of the curve.
   # Degree = 1 will produce a straight line.
   lowerCamelCase_      =  len(UpperCamelCase     ) - 1






  def   snake_case		(    self			,  UpperCamelCase     ):







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






  def   snake_case		(    self			,  UpperCamelCase     ):







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

   lowerCamelCase_      =  self.basis_function(UpperCamelCase     )
   lowerCamelCase_      =  0.0
   lowerCamelCase_      =  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			,  UpperCamelCase = 0.01     ):







   """simple docstring"""
   from matplotlib import pyplot as plt  # type: ignore

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

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

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

   plt.plot(
       UpperCamelCase			,  UpperCamelCase			,  color="blue"			,  label="Curve of Degree " + str(self.degree     )			,  )
   plt.scatter(UpperCamelCase			,  UpperCamelCase			,  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 os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union

import torch
from torch import nn

from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging


a_  :				Dict						= logging.get_logger(__name__)





class      snake_case    (    lowercase			):





  """simple docstring"""




  def __init__(    self			,  UpperCamelCase     ):







   """simple docstring"""
   super().__init__()
   lowerCamelCase_      =  nn.ModuleList(UpperCamelCase     )






  def   snake_case		(    self			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase = None			,  UpperCamelCase = None			,  UpperCamelCase = None			,  UpperCamelCase = None			,  UpperCamelCase = False			,  UpperCamelCase = True			,  ):







   """simple docstring"""
   for i, (image, scale, controlnet) in enumerate(zip(UpperCamelCase			,  UpperCamelCase			,  self.nets     )     ):
    lowerCamelCase_ ,lowerCamelCase_      =  controlnet(
        UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  )

    # merge samples
    if i == 0:
     lowerCamelCase_ ,lowerCamelCase_      =  down_samples, mid_sample
    else:
     lowerCamelCase_      =  [
         samples_prev + samples_curr
         for samples_prev, samples_curr in zip(UpperCamelCase			,  UpperCamelCase     )
     ]
     mid_block_res_sample += mid_sample

   return down_block_res_samples, mid_block_res_sample






  def   snake_case		(    self			,  UpperCamelCase			,  UpperCamelCase = True			,  UpperCamelCase = None			,  UpperCamelCase = False			,  UpperCamelCase = None			,  ):







   """simple docstring"""
   lowerCamelCase_      =  0
   lowerCamelCase_      =  save_directory
   for controlnet in self.nets:
    controlnet.save_pretrained(
        UpperCamelCase			,  is_main_process=UpperCamelCase			,  save_function=UpperCamelCase			,  safe_serialization=UpperCamelCase			,  variant=UpperCamelCase			,  )

    idx += 1
    lowerCamelCase_      =  model_path_to_save + f'''_{idx}'''







  @classmethod
  def   snake_case		(    cls			,  UpperCamelCase			,  **UpperCamelCase     ):







   """simple docstring"""
   lowerCamelCase_      =  0
   lowerCamelCase_      =  []

   # load controlnet and append to list until no controlnet directory exists anymore
   # first controlnet has to be saved under `./mydirectory/controlnet` to be compliant with `DiffusionPipeline.from_prertained`
   # second, third, ... controlnets have to be saved under `./mydirectory/controlnet_1`, `./mydirectory/controlnet_2`, ...
   lowerCamelCase_      =  pretrained_model_path
   while os.path.isdir(UpperCamelCase     ):
    lowerCamelCase_      =  ControlNetModel.from_pretrained(UpperCamelCase			,  **UpperCamelCase     )
    controlnets.append(UpperCamelCase     )

    idx += 1
    lowerCamelCase_      =  pretrained_model_path + f'''_{idx}'''

   logger.info(f'''{len(UpperCamelCase     )} controlnets loaded from {pretrained_model_path}.'''     )

   if len(UpperCamelCase     ) == 0:
    raise ValueError(
        f'''No ControlNets found under {os.path.dirname(UpperCamelCase     )}. Expected at least {pretrained_model_path + "_0"}.'''     )

   return cls(UpperCamelCase     )



