
import torch

from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device

from .test_schedulers import SchedulerCommonTest



class 		UpperCamelCase__  (       __lowercase    ):
   _SCREAMING_SNAKE_CASE      :							Optional[int]	       =      (KDPMaDiscreteScheduler,)
   _SCREAMING_SNAKE_CASE      :							List[str]	       =      10
   def       lowerCAmelCase			(self :					Optional[int]					,				**snake_case_ :					Optional[int]   ):
    __a :  List[Any]						=  {
        '''num_train_timesteps''': 1_1_0_0,
        '''beta_start''': 0.0001,
        '''beta_end''': 0.02,
        '''beta_schedule''': '''linear''',
    }

    config.update(**snake_case_   )
    return config
   def       lowerCAmelCase			(self :					Any   ):
    for timesteps in [1_0, 5_0, 1_0_0, 1_0_0_0]:
     self.check_over_configs(num_train_timesteps=snake_case_   )
   def       lowerCAmelCase			(self :					str   ):
    for beta_start, beta_end in zip([0.0_0001, 0.0001, 0.001]					,				[0.0002, 0.002, 0.02]   ):
     self.check_over_configs(beta_start=snake_case_					,				beta_end=snake_case_   )
   def       lowerCAmelCase			(self :					str   ):
    for schedule in ["linear", "scaled_linear"]:
     self.check_over_configs(beta_schedule=snake_case_   )
   def       lowerCAmelCase			(self :					int   ):
    for prediction_type in ["epsilon", "v_prediction"]:
     self.check_over_configs(prediction_type=snake_case_   )
   def       lowerCAmelCase			(self :					int   ):
    __a :  Union[str, Any]						=  self.scheduler_classes[0]
    __a :  str						=  self.get_scheduler_config(prediction_type='''v_prediction'''   )
    __a :  Any						=  scheduler_class(**snake_case_   )

    scheduler.set_timesteps(self.num_inference_steps   )

    __a :  Optional[int]						=  self.dummy_model()
    __a :  Dict						=  self.dummy_sample_deter * scheduler.init_noise_sigma
    __a :  Optional[int]						=  sample.to(snake_case_   )

    for i, t in enumerate(scheduler.timesteps   ):
     __a :  Optional[Any]						=  scheduler.scale_model_input(snake_case_					,				snake_case_   )

     __a :  List[Any]						=  model(snake_case_					,				snake_case_   )

     __a :  Union[str, Any]						=  scheduler.step(snake_case_					,				snake_case_					,				snake_case_   )
     __a :  Optional[int]						=  output.prev_sample

    __a :  Optional[Any]						=  torch.sum(torch.abs(snake_case_   )   )
    __a :  Dict						=  torch.mean(torch.abs(snake_case_   )   )

    if torch_device in ["cpu", "mps"]:
     assert abs(result_sum.item() - 4.6934E-07   ) < 1E-2
     assert abs(result_mean.item() - 6.1112E-10   ) < 1E-3
    else:
     # CUDA
     assert abs(result_sum.item() - 4.693_4286_5017_0972E-07   ) < 1E-2
     assert abs(result_mean.item() - 0.0002   ) < 1E-3
   def       lowerCAmelCase			(self :					Dict   ):
    if torch_device == "mps":
     return
    __a :  Dict						=  self.scheduler_classes[0]
    __a :  Optional[int]						=  self.get_scheduler_config()
    __a :  Tuple						=  scheduler_class(**snake_case_   )

    scheduler.set_timesteps(self.num_inference_steps   )

    __a :  str						=  self.dummy_model()
    __a :  Optional[int]						=  self.dummy_sample_deter * scheduler.init_noise_sigma
    __a :  Optional[int]						=  sample.to(snake_case_   )

    for i, t in enumerate(scheduler.timesteps   ):
     __a :  List[Any]						=  scheduler.scale_model_input(snake_case_					,				snake_case_   )

     __a :  List[Any]						=  model(snake_case_					,				snake_case_   )

     __a :  Dict						=  scheduler.step(snake_case_					,				snake_case_					,				snake_case_   )
     __a :  List[Any]						=  output.prev_sample

    __a :  Optional[int]						=  torch.sum(torch.abs(snake_case_   )   )
    __a :  Union[str, Any]						=  torch.mean(torch.abs(snake_case_   )   )

    if torch_device in ["cpu", "mps"]:
     assert abs(result_sum.item() - 20.4125   ) < 1E-2
     assert abs(result_mean.item() - 0.0266   ) < 1E-3
    else:
     # CUDA
     assert abs(result_sum.item() - 20.4125   ) < 1E-2
     assert abs(result_mean.item() - 0.0266   ) < 1E-3







   def       lowerCAmelCase			(self :					Tuple   ):
    if torch_device == "mps":
     return
    __a :  Tuple						=  self.scheduler_classes[0]
    __a :  Dict						=  self.get_scheduler_config()
    __a :  List[str]						=  scheduler_class(**snake_case_   )

    scheduler.set_timesteps(self.num_inference_steps					,				device=snake_case_   )

    __a :  Dict						=  self.dummy_model()
    __a :  Optional[int]						=  self.dummy_sample_deter.to(snake_case_   ) * scheduler.init_noise_sigma

    for t in scheduler.timesteps:
     __a :  Tuple						=  scheduler.scale_model_input(snake_case_					,				snake_case_   )

     __a :  Union[str, Any]						=  model(snake_case_					,				snake_case_   )

     __a :  str						=  scheduler.step(snake_case_					,				snake_case_					,				snake_case_   )
     __a :  Dict						=  output.prev_sample

    __a :  Union[str, Any]						=  torch.sum(torch.abs(snake_case_   )   )
    __a :  Tuple						=  torch.mean(torch.abs(snake_case_   )   )

    if str(snake_case_   ).startswith('''cpu'''   ):
     # The following sum varies between 148 and 156 on mps. Why?
     assert abs(result_sum.item() - 20.4125   ) < 1E-2
     assert abs(result_mean.item() - 0.0266   ) < 1E-3
    else:
     # CUDA
     assert abs(result_sum.item() - 20.4125   ) < 1E-2
     assert abs(result_mean.item() - 0.0266   ) < 1E-3


from __future__ import annotations

from typing import Any



class 		UpperCamelCase__  :
   def __init__(self :					Union[str, Any]					,				snake_case_ :					int   ):
    __a :  Dict						=  num_of_nodes
    __a :  list[list[int]]						=  []
    __a :  dict[int, int]						=  {}
   def       lowerCAmelCase			(self :					Optional[Any]					,				snake_case_ :					int					,				snake_case_ :					int					,				snake_case_ :					int   ):
    self.m_edges.append([u_node, v_node, weight]   )
   def       lowerCAmelCase			(self :					Any					,				snake_case_ :					int   ):

    if self.m_component[u_node] == u_node:
     return u_node
    return self.find_component(self.m_component[u_node]   )
   def       lowerCAmelCase			(self :					str					,				snake_case_ :					int   ):

    if self.m_component[u_node] != u_node:
     for k in self.m_component:
      __a :  Optional[int]						=  self.find_component(snake_case_   )
   def       lowerCAmelCase			(self :					Any					,				snake_case_ :					list[int]					,				snake_case_ :					int					,				snake_case_ :					int   ):

    if component_size[u_node] <= component_size[v_node]:
     __a :  List[str]						=  v_node
     component_size[v_node] += component_size[u_node]
     self.set_component(snake_case_   )

    elif component_size[u_node] >= component_size[v_node]:
     __a :  Optional[int]						=  self.find_component(snake_case_   )
     component_size[u_node] += component_size[v_node]
     self.set_component(snake_case_   )







   def       lowerCAmelCase			(self :					Optional[Any]   ):
    __a :  str						=  []
    __a :  int						=  0

    __a :  list[Any]						=  [-1] * self.m_num_of_nodes

    # A list of components (initialized to all of the nodes)
    for node in range(self.m_num_of_nodes   ):
     self.m_component.update({node: node}   )
     component_size.append(1   )

    __a :  Union[str, Any]						=  self.m_num_of_nodes

    while num_of_components > 1:
     for edge in self.m_edges:
      __a				,       __a				,       __a :  Optional[Any]						=  edge

      __a :  List[str]						=  self.m_component[u]
      __a :  List[Any]						=  self.m_component[v]

      if u_component != v_component:

       for component in (u_component, v_component):
        if (
            minimum_weight_edge[component] == -1
            or minimum_weight_edge[component][2] > w
        ):
         __a :  str						=  [u, v, w]

     for edge in minimum_weight_edge:
      if isinstance(snake_case_					,				snake_case_   ):
       __a				,       __a				,       __a :  str						=  edge

       __a :  Any						=  self.m_component[u]
       __a :  Any						=  self.m_component[v]

       if u_component != v_component:
        mst_weight += w
        self.union(snake_case_					,				snake_case_					,				snake_case_   )
        print(f"Added edge [{u} - {v}]\nAdded weight: {w}\n"   )
        num_of_components -= 1

     __a :  Optional[int]						=  [-1] * self.m_num_of_nodes
    print(f"The total weight of the minimal spanning tree is: {mst_weight}"   )





def    __UpperCamelCase     (				):
 pass


if __name__ == "__main__":
      import doctest

      doctest.testmod()
