






import glob
import os
from typing import Dict, List, Union

import torch

from diffusers.utils import is_safetensors_available


if is_safetensors_available():
  import safetensors.torch

from huggingface_hub import snapshot_download

from diffusers import DiffusionPipeline, __version__
from diffusers.schedulers.scheduling_utils import SCHEDULER_CONFIG_NAME
from diffusers.utils import CONFIG_NAME, DIFFUSERS_CACHE, ONNX_WEIGHTS_NAME, WEIGHTS_NAME




class 							lowerCAmelCase					(							UpperCamelCase__   ):







   """simple docstring"""







   def __init__( self			)    ->   List[str]:
    self.register_to_config()
    super().__init__()



   def    __magic_name__    ( self   ,   _A   ,   _A			)    ->   int:




    if dicta == dicta:
     return True
    else:
     __a    :	Tuple									=						self._remove_meta_keys(lowerCAmelCase__			)
     __a    :	str									=						self._remove_meta_keys(lowerCAmelCase__			)
     if configa == configa:
      print(f'''Warning !: Mismatch in keys {meta_keysa} and {meta_keysa}.'''			)
      return True
    return False



   def    __magic_name__    ( self   ,   _A			)    ->   Tuple:
    __a    :	Dict									=						[]
    __a    :	List[str]									=						config_dict.copy()
    for key in config_dict.keys():
     if key.startswith('_'			):
      temp_dict.pop(lowerCAmelCase__			)
      meta_keys.append(lowerCAmelCase__			)
    return (temp_dict, meta_keys)



   @torch.no_grad()
   def    __magic_name__    ( self   ,   _A   ,   **_A			)    ->   Optional[int]:
    __a    :	Dict									=						kwargs.pop('cache_dir'   ,   lowerCAmelCase__			)
    __a    :	Dict									=						kwargs.pop('resume_download'   ,   lowerCAmelCase__			)
    __a    :	Optional[Any]									=						kwargs.pop('force_download'   ,   lowerCAmelCase__			)
    __a    :	Tuple									=						kwargs.pop('proxies'   ,   lowerCAmelCase__			)
    __a    :	Dict									=						kwargs.pop('local_files_only'   ,   lowerCAmelCase__			)
    __a    :	List[Any]									=						kwargs.pop('use_auth_token'   ,   lowerCAmelCase__			)
    __a    :	int									=						kwargs.pop('revision'   ,   lowerCAmelCase__			)
    __a    :	int									=						kwargs.pop('torch_dtype'   ,   lowerCAmelCase__			)
    __a    :	List[str]									=						kwargs.pop('device_map'   ,   lowerCAmelCase__			)

    __a    :	Union[str, Any]									=						kwargs.pop('alpha'   ,   0.5			)
    __a    :	Any									=						kwargs.pop('interp'   ,   lowerCAmelCase__			)

    print('Received list'   ,   lowerCAmelCase__			)
    print(f'''Combining with alpha={alpha}, interpolation mode={interp}'''			)

    __a    :	List[str]									=						len(lowerCAmelCase__			)
    # Ignore result from model_index_json comparision of the two checkpoints
    __a    :	Dict									=						kwargs.pop('force'   ,   lowerCAmelCase__			)

    # If less than 2 checkpoints, nothing to merge. If more than 3, not supported for now.
    if checkpoint_count > 3 or checkpoint_count < 2:
     raise ValueError(
         'Received incorrect number of checkpoints to merge. Ensure that either 2 or 3 checkpoints are being'
         ' passed.'			)

    print('Received the right number of checkpoints'			)
    # chkpt0, chkpt1 = pretrained_model_name_or_path_list[0:2]
    # chkpt2 = pretrained_model_name_or_path_list[2] if checkpoint_count == 3 else None

    # Validate that the checkpoints can be merged
    # Step 1: Load the model config and compare the checkpoints. We'll compare the model_index.json first while ignoring the keys starting with '_'
    __a    :	List[Any]									=						[]
    for pretrained_model_name_or_path in pretrained_model_name_or_path_list:
     __a    :	int									=						DiffusionPipeline.load_config(
         lowerCAmelCase__   ,   cache_dir=lowerCAmelCase__   ,   resume_download=lowerCAmelCase__   ,   force_download=lowerCAmelCase__   ,   proxies=lowerCAmelCase__   ,   local_files_only=lowerCAmelCase__   ,   use_auth_token=lowerCAmelCase__   ,   revision=lowerCAmelCase__   ,   )
     config_dicts.append(lowerCAmelCase__			)

    __a    :	Tuple									=						True
    for idx in range(1   ,   len(lowerCAmelCase__			)			):
     comparison_result &= self._compare_model_configs(config_dicts[idx - 1]   ,   config_dicts[idx]			)
     if not force and comparison_result is False:
      raise ValueError('Incompatible checkpoints. Please check model_index.json for the models.'			)
      print(config_dicts[0]   ,   config_dicts[1]			)
    print('Compatible model_index.json files found'			)
    # Step 2: Basic Validation has succeeded. Let's download the models and save them into our local files.
    __a    :	List[str]									=						[]
    for pretrained_model_name_or_path, config_dict in zip(lowerCAmelCase__   ,   lowerCAmelCase__			):
     __a    :	int									=						[k for k in config_dict.keys() if not k.startswith('_'			)]
     __a    :	Dict									=						[os.path.join(lowerCAmelCase__   ,   '*'			) for k in folder_names]
     allow_patterns += [
         WEIGHTS_NAME,
         SCHEDULER_CONFIG_NAME,
         CONFIG_NAME,
         ONNX_WEIGHTS_NAME,
         DiffusionPipeline.config_name,
     ]
     __a    :	Dict									=						config_dict.get('_class_name'			)
     __a    :	Optional[int]									=						{"diffusers": __version__, "pipeline_class": requested_pipeline_class}

     __a    :	List[str]									=						(
         pretrained_model_name_or_path
         if os.path.isdir(lowerCAmelCase__			)
         else snapshot_download(
             lowerCAmelCase__   ,   cache_dir=lowerCAmelCase__   ,   resume_download=lowerCAmelCase__   ,   proxies=lowerCAmelCase__   ,   local_files_only=lowerCAmelCase__   ,   use_auth_token=lowerCAmelCase__   ,   revision=lowerCAmelCase__   ,   allow_patterns=lowerCAmelCase__   ,   user_agent=lowerCAmelCase__   ,   )
     )
     print('Cached Folder'   ,   lowerCAmelCase__			)
     cached_folders.append(lowerCAmelCase__			)

    # Step 3:-
    # Load the first checkpoint as a diffusion pipeline and modify its module state_dict in place
    __a    :	Any									=						DiffusionPipeline.from_pretrained(
        cached_folders[0]   ,   torch_dtype=lowerCAmelCase__   ,   device_map=lowerCAmelCase__			)
    final_pipe.to(self.device			)

    __a    :	List[str]									=						None
    if len(lowerCAmelCase__			) > 2:
     __a    :	Any									=						os.path.join(cached_folders[2]			)

    if interp == "sigmoid":
     __a    :	Union[str, Any]									=						CheckpointMergerPipeline.sigmoid
    elif interp == "inv_sigmoid":
     __a    :	Optional[int]									=						CheckpointMergerPipeline.inv_sigmoid
    elif interp == "add_diff":
     __a    :	Any									=						CheckpointMergerPipeline.add_difference
    else:
     __a    :	Tuple									=						CheckpointMergerPipeline.weighted_sum

    # Find each module's state dict.
    for attr in final_pipe.config.keys():
     if not attr.startswith('_'			):
      __a    :	int									=						os.path.join(cached_folders[1]   ,   lowerCAmelCase__			)
      if os.path.exists(lowerCAmelCase__			):
       __a    :	str									=						[
           *glob.glob(os.path.join(lowerCAmelCase__   ,   '*.safetensors'			)			),
           *glob.glob(os.path.join(lowerCAmelCase__   ,   '*.bin'			)			),
       ]
       __a    :	str									=						files[0] if len(lowerCAmelCase__			) > 0 else None
      if len(lowerCAmelCase__			) < 3:
       __a    :	Union[str, Any]									=						None
      else:
       __a    :	Dict									=						os.path.join(cached_folders[2]   ,   lowerCAmelCase__			)
       if os.path.exists(lowerCAmelCase__			):
        __a    :	List[Any]									=						[
            *glob.glob(os.path.join(lowerCAmelCase__   ,   '*.safetensors'			)			),
            *glob.glob(os.path.join(lowerCAmelCase__   ,   '*.bin'			)			),
        ]
        __a    :	Optional[Any]									=						files[0] if len(lowerCAmelCase__			) > 0 else None
        # For an attr if both checkpoint_path_1 and 2 are None, ignore.
        # If atleast one is present, deal with it according to interp method, of course only if the state_dict keys match.
      if checkpoint_path_a is None and checkpoint_path_a is None:
       print(f'''Skipping {attr}: not present in 2nd or 3d model'''			)
       continue
      try:
       __a    :	Union[str, Any]									=						getattr(lowerCAmelCase__   ,   lowerCAmelCase__			)
       if isinstance(lowerCAmelCase__   ,   lowerCAmelCase__			):  # ignore requires_safety_checker boolean
        continue
       __a    :	Tuple									=						getattr(lowerCAmelCase__   ,   'state_dict'			)
       __a    :	List[Any]									=						theta_a()

       __a    :	Any									=						getattr(lowerCAmelCase__   ,   'load_state_dict'			)
       __a    :	List[str]									=						(
           safetensors.torch.load_file(lowerCAmelCase__			)
           if (is_safetensors_available() and checkpoint_path_a.endswith('.safetensors'			))
           else torch.load(lowerCAmelCase__   ,   map_location='cpu'			)
       )
       __a    :	Tuple									=						None
       if checkpoint_path_a:
        __a    :	str									=						(
            safetensors.torch.load_file(lowerCAmelCase__			)
            if (is_safetensors_available() and checkpoint_path_a.endswith('.safetensors'			))
            else torch.load(lowerCAmelCase__   ,   map_location='cpu'			)
        )

       if not theta_a.keys() == theta_a.keys():
        print(f'''Skipping {attr}: key mismatch'''			)
        continue
       if theta_a and not theta_a.keys() == theta_a.keys():
        print(f'''Skipping {attr}:y mismatch'''			)
      except Exception as e:
       print(f'''Skipping {attr} do to an unexpected error: {str(lowerCAmelCase__			)}'''			)
       continue
      print(f'''MERGING {attr}'''			)

      for key in theta_a.keys():
       if theta_a:
        __a    :	Dict									=						theta_func(theta_a[key]   ,   theta_a[key]   ,   theta_a[key]   ,   lowerCAmelCase__			)
       else:
        __a    :	Dict									=						theta_func(theta_a[key]   ,   theta_a[key]   ,   lowerCAmelCase__   ,   lowerCAmelCase__			)

      del theta_a
      del theta_a
      update_theta_a(lowerCAmelCase__			)

      del theta_a
    return final_pipe



   @staticmethod
   def    __magic_name__    ( _A   ,   _A   ,   _A   ,   _A			)    ->   Union[str, Any]:
    return ((1 - alpha) * thetaa) + (alpha * thetaa)



   @staticmethod
   def    __magic_name__    ( _A   ,   _A   ,   _A   ,   _A			)    ->   List[str]:
    __a    :	Any									=						alpha * alpha * (3 - (2 * alpha))
    return thetaa + ((thetaa - thetaa) * alpha)



   @staticmethod
   def    __magic_name__    ( _A   ,   _A   ,   _A   ,   _A			)    ->   str:
    import math

    __a    :	Dict									=						0.5 - math.sin(math.asin(1.0 - 2.0 * alpha			) / 3.0			)
    return thetaa + ((thetaa - thetaa) * alpha)



   @staticmethod
   def    __magic_name__    ( _A   ,   _A   ,   _A   ,   _A			)    ->   str:
    return thetaa + (thetaa - thetaa) * (1.0 - alpha)












'''simple docstring'''


from __future__ import annotations

import random

from matplotlib import animation
from matplotlib import pyplot as plt

# Frame rate of the animation
SCREAMING_SNAKE_CASE_				      =							2_0

# Time between time steps in seconds
SCREAMING_SNAKE_CASE_				      =							INTERVAL / 1_0_0_0




class 							lowerCAmelCase					:







   """simple docstring"""







   def __init__( self   ,   _A   ,   _A   ,   _A   ,   _A   ,   _A = 1.0   ,   _A = 1.0   ,   _A = "blue"   ,   )    ->   None:
    __a    :	str									=						position_x
    __a    :	Optional[Any]									=						position_y
    __a    :	List[Any]									=						velocity_x
    __a    :	Tuple									=						velocity_y
    __a    :	Dict									=						mass
    __a    :	int									=						size
    __a    :	Tuple									=						color



   @property
   def    __magic_name__    ( self			)    ->   tuple[float, float]:
    return self.position_x, self.position_y



   @property
   def    __magic_name__    ( self			)    ->   tuple[float, float]:
    return self.velocity_x, self.velocity_y



   def    __magic_name__    ( self   ,   _A   ,   _A   ,   _A			)    ->   None:
    self.velocity_x += force_x * delta_time
    self.velocity_y += force_y * delta_time



   def    __magic_name__    ( self   ,   _A			)    ->   None:
    self.position_x += self.velocity_x * delta_time
    self.position_y += self.velocity_y * delta_time




class 							lowerCAmelCase					:







   """simple docstring"""







   def __init__( self   ,   _A   ,   _A = 1.0   ,   _A = 1.0   ,   _A = 0.0   ,   )    ->   None:
    __a    :	List[str]									=						bodies
    __a    :	List[str]									=						gravitation_constant
    __a    :	int									=						time_factor
    __a    :	List[str]									=						softening_factor



   def __len__( self			)    ->   int:
    return len(self.bodies			)



   def    __magic_name__    ( self   ,   _A			)    ->   None:
    for bodya in self.bodies:
     __a    :	Any									=						0.0
     __a    :	str									=						0.0
     for bodya in self.bodies:
      if bodya != bodya:
       __a    :	Optional[Any]									=						bodya.position_x - bodya.position_x
       __a    :	Dict									=						bodya.position_y - bodya.position_y

       # Calculation of the distance using Pythagoras's theorem
       # Extra factor due to the softening technique
       __a    :	Optional[Any]									=						(dif_x**2 + dif_y**2 + self.softening_factor) ** (
           1 / 2
       )

       # Newton's law of universal gravitation.
       force_x += (
           self.gravitation_constant * bodya.mass * dif_x / distance**3
       )
       force_y += (
           self.gravitation_constant * bodya.mass * dif_y / distance**3
       )

            # Update the body's velocity once all the force components have been added
     bodya.update_velocity(_A   ,   _A   ,   delta_time * self.time_factor			)

    # Update the positions only after all the velocities have been updated
    for body in self.bodies:
     body.update_position(delta_time * self.time_factor			)






def   lowerCAmelCase__			(					SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__		):
 body_system.update_system(SCREAMING_SNAKE_CASE__		)

 # Update the positions of the patches
 for patch, body in zip(SCREAMING_SNAKE_CASE__       ,		body_system.bodies		):
  __a    :	Dict									=						(body.position_x, body.position_y)






def   lowerCAmelCase__			(					SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__ = -1       ,		SCREAMING_SNAKE_CASE__ = 1       ,		SCREAMING_SNAKE_CASE__ = -1       ,		SCREAMING_SNAKE_CASE__ = 1       ,		):
 __a    :	int									=						plt.figure()
 fig.canvas.set_window_title(SCREAMING_SNAKE_CASE__		)
 __a    :	int									=						plt.axes(
     xlim=(x_start, x_end)       ,		ylim=(y_start, y_end)		)  # Set section to be plotted
 plt.gca().set_aspect('equal'		)  # Fix aspect ratio

 # Each body is drawn as a patch by the plt-function
 __a    :	str									=						[
     plt.Circle((body.position_x, body.position_y)       ,		body.size       ,		fc=body.color		)
     for body in body_system.bodies
 ]

 for patch in patches:
  ax.add_patch(SCREAMING_SNAKE_CASE__		)

 # Function called at each step of the animation
 def update(SCREAMING_SNAKE_CASE__		) -> list[plt.Circle]:
  update_step(SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__		)
  return patches

 __a    :	Dict									=						animation.FuncAnimation(  # noqa: F841
     SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		interval=SCREAMING_SNAKE_CASE__       ,		blit=SCREAMING_SNAKE_CASE__		)

 plt.show()






def   lowerCAmelCase__			(					):
 __a    :	Dict									=						0.970_0436
 __a    :	List[Any]									=						-0.2430_8753
 __a    :	Union[str, Any]									=						0.4_6620_3685
 __a    :	Any									=						0.4323_6573

 __a    :	Optional[int]									=						[
     Body(SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		size=0.2       ,		color='red'		),
     Body(-position_x       ,		-position_y       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		size=0.2       ,		color='green'		),
     Body(0       ,		0       ,		-2 * velocity_x       ,		-2 * velocity_y       ,		size=0.2       ,		color='blue'		),
 ]
 return BodySystem(SCREAMING_SNAKE_CASE__       ,		time_factor=3		)






def   lowerCAmelCase__			(					):
 __a    :	Optional[int]									=						7.34_76E22
 __a    :	List[Any]									=						5.9_72E24
 __a    :	List[Any]									=						1022
 __a    :	str									=						384399000
 __a    :	Optional[int]									=						6.6_74E-11

 # Calculation of the respective velocities so that total impulse is zero,
 # i.e. the two bodies together don't move
 __a    :	str									=						earth_mass * velocity_dif / (earth_mass + moon_mass)
 __a    :	Optional[int]									=						moon_velocity - velocity_dif

 __a    :	Union[str, Any]									=						Body(-earth_moon_distance       ,		0       ,		0       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		10000000       ,		'grey'		)
 __a    :	Union[str, Any]									=						Body(0       ,		0       ,		0       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		50000000       ,		'blue'		)
 return BodySystem([earth, moon]       ,		SCREAMING_SNAKE_CASE__       ,		time_factor=1000000		)






def   lowerCAmelCase__			(					):
 __a    :	Tuple									=						[]
 for _ in range(10		):
  __a    :	Dict									=						random.uniform(-0.5       ,		0.5		)
  __a    :	Optional[int]									=						random.uniform(-0.5       ,		0.5		)

  # Bodies are created pairwise with opposite velocities so that the
  # total impulse remains zero
  bodies.append(
      Body(
          random.uniform(-0.5       ,		0.5		)       ,		random.uniform(-0.5       ,		0.5		)       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		size=0.05       ,		)		)
  bodies.append(
      Body(
          random.uniform(-0.5       ,		0.5		)       ,		random.uniform(-0.5       ,		0.5		)       ,		-velocity_x       ,		-velocity_y       ,		size=0.05       ,		)		)
 return BodySystem(SCREAMING_SNAKE_CASE__       ,		0.01       ,		10       ,		0.1		)


if __name__ == "__main__":
  plot("Figure-8 solution to the 3-body-problem", example_a(), -2, 2, -2, 2)
  plot(
      "Moon's orbit around the earth",
      example_a(),
      -4_3_0_0_0_0_0_0_0,
      4_3_0_0_0_0_0_0_0,
      -4_3_0_0_0_0_0_0_0,
      4_3_0_0_0_0_0_0_0,
  )
  plot("Random system with many bodies", example_a(), -1.5, 1.5, -1.5, 1.5)




