


import argparse

import OmegaConf
import torch

from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel




def  a   (lowerCAmelCase__		,				lowerCAmelCase__		,				lowerCAmelCase__   ):
   __a					=  OmegaConf.load(lowerCAmelCase__   )
   __a					=  torch.load(lowerCAmelCase__		,				map_location="""cpu"""   )["""model"""]
   __a					=  list(state_dict.keys()   )

   # extract state_dict for VQVAE
   __a					=  {}
   __a					=  """first_stage_model."""
   for key in keys:
      if key.startswith(lowerCAmelCase__   ):
         __a					=  state_dict[key]

    # extract state_dict for UNetLDM
   __a					=  {}
   __a					=  """model.diffusion_model."""
   for key in keys:
      if key.startswith(lowerCAmelCase__   ):
         __a					=  state_dict[key]

   __a					=  config.model.params.first_stage_config.params
   __a					=  config.model.params.unet_config.params

   __a					=  VQModel(**lowerCAmelCase__   ).eval()
   vqvae.load_state_dict(lowerCAmelCase__   )

   __a					=  UNetLDMModel(**lowerCAmelCase__   ).eval()
   unet.load_state_dict(lowerCAmelCase__   )

   __a					=  DDIMScheduler(
       timesteps=config.model.params.timesteps		,				beta_schedule="""scaled_linear"""		,				beta_start=config.model.params.linear_start		,				beta_end=config.model.params.linear_end		,				clip_sample=lowerCAmelCase__		,				)

   __a					=  LDMPipeline(lowerCAmelCase__		,				lowerCAmelCase__		,				lowerCAmelCase__   )
   pipeline.save_pretrained(lowerCAmelCase__   )


if __name__ == "__main__":
  SCREAMING_SNAKE_CASE							    =							argparse.ArgumentParser()
  parser.add_argument('--checkpoint_path', type=str, required=True)
  parser.add_argument('--config_path', type=str, required=True)
  parser.add_argument('--output_path', type=str, required=True)
  SCREAMING_SNAKE_CASE							    =							parser.parse_args()

  convert_ldm_original(args.checkpoint_path, args.config_path, args.output_path)







def  a   (lowerCAmelCase__   ):
   __a					=  False
   while is_sorted is False:  # Until all the indices are traversed keep looping
      __a					=  True
      for i in range(0		,				len(lowerCAmelCase__   ) - 1		,				2   ):  # iterating over all even indices
         if input_list[i] > input_list[i + 1]:
            __a	,    __a					=  input_list[i + 1], input_list[i]
            # swapping if elements not in order
            __a					=  False

      for i in range(1		,				len(lowerCAmelCase__   ) - 1		,				2   ):  # iterating over all odd indices
         if input_list[i] > input_list[i + 1]:
            __a	,    __a					=  input_list[i + 1], input_list[i]
            # swapping if elements not in order
            __a					=  False
   return input_list


if __name__ == "__main__":
  print('Enter list to be sorted')
  SCREAMING_SNAKE_CASE							    =							[int(x) for x in input().split()]
  # inputing elements of the list in one line
  SCREAMING_SNAKE_CASE							    =							odd_even_sort(input_list)
  print('The sorted list is')
  print(sorted_list)



