


import argparse

import OmegaConf
import torch

from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel







def        _lowerCamelCase(	lowercase__   , lowercase__   , lowercase__	)						->	Tuple:

		'''simple docstring'''







		__lowercase=			OmegaConf.load(lowercase__	)
		__lowercase=			torch.load(lowercase__   , map_location='cpu'	)['model']
		__lowercase=			list(state_dict.keys()	)

		# extract state_dict for VQVAE
		__lowercase=			{}
		__lowercase=			'first_stage_model.'
		for key in keys:
				if key.startswith(lowercase__	):
						__lowercase=			state_dict[key]

    # extract state_dict for UNetLDM
		__lowercase=			{}
		__lowercase=			'model.diffusion_model.'
		for key in keys:
				if key.startswith(lowercase__	):
						__lowercase=			state_dict[key]

		__lowercase=			config.model.params.first_stage_config.params
		__lowercase=			config.model.params.unet_config.params

		__lowercase=			VQModel(**lowercase__	).eval()
		vqvae.load_state_dict(lowercase__	)

		__lowercase=			UNetLDMModel(**lowercase__	).eval()
		unet.load_state_dict(lowercase__	)

		__lowercase=			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=lowercase__   , )

		__lowercase=			LDMPipeline(lowercase__   , lowercase__   , lowercase__	)
		pipeline.save_pretrained(lowercase__	)


if __name__ == "__main__":
	lowerCAmelCase           =		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)
	lowerCAmelCase           =		parser.parse_args()

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










from collections.abc import Sequence







def        _lowerCamelCase(	lowercase__   , lowercase__ = False	)						->	float:

		'''simple docstring'''







		if not arr:
				return 0

		__lowercase=			0 if allow_empty_subarrays else float('-inf'	)
		__lowercase=			0.0
		for num in arr:
				__lowercase=			max(0 if allow_empty_subarrays else num   , curr_sum + num	)
				__lowercase=			max(lowercase__   , lowercase__	)

		return max_sum


if __name__ == "__main__":
	from doctest import testmod

	testmod()

	lowerCAmelCase           =		[-2, 1, -3, 4, -1, 2, 1, -5, 4]
	print(F'{max_subarray_sum(nums) = }')






