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add euler sgm preset

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Vladimir Mandic
2024-04-13 11:49:03 -04:00
parent bb0f2365f1
commit 744391af7e
3 changed files with 42 additions and 28 deletions
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modules/sd_samplers_diffusers.py
+34 -26
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@@ -40,51 +40,54 @@ config = {
# prediction_type is ideally set in model as well, but it maybe needed that we do auto-detect of model type in the future
'All': { 'num_train_timesteps': 1000, 'beta_start': 0.0001, 'beta_end': 0.02, 'beta_schedule': 'linear', 'prediction_type': 'epsilon' },
'DDIM': { 'clip_sample': False, 'set_alpha_to_one': True, 'steps_offset': 0, 'clip_sample_range': 1.0, 'sample_max_value': 1.0, 'timestep_spacing': 'linspace', 'rescale_betas_zero_snr': False },
'UniPC': { 'solver_order': 2, 'thresholding': False, 'sample_max_value': 1.0, 'predict_x0': 'bh2', 'lower_order_final': True },
'DEIS': { 'solver_order': 2, 'thresholding': False, 'sample_max_value': 1.0, 'algorithm_type': "deis", 'solver_type': "logrho", 'lower_order_final': True },
'UniPC': { 'solver_order': 2, 'thresholding': False, 'sample_max_value': 1.0, 'predict_x0': 'bh2', 'lower_order_final': True, 'timestep_spacing': 'linspace' },
'DEIS': { 'solver_order': 2, 'thresholding': False, 'sample_max_value': 1.0, 'algorithm_type': "deis", 'solver_type': "logrho", 'lower_order_final': True, 'timestep_spacing': 'linspace' },
'DPM++': { 'solver_order': 2, 'thresholding': False, 'sample_max_value': 1.0, 'algorithm_type': "dpmsolver++", 'solver_type': "midpoint", 'lower_order_final': True, 'use_karras_sigmas': False, 'final_sigmas_type': 'sigma_min' },
'DPM++ 2M': { 'thresholding': False, 'sample_max_value': 1.0, 'algorithm_type': "dpmsolver++", 'solver_type': "midpoint", 'lower_order_final': True, 'use_karras_sigmas': False, 'final_sigmas_type': 'zero' },
'DPM++ 2M': { 'thresholding': False, 'sample_max_value': 1.0, 'algorithm_type': "dpmsolver++", 'solver_type': "midpoint", 'lower_order_final': True, 'use_karras_sigmas': False, 'final_sigmas_type': 'zero', 'timestep_spacing': 'linspace' },
'DPM SDE': { 'use_karras_sigmas': False, 'noise_sampler_seed': None, 'timestep_spacing': 'linspace', 'steps_offset': 0 },
'DPM++ 2M EDM': { 'solver_order': 2, 'solver_type': 'midpoint', 'final_sigmas_type': 'zero', 'algorithm_type': 'dpmsolver++' },
'Euler EDM': { },
'Euler a': { 'rescale_betas_zero_snr': False },
'Euler': { 'interpolation_type': "linear", 'use_karras_sigmas': False, 'rescale_betas_zero_snr': False },
'Heun': { 'use_karras_sigmas': False },
'Euler a': { 'rescale_betas_zero_snr': False, 'timestep_spacing': 'linspace' },
'Euler': { 'interpolation_type': "linear", 'use_karras_sigmas': False, 'rescale_betas_zero_snr': False, 'timestep_spacing': 'linspace' },
'Heun': { 'use_karras_sigmas': False, 'timestep_spacing': 'linspace' },
'DDPM': { 'variance_type': "fixed_small", 'clip_sample': False, 'thresholding': False, 'clip_sample_range': 1.0, 'sample_max_value': 1.0, 'timestep_spacing': 'linspace', 'rescale_betas_zero_snr': False },
'KDPM2': { 'steps_offset': 0 },
'KDPM2 a': { 'steps_offset': 0 },
'KDPM2': { 'steps_offset': 0, 'timestep_spacing': 'linspace' },
'KDPM2 a': { 'steps_offset': 0, 'timestep_spacing': 'linspace' },
'LMSD': { 'use_karras_sigmas': False, 'timestep_spacing': 'linspace', 'steps_offset': 0 },
'PNDM': { 'skip_prk_steps': False, 'set_alpha_to_one': False, 'steps_offset': 0 },
'IPNDM': { },
'LCM': { 'beta_start': 0.00085, 'beta_end': 0.012, 'beta_schedule': "scaled_linear", 'set_alpha_to_one': True, 'rescale_betas_zero_snr': False, 'thresholding': False },
'TCD': { 'set_alpha_to_one': True, 'rescale_betas_zero_snr': False, 'beta_schedule': 'scaled_linear' },
'CMSI': { }, #{ 'sigma_min': 0.002, 'sigma_max': 80.0, 'sigma_data': 0.5, 's_noise': 1.0, 'rho': 7.0, 'clip_denoised': True },
'PNDM': { 'skip_prk_steps': False, 'set_alpha_to_one': False, 'steps_offset': 0, 'timestep_spacing': 'linspace' },
'SA Solver': {'predictor_order': 2, 'corrector_order': 2, 'thresholding': False, 'lower_order_final': True, 'use_karras_sigmas': False, 'timestep_spacing': 'linspace'},
'LCM': { 'beta_start': 0.00085, 'beta_end': 0.012, 'beta_schedule': "scaled_linear", 'set_alpha_to_one': True, 'rescale_betas_zero_snr': False, 'thresholding': False, 'timestep_spacing': 'linspace' },
'TCD': { 'set_alpha_to_one': True, 'rescale_betas_zero_snr': False, 'beta_schedule': 'scaled_linear' },
'Euler SGM': { 'timestep_spacing': "trailing", 'prediction_type': "sample" },
'Euler EDM': { },
'DPM++ 2M EDM': { 'solver_order': 2, 'solver_type': 'midpoint', 'final_sigmas_type': 'zero', 'algorithm_type': 'dpmsolver++' },
'CMSI': { }, #{ 'sigma_min': 0.002, 'sigma_max': 80.0, 'sigma_data': 0.5, 's_noise': 1.0, 'rho': 7.0, 'clip_denoised': True },
'IPNDM': { },
}
samplers_data_diffusers = [
sd_samplers_common.SamplerData('Default', None, [], {}),
sd_samplers_common.SamplerData('UniPC', lambda model: DiffusionSampler('UniPC', UniPCMultistepScheduler, model), [], {}),
sd_samplers_common.SamplerData('DEIS', lambda model: DiffusionSampler('DEIS', DEISMultistepScheduler, model), [], {}),
sd_samplers_common.SamplerData('PNDM', lambda model: DiffusionSampler('PNDM', PNDMScheduler, model), [], {}),
sd_samplers_common.SamplerData('IPNDM', lambda model: DiffusionSampler('IPNDM', IPNDMScheduler, model), [], {}),
sd_samplers_common.SamplerData('DDPM', lambda model: DiffusionSampler('DDPM', DDPMScheduler, model), [], {}),
sd_samplers_common.SamplerData('SA Solver', lambda model: DiffusionSampler('SA Solver', SASolverScheduler, model), [], {}),
sd_samplers_common.SamplerData('DDIM', lambda model: DiffusionSampler('DDIM', DDIMScheduler, model), [], {}),
sd_samplers_common.SamplerData('LMSD', lambda model: DiffusionSampler('LMSD', LMSDiscreteScheduler, model), [], {}),
sd_samplers_common.SamplerData('KDPM2', lambda model: DiffusionSampler('KDPM2', KDPM2DiscreteScheduler, model), [], {}),
sd_samplers_common.SamplerData('KDPM2 a', lambda model: DiffusionSampler('KDPM2 a', KDPM2AncestralDiscreteScheduler, model), [], {}),
sd_samplers_common.SamplerData('Heun', lambda model: DiffusionSampler('Heun', HeunDiscreteScheduler, model), [], {}),
sd_samplers_common.SamplerData('Euler', lambda model: DiffusionSampler('Euler', EulerDiscreteScheduler, model), [], {}),
sd_samplers_common.SamplerData('Euler a', lambda model: DiffusionSampler('Euler a', EulerAncestralDiscreteScheduler, model), [], {}),
sd_samplers_common.SamplerData('DPM++', lambda model: DiffusionSampler('DPM++', DPMSolverSinglestepScheduler, model), [], {}),
sd_samplers_common.SamplerData('DPM++ 2M', lambda model: DiffusionSampler('DPM++ 2M', DPMSolverMultistepScheduler, model), [], {}),
sd_samplers_common.SamplerData('DPM SDE', lambda model: DiffusionSampler('DPM SDE', DPMSolverSDEScheduler, model), [], {}),
sd_samplers_common.SamplerData('PNDM', lambda model: DiffusionSampler('PNDM', PNDMScheduler, model), [], {}),
sd_samplers_common.SamplerData('IPNDM', lambda model: DiffusionSampler('IPNDM', IPNDMScheduler, model), [], {}),
sd_samplers_common.SamplerData('DDPM', lambda model: DiffusionSampler('DDPM', DDPMScheduler, model), [], {}),
sd_samplers_common.SamplerData('LMSD', lambda model: DiffusionSampler('LMSD', LMSDiscreteScheduler, model), [], {}),
sd_samplers_common.SamplerData('KDPM2', lambda model: DiffusionSampler('KDPM2', KDPM2DiscreteScheduler, model), [], {}),
sd_samplers_common.SamplerData('KDPM2 a', lambda model: DiffusionSampler('KDPM2 a', KDPM2AncestralDiscreteScheduler, model), [], {}),
sd_samplers_common.SamplerData('DPM++ 2M EDM', lambda model: DiffusionSampler('DPM++ 2M EDM', EDMDPMSolverMultistepScheduler, model), [], {}),
sd_samplers_common.SamplerData('Euler EDM', lambda model: DiffusionSampler('Euler EDM', EDMEulerScheduler, model), [], {}),
sd_samplers_common.SamplerData('Euler', lambda model: DiffusionSampler('Euler', EulerDiscreteScheduler, model), [], {}),
sd_samplers_common.SamplerData('Euler a', lambda model: DiffusionSampler('Euler a', EulerAncestralDiscreteScheduler, model), [], {}),
sd_samplers_common.SamplerData('Heun', lambda model: DiffusionSampler('Heun', HeunDiscreteScheduler, model), [], {}),
sd_samplers_common.SamplerData('Euler SGM', lambda model: DiffusionSampler('Euler SGM', EulerDiscreteScheduler, model), [], {}),
sd_samplers_common.SamplerData('LCM', lambda model: DiffusionSampler('LCM', LCMScheduler, model), [], {}),
sd_samplers_common.SamplerData('TCD', lambda model: DiffusionSampler('TCD', TCDScheduler, model), [], {}),
sd_samplers_common.SamplerData('CMSI', lambda model: DiffusionSampler('CMSI', TCDScheduler, model), [], {}),
sd_samplers_common.SamplerData('SA Solver', lambda model: DiffusionSampler('SA Solver', SASolverScheduler, model), [], {}),
sd_samplers_common.SamplerData('CMSI', lambda model: DiffusionSampler('CMSI', CMStochasticIterativeScheduler, model), [], {}),
]
@@ -135,6 +138,9 @@ class DiffusionSampler:
self.config['beta_end'] = shared.opts.schedulers_beta_end
if 'rescale_betas_zero_snr' in self.config:
self.config['rescale_betas_zero_snr'] = shared.opts.schedulers_rescale_betas
if 'timestep_spacing' in self.config and shared.opts.schedulers_timestep_spacing != 'default':
print('HERE', shared.opts.schedulers_timestep_spacing)
self.config['timestep_spacing'] = shared.opts.schedulers_timestep_spacing
if 'num_train_timesteps' in self.config:
self.config['num_train_timesteps'] = shared.opts.schedulers_timesteps_range
if name in {'DPM++ 2M', 'DPM++ 2M EDM'}:
@@ -150,6 +156,8 @@ class DiffusionSampler:
del self.config['beta_end']
del self.config['beta_schedule']
del self.config['prediction_type']
if 'SGM' in name:
self.config['timestep_spacing'] = 'trailing'
# validate all config params
signature = inspect.signature(constructor, follow_wrapped=True)
possible = signature.parameters.keys()