41 lines
1.4 KiB
Python
41 lines
1.4 KiB
Python
# These codes are copied from modelscope revision c58451baead80d83281f063d12fb377fad415257
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# This code is borrowed and modified from Guided Diffusion Model,
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# made publicly available under MIT license
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# at https://github.com/IDEA-CCNL/Fengshenbang-LM/tree/main/fengshen/examples/disco_project
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from modelscope.models.cv.motion_generation.modules.respace import \
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space_timesteps
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from . import gaussian_diffusion as gd
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from .respace import SpacedDiffusion
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def create_diffusion(diffusion_config):
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predict_xstart = False
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sigma_small = False
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learn_sigma = True
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steps = diffusion_config['steps']
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timestep_respacing = f'ddim{steps}'
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diffusion_steps = 1000
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rescale_timesteps = True
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betas = gd.get_named_beta_schedule('linear', diffusion_steps)
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loss_type = gd.LossType.MSE
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if not timestep_respacing:
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timestep_respacing = [diffusion_steps]
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diffusion = SpacedDiffusion(
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use_timesteps=space_timesteps(diffusion_steps, timestep_respacing),
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betas=betas,
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model_mean_type=(gd.ModelMeanType.EPSILON
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if not predict_xstart else gd.ModelMeanType.START_X),
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model_var_type=((gd.ModelVarType.FIXED_LARGE
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if not sigma_small else gd.ModelVarType.FIXED_SMALL)
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if not learn_sigma else gd.ModelVarType.LEARNED_RANGE),
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loss_type=loss_type,
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rescale_timesteps=rescale_timesteps)
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return diffusion
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