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Running
on
Zero
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import pdb
from diffusion import gaussian_diffusion as gd
from diffusion.respace import SpacedDiffusion, space_timesteps
def create_gaussian_diffusion(DiffusionClass=SpacedDiffusion,use_ddim=False):
noise_schedule = 'cosine'
sigma_small = True
lambda_vel = 0.0
lambda_rcxyz = 0.0
lambda_fc = 0.0
# default params
predict_xstart = True # we always predict x_start (a.k.a. x0), that's our deal!
steps = 1000
scale_beta = 1. # no scaling
timestep_respacing =None
if use_ddim:
timestep_respacing = 'ddim50' # can be used for ddim sampling, we don't use it.
learn_sigma = False
rescale_timesteps = False
betas = gd.get_named_beta_schedule(noise_schedule, steps, scale_beta)
loss_type = gd.LossType.MSE
if not timestep_respacing:
timestep_respacing = [steps]
return DiffusionClass(
use_timesteps=space_timesteps(steps, timestep_respacing),
betas=betas,
model_mean_type=(
gd.ModelMeanType.EPSILON if not predict_xstart else gd.ModelMeanType.START_X
),
model_var_type=(
(
gd.ModelVarType.FIXED_LARGE
if not sigma_small
else gd.ModelVarType.FIXED_SMALL
)
if not learn_sigma
else gd.ModelVarType.LEARNED_RANGE
),
loss_type=loss_type,
rescale_timesteps=rescale_timesteps,
lambda_vel=lambda_vel,
lambda_rcxyz=lambda_rcxyz,
lambda_fc=lambda_fc,
) |