Update src/loss.py
Browse files- src/loss.py +1 -1
src/loss.py
CHANGED
|
@@ -137,7 +137,7 @@ class SchedulerWrapper:
|
|
| 137 |
A.loss_scheduler=_A
|
| 138 |
A.loss_params_path=loss_params_path
|
| 139 |
def set_timesteps(A,num_inference_steps,**C):
|
| 140 |
-
D=
|
| 141 |
if A.loss_scheduler is _A:B=A.scheduler.set_timesteps(D,**C);A.timesteps=A.scheduler.timesteps;A.init_noise_sigma=A.scheduler.init_noise_sigma;A.order=A.scheduler.order;return B
|
| 142 |
else:B=A.loss_scheduler.set_timesteps(D,**C);A.timesteps=A.loss_scheduler.timesteps;A.init_noise_sigma=A.scheduler.init_noise_sigma;A.order=A.scheduler.order;return B
|
| 143 |
def step(B,model_output,timestep,sample,**F):
|
|
|
|
| 137 |
A.loss_scheduler=_A
|
| 138 |
A.loss_params_path=loss_params_path
|
| 139 |
def set_timesteps(A,num_inference_steps,**C):
|
| 140 |
+
D=11
|
| 141 |
if A.loss_scheduler is _A:B=A.scheduler.set_timesteps(D,**C);A.timesteps=A.scheduler.timesteps;A.init_noise_sigma=A.scheduler.init_noise_sigma;A.order=A.scheduler.order;return B
|
| 142 |
else:B=A.loss_scheduler.set_timesteps(D,**C);A.timesteps=A.loss_scheduler.timesteps;A.init_noise_sigma=A.scheduler.init_noise_sigma;A.order=A.scheduler.order;return B
|
| 143 |
def step(B,model_output,timestep,sample,**F):
|