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trained_betas ignored in some schedulers (#635)

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* correcting the beta value assignment

* updating DDIM and LMSDiscreteFlax schedulers

* bringing back the changes that were lost as part of main branch merge
This commit is contained in:
V Vishnu Anirudh
2022-09-29 18:21:04 +01:00
committed by GitHub
parent f10576ad5c
commit 3dacbb94ca
5 changed files with 5 additions and 5 deletions
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2
src/diffusers/schedulers/scheduling_ddim.py
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@@ -131,7 +131,7 @@ class DDIMScheduler(SchedulerMixin, ConfigMixin):
if trained_betas is not None:
self.betas = torch.from_numpy(trained_betas)
if beta_schedule == "linear":
elif beta_schedule == "linear":
self.betas = torch.linspace(beta_start, beta_end, num_train_timesteps, dtype=torch.float32)
elif beta_schedule == "scaled_linear":
# this schedule is very specific to the latent diffusion model.

2
src/diffusers/schedulers/scheduling_lms_discrete.py
View File

@@ -86,7 +86,7 @@ class LMSDiscreteScheduler(SchedulerMixin, ConfigMixin):
if trained_betas is not None:
self.betas = torch.from_numpy(trained_betas)
if beta_schedule == "linear":
elif beta_schedule == "linear":
self.betas = torch.linspace(beta_start, beta_end, num_train_timesteps, dtype=torch.float32)
elif beta_schedule == "scaled_linear":
# this schedule is very specific to the latent diffusion model.

2
src/diffusers/schedulers/scheduling_lms_discrete_flax.py
View File

@@ -74,7 +74,7 @@ class FlaxLMSDiscreteScheduler(SchedulerMixin, ConfigMixin):
):
if trained_betas is not None:
self.betas = jnp.asarray(trained_betas)
if beta_schedule == "linear":
elif beta_schedule == "linear":
self.betas = jnp.linspace(beta_start, beta_end, num_train_timesteps, dtype=jnp.float32)
elif beta_schedule == "scaled_linear":
# this schedule is very specific to the latent diffusion model.

2
src/diffusers/schedulers/scheduling_pndm.py
View File

@@ -111,7 +111,7 @@ class PNDMScheduler(SchedulerMixin, ConfigMixin):
if trained_betas is not None:
self.betas = torch.from_numpy(trained_betas)
if beta_schedule == "linear":
elif beta_schedule == "linear":
self.betas = torch.linspace(beta_start, beta_end, num_train_timesteps, dtype=torch.float32)
elif beta_schedule == "scaled_linear":
# this schedule is very specific to the latent diffusion model.

2
src/diffusers/schedulers/scheduling_pndm_flax.py
View File

@@ -132,7 +132,7 @@ class FlaxPNDMScheduler(SchedulerMixin, ConfigMixin):
):
if trained_betas is not None:
self.betas = jnp.asarray(trained_betas)
if beta_schedule == "linear":
elif beta_schedule == "linear":
self.betas = jnp.linspace(beta_start, beta_end, num_train_timesteps, dtype=jnp.float32)
elif beta_schedule == "scaled_linear":
# this schedule is very specific to the latent diffusion model.