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[schedulers] hanlde dtype in add_noise #767

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Merged
merged 4 commits into from
Oct 7, 2022
Merged

[schedulers] hanlde dtype in add_noise #767

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21fc39b
handle dtype in vae and image2image pipeline
patil-suraj Oct 7, 2022
faf41fd
handle dtype in add noise
patil-suraj Oct 7, 2022
3536b43
don't modify vae and pipeline
patil-suraj Oct 7, 2022
9f48d79
remove the if
patil-suraj Oct 7, 2022
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8 changes: 3 additions & 5 deletions src/diffusers/schedulers/scheduling_ddim.py
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Original file line number Diff line number Diff line change
Expand Up @@ -300,11 +300,9 @@ def add_noise(
noise: torch.FloatTensor,
timesteps: torch.IntTensor,
) -> torch.FloatTensor:
if self.alphas_cumprod.device != original_samples.device:
self.alphas_cumprod = self.alphas_cumprod.to(original_samples.device)

if timesteps.device != original_samples.device:
timesteps = timesteps.to(original_samples.device)
# Make sure alphas_cumprod and timestep have same device and dtype as original_samples
self.alphas_cumprod = self.alphas_cumprod.to(device=original_samples.device, dtype=original_samples.dtype)
timesteps = timesteps.to(original_samples.device)

sqrt_alpha_prod = self.alphas_cumprod[timesteps] ** 0.5
sqrt_alpha_prod = sqrt_alpha_prod.flatten()
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8 changes: 3 additions & 5 deletions src/diffusers/schedulers/scheduling_ddpm.py
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Expand Up @@ -294,11 +294,9 @@ def add_noise(
noise: torch.FloatTensor,
timesteps: torch.IntTensor,
) -> torch.FloatTensor:
if self.alphas_cumprod.device != original_samples.device:
self.alphas_cumprod = self.alphas_cumprod.to(original_samples.device)

if timesteps.device != original_samples.device:
timesteps = timesteps.to(original_samples.device)
# Make sure alphas_cumprod and timestep have same device and dtype as original_samples
self.alphas_cumprod = self.alphas_cumprod.to(device=original_samples.device, dtype=original_samples.dtype)
timesteps = timesteps.to(original_samples.device)

sqrt_alpha_prod = self.alphas_cumprod[timesteps] ** 0.5
sqrt_alpha_prod = sqrt_alpha_prod.flatten()
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10 changes: 7 additions & 3 deletions src/diffusers/schedulers/scheduling_lms_discrete.py
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Expand Up @@ -257,9 +257,13 @@ def add_noise(
noise: torch.FloatTensor,
timesteps: torch.FloatTensor,
) -> torch.FloatTensor:
sigmas = self.sigmas.to(original_samples.device)
schedule_timesteps = self.timesteps.to(original_samples.device)
# Make sure sigmas and timesteps have the same device and dtype as original_samples
self.sigmas = self.sigmas.to(device=original_samples.device, dtype=original_samples.dtype)
self.timesteps = self.timesteps.to(original_samples.device)
timesteps = timesteps.to(original_samples.device)

schedule_timesteps = self.timesteps

if isinstance(timesteps, torch.IntTensor) or isinstance(timesteps, torch.LongTensor):
deprecate(
"timesteps as indices",
Expand All @@ -273,7 +277,7 @@ def add_noise(
else:
step_indices = [(schedule_timesteps == t).nonzero().item() for t in timesteps]

sigma = sigmas[step_indices].flatten()
sigma = self.sigmas[step_indices].flatten()
while len(sigma.shape) < len(original_samples.shape):
sigma = sigma.unsqueeze(-1)

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8 changes: 3 additions & 5 deletions src/diffusers/schedulers/scheduling_pndm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -400,11 +400,9 @@ def add_noise(
noise: torch.FloatTensor,
timesteps: torch.IntTensor,
) -> torch.Tensor:
if self.alphas_cumprod.device != original_samples.device:
self.alphas_cumprod = self.alphas_cumprod.to(original_samples.device)

if timesteps.device != original_samples.device:
timesteps = timesteps.to(original_samples.device)
# Make sure alphas_cumprod and timestep have same device and dtype as original_samples
self.alphas_cumprod = self.alphas_cumprod.to(device=original_samples.device, dtype=original_samples.dtype)
timesteps = timesteps.to(original_samples.device)

sqrt_alpha_prod = self.alphas_cumprod[timesteps] ** 0.5
sqrt_alpha_prod = sqrt_alpha_prod.flatten()
Expand Down