Revert "enforce zero terminal snr for cosine schedule"

This reverts commit 6d15667.

Author: lucidrains

README.md

@@ -311,11 +311,3 @@ You could consider adding a suitable metric to the training loop yourself after
     year    = {2023}
 }
 ```
-
-```bibtex
-@inproceedings{Lin2023CommonDN,
-    title   = {Common Diffusion Noise Schedules and Sample Steps are Flawed},
-    author  = {Shanchuan Lin and Bingchen Liu and Jiashi Li and Xiao Yang},
-    year    = {2023}
-}
-```

denoising_diffusion_pytorch/denoising_diffusion_pytorch.py

@@ -424,7 +424,7 @@ def cosine_beta_schedule(timesteps, s = 0.008):
     alphas_cumprod = torch.cos((t + s) / (1 + s) * math.pi * 0.5) ** 2
     alphas_cumprod = alphas_cumprod / alphas_cumprod[0]
     betas = 1 - (alphas_cumprod[1:] / alphas_cumprod[:-1])
-    return torch.clip(betas, 0, 1.)
+    return torch.clip(betas, 0, 0.999)
 
 def sigmoid_beta_schedule(timesteps, start = -3, end = 3, tau = 1, clamp_min = 1e-5):
     """
@@ -439,7 +439,7 @@ def sigmoid_beta_schedule(timesteps, start = -3, end = 3, tau = 1, clamp_min = 1
     alphas_cumprod = (-((t * (end - start) + start) / tau).sigmoid() + v_end) / (v_end - v_start)
     alphas_cumprod = alphas_cumprod / alphas_cumprod[0]
     betas = 1 - (alphas_cumprod[1:] / alphas_cumprod[:-1])
-    return torch.clip(betas, 0, 1.)
+    return torch.clip(betas, 0, 0.999)
 
 class GaussianDiffusion(nn.Module):
     def __init__(

denoising_diffusion_pytorch/denoising_diffusion_pytorch_1d.py

@@ -407,7 +407,7 @@ def cosine_beta_schedule(timesteps, s = 0.008):
     alphas_cumprod = torch.cos(((x / timesteps) + s) / (1 + s) * math.pi * 0.5) ** 2
     alphas_cumprod = alphas_cumprod / alphas_cumprod[0]
     betas = 1 - (alphas_cumprod[1:] / alphas_cumprod[:-1])
-    return torch.clip(betas, 0, 1.)
+    return torch.clip(betas, 0, 0.999)
 
 class GaussianDiffusion1D(nn.Module):
     def __init__(

denoising_diffusion_pytorch/version.py

@@ -1 +1 @@
-__version__ = '1.6.0'
+__version__ = '1.5.8'