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Don't use numpy for calculating sigmas.

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comfyanonymous
2024-02-07 18:52:51 -05:00
parent 7daad468ec
commit c661a8b118
2 changed files with 5 additions and 7 deletions
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8
comfy/model_sampling.py
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@@ -1,5 +1,4 @@
import torch
import numpy as np
from comfy.ldm.modules.diffusionmodules.util import make_beta_schedule
import math
@@ -42,8 +41,7 @@ class ModelSamplingDiscrete(torch.nn.Module):
else:
betas = make_beta_schedule(beta_schedule, timesteps, linear_start=linear_start, linear_end=linear_end, cosine_s=cosine_s)
alphas = 1. - betas
alphas_cumprod = torch.tensor(np.cumprod(alphas, axis=0), dtype=torch.float32)
# alphas_cumprod_prev = np.append(1., alphas_cumprod[:-1])
alphas_cumprod = torch.cumprod(alphas, dim=0)
timesteps, = betas.shape
self.num_timesteps = int(timesteps)
@@ -58,8 +56,8 @@ class ModelSamplingDiscrete(torch.nn.Module):
self.set_sigmas(sigmas)
def set_sigmas(self, sigmas):
self.register_buffer('sigmas', sigmas)
self.register_buffer('log_sigmas', sigmas.log())
self.register_buffer('sigmas', sigmas.float())
self.register_buffer('log_sigmas', sigmas.log().float())
@property
def sigma_min(self):