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Merge branch 'feature/add-tcd-sampler'
# Conflicts: # modules/flags.py
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@@ -50,17 +50,17 @@ class ModelSamplingDiscrete(torch.nn.Module):
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self.linear_start = linear_start
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self.linear_end = linear_end
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# self.register_buffer('betas', torch.tensor(betas, dtype=torch.float32))
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# self.register_buffer('alphas_cumprod', torch.tensor(alphas_cumprod, dtype=torch.float32))
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# self.register_buffer('alphas_cumprod_prev', torch.tensor(alphas_cumprod_prev, dtype=torch.float32))
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sigmas = ((1 - alphas_cumprod) / alphas_cumprod) ** 0.5
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self.set_sigmas(sigmas)
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self.set_alphas_cumprod(alphas_cumprod.float())
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def set_sigmas(self, sigmas):
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self.register_buffer('sigmas', sigmas)
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self.register_buffer('log_sigmas', sigmas.log())
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def set_alphas_cumprod(self, alphas_cumprod):
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self.register_buffer("alphas_cumprod", alphas_cumprod.float())
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@property
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def sigma_min(self):
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return self.sigmas[0]
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@@ -523,7 +523,7 @@ class UNIPCBH2(Sampler):
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KSAMPLER_NAMES = ["euler", "euler_ancestral", "heun", "heunpp2","dpm_2", "dpm_2_ancestral",
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"lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_sde", "dpmpp_sde_gpu",
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"dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm"]
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"dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm", "tcd"]
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class KSAMPLER(Sampler):
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def __init__(self, sampler_function, extra_options={}, inpaint_options={}):
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