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Allow ModelSamplingDiscrete to be instantiated without a model config.

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comfyanonymous 2023-11-01 19:13:03 -04:00
parent e73ec8c4da
commit ecb80abb58
1 changed files with 5 additions and 2 deletions
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7
comfy/model_base.py
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@ -32,9 +32,12 @@ class V_PREDICTION(EPS):
class ModelSamplingDiscrete(torch.nn.Module): class ModelSamplingDiscrete(torch.nn.Module):
def __init__(self, model_config): def __init__(self, model_config=None):
super().__init__() super().__init__()
self._register_schedule(given_betas=None, beta_schedule=model_config.beta_schedule, timesteps=1000, linear_start=0.00085, linear_end=0.012, cosine_s=8e-3) beta_schedule = "linear"
if model_config is not None:
beta_schedule = model_config.beta_schedule
self._register_schedule(given_betas=None, beta_schedule=beta_schedule, timesteps=1000, linear_start=0.00085, linear_end=0.012, cosine_s=8e-3)
self.sigma_data = 1.0 self.sigma_data = 1.0
def _register_schedule(self, given_betas=None, beta_schedule="linear", timesteps=1000, def _register_schedule(self, given_betas=None, beta_schedule="linear", timesteps=1000,