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Allow ModelSamplingDiscrete to be instantiated without a model config.
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@ -32,9 +32,12 @@ class V_PREDICTION(EPS):
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class ModelSamplingDiscrete(torch.nn.Module):
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def __init__(self, model_config):
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def __init__(self, model_config=None):
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super().__init__()
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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)
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beta_schedule = "linear"
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if model_config is not None:
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beta_schedule = model_config.beta_schedule
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self._register_schedule(given_betas=None, beta_schedule=beta_schedule, timesteps=1000, linear_start=0.00085, linear_end=0.012, cosine_s=8e-3)
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self.sigma_data = 1.0
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def _register_schedule(self, given_betas=None, beta_schedule="linear", timesteps=1000,
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