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New CheckpointLoaderSimple to load checkpoints without a config.
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@@ -81,7 +81,7 @@ class DDPM(torch.nn.Module):
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super().__init__()
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assert parameterization in ["eps", "x0", "v"], 'currently only supporting "eps" and "x0" and "v"'
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self.parameterization = parameterization
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print(f"{self.__class__.__name__}: Running in {self.parameterization}-prediction mode")
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# print(f"{self.__class__.__name__}: Running in {self.parameterization}-prediction mode")
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self.cond_stage_model = None
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self.clip_denoised = clip_denoised
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self.log_every_t = log_every_t
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@@ -522,8 +522,8 @@ class LatentDiffusion(DDPM):
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"""main class"""
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def __init__(self,
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first_stage_config,
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cond_stage_config,
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first_stage_config={},
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cond_stage_config={},
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num_timesteps_cond=None,
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cond_stage_key="image",
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cond_stage_trainable=False,
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@@ -562,8 +562,6 @@ class LatentDiffusion(DDPM):
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# self.instantiate_first_stage(first_stage_config)
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# self.instantiate_cond_stage(cond_stage_config)
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self.first_stage_config = first_stage_config
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self.cond_stage_config = cond_stage_config
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self.cond_stage_forward = cond_stage_forward
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self.clip_denoised = False
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