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@ -284,7 +284,7 @@ class ChromaRadiance(Chroma):
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# non zero during training to prevent 0 div
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eps = 0.0
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return (noisy - predicted) / (timesteps.view(-1,1,1,1) + eps)
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def _forward(
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self,
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x: Tensor,
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@ -257,7 +257,7 @@ def detect_unet_config(state_dict, key_prefix, metadata=None):
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dit_config["nerf_tile_size"] = 512
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dit_config["nerf_final_head_type"] = "conv" if f"{key_prefix}nerf_final_layer_conv.norm.scale" in state_dict_keys else "linear"
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dit_config["nerf_embedder_dtype"] = torch.float32
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if f"__x0__" in state_dict_keys: # x0 pred
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if "__x0__" in state_dict_keys: # x0 pred
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dit_config["use_x0"] = True
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else:
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dit_config["guidance_embed"] = "{}guidance_in.in_layer.weight".format(key_prefix) in state_dict_keys
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