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@ -843,8 +843,8 @@ class Trellis2(nn.Module):
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else: # structure
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else: # structure
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orig_bsz = x.shape[0]
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orig_bsz = x.shape[0]
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if shape_rule:
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if shape_rule:
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x = x[0].unsqueeze(0)
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x = x[1].unsqueeze(0)
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timestep = timestep[0].unsqueeze(0)
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timestep = timestep[1].unsqueeze(0)
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out = self.structure_model(x, timestep, context if not shape_rule else cond)
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out = self.structure_model(x, timestep, context if not shape_rule else cond)
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if shape_rule:
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if shape_rule:
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out = out.repeat(orig_bsz, 1, 1, 1, 1)
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out = out.repeat(orig_bsz, 1, 1, 1, 1)
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@ -441,7 +441,11 @@ class EmptyTextureLatentTrellis2(IO.ComfyNode):
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shape_latent = shape_latent["samples"]
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shape_latent = shape_latent["samples"]
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if shape_latent.ndim == 4:
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if shape_latent.ndim == 4:
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shape_latent = shape_latent.squeeze(-1).transpose(1, 2).reshape(-1, channels)
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shape_latent = shape_latent.squeeze(-1).transpose(1, 2).reshape(-1, channels)
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shape_latent = shape_norm(shape_latent, coords)
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std = shape_slat_normalization["std"].to(shape_latent)
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mean = shape_slat_normalization["mean"].to(shape_latent)
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shape_latent = SparseTensor(feats = shape_latent, coords=coords)
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shape_latent = (shape_latent - mean) / std
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latent = torch.randn(1, channels, coords.shape[0], 1)
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latent = torch.randn(1, channels, coords.shape[0], 1)
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model = model.clone()
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model = model.clone()
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