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Do tripo dinov3 inference in fp32. (#14221)

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comfyanonymous
2026-06-01 18:08:20 -07:00
committed by GitHub
parent 06b710aa68
commit 4b48535a7d
2 changed files with 5 additions and 5 deletions
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7
comfy/image_encoders/dino3.py
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@@ -3,6 +3,7 @@ import torch
import torch.nn as nn
import torch.nn.functional as F
import comfy.ops
from comfy.ldm.modules.attention import optimized_attention_for_device
from comfy.image_encoders.dino2 import LayerScale as DINOv3ViTLayerScale
@@ -171,11 +172,11 @@ class DINOv3ViTEmbeddings(nn.Module):
patch_embeddings = patch_embeddings.flatten(2).transpose(1, 2)
if bool_masked_pos is not None:
mask_token = self.mask_token.to(patch_embeddings.dtype)
mask_token = comfy.ops.cast_to_input(self.mask_token, patch_embeddings)
patch_embeddings = torch.where(bool_masked_pos.unsqueeze(-1), mask_token, patch_embeddings)
cls_token = self.cls_token.expand(batch_size, -1, -1).to(patch_embeddings.device)
register_tokens = self.register_tokens.expand(batch_size, -1, -1).to(patch_embeddings.device)
cls_token = comfy.ops.cast_to_input(self.cls_token.expand(batch_size, -1, -1), patch_embeddings)
register_tokens = comfy.ops.cast_to_input(self.register_tokens.expand(batch_size, -1, -1), patch_embeddings)
embeddings = torch.cat([cls_token, register_tokens, patch_embeddings], dim=1)
return embeddings