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https://github.com/comfyanonymous/ComfyUI.git
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Remove unused code.
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@ -184,8 +184,7 @@ class RotaryPositionEmbedding2D(torch.nn.Module):
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class Dino2Encoder(torch.nn.Module):
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def __init__(self, dim, num_heads, layer_norm_eps, num_layers, dtype, device, operations, use_swiglu_ffn,
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qknorm_start: int = -1, rope: "RotaryPositionEmbedding2D | None" = None,
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rope_start: int = -1):
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qknorm_start: int = -1):
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super().__init__()
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self.layer = torch.nn.ModuleList([
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Dino2Block(
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@ -195,8 +194,6 @@ class Dino2Encoder(torch.nn.Module):
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)
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for i in range(num_layers)
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])
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self.rope = rope
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self.rope_start = rope_start
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def forward(self, x, intermediate_output=None):
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# Backward-compat path used by ``ClipVisionModel`` (no DA3 extensions).
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@ -282,7 +279,6 @@ class Dino2Embeddings(torch.nn.Module):
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return torch.cat((class_pos, patch_pos), dim=1).to(x.dtype)
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def forward(self, pixel_values):
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_, _, H, W = pixel_values.shape
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x = self.patch_embeddings(pixel_values)
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x = torch.cat((self.cls_token.to(device=x.device, dtype=x.dtype).expand(x.shape[0], -1, -1), x), dim=1)
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if x.shape[1] - 1 == self.position_embeddings.shape[1] - 1:
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@ -351,11 +347,16 @@ class Dinov2Model(torch.nn.Module):
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dim, heads, layer_norm_eps, num_layers, dtype, device, operations,
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use_swiglu_ffn=use_swiglu_ffn,
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qknorm_start=self.qknorm_start,
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rope=self.rope, rope_start=self.rope_start,
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)
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self.layernorm = operations.LayerNorm(dim, eps=layer_norm_eps, dtype=dtype, device=device)
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def forward(self, pixel_values, attention_mask=None, intermediate_output=None):
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if self.alt_start != -1:
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raise RuntimeError(
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"Dinov2Model.forward() is the backward-compatible CLIP-vision path and does not "
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"apply DA3 extensions (RoPE, alternating attention, camera-token injection). "
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"Use get_intermediate_layers_da3() for Depth Anything 3 models."
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)
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x = self.embeddings(pixel_values)
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x, i = self.encoder(x, intermediate_output=intermediate_output)
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x = self.layernorm(x)
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