From be7e57252f0f57b13d9d939fb4baebc1bc8087a1 Mon Sep 17 00:00:00 2001
From: Patrick Labatut <60359573+patricklabatut@users.noreply.github.com>
Date: Tue, 29 Aug 2023 16:05:32 +0200
Subject: [PATCH] Add missing hubconf arg (#178)
Add missing explicit layers argument
---
hubconf.py | 12 ++++++------
1 file changed, 6 insertions(+), 6 deletions(-)
diff --git a/hubconf.py b/hubconf.py
index 69d7600..954a82a 100644
--- a/hubconf.py
+++ b/hubconf.py
@@ -159,24 +159,24 @@ def dinov2_vits14_lc(*, layers: int = 4, pretrained: bool = True, **kwargs):
return _make_dinov2_linear_classifier(arch_name="vit_small", layers=layers, pretrained=pretrained, **kwargs)
-def dinov2_vitb14_lc(*, pretrained: bool = True, **kwargs):
+def dinov2_vitb14_lc(*, layers: int = 4, pretrained: bool = True, **kwargs):
"""
Linear classifier (1 or 4 layers) on top of a DINOv2 ViT-B/14 backbone (optionally) pretrained on the LVD-142M dataset and trained on ImageNet-1k.
"""
- return _make_dinov2_linear_classifier(arch_name="vit_base", pretrained=pretrained, **kwargs)
+ return _make_dinov2_linear_classifier(arch_name="vit_base", layers=layers, pretrained=pretrained, **kwargs)
-def dinov2_vitl14_lc(*, pretrained: bool = True, **kwargs):
+def dinov2_vitl14_lc(*, layers: int = 4, pretrained: bool = True, **kwargs):
"""
Linear classifier (1 or 4 layers) on top of a DINOv2 ViT-L/14 backbone (optionally) pretrained on the LVD-142M dataset and trained on ImageNet-1k.
"""
- return _make_dinov2_linear_classifier(arch_name="vit_large", pretrained=pretrained, **kwargs)
+ return _make_dinov2_linear_classifier(arch_name="vit_large", layers=layers, pretrained=pretrained, **kwargs)
-def dinov2_vitg14_lc(*, pretrained: bool = True, **kwargs):
+def dinov2_vitg14_lc(*, layers: int = 4, pretrained: bool = True, **kwargs):
"""
Linear classifier (1 or 4 layers) on top of a DINOv2 ViT-g/14 backbone (optionally) pretrained on the LVD-142M dataset and trained on ImageNet-1k.
"""
return _make_dinov2_linear_classifier(
- arch_name="vit_giant2", ffn_layer="swiglufused", pretrained=pretrained, **kwargs
+ arch_name="vit_giant2", layers=layers, ffn_layer="swiglufused", pretrained=pretrained, **kwargs
)
--
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