Closed seabearlmx closed 5 months ago
FrozenBackboneEncoderDecoder
freezes the entire backbone (including the rein) and disables gradient backpropagation
throughout the backbone. Here, Backbone operates under torch.no_grad()
, ensuring a very fast execution due to reduced computational overhead.
During the training of Rein, only the pretrained backbone is frozen, allowing for the fine-tuning of Rein. This selective freezing is implemented through the train()
function of the backbone coupled with the PEFTOptimizerConstructor
, and it is distinct from the functionality of FrozenBackboneEncoderDecoder
.
Rein will not be fine-tuned if you add add the code model = dict(type="FrozenBackboneEncoderDecoder")
to the file rein_dinov2_mask2former_512x512_bs1x4.py
.
Hello, the Rein is trained on the frozen dinov2 backbones, but the Rein likely uses EncoderDecoder. so, what is the difference when I add the code
model = dict(type="FrozenBackboneEncoderDecoder")
to the filerein_dinov2_mask2former_512x512_bs1x4.py