ML_Decoder
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Official PyTorch implementation of "ML-Decoder: Scalable and Versatile Classification Head" (2021)
What should I do if I want to train ML_Decoder on a custom dataset. [multi-label task]
What are the specific training parameters for the training commands on CIFAR100?
here is my code `model = create_model_test(args, load_head=True).cuda() ########### eliminate BN for faster inference ########### model.load_state_dict(torch.load(args.model_path, map_location='cpu')) model = model.cpu() model = InplacABN_to_ABN(model) model = fuse_bn_recursively(model) model = model.cpu() `...
When loading a model with `load_head=True` it would throw an exception because the `key` variable isn't defined. This PR moves the variable definition to fix this bug.
hi, thanks for your wonderful work. Could you please provide the NUS-WIDE weights just as you provided for MSCOCO and other datasets?
Hi, thanks for your excellent work. I am trying to apply it on my custom dataset with 4 classes with 2 seen and 2 unseen classes . I m tryng...
https://github.com/Alibaba-MIIL/ML_Decoder/blob/8a9e984f671c9c30c98d2c45dfcaf4383381c254/src_files/models/utils/factory.py#L47-L56 when load_head is True, it didn't defined `key`. \+ i know solution. so, i just notified this problem. plz fix it