NPID + MoCoV2 weights are the same?

[ColinConwell]

The weights from the download URLs for NPID and MoCoV2 appear to be the same. Perhaps a copying error?

The code below may be run to demonstrate the equivalence:

def get_vissl_model(weights_url):
    from torch.hub import load_state_dict_from_url
    weights = load_state_dict_from_url(weights_url, map_location = torch.device('cpu'))
    
    def replace_module_prefix(state_dict, prefix, replace_with = ''):
        return {(key.replace(prefix, replace_with, 1) if key.startswith(prefix) else key): val
                      for (key, val) in state_dict.items()}

    def convert_model_weights(model):
        if "classy_state_dict" in model.keys():
            model_trunk = model["classy_state_dict"]["base_model"]["model"]["trunk"]
        elif "model_state_dict" in model.keys():
            model_trunk = model["model_state_dict"]
        else:
            model_trunk = model
        return replace_module_prefix(model_trunk, "_feature_blocks.")

    converted_weights = convert_model_weights(weights)
    excess_weights = ['fc','projection', 'prototypes']
    converted_weights = {key:value for (key,value) in converted_weights.items()
                             if not any([x in key for x in excess_weights])}
    
    if 'module' in next(iter(converted_weights)):
        converted_weights = {key.replace('module.',''):value for (key,value) in converted_weights.items()
                             if 'fc' not in key}
        
    from torchvision.models import resnet50
    import torch.nn as nn

    class Identity(nn.Module):
        def __init__(self):
            super(Identity, self).__init__()

        def forward(self, x):
            return x

    model = resnet50()
    model.fc = Identity()

    model.load_state_dict(converted_weights)
    
    return model

### NPID 
weights_url = 'https://dl.fbaipublicfiles.com/vissl/model_zoo/npid_1node_200ep_4kneg_npid_8gpu_resnet_23_07_20.9eb36512/model_final_checkpoint_phase199.torch'
model = get_vissl_model(weights_url)
print(model.parameters())[1:10,1,1,1])

### MoCoV2 
weights_url = 'https://dl.fbaipublicfiles.com/vissl/model_zoo/moco_v2_1node_lr.03_step_b32_zero_init/model_final_checkpoint_phase199.torch'
model = get_vissl_model(weights_url)
print(model.parameters())[1:10,1,1,1])

### BarlowTwins to show the difference
weights_url = 'https://dl.fbaipublicfiles.com/vissl/model_zoo/barlow_twins/barlow_twins_32gpus_4node_imagenet1k_1000ep_resnet50.torch'
model = get_vissl_model(weights_url)
print(model.parameters())[1:10,1,1,1])

[QuentinDuval]

Hi @ColinConwell,

Thanks a lot for using VISSL and thanks a lot for raising this issue :)

Let me check this and come back to you !

Thank you,
Quentin