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model parameters

Open yoonsanghyu opened this issue 5 years ago • 4 comments

I implemented DPTNet using shi's code. But I got 2.8M model size. how can i reduce model size to 2.69M?

yoonsanghyu avatar Sep 21 '20 08:09 yoonsanghyu

I just updated the code, you can try it again.

ujscjj avatar Dec 31 '20 08:12 ujscjj

Hi, thank you for sharing your codes.

I got 2.632M (2,631,680) model size using your code. Do the hyperparameters match the configuration in the paper? In the paper, the model size is 2.69M.

tky823 avatar Jan 24 '21 13:01 tky823

Using the following script, I got different values: 2.835M (2,834,945) thop library may miss some trainable parameters.

# dpt_net.py
def main():
    model = DPTNet_base(enc_dim=256, feature_dim=64, hidden_dim=128, layer=6, segment_size=250, nspk=2, win_len=2)

    params = 0
    for p in model.parameters():
        if p.requires_grad:
            params += p.numel()
    print(params)

tky823 avatar Jan 24 '21 13:01 tky823

Sorry for responding later. The hyperparameters match the configuration in the paper. On my machine, the model size is 2.69MB.

ujscjj avatar Feb 13 '21 05:02 ujscjj