Implementation of SimCLR in PyTorch
License: GNU General Public License v3.0
The whole code has been implemented in Jupyter Notebook.
param_names = []
for n,p in self.net.named_parameters():
params.append(p)
param_names.append(n)
parameters = [{'params':params,'param_names':param_names}]
optimizer = LARS(parameters,
lr = self.lr,
weight_decay = self.weight_decay,
exclude_from_weight_decay=["batch_normalization", "bias"])
I cannot find the test result of you experiment report anywhere both in the blog or in the github notebook.
P.S. One assumption is that the value must be very high since the network is pre-trained with ImageNet isn't it?
Hi, @sadimanna , in the PreModel, why do we need below? Thanks!
self.pretrained.conv1 = nn.Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), bias=False)
----> 1 criterion = Imrealun(batch_size = 128, loss_weight = 0.5, temperature = 0.5)
NameError: name 'Imrealun' is not defined
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