Hi,
i am trying to train pnasnet5large from scratch of my custom dataset and i am using pretrainedmodels package. i have modified my input and final layers as suggested in this site
https://github.com/Cadene/pretrained-models.pytorch 63.
My code snippet
model = pnasnet5large (pretrained=“imagenet”)
model.conv1 = nn.Conv2d(4, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3))
model.avgpool = nn.AdaptiveAvgPool2d(1)
model.last_linear = nn.Sequential(nn.BatchNorm1d(1024),nn.Dropout(0.5),nn.Linear(1024, config.num_classes))
my number of channels is 4 and num of classes is 28 and its a multilabel classification problem
but i am getting the following error
RuntimeError: running_mean should contain 64 elements not 96
What could be the issue?