Hi,
I would like to use se_resnet50 with the Unet, similar to what was used in the carvana challenge.
I understand that model_meta does not contain the cut,cut_lr for this model.
So I used the example given here to extract the encoder part.
The part I replaced for this is the simple_up component from lesson 14
simple_up = nn.Sequential(
nn.ReLU(),
StdUpsample(512,256),
StdUpsample(256,256),
StdUpsample(256,256),
StdUpsample(256,256),
nn.ConvTranspose2d(256, 1, 2, stride=2),
flatten_channel
)
While trying to fit, I am getting the below error.
RuntimeError: Given transposed=1, weight of size [512, 256, 2, 2], expected input[8, 2048, 8, 8] to have 512 channels, but got 2048 channels instead
Can anyone confirm if this is the way to approach this? Am I doing something wrong?
cadene_model_ch3 = nn.Sequential(*list(children(model_cadene))[:-2], simple_up)