Solved by Juan_Sensio in post #2 
              
              
                You can always define a custom resnet and change the first layer to adapt for your input shape. For example, with resnet18: 
import torch 
import torchvision

resnet = torchvision.models.resnet18()

input = torch.randn((16,3,244,244))
output = resnet(input)
print(output.shape)

# this fails becasue …