I’m working on satellite imagery in a Kaggle kernel, using primarily sample code from the class. I am training a segmentation learner, and can reach about 80% accuracy (DICE) after a few minutes. However, when I try to swap the data out for the same images, but in 2x resolution,
seg_learn.load('stage-2') fails to load! In particular, it complains as follows:
RuntimeError: Error(s) in loading state_dict for DynamicUnet: Missing key(s) in state_dict: "layers.10.layers.0.0.weight", "layers.10.layers.0.0.bias", "layers.10.layers.1.0.weight", "layers.10.layers.1.0.bias", "layers.11.0.weight", "layers.11.0.bias". Unexpected key(s) in state_dict: "layers.12.0.weight", "layers.12.0.bias", "layers.11.layers.0.0.weight", "layers.11.layers.0.0.bias", "layers.11.layers.1.0.weight", "layers.11.layers.1.0.bias".
To my untrained eye, it seems like the save has failed to prepare the file in a way that the loader expects. Am I doing something wrong? Have you seen this before? Can you help me get past this blocker?