@ptrblck thanks, that’s what I was leaning towards as solution but thought it odd that I couldn’t directly consume the output of the pre-calculated denselayers and was concerned changing to in_features=2208*7*7 will lead to incorrect model since the default pretrained model used in_features=2208. I’m actually surprised I didn’t get a tensor with [batch_size, 2208, 1, 1], shouldn’t the output from the denselayer feed in a flattened features without me having to manually implement pooling afterwards?