inception_v3 requires an input of (299, 299) while other models requires an input of (224, 224). Due to adaptive pooling used in some models, they can run on varying sized intput without throwing errors (but the results are usually not correct). You have to resize/crop an image to be the right input size (and then other necessary transformations, e.g., to_tensor

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1. Transformations in torchvision.transforms work on images, tensors (representing images) and possibly on numpy arrays (representing images). However, a transformation (e.g., ToTensor) might work differently on different input types. So you'd be clear about what exactly a transformation function does. A good practice is to always convert your non-tensor input data to tensors using the transformation ToTensor