How to get ResNet features from a pre-trained model?
Hi all,I tried to load a pre-trained ResNetModel, however I’m getting the following weird exception:Some weights of the model checkpoint at microsoft/resnet-50 were not used when initializing ResNetModel: [‘classifier.1.bias’, ‘classifier.1.weight’]This IS expected if you are initializing ResNetModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).This IS NOT expected if you are initializing ResNetModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).My code for loading the model is:model = ResNetModel.from_pretrained(“microsoft/resnet-50”, force_download=True)And I wanted to use the following code as some pre-trained features:model(images)[‘pooler_output’]   # images is a tensor of images of the correct shapeIs my code incorrect in some way?From reading related questions I worry that somehow not all parts of the model were loaded correctly.Thanks,Tom