zhreshold commented on issue #10638: [Feature Request] Gluon model zoo allow fine-tuning URL: https://github.com/apache/incubator-mxnet/issues/10638#issuecomment-391819304 This could be long term transition because training models on different dataset is not purely an engineering work. Without breaking current API, I would propose to provide the default as Imagenet 1000 class, and allow user to specify the targeting task such as ``` vision.resnet18_v1(pretrained=True) # for the default imagnet 1000 vision.resnet18_v1(pretrained=True, class=10) # raise error vision.resnet18_v1(pretrained=True, class=10, finetune=True) # okay, we strip off the dense layer for user implicitly and replace a new output layer # the above all assume pertained weights are from ImageNet # later we can have vision.resnet18_v1(pretrained=True, class=xxx, dataset=yyy) ```
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