cef6a94ad99e70513c08170b29f56cd8b2c53b74,gluon/models/resnet.py,,_test,#,733

Before Change

        net = model(pretrained=True)

        ctx = mx.cpu()
        net.initialize(ctx=ctx)

        net_params = net.collect_params()
        weight_count = 0
        for param in net_params.values():

After Change

    import numpy as np
    import mxnet as mx

    pretrained = True

    models = [
        //resnet10,
        //resnet12,
        //resnet14,
        //resnet16,
        resnet18,
        //resnet18_w3d4,
        //resnet18_wd2,
        //resnet18_wd4,
        resnet34,
        resnet50,
        resnet50b,
        resnet101,
        resnet101b,
        resnet152,
        resnet152b,
        //resnet200,
        //resnet200b,
    ]

    for model in models:

        net = model(pretrained=pretrained)

        ctx = mx.cpu()
        if not pretrained:
            net.initialize(ctx=ctx)

        net_params = net.collect_params()
        weight_count = 0
        for param in net_params.values():
            if (param.shape is None) or (not param._differentiable):

Instances