bf0c7bd1636f34eb6ed322e4194f987daa3336f1,pytorch/pytorchcv/models/others/oth_naivenet.py,,,#,289

Before Change

    // return get_naivenet("naivenet20", Resv1Block, [3, 1, 1, 1, 1])


if __name__ == "__main__":
    import os
    from torch.autograd import Variable
    from torchsummary import summary
    from torchviz import make_dot
    import tensorwatch

    os.environ["CUDA_VISIBLE_DEVICES"] = "0"

    x_image = Variable(torch.randn(8, 3, 640, 640))

    // net = naivenet25()
    net = naivenet20()
    print(net)
    y = net(x_image)
    // print(y)

    summary(net.to("cuda"), (3, 640, 640))

    // tensorwatch.draw_model(net, [1, 3, 640, 640])

     
    If you want to show with torchviz,
    you need to modify the return format of the network.
    
    // vis_graph = make_dot(y, params=dict(list(net.named_parameters()) + [("x", x_image)]))

    // // vis_graph.format = "png"
    // // vis_graph.format = "pdf"

After Change

if __name__ == "__main__":
    _test()

Instances