Open baihualinxin opened 5 years ago
styleNet = Network(device: device, inputSize: inputSize, parameterLoader: loader)
styleNet.start ->> Convolution(size: ConvSize(outputChannels: 32, kernelSize: 9, stride: 1), id: “conv1”) ->> Convolution(size: ConvSize(outputChannels: 64, kernelSize: 3, stride: 2), id: “conv2”) ->> Convolution(size: ConvSize(outputChannels: 128, kernelSize: 3, stride: 2), id: “conv3”) ->> Residual(size: ConvSize(outputChannels: 128, kernelSize: 3, stride: 1), id: “res_block1”) ->> Residual(size: ConvSize(outputChannels: 128, kernelSize: 3, stride: 1), id: “res_block2”) ->> Residual(size: ConvSize(outputChannels: 128, kernelSize: 3, stride: 1), id: “res_block3”) ->> Residual(size: ConvSize(outputChannels: 128, kernelSize: 3, stride: 1), id: “res_block4”) —>> ConvTranspose(size: ConvSize(outputChannles: 64, kernelSize: 3, stride: 2), id: “convt1”) —>> ConvTranspose(size: ConvSize(outputChannles: 32, kernelSize: 3, stride: 2), id: “convt2”) ->> Convolution(size: ConvSize(outputChannels: 3, kernelSize: 9, stride: 1), neuron: .tanh, id: “convFinal”)
1.I want to do two pool layers for the add operation How to get the weight of each layer of neural network? 2.Model.run the self? .network. Run is going to be returned to tensor, I need to take care of it, don't return the label？
styleNet = Network(device: device, inputSize: inputSize, parameterLoader: loader)
styleNet.start ->> Convolution(size: ConvSize(outputChannels: 32, kernelSize: 9, stride: 1), id: “conv1”) ->> Convolution(size: ConvSize(outputChannels: 64, kernelSize: 3, stride: 2), id: “conv2”) ->> Convolution(size: ConvSize(outputChannels: 128, kernelSize: 3, stride: 2), id: “conv3”) ->> Residual(size: ConvSize(outputChannels: 128, kernelSize: 3, stride: 1), id: “res_block1”) ->> Residual(size: ConvSize(outputChannels: 128, kernelSize: 3, stride: 1), id: “res_block2”) ->> Residual(size: ConvSize(outputChannels: 128, kernelSize: 3, stride: 1), id: “res_block3”) ->> Residual(size: ConvSize(outputChannels: 128, kernelSize: 3, stride: 1), id: “res_block4”) —>> ConvTranspose(size: ConvSize(outputChannles: 64, kernelSize: 3, stride: 2), id: “convt1”) —>> ConvTranspose(size: ConvSize(outputChannles: 32, kernelSize: 3, stride: 2), id: “convt2”) ->> Convolution(size: ConvSize(outputChannels: 3, kernelSize: 9, stride: 1), neuron: .tanh, id: “convFinal”)
1.I want to do two pool layers for the add operation How to get the weight of each layer of neural network? 2.Model.run the self? .network. Run is going to be returned to tensor, I need to take care of it, don't return the label？