Method FPABlockImpl

src/architectures/PANDecoder.cpp:26–48

}

FPABlockImpl::FPABlockImpl(int in_channels, int out_channels, std::string _upscale_mode) {
	align_corners = _upscale_mode == "bilinear";
	branch1 = torch::nn::Sequential(torch::nn::AdaptiveAvgPool2d(torch::nn::AdaptiveAvgPool2dOptions(1)),
		ConvBnRelu(in_channels, out_channels, 1, 1, 0));
	mid = torch::nn::Sequential(ConvBnRelu(in_channels, out_channels, 1, 1, 0));
	down1 = torch::nn::Sequential(torch::nn::MaxPool2d(torch::nn::MaxPool2dOptions(2).stride(2)),
		ConvBnRelu(in_channels, 1, 7, 1, 3));
	down2 = torch::nn::Sequential(torch::nn::MaxPool2d(torch::nn::MaxPool2dOptions(2).stride(2)),
		ConvBnRelu(1, 1, 5, 1, 2));
	down3 = torch::nn::Sequential(torch::nn::MaxPool2d(torch::nn::MaxPool2dOptions(2).stride(2)),
		ConvBnRelu(1, 1, 3, 1, 1),
		ConvBnRelu(1, 1, 3, 1, 1));
	conv2 = ConvBnRelu(1, 1, 5, 1, 2);
	conv1 = ConvBnRelu(1, 1, 7, 1, 3);

	register_module("branch1", branch1);
	register_module("mid", mid);
	register_module("down1", down1);
	register_module("down2", down2);
	register_module("down3", down3);
	register_module("conv2", conv2);
	register_module("conv1", conv1);
}

torch::Tensor FPABlockImpl::forward(torch::Tensor x) {
	auto h = x.sizes()[2];