How can I create a graph element in Deeplearnjs which turns my [h, w, d] shape tensor in to one which is [d] shape where each is the max of that layer. If h and w are the same, this can be done with the maxpool function. If like the same for mean. Mean can be achieved using conv2d, but only if w and h are equal.
I need this in a graph so I can apply training.
You can do dl.mean(your_tensor, [0, 1]) or your_tensor.mean([0, 1]) to get the mean along the h and w dimensions. Either one will return a tensor with shape [d]. This also works in training because deeplearnjs has moved to an eager execution mode and a gradient is defined in the mean reduction op. You can see the mnist_eager demo for an example of training without a Graph.
