Beispiel #1
0
 /// <summary>
 /// Applies a 3D adaptive max pooling over an input signal composed of several input planes.
 /// The output is of size D x H x W, for any input size.The number of output features is equal to the number of input planes.
 /// </summary>
 /// <param name="x">The input tensor</param>
 /// <param name="outputSize">The target output size of the image of the form D x H x W.
 /// Can be a tuple (D, H, W) or a single D for a cube D x D x D. D, H and W can be either a int, or null which means the size will be the same as that of the input.</param>
 /// <returns></returns>
 static public TorchTensor AdaptiveMaxPool3d(TorchTensor x, long[] outputSize)
 {
     using (var d = Modules.AdaptiveMaxPool3d(outputSize)) {
         return(d.forward(x));
     }
 }