Applies a 2D max pooling over an input signal composed of several input planes.

nnf_max_pool2d(
input,
kernel_size,
stride = kernel_size,
)
input input tensor (minibatch, in_channels , iH , iW) size of the pooling region. Can be a single number or a tuple (kH, kW) stride of the pooling operation. Can be a single number or a tuple (sH, sW). Default: kernel_size implicit zero paddings on both sides of the input. Can be a single number or a tuple (padH, padW). Default: 0 controls the spacing between the kernel points; also known as the à trous algorithm. when True, will use ceil instead of floor in the formula to compute the output shape. Default: FALSE whether to return the indices where the max occurs.