The input tensor, of rank 4 or rank 3 of shape
[batch, height, width, inChannels]. If rank 3, batch of 1 is assumed.
The filter size: [filterHeight, filterWidth]. If
filterSize is a single number, then filterHeight == filterWidth.
The strides of the pooling: [strideHeight, strideWidth]. If
strides is a single number, then strideHeight == strideWidth.
The type of padding algorithm.
same and stride 1: output will be of same size as input,
regardless of filter size.valid: output will be smaller than input if filter is larger
than 1x1.Optional includeBatchInIndex: booleanGenerated using TypeDoc
Computes the 2D max pooling of an image with Argmax index. The indices in argmax are flattened, so that a maximum value at position
[b, y, x, c]becomes flattened index:(y * width + x) * channels + cif include_batch_in_index is False;((b * height + y) * width + x) * channels +cif include_batch_in_index is True.The indices returned are always in
[0, height) x [0, width)before flattening.