mars.tensor.
hsplit
Split a tensor into multiple sub-tensors horizontally (column-wise).
Please refer to the split documentation. hsplit is equivalent to split with axis=1, the tensor is always split along the second axis regardless of the tensor dimension.
axis=1
See also
split
Split an array into multiple sub-arrays of equal size.
Examples
>>> import mars.tensor as mt
>>> x = mt.arange(16.0).reshape(4, 4) >>> x.execute() array([[ 0., 1., 2., 3.], [ 4., 5., 6., 7.], [ 8., 9., 10., 11.], [ 12., 13., 14., 15.]]) >>> mt.hsplit(x, 2).execute() [array([[ 0., 1.], [ 4., 5.], [ 8., 9.], [ 12., 13.]]), array([[ 2., 3.], [ 6., 7.], [ 10., 11.], [ 14., 15.]])] >>> mt.hsplit(x, mt.array([3, 6])).execute() [array([[ 0., 1., 2.], [ 4., 5., 6.], [ 8., 9., 10.], [ 12., 13., 14.]]), array([[ 3.], [ 7.], [ 11.], [ 15.]]), array([], dtype=float64)]
With a higher dimensional array the split is still along the second axis.
>>> x = mt.arange(8.0).reshape(2, 2, 2) >>> x.execute() array([[[ 0., 1.], [ 2., 3.]], [[ 4., 5.], [ 6., 7.]]]) >>> mt.hsplit(x, 2) [array([[[ 0., 1.]], [[ 4., 5.]]]), array([[[ 2., 3.]], [[ 6., 7.]]])]