mxnet.ndarray.depth_to_space¶
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mxnet.ndarray.depth_to_space(data=None, block_size=_Null, out=None, name=None, **kwargs)¶ Rearranges(permutes) data from depth into blocks of spatial data. Similar to ONNX DepthToSpace operator: https://github.com/onnx/onnx/blob/master/docs/Operators.md#DepthToSpace. The output is a new tensor where the values from depth dimension are moved in spatial blocks to height and width dimension. The reverse of this operation is
space_to_depth.\[\begin{split}\begin{gather*} x \prime = reshape(x, [N, block\_size, block\_size, C / (block\_size ^ 2), H * block\_size, W * block\_size]) \\ x \prime \prime = transpose(x \prime, [0, 3, 4, 1, 5, 2]) \\ y = reshape(x \prime \prime, [N, C / (block\_size ^ 2), H * block\_size, W * block\_size]) \end{gather*}\end{split}\]where \(x\) is an input tensor with default layout as \([N, C, H, W]\): [batch, channels, height, width] and \(y\) is the output tensor of layout \([N, C / (block\_size ^ 2), H * block\_size, W * block\_size]\)
Example:
x = [[[[0, 1, 2], [3, 4, 5]], [[6, 7, 8], [9, 10, 11]], [[12, 13, 14], [15, 16, 17]], [[18, 19, 20], [21, 22, 23]]]] depth_to_space(x, 2) = [[[[0, 6, 1, 7, 2, 8], [12, 18, 13, 19, 14, 20], [3, 9, 4, 10, 5, 11], [15, 21, 16, 22, 17, 23]]]]
Defined in src/operator/tensor/matrix_op.cc:L1002