openvino.runtime.opset14.shuffle_channels#
- openvino.runtime.opset14.shuffle_channels(data: Node, axis: int, group: int, name: str | None = None) Node #
Perform permutation on data in the channel dimension of the input tensor.
- Parameters:
data – The node with input tensor.
axis – Channel dimension index in the data tensor. A negative value means that the index should be calculated from the back of the input data shape.
group – The channel dimension specified by the axis parameter should be split into this number of groups.
name – Optional output node name.
- Returns:
The new node performing a permutation on data in the channel dimension of the input tensor.
The operation is the equivalent with the following transformation of the input tensor data of shape [N, C, H, W]:
data_reshaped = reshape(data, [N, group, C / group, H * W])
data_transposed = transpose(data_reshaped, [0, 2, 1, 3])
output = reshape(data_transposed, [N, C, H, W])
For example:
Inputs: tensor of shape [1, 6, 2, 2] data = [[[[ 0., 1.], [ 2., 3.]], [[ 4., 5.], [ 6., 7.]], [[ 8., 9.], [10., 11.]], [[12., 13.], [14., 15.]], [[16., 17.], [18., 19.]], [[20., 21.], [22., 23.]]]] axis = 1 groups = 3 Output: tensor of shape [1, 6, 2, 2] output = [[[[ 0., 1.], [ 2., 3.]], [[ 8., 9.], [10., 11.]], [[16., 17.], [18., 19.]], [[ 4., 5.], [ 6., 7.]], [[12., 13.], [14., 15.]], [[20., 21.], [22., 23.]]]]