mindspore.ops.kron

mindspore.ops.kron(input, other)[source]

Compute the Kronecker product of two tensors.

If the shape of input is \((a_{0}\) input \(a_{1}\) input … input \(a_{n})\) and the shape of other is \((b_{0}\) input \(b_{1}\) input … input \(b_{n})\) , the result will be \((a_{0}*b_{0}\) input \(a_{1}*b_{1}\) input … input \(a_{n}*b_{n})\) .

\[(input ⊗ other)_{k_{0},k_{1},...k_{n}} = input_{i_{0},i_{1},...i_{n}} * other_{j_{0},j_{1},...j_{n}},\]

where \(k_{t} = i_{t} * b_{t} + j_{t}\) for 0 ≤ t ≤ n.

Note

Supports real-valued and complex-valued inputs.

Parameters

input (Tensor) – First input tensor.
other (Tensor) – Second input tensor.

Returns

Tensor

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> input = mindspore.tensor([[0., 1., 2.], [3., 4., 5.]])
>>> other = mindspore.tensor([[-1., -2., -3.], [-4., -6., -8.]])
>>> output = mindspore.ops.kron(input, other)
>>> print(output)
[[  0.   0.   0.  -1.  -2.  -3.  -2.  -4.  -6.]
 [  0.   0.   0.  -4.  -6.  -8.  -8. -12. -16.]
 [ -3.  -6.  -9.  -4.  -8. -12.  -5. -10. -15.]
 [-12. -18. -24. -16. -24. -32. -20. -30. -40.]]