# kron¶

`paddle.` `kron` ( x, y, name=None ) [source]

Kron Operator.

This operator computes the Kronecker product of two tensors, a composite tensor made of blocks of the second tensor scaled by the first.

This operator assumes that the rank of the two tensors, \$X\$ and \$Y\$ are the same, if necessary prepending the smallest with ones. If the shape of \$X\$ is [\$r_0\$, \$r_1\$, …, \$r_N\$] and the shape of \$Y\$ is [\$s_0\$, \$s_1\$, …, \$s_N\$], then the shape of the output tensor is [\$r_{0}s_{0}\$, \$r_{1}s_{1}\$, …, \$r_{N}s_{N}\$]. The elements are products of elements from \$X\$ and \$Y\$.

The equation is: \$\$ output[k_{0}, k_{1}, …, k_{N}] = X[i_{0}, i_{1}, …, i_{N}] * Y[j_{0}, j_{1}, …, j_{N}] \$\$

where \$\$ k_{t} = i_{t} * s_{t} + j_{t}, t = 0, 1, …, N \$\$

Args:
x (Tensor): the fist operand of kron op, data type: float16, float32,

float64, int32 or int64.

y (Tensor): the second operand of kron op, data type: float16,

float32, float64, int32 or int64. Its data type should be the same with x.

name(str, optional): The default value is None. Normally there is no

need for user to set this property. For more information, please refer to Name.

Returns:

Tensor: The output of kron op, data type: float16, float32, float64, int32 or int64. Its data is the same with x.

Examples:
```import paddle
x = paddle.to_tensor([[1, 2], [3, 4]], dtype='int64')
y = paddle.to_tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype='int64')
out = paddle.kron(x, y)
print(out)
#        [[1, 2, 3, 2, 4, 6],
#         [ 4,  5,  6,  8, 10, 12],
#         [ 7,  8,  9, 14, 16, 18],
#         [ 3,  6,  9,  4,  8, 12],
#         [12, 15, 18, 16, 20, 24],
#         [21, 24, 27, 28, 32, 36]])
```