mindspore.ops.Ger

class mindspore.ops.Ger[source]

Ger product of x1 and x2. Calculate the outer product of two one-dimensional arrays.If x1 is a 1D Tensor of shape \((m,)\) and x2 is a 1D Tensor of shape \((n,)\),then output must be a Tensor of shape \((m * n)\).

Inputs:

x1 - (Tensor) - 1-D input Tensor, with dtype of float16 or float32.
x2 - (Tensor) - 1-D input Tensor, with dtype of float16 or float32.

Outputs:

Tensor, output matrix with the same dtype as inputs.With x1 shape \((m,)\) and x2 shape of \((n,)\),the output has shape \((m * n)\).

Raises

TypeError – If x1 or x2 is not a Tensor.
TypeError – If the dtype of x1 and x2 is neither float16 nor float32.
ValueError – If x1 or x2 is not a 1D Tensor.

Supported Platforms:: Ascend

Examples

>>> x1 = Tensor([1., 2., 3., 4.], mindspore.float32)
>>> x2 = Tensor([1., 2., 3.], mindspore.float32)
>>> ger = ops.Ger()
>>> output = ger(x1, x2)
>>> print(output)
[[ 1.  2.  3.]
 [ 2.  4.  6.]
 [ 3.  6.  9.]
 [ 4.  8. 12.]]