mindspore.Tensor.ger

Tensor.ger(x)[source]

Ger product of self and x. Calculate the outer product of two arrays. If self is a 1D Tensor of shape \((m,)\) and x is a 1D Tensor of shape \((n,)\), then output must be a Tensor of shape \((m, n)\).

Note

Currently Ascend does not support float64 data input.

Refer to mindspore.ops.ger() for more detail.

Parameters: x (Tensor) – input Tensor, with dtype of float16, float32 or float64.
Returns: Tensor, output matrix with the same dtype as inputs.With self shape \((m,)\) and x shape of \((n,)\), the output has shape \((m, n)\).

Supported Platforms:: Ascend GPU CPU

Examples

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