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.]]