mindspore.ops.Mul
- class mindspore.ops.Mul[source]
Multiplies two tensors element-wise.
Refer to
mindspore.ops.mul()
for more details.Note
One of the two inputs must be a Tensor, when the two inputs have different shapes, they must be able to broadcast to a common shape.
The two inputs can not be bool type at the same time, [True, Tensor(True, bool_), Tensor(np.array([True]), bool_)] are all considered bool type.
The two inputs comply with the implicit type conversion rules to make the data types consistent.
- Inputs:
x (Union[Tensor, number.Number, bool]) - The first input is a number.Number or a bool or a tensor whose data type is number or bool_.
y (Union[Tensor, number.Number, bool]) - The second input, when the first input is a Tensor, the second input should be a number.Number or bool value, or a Tensor whose data type is number or bool. When the first input is Scalar, the second input must be a Tensor whose data type is number or bool.
- Outputs:
Tensor, the shape is the same as the one after broadcasting, and the data type is the one with higher precision or higher digits among the two inputs.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore >>> import numpy as np >>> from mindspore import Tensor, ops >>> x = Tensor(np.array([1.0, 2.0, 3.0]), mindspore.float32) >>> y = Tensor(np.array([4.0, 5.0, 6.0]), mindspore.float32) >>> mul = ops.Mul() >>> output = mul(x, y) >>> print(output) [ 4. 10. 18.]