multiply¶
- paddle. multiply ( x, y, name=None ) [source]
-
multiply two tensors element-wise. The equation is:
\[out = x * y\]Note
Supported shape of
xandyfor this operator: 1. x.shape == y.shape. 2. x.shape could be the continuous subsequence of y.shape.paddle.multiplysupports broadcasting. If you would like to know more about broadcasting, please refer to Introduction to Tensor .- Parameters
-
x (Tensor) – the input tensor, its data type should be one of float32, float64, int32, int64, bool.
y (Tensor) – the input tensor, its data type should be one of float32, float64, int32, int64, bool.
name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.
- Returns
-
N-D Tensor. A location into which the result is stored. If
x,yhave different shapes and are “broadcastable”, the resulting tensor shape is the shape ofxandyafter broadcasting. Ifx,yhave the same shape, its shape is the same asxandy.
Examples
>>> import paddle >>> x = paddle.to_tensor([[1, 2], [3, 4]]) >>> y = paddle.to_tensor([[5, 6], [7, 8]]) >>> res = paddle.multiply(x, y) >>> print(res) Tensor(shape=[2, 2], dtype=int64, place=Place(cpu), stop_gradient=True, [[5 , 12], [21, 32]]) >>> x = paddle.to_tensor([[[1, 2, 3], [1, 2, 3]]]) >>> y = paddle.to_tensor([2]) >>> res = paddle.multiply(x, y) >>> print(res) Tensor(shape=[1, 2, 3], dtype=int64, place=Place(cpu), stop_gradient=True, [[[2, 4, 6], [2, 4, 6]]])
