Shortcuts

# torch.mul¶

torch.mul(input, other, *, out=None)

Multiplies each element of the input input with the scalar other and returns a new resulting tensor.

$\text{out}_i = \text{other} \times \text{input}_i$

If input is of type FloatTensor or DoubleTensor, other should be a real number, otherwise it should be an integer

Parameters
• {input}

• other (Number) – the number to be multiplied to each element of input

Keyword Arguments

{out}

Example:

>>> a = torch.randn(3)
>>> a
tensor([ 0.2015, -0.4255,  2.6087])
>>> torch.mul(a, 100)
tensor([  20.1494,  -42.5491,  260.8663])

torch.mul(input, other, *, out=None)

Each element of the tensor input is multiplied by the corresponding element of the Tensor other. The resulting tensor is returned.

The shapes of input and other must be broadcastable.

$\text{out}_i = \text{input}_i \times \text{other}_i$
Parameters
• input (Tensor) – the first multiplicand tensor

• other (Tensor) – the second multiplicand tensor

Keyword Arguments

out (Tensor, optional) – the output tensor.

Example:

>>> a = torch.randn(4, 1)
>>> a
tensor([[ 1.1207],
[-0.3137],
[ 0.0700],
[ 0.8378]])
>>> b = torch.randn(1, 4)
>>> b
tensor([[ 0.5146,  0.1216, -0.5244,  2.2382]])
>>> torch.mul(a, b)
tensor([[ 0.5767,  0.1363, -0.5877,  2.5083],
[-0.1614, -0.0382,  0.1645, -0.7021],
[ 0.0360,  0.0085, -0.0367,  0.1567],
[ 0.4312,  0.1019, -0.4394,  1.8753]])


## Docs

Access comprehensive developer documentation for PyTorch

View Docs

## Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials