add¶

Documentation¶

treetensor.torch.add(input, other, *args, **kwargs)[source]¶

Adds the scalar other to each element of the input input and returns a new resulting tree tensor.

Examples:

>>> import torch
>>> import treetensor.torch as ttorch
>>> ttorch.add(
...     ttorch.tensor([1, 2, 3]),
...     ttorch.tensor([3, 5, 11]),
... )
tensor([ 4,  7, 14])

>>> ttorch.add(
...     ttorch.tensor({
...         'a': [1, 2, 3],
...         'b': {'x': [[3, 5], [9, 12]]},
...     }),
...     ttorch.tensor({
...         'a': [3, 5, 11],
...         'b': {'x': [[31, -15], [13, 23]]},
...     })
... )
<Tensor 0x7f11b139c710>
├── a --> tensor([ 4,  7, 14])
└── b --> <Tensor 0x7f11b139c630>
    └── x --> tensor([[ 34, -10],
                      [ 22,  35]])

Torch Version Related

This documentation is based on torch.add in torch v2.0.1+cu117. Its arguments’ arrangements depend on the version of pytorch you installed.

If some arguments listed here are not working properly, please check your pytorch’s version with the following command and find its documentation.

python -c 'import torch;print(torch.__version__)'

The arguments and keyword arguments supported in torch v2.0.1+cu117 is listed below.

Description From Torch v2.0.1+cu117¶

torch.add(input, other, *, out=None) → Tensor ¶

Adds the scalar other to each element of the input input and returns a new resulting tensor.

\[\text{out} = \text{input} + \text{other}\]

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

Args:: input (Tensor): the input tensor. other (Number): the number to be added to each element of input
Keyword arguments:: out (Tensor, optional): the output tensor.

Example:

>>> a = torch.randn(4)
>>> a
tensor([ 0.0202,  1.0985,  1.3506, -0.6056])
>>> torch.add(a, 20)
tensor([ 20.0202,  21.0985,  21.3506,  19.3944])

torch.add(input, other, *, alpha=1, out=None) → Tensor ¶

Each element of the tensor other is multiplied by the scalar alpha and added to each element of the tensor input. The resulting tensor is returned.

The shapes of input and other must be broadcastable.

\[\text{out} = \text{input} + \text{alpha} \times \text{other}\]

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

Args:: input (Tensor): the first input tensor other (Tensor): the second input tensor
Keyword args:: alpha (Number): the scalar multiplier for other out (Tensor, optional): the output tensor.

Example:

>>> a = torch.randn(4)
>>> a
tensor([-0.9732, -0.3497,  0.6245,  0.4022])
>>> b = torch.randn(4, 1)
>>> b
tensor([[ 0.3743],
        [-1.7724],
        [-0.5811],
        [-0.8017]])
>>> torch.add(a, b, alpha=10)
tensor([[  2.7695,   3.3930,   4.3672,   4.1450],
        [-18.6971, -18.0736, -17.0994, -17.3216],
        [ -6.7845,  -6.1610,  -5.1868,  -5.4090],
        [ -8.9902,  -8.3667,  -7.3925,  -7.6147]])