PyTorch mapping operators to functions

Question

What are all the PyTorch operators, and what are their function equivalents?

Eg, is a @ b equivalent to a.mm(b) or a.matmul(b)?

I'm after a canonical listing of operator -> function mappings.

I'd be happy to be given a PyTorch documentation link as an answer - my googlefu couldn't track it down.

Answer 1

This defines tensor operations for 0.3.1 (it does also contain the definitions of the other operators): https://pytorch.org/docs/0.3.1/_modules/torch/tensor.html

The code for the current stable has been rearranged (I guess they do more in C now), but since the behaviour of matrix multiplication hasn't changed, I think it is save to assume that this is still valid.

See for the definition of __matmul__:

def __matmul__(self, other):
    if not torch.is_tensor(other):
        return NotImplemented
    return self.matmul(other)

and

def matmul(self, other):
    r"""Matrix product of two tensors.

    See :func:`torch.matmul`."""
    return torch.matmul(self, other)

The operator @ was introduced with PEP 465 and is mapped to __matmul__.

See also here for this:
What is the '@=' symbol for in Python?

Answer 2

The Python documentation table Mapping Operators to Functions provides canonical mappings from:

operator -> __function__()

Eg:

Matrix Multiplication        a @ b        matmul(a, b)

Elsewhere on the page, you will see the __matmul__ name as an alternate to matmul.

The definitions of the PyTorch __functions__ are found either in:

• The torch.Tensor module documentation

• python_variable_methods.cpp

You can look up the documentation for the named functions at:

https://pytorch.org/docs/stable/torch.html?#torch.<FUNCTION-NAME>