Add docs to torch_sparse.matmul (rusty1s#315)

* Add docs to torch_sparse.matmul * Update comment formatting * Update torch_sparse/matmul.py * Update torch_sparse/matmul.py * Update torch_sparse/matmul.py * Update torch_sparse/matmul.py * Update torch_sparse/matmul.py --------- Co-authored-by: Matthias Fey <matthias.fey@tu-dortmund.de>

Author: bslin

torch_sparse/matmul.py

@@ -139,6 +139,23 @@ def matmul(src, other, reduce): # noqa: F811
 
 
 def matmul(src, other, reduce="sum"): # noqa: F811
+ """Matrix product of a sparse tensor with either another sparse tensor or a
+ dense tensor. The sparse tensor represents an adjacency matrix and is
+ stored as a list of edges. This method multiplies elements along the rows
+ of the adjacency matrix with the column of the other matrix. In regular
+ matrix multiplication, the products are then summed together, but this
+ method allows us to use other aggregation functions as well.
+
+ Args:
+ src (:class:`SparseTensor`): The sparse tensor.
+ other (:class:`Tensor` or :class:`SparseTensor`): The second matrix.
+ reduce (string, optional): The function to reduce along the rows of
+ :obj:`src` and columns of :obj:`other`. Can be :obj:`"sum"`,
+ :obj:`"mean"`, :obj:`"min"` or :obj:`"max"`.
+ (default: :obj:`"sum"`)
+
+ :rtype: (:class:`Tensor`)
+ """
  if isinstance(other, torch.Tensor):
  return spmm(src, other, reduce)
  elif isinstance(other, SparseTensor):