def addmm(mat, mat1, mat2, beta=1, alpha=1):
r"""
This function does exact same thing as :func:`torch.addmm` in the forward,
except that it supports backward for coalesced sparse matrix `mat1`.
Args:
mat (Tensor): a dense matrix to be added
mat1 (Tensor): a sparse matrix to be multiplied
mat2 (Tensor): a dense matrix be multiplied
beta (Number, optional): multiplier for :attr:`mat` (:math:`\beta`)
alpha (Number, optional): multiplier for :math:`mat1 @ mat2` (:math:`\alpha`)
"""
return torch._sparse_addmm(mat, mat1, mat2, beta=beta, alpha=alpha)
def addmm(mat, mat1, mat2, beta=1, alpha=1):
# type: (Tensor, Tensor, Tensor, float, float) -> Tensor
r"""
This function does exact same thing as :func:`torch.addmm` in the forward,
except that it supports backward for sparse matrix :attr:`mat1`. :attr:`mat1`
need to have `sparse_dim = 2`. Note that the gradients of :attr:`mat1` is a
coalesced sparse tensor.
Args:
mat (Tensor): a dense matrix to be added
mat1 (SparseTensor): a sparse matrix to be multiplied
mat2 (Tensor): a dense matrix be multiplied
beta (Number, optional): multiplier for :attr:`mat` (:math:`\beta`)
alpha (Number, optional): multiplier for :math:`mat1 @ mat2` (:math:`\alpha`)
"""
return torch._sparse_addmm(mat, mat1, mat2, beta=beta, alpha=alpha)
