Baddbmm
Baddbmm
torch_baddbmm(self, batch1, batch2, beta = 1L, alpha = 1L)
self |
(Tensor) the tensor to be added |
batch1 |
(Tensor) the first batch of matrices to be multiplied |
batch2 |
(Tensor) the second batch of matrices to be multiplied |
beta |
(Number, optional) multiplier for |
alpha |
(Number, optional) multiplier for \mbox{batch1} \mathbin{@} \mbox{batch2} (α) |
Performs a batch matrix-matrix product of matrices in batch1
and batch2.
input is added to the final result.
batch1 and batch2 must be 3-D tensors each containing the same
number of matrices.
If batch1 is a (b \times n \times m) tensor, batch2 is a
(b \times m \times p) tensor, then input must be
broadcastable with a
(b \times n \times p) tensor and out will be a
(b \times n \times p) tensor. Both alpha and beta mean the
same as the scaling factors used in torch_addbmm.
\mbox{out}_i = β\ \mbox{input}_i + α\ (\mbox{batch1}_i \mathbin{@} \mbox{batch2}_i)
For inputs of type FloatTensor or DoubleTensor, arguments beta and
alpha must be real numbers, otherwise they should be integers.
if (torch_is_installed()) {
M = torch_randn(c(10, 3, 5))
batch1 = torch_randn(c(10, 3, 4))
batch2 = torch_randn(c(10, 4, 5))
torch_baddbmm(M, batch1, batch2)
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