Bmm
Note
This function does not broadcast .
For broadcasting matrix products, see torch_matmul.
bmm(input, mat2, out=NULL) -> Tensor
Performs a batch matrix-matrix product of matrices stored in input
and mat2.
input and mat2 must be 3-D tensors each containing
the same number of matrices.
If input is a \((b \times n \times m)\) tensor, mat2 is a
\((b \times m \times p)\) tensor, out will be a
\((b \times n \times p)\) tensor.
$$ \mbox{out}_i = \mbox{input}_i \mathbin{@} \mbox{mat2}_i $$
Examples
if (torch_is_installed()) {
input = torch_randn(c(10, 3, 4))
mat2 = torch_randn(c(10, 4, 5))
res = torch_bmm(input, mat2)
res
}
#> torch_tensor
#> (1,.,.) =
#> -2.5762 0.9064 2.6188 -1.2428 -0.6370
#> -0.0779 -1.6015 0.8754 2.8514 -2.1953
#> 2.8408 0.8272 -0.9720 1.1550 -2.1220
#>
#> (2,.,.) =
#> -1.3157 1.6571 -0.9617 0.3398 2.0435
#> 3.7201 4.2012 0.4687 2.1779 0.4565
#> -3.7667 0.6676 -1.0373 -1.2998 1.5692
#>
#> (3,.,.) =
#> 3.0604 -0.4780 1.8066 -1.7644 -0.2946
#> 0.7258 -1.6699 -0.8432 -1.6230 1.0900
#> -1.1131 -0.5467 -1.0947 0.3282 0.6238
#>
#> (4,.,.) =
#> 0.0938 0.1875 2.7153 -0.0415 0.3297
#> -1.5512 0.4386 2.5510 1.9756 -2.3535
#> 0.5281 0.2999 0.7445 -0.2121 -1.7245
#>
#> (5,.,.) =
#> -0.1095 -0.3222 -1.1873 -0.9615 -7.1227
#> 0.2925 0.9943 -1.5440 0.7750 2.1509
#> 3.9663 -2.1539 3.0488 0.3026 -4.1096
#>
#> (6,.,.) =
#> -1.1583 0.4864 -2.9403 2.5869 -2.0625
#> 3.9260 1.9082 1.6521 -0.3094 0.1916
#> 3.7880 1.6600 -0.0927 0.1498 0.1911
#>
#> ... [the output was truncated (use n=-1 to disable)]
#> [ CPUFloatType{10,3,5} ]