Skip to contents

Flattens a contiguous range of dims into a tensor.

Source: R/nn-flatten.R
nn_flatten.Rd

For use with nn_sequential.

Usage

nn_flatten(start_dim = 2, end_dim = -1)

Arguments

start_dim

first dim to flatten (default = 2).

end_dim

last dim to flatten (default = -1).

Shape

  • Input: (*, S_start,..., S_i, ..., S_end, *), where S_i is the size at dimension i and * means any number of dimensions including none.

  • Output: (*, S_start*...*S_i*...S_end, *).

See also

nn_unflatten

Examples

if (torch_is_installed()) {
input <- torch_randn(32, 1, 5, 5)
m <- nn_flatten()
m(input)
}
#> torch_tensor
#> Columns 1 to 10-0.5323  0.7914  0.8055 -1.5571 -2.7017 -2.1485  1.4615  0.0120  0.9736 -0.9444
#>  0.4322  1.8139 -1.2508 -0.2912 -0.5599 -1.5309  1.7730 -1.2344  0.4836 -0.3568
#>  0.4741  0.0986  0.3036  1.4667 -0.6151 -0.1850 -2.1041 -0.7848  0.0942  1.7105
#>  1.1324 -0.7944  1.5266  0.5180  1.7285 -0.8715  0.7018  0.2911  1.8261  0.0928
#> -1.1297 -1.5084 -1.5635 -0.3039  0.3328 -0.4635 -1.0578 -0.6043 -0.0493  1.3262
#>  1.1969  0.2623 -0.1365  0.6874 -0.8377 -1.0260 -0.3675  1.7943  1.1193 -0.0988
#> -1.3289 -1.9703 -1.2593  1.2596  1.2783  1.8747  0.9911 -0.4761  0.1253  0.5903
#> -0.9472 -0.9097  0.0755  1.3873  1.1577  1.0626 -0.1018  1.2210  1.4032  0.3106
#> -1.1479 -1.2686  0.6829  1.0225 -0.4061  1.0058  0.0912 -0.8357  0.0714 -0.7613
#> -0.4531  0.3183  0.1503  1.3292 -0.2573 -0.0188 -1.5015 -0.3813  1.0945 -2.1248
#> -0.0959  0.4481 -0.6593  0.9853 -2.7289  0.1699 -0.6961 -0.5189  1.0364  0.0701
#>  0.8283  2.5047  0.4121 -0.6449  0.8600  1.3818 -0.0772 -1.8232 -0.1946 -0.8324
#> -0.5144  0.4445 -0.0204 -0.1818 -0.8557 -0.2157  1.6438 -2.2822 -1.2997  0.0894
#> -0.6338 -1.5578  0.1349 -0.7951  2.3758  0.3265 -0.6223 -0.6363 -0.9099  0.6410
#>  0.8209 -0.6579 -0.5816  1.8266 -0.6944  1.1962 -1.9803  1.2401 -0.0454 -2.4813
#> -1.2920  1.0462  0.1010  0.4184 -1.4312  0.2113  0.6778 -0.3708  0.1104  0.3188
#> -0.3377  0.3693 -0.3925 -0.2370  0.7831  0.6065  0.1395 -0.4003  2.0919 -0.7659
#>  0.1570  0.4832  1.4433 -0.4278 -0.5198  0.5446 -1.0989 -0.9049  0.0595 -0.7692
#> -0.0463 -1.3909  2.7675 -2.1994  0.7258 -0.9248  1.3351  1.3713 -0.1426  0.1724
#> -0.4918  1.2205  1.0043  0.3490 -0.1135  1.4005  2.1771  0.2452 -1.0130  0.5716
#> -0.2040 -0.8590  1.0088 -0.1578 -1.5889  0.4635 -1.1594 -0.2269  0.3126  0.1363
#> -1.1458  1.9362  0.4537  1.2999 -0.6429  1.3710  0.5977  0.1056 -0.3668 -0.7516
#> -0.0165 -0.3694 -0.1787  0.5755 -0.6591  1.0324 -1.0115  0.0971  0.4780 -0.0292
#>  0.9075 -0.6972  0.6900  0.0666  0.3476 -0.7101 -0.0841 -0.5424  0.7682  1.2324
#> -1.0078  0.8806 -0.2856  0.2866  0.3267  1.4083  2.0584  0.4789 -0.9918 -1.3223
#>  2.0853 -0.6825  0.2140  1.0394 -1.2656  0.7614 -0.8907  0.3011  1.6871  0.6352
#>  0.2405  1.3308 -0.3534  1.0292  1.1903  0.8943 -1.2025  1.4763 -0.9065 -1.7503
#>  0.5954 -0.1114 -0.6051  0.4637 -0.9679  1.0432 -0.2765 -0.0136  1.4138 -1.0906
#>  0.0942 -3.2235 -1.1174 -0.9202 -0.6290  0.5714 -0.4955  2.7457 -0.2993  1.5302
#> -0.0372  1.4559  0.3616 -0.9499  1.2516 -1.4699  1.2853 -0.6512  0.4564 -0.0764
#> ... [the output was truncated (use n=-1 to disable)]
#> [ CPUFloatType{32,25} ]