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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 10-0.2061  0.5926  0.6800 -0.3597  0.2644 -0.5257  0.1042 -0.9326 -0.8547 -1.2562
#>  0.2783  0.5612  0.1489 -0.4697  0.6776  0.5832 -1.0390 -1.4859  0.2804  1.1474
#> -1.2395 -0.0919 -0.1514 -0.6147 -1.7027  0.5231 -0.1818 -1.8060 -0.2522 -0.2575
#>  1.3485 -0.7461  1.3595  1.9313 -1.7233 -1.0740 -1.1430  1.1714 -0.9156 -0.8039
#> -2.0064 -1.4307  0.0072  1.2391  0.2070  1.7725 -0.9827 -0.5497 -0.5584  0.8348
#>  0.7009 -1.7190 -1.9887 -0.1877 -0.1691 -0.7999 -1.1704  0.8539  0.8351  0.0943
#>  0.7007  0.3993  0.4109  1.4820  1.1792  2.1885 -0.0446 -0.8584  2.4315 -0.0359
#> -0.9200 -0.3903 -0.4532  1.0427  0.1550 -0.7777 -0.4709  0.9434  0.2150 -0.4901
#>  0.6205  0.3783 -0.6096 -0.9591 -0.5497  0.0217 -0.9843 -0.5777  1.5201 -0.8664
#>  0.5181 -0.7818 -0.6255  1.2758 -0.4357 -0.0431 -0.5118 -0.2483  0.6868 -0.4833
#> -0.3160  0.1242  0.0536 -0.7888 -0.6800  0.2286 -0.2428 -0.4903 -1.1189  1.0464
#>  0.7026 -1.1695  1.2333  1.1553  1.3874 -0.0843  0.5393 -0.6196  0.9076  1.0923
#> -2.2958  0.3708 -1.5479  0.0046  0.7976 -0.0206  0.4327  0.7761  0.1882 -1.2645
#> -0.0827 -1.1767 -0.6671  0.9020 -1.4176 -0.3433 -0.1471  0.0091  1.8391  1.3508
#> -0.8594 -0.8377 -0.6192  0.9613  0.5887 -0.2027 -0.4690 -0.1376  0.0543  1.5517
#>  0.6484 -0.8588  0.9828 -0.9731  0.5196  0.0569  0.4614 -1.6472 -0.7188  0.2071
#>  0.4826 -1.6939  0.6183  0.0819  1.0094 -0.0200  0.9866 -1.5408  0.7429 -0.0823
#> -0.7354 -0.6771 -0.8575 -1.0925  0.8054  1.0574 -0.5689  1.8546 -1.1928 -0.1752
#> -0.1378  0.9201  0.8152  0.0818  0.0531 -2.3447  0.8267 -1.2707 -0.0069 -1.0040
#> -0.3522 -0.9843 -0.8313  0.6468 -0.3817  0.0399  0.2351 -0.5011  0.5512  0.2125
#>  0.7718  0.3691  0.0227  0.3448  0.1790  0.7582  1.6185  0.1086  2.1357 -0.4894
#> -1.0115 -0.4153  1.7637  1.0019 -0.7599 -0.2473 -0.6647 -1.0672  1.2728 -0.4579
#>  0.4429  0.4245  0.2358  1.2267 -0.5137 -0.7538  1.1298  0.8629  0.6204 -1.0294
#>  1.2114  1.3885 -0.0376 -1.4533 -0.8043  1.3162 -0.8944  0.7620  0.4583  1.7064
#>  1.3063  0.5083 -1.6361  0.2766  2.1287  0.5842 -1.2342 -0.7924 -3.3385  0.4230
#> -0.5648  1.0770  0.9727 -0.6774 -0.3351 -0.8140  0.9766  0.6885  2.0893  0.1109
#> -1.1653  0.5656 -0.3703 -2.1824  0.4589 -2.5347 -1.1149  0.0803  0.5300  0.3586
#>  2.0128  0.1394 -0.7910 -1.1782 -0.5336  1.5971  0.4216 -0.2752  0.2078 -0.1693
#> -0.7862  0.2946 -0.2903  0.9678  0.6501 -2.2288  0.5504  0.1948  0.6873 -0.4591
#> -0.2279  0.6900  0.0843 -0.7947 -0.2358 -0.3146 -1.4641  0.5708 -0.0272  1.0409
#> ... [the output was truncated (use n=-1 to disable)]
#> [ CPUFloatType{32,25} ]