X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?p=flatland.git;a=blobdiff_plain;f=mylib.c;fp=mylib.c;h=0000000000000000000000000000000000000000;hp=6d62c2488bdbb9fbe4ceb67fa534df979d1dce02;hb=5d4e9eaeec9263692d39ca840e498a5f1d818eaa;hpb=ee0d125312834bf7692df2e9caa1f858780f335c diff --git a/mylib.c b/mylib.c deleted file mode 100644 index 6d62c24..0000000 --- a/mylib.c +++ /dev/null @@ -1,62 +0,0 @@ - -#include - -/* - - Example of FFI extension I started from: - - https://github.com/pytorch/extension-ffi.git - - There is this tutorial - - https://github.com/pytorch/tutorials/blob/master/Creating%20Extensions%20using%20FFI.md - - And TH's Tensor definition are here in my install: - - anaconda3/lib/python3.5/site-packages/torch/lib/include/TH/generic/THTensor.h - - */ - -#include "flatland.h" - -int generate_sequence(long nb_sequences, THByteTensor *output) { - long nb_images_per_sequence = 5; - long depth = 3; - long width = 64; - long height = 64; - long s; - unsigned char *a, *b; - int c, k, i, j, st0, st1, st2, st3, st4; - - THByteTensor_resize5d(output, nb_sequences, nb_images_per_sequence, depth, height, width); - - st0 = THByteTensor_stride(output, 0); - st1 = THByteTensor_stride(output, 1); - st2 = THByteTensor_stride(output, 2); - st3 = THByteTensor_stride(output, 3); - st4 = THByteTensor_stride(output, 4); - - a = - THByteTensor_storage(output)->data + THByteTensor_storageOffset(output); - - for(s = 0; s < nb_sequences; s++) { - unsigned char result[nb_images_per_sequence * depth * width * height]; - unsigned char *r = result; - fl_generate_sequences(1, nb_images_per_sequence, width, height, result); - for(k = 0; k < nb_images_per_sequence; k++) { - for(c = 0; c < depth; c++) { - for(i = 0; i < height; i++) { - b = a - + s * st0 + k * st1 + c * st2 + i * st3; - for(j = 0; j < width; j++) { - *b = (unsigned char) (*r); - r++; - b += st4; - } - } - } - } - } - - return 1; -}