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;
-}
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