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-rw-r--r--contrib/lua-torch/nn/lib/THNN/generic/SpatialReflectionPadding.c260
1 files changed, 260 insertions, 0 deletions
diff --git a/contrib/lua-torch/nn/lib/THNN/generic/SpatialReflectionPadding.c b/contrib/lua-torch/nn/lib/THNN/generic/SpatialReflectionPadding.c
new file mode 100644
index 000000000..dcde660ea
--- /dev/null
+++ b/contrib/lua-torch/nn/lib/THNN/generic/SpatialReflectionPadding.c
@@ -0,0 +1,260 @@
+#ifndef TH_GENERIC_FILE
+#define TH_GENERIC_FILE "generic/SpatialReflectionPadding.c"
+#else
+
+static void THNN_(SpatialReflectionPadding_updateOutput_frame)(
+ real *input_p, real *output_p,
+ long nslices,
+ long iwidth, long iheight,
+ long owidth, long oheight,
+ int pad_l, int pad_r,
+ int pad_t, int pad_b)
+{
+ int iStartX = fmax(0, -pad_l);
+ int iStartY = fmax(0, -pad_t);
+ int oStartX = fmax(0, pad_l);
+ int oStartY = fmax(0, pad_t);
+
+ long k, ip_x, ip_y;
+#pragma omp parallel for private(k, ip_x, ip_y)
+
+ for (k = 0; k < nslices; k++)
+ {
+ long i, j;
+ for (i = 0; i < oheight; i++) {
+ for (j = 0; j < owidth; j++) {
+ if (j < pad_l) {
+ ip_x = pad_l * 2 - j;
+ } else if (j >= pad_l && j < iwidth + pad_l) {
+ ip_x = j;
+ } else {
+ ip_x = (iwidth + pad_l - 1) * 2 - j;
+ }
+ ip_x = ip_x - oStartX + iStartX;
+
+ if (i < pad_t) {
+ ip_y = pad_t * 2 - i;
+ } else if (i >= pad_t && i < iheight + pad_t) {
+ ip_y = i;
+ } else {
+ ip_y = (iheight + pad_t - 1) * 2 - i;
+ }
+ ip_y = ip_y - oStartY + iStartY;
+
+ real *dest_p = output_p + k*owidth*oheight + i * owidth + j;
+ real *src_p = input_p + k*iwidth*iheight + ip_y * iwidth + ip_x;
+ *dest_p = *src_p;
+ }
+ }
+ }
+}
+
+void THNN_(SpatialReflectionPadding_updateOutput)(THNNState *state,
+ THTensor *input,
+ THTensor *output,
+ int pad_l, int pad_r,
+ int pad_t, int pad_b)
+{
+ int dimw = 2;
+ int dimh = 1;
+ int dimslices = 0;
+ long nbatch = 1;
+ long nslices;
+ long iheight;
+ long iwidth;
+ long oheight;
+ long owidth;
+ real *input_data;
+ real *output_data;
+
+ THNN_ARGCHECK(input->nDimension == 3 || input->nDimension == 4, 2, input,
+ "3D or 4D (batch mode) tensor expected for input, but got: %s");
+
+ if (input->nDimension == 4)
+ {
+ nbatch = input->size[0];
+ dimw++;
+ dimh++;
+ dimslices++;
+ }
+
+ /* sizes */
+ nslices = input->size[dimslices];
+ iheight = input->size[dimh];
+ iwidth = input->size[dimw];
+ oheight = iheight + pad_t + pad_b;
+ owidth = iwidth + pad_l + pad_r;
+
+ THArgCheck(owidth >= 1 || oheight >= 1 , 2,
+ "input (H: %d, W: %d)is too small."
+ " Calculated output H: %d W: %d",
+ iheight, iwidth, oheight, owidth);
+
+ /* get contiguous input */
+ input = THTensor_(newContiguous)(input);
+
+ /* resize output */
+ if (input->nDimension == 3)
+ {
+ THTensor_(resize3d)(output, nslices, oheight, owidth);
+
+ input_data = THTensor_(data)(input);
+ output_data = THTensor_(data)(output);
+
+ THNN_(SpatialReflectionPadding_updateOutput_frame)(input_data, output_data,
+ nslices,
+ iwidth, iheight,
+ owidth, oheight,
+ pad_l, pad_r,
+ pad_t, pad_b);
+ }
+ else
+ {
+ long p;
+
+ THTensor_(resize4d)(output, nbatch, nslices, oheight, owidth);
+
+ input_data = THTensor_(data)(input);
+ output_data = THTensor_(data)(output);
+
+#pragma omp parallel for private(p)
+ for (p = 0; p < nbatch; p++)
+ {
+ THNN_(SpatialReflectionPadding_updateOutput_frame)(
+ input_data+p*nslices*iwidth*iheight,
+ output_data+p*nslices*owidth*oheight,
+ nslices,
+ iwidth, iheight,
+ owidth, oheight,
+ pad_l, pad_r,
+ pad_t, pad_b);
+ }
+ }
+
+ /* cleanup */
+ THTensor_(free)(input);
+}
+
+static void THNN_(SpatialReflectionPadding_updateGradInput_frame)(
+ real *ginput_p, real *goutput_p,
+ long nslices,
+ long iwidth, long iheight,
+ long owidth, long oheight,
+ int pad_l, int pad_r,
+ int pad_t, int pad_b)
+{
+ int iStartX = fmax(0, -pad_l);
+ int iStartY = fmax(0, -pad_t);
+ int oStartX = fmax(0, pad_l);
+ int oStartY = fmax(0, pad_t);
+
+ long k, ip_x, ip_y;
+#pragma omp parallel for private(k, ip_x, ip_y)
+
+ for (k = 0; k < nslices; k++)
+ {
+ long i, j;
+ for (i = 0; i < oheight; i++) {
+ for (j = 0; j < owidth; j++) {
+ if (j < pad_l) {
+ ip_x = pad_l * 2 - j;
+ } else if (j >= pad_l && j < iwidth + pad_l) {
+ ip_x = j;
+ } else {
+ ip_x = (iwidth + pad_l - 1) * 2 - j;
+ }
+ ip_x = ip_x - oStartX + iStartX;
+
+ if (i < pad_t) {
+ ip_y = pad_t * 2 - i;
+ } else if (i >= pad_t && i < iheight + pad_t) {
+ ip_y = i;
+ } else {
+ ip_y = (iheight + pad_t - 1) * 2 - i;
+ }
+ ip_y = ip_y - oStartY + iStartY;
+
+ real *src_p = goutput_p + k*owidth*oheight + i * owidth + j;
+ real *dest_p = ginput_p + k*iwidth*iheight + ip_y * iwidth + ip_x;
+ *dest_p += *src_p;
+ }
+ }
+ }
+}
+
+void THNN_(SpatialReflectionPadding_updateGradInput)(THNNState *state,
+ THTensor *input,
+ THTensor *gradOutput,
+ THTensor *gradInput,
+ int pad_l, int pad_r,
+ int pad_t, int pad_b)
+{
+ int dimw = 2;
+ int dimh = 1;
+ int dimslices = 0;
+ long nbatch = 1;
+ long nslices;
+ long iheight;
+ long iwidth;
+ long oheight;
+ long owidth;
+
+ if (input->nDimension == 4)
+ {
+ nbatch = input->size[0];
+ dimw++;
+ dimh++;
+ dimslices++;
+ }
+
+ /* sizes */
+ nslices = input->size[dimslices];
+ iheight = input->size[dimh];
+ iwidth = input->size[dimw];
+ oheight = iheight + pad_t + pad_b;
+ owidth = iwidth + pad_l + pad_r;
+
+ THArgCheck(owidth == THTensor_(size)(gradOutput, dimw), 3,
+ "gradOutput width unexpected. Expected: %d, Got: %d",
+ owidth, THTensor_(size)(gradOutput, dimw));
+ THArgCheck(oheight == THTensor_(size)(gradOutput, dimh), 3,
+ "gradOutput height unexpected. Expected: %d, Got: %d",
+ oheight, THTensor_(size)(gradOutput, dimh));
+
+ /* get contiguous gradOutput */
+ gradOutput = THTensor_(newContiguous)(gradOutput);
+
+ /* resize */
+ THTensor_(resizeAs)(gradInput, input);
+ THTensor_(zero)(gradInput);
+
+ /* backprop */
+ if (input->nDimension == 3) {
+ THNN_(SpatialReflectionPadding_updateGradInput_frame)(
+ THTensor_(data)(gradInput),
+ THTensor_(data)(gradOutput),
+ nslices,
+ iwidth, iheight,
+ owidth, oheight,
+ pad_l, pad_r,
+ pad_t, pad_b);
+ } else {
+ long p;
+#pragma omp parallel for private(p)
+ for (p = 0; p < nbatch; p++) {
+ THNN_(SpatialReflectionPadding_updateGradInput_frame)(
+ THTensor_(data)(gradInput) + p * nslices * iheight * iwidth,
+ THTensor_(data)(gradOutput) + p * nslices * oheight * owidth,
+ nslices,
+ iwidth, iheight,
+ owidth, oheight,
+ pad_l, pad_r,
+ pad_t, pad_b);
+ }
+ }
+
+ /* cleanup */
+ THTensor_(free)(gradOutput);
+}
+
+#endif
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