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Joseph Redmon
2017-06-18 13:05:37 -07:00
parent 1467621453
commit 8215a8864d
42 changed files with 699 additions and 497 deletions
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68
examples/lsd.c
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@ -64,7 +64,7 @@ void train_lsd3(char *fcfg, char *fweight, char *gcfg, char *gweight, char *acfg
int ax_size = anet.inputs*anet.batch;
int ay_size = anet.truths*anet.batch;
fill_ongpu(ay_size, .9, anet.truth_gpu, 1);
fill_gpu(ay_size, .9, anet.truth_gpu, 1);
anet.delta_gpu = cuda_make_array(0, ax_size);
anet.train = 1;
@ -102,36 +102,36 @@ void train_lsd3(char *fcfg, char *fweight, char *gcfg, char *gweight, char *acfg
forward_network_gpu(fnet, fstate);
float *feats = fnet.layers[fnet.n - 2].output_gpu;
copy_ongpu(y_size, feats, 1, fstate.truth, 1);
copy_gpu(y_size, feats, 1, fstate.truth, 1);
forward_network_gpu(gnet, gstate);
float *gen = gnet.layers[gnet.n-1].output_gpu;
copy_ongpu(x_size, gen, 1, fstate.input, 1);
copy_gpu(x_size, gen, 1, fstate.input, 1);
fill_ongpu(x_size, 0, fstate.delta, 1);
fill_gpu(x_size, 0, fstate.delta, 1);
forward_network_gpu(fnet, fstate);
backward_network_gpu(fnet, fstate);
//HERE
astate.input = gen;
fill_ongpu(ax_size, 0, astate.delta, 1);
fill_gpu(ax_size, 0, astate.delta, 1);
forward_network_gpu(anet, astate);
backward_network_gpu(anet, astate);
float *delta = imlayer.delta_gpu;
fill_ongpu(x_size, 0, delta, 1);
scal_ongpu(x_size, 100, astate.delta, 1);
scal_ongpu(x_size, .001, fstate.delta, 1);
axpy_ongpu(x_size, 1, fstate.delta, 1, delta, 1);
axpy_ongpu(x_size, 1, astate.delta, 1, delta, 1);
fill_gpu(x_size, 0, delta, 1);
scal_gpu(x_size, 100, astate.delta, 1);
scal_gpu(x_size, .001, fstate.delta, 1);
axpy_gpu(x_size, 1, fstate.delta, 1, delta, 1);
axpy_gpu(x_size, 1, astate.delta, 1, delta, 1);
//fill_ongpu(x_size, 0, delta, 1);
//fill_gpu(x_size, 0, delta, 1);
//cuda_push_array(delta, X, x_size);
//axpy_ongpu(x_size, -1, imlayer.output_gpu, 1, delta, 1);
//axpy_gpu(x_size, -1, imlayer.output_gpu, 1, delta, 1);
//printf("pix error: %f\n", cuda_mag_array(delta, x_size));
printf("fea error: %f\n", cuda_mag_array(fstate.delta, x_size));
printf("adv error: %f\n", cuda_mag_array(astate.delta, x_size));
//axpy_ongpu(x_size, 1, astate.delta, 1, delta, 1);
//axpy_gpu(x_size, 1, astate.delta, 1, delta, 1);
backward_network_gpu(gnet, gstate);
@ -273,7 +273,7 @@ void train_pix2pix(char *cfg, char *weight, char *acfg, char *aweight, int clear
float *imerror = cuda_make_array(0, imlayer.outputs);
float *ones_gpu = cuda_make_array(0, ay_size);
fill_ongpu(ay_size, .9, ones_gpu, 1);
fill_gpu(ay_size, .9, ones_gpu, 1);
float aloss_avg = -1;
float gloss_avg = -1;
@ -318,23 +318,23 @@ void train_pix2pix(char *cfg, char *weight, char *acfg, char *aweight, int clear
*net.seen += net.batch;
forward_network_gpu(net, gstate);
fill_ongpu(imlayer.outputs, 0, imerror, 1);
fill_gpu(imlayer.outputs, 0, imerror, 1);
astate.input = imlayer.output_gpu;
astate.delta = imerror;
astate.truth = ones_gpu;
forward_network_gpu(anet, astate);
backward_network_gpu(anet, astate);
scal_ongpu(imlayer.outputs, .1, net.layers[net.n-1].delta_gpu, 1);
scal_gpu(imlayer.outputs, .1, net.layers[net.n-1].delta_gpu, 1);
backward_network_gpu(net, gstate);
scal_ongpu(imlayer.outputs, 1000, imerror, 1);
scal_gpu(imlayer.outputs, 1000, imerror, 1);
printf("realness %f\n", cuda_mag_array(imerror, imlayer.outputs));
printf("features %f\n", cuda_mag_array(net.layers[net.n-1].delta_gpu, imlayer.outputs));
axpy_ongpu(imlayer.outputs, 1, imerror, 1, imlayer.delta_gpu, 1);
axpy_gpu(imlayer.outputs, 1, imerror, 1, imlayer.delta_gpu, 1);
gloss += get_network_cost(net) /(net.subdivisions*net.batch);
@ -533,9 +533,9 @@ void train_dcgan(char *cfg, char *weight, char *acfg, char *aweight, int clear,
*gnet.seen += gnet.batch;
forward_network_gpu(gnet);
fill_ongpu(imlayer.outputs*imlayer.batch, 0, imerror, 1);
fill_ongpu(anet.truths*anet.batch, .95, anet.truth_gpu, 1);
copy_ongpu(anet.inputs*anet.batch, imlayer.output_gpu, 1, anet.input_gpu, 1);
fill_gpu(imlayer.outputs*imlayer.batch, 0, imerror, 1);
fill_gpu(anet.truths*anet.batch, .95, anet.truth_gpu, 1);
copy_gpu(anet.inputs*anet.batch, imlayer.output_gpu, 1, anet.input_gpu, 1);
anet.delta_gpu = imerror;
forward_network_gpu(anet);
backward_network_gpu(anet);
@ -543,13 +543,13 @@ void train_dcgan(char *cfg, char *weight, char *acfg, char *aweight, int clear,
float genaloss = *anet.cost / anet.batch;
printf("%f\n", genaloss);
scal_ongpu(imlayer.outputs*imlayer.batch, 1, imerror, 1);
scal_ongpu(imlayer.outputs*imlayer.batch, .00, gnet.layers[gnet.n-1].delta_gpu, 1);
scal_gpu(imlayer.outputs*imlayer.batch, 1, imerror, 1);
scal_gpu(imlayer.outputs*imlayer.batch, .00, gnet.layers[gnet.n-1].delta_gpu, 1);
printf("realness %f\n", cuda_mag_array(imerror, imlayer.outputs*imlayer.batch));
printf("features %f\n", cuda_mag_array(gnet.layers[gnet.n-1].delta_gpu, imlayer.outputs*imlayer.batch));
axpy_ongpu(imlayer.outputs*imlayer.batch, 1, imerror, 1, gnet.layers[gnet.n-1].delta_gpu, 1);
axpy_gpu(imlayer.outputs*imlayer.batch, 1, imerror, 1, gnet.layers[gnet.n-1].delta_gpu, 1);
backward_network_gpu(gnet);
@ -716,21 +716,21 @@ void train_colorizer(char *cfg, char *weight, char *acfg, char *aweight, int cle
*net.seen += net.batch;
forward_network_gpu(net);
fill_ongpu(imlayer.outputs*imlayer.batch, 0, imerror, 1);
copy_ongpu(anet.inputs*anet.batch, imlayer.output_gpu, 1, anet.input_gpu, 1);
fill_ongpu(anet.inputs*anet.batch, .95, anet.truth_gpu, 1);
fill_gpu(imlayer.outputs*imlayer.batch, 0, imerror, 1);
copy_gpu(anet.inputs*anet.batch, imlayer.output_gpu, 1, anet.input_gpu, 1);
fill_gpu(anet.inputs*anet.batch, .95, anet.truth_gpu, 1);
anet.delta_gpu = imerror;
forward_network_gpu(anet);
backward_network_gpu(anet);
scal_ongpu(imlayer.outputs*imlayer.batch, 1./100., net.layers[net.n-1].delta_gpu, 1);
scal_gpu(imlayer.outputs*imlayer.batch, 1./100., net.layers[net.n-1].delta_gpu, 1);
scal_ongpu(imlayer.outputs*imlayer.batch, 1, imerror, 1);
scal_gpu(imlayer.outputs*imlayer.batch, 1, imerror, 1);
printf("realness %f\n", cuda_mag_array(imerror, imlayer.outputs*imlayer.batch));
printf("features %f\n", cuda_mag_array(net.layers[net.n-1].delta_gpu, imlayer.outputs*imlayer.batch));
axpy_ongpu(imlayer.outputs*imlayer.batch, 1, imerror, 1, net.layers[net.n-1].delta_gpu, 1);
axpy_gpu(imlayer.outputs*imlayer.batch, 1, imerror, 1, net.layers[net.n-1].delta_gpu, 1);
backward_network_gpu(net);
@ -876,7 +876,7 @@ void train_lsd2(char *cfgfile, char *weightfile, char *acfgfile, char *aweightfi
float *imerror = cuda_make_array(0, imlayer.outputs);
float *ones_gpu = cuda_make_array(0, ay_size);
fill_ongpu(ay_size, 1, ones_gpu, 1);
fill_gpu(ay_size, 1, ones_gpu, 1);
float aloss_avg = -1;
float gloss_avg = -1;
@ -902,15 +902,15 @@ void train_lsd2(char *cfgfile, char *weightfile, char *acfgfile, char *aweightfi
*net.seen += net.batch;
forward_network_gpu(net, gstate);
fill_ongpu(imlayer.outputs, 0, imerror, 1);
fill_gpu(imlayer.outputs, 0, imerror, 1);
astate.input = imlayer.output_gpu;
astate.delta = imerror;
astate.truth = ones_gpu;
forward_network_gpu(anet, astate);
backward_network_gpu(anet, astate);
scal_ongpu(imlayer.outputs, 1, imerror, 1);
axpy_ongpu(imlayer.outputs, 1, imerror, 1, imlayer.delta_gpu, 1);
scal_gpu(imlayer.outputs, 1, imerror, 1);
axpy_gpu(imlayer.outputs, 1, imerror, 1, imlayer.delta_gpu, 1);
backward_network_gpu(net, gstate);