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Minor output fixes

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This commit is contained in:
AlexeyAB
2019-06-29 16:52:49 +03:00
parent 88cccfcad4
commit 7d4143332d
7 changed files with 13 additions and 9 deletions
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4
scripts/imagenet_label.sh
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@ -1,5 +1,9 @@
#!/bin/bash #!/bin/bash
#wget http://www.image-net.org/challenges/LSVRC/2012/nnoupb/ILSVRC2012_bbox_val_v3.tgz
#other downloads: http://www.image-net.org/challenges/LSVRC/2012/nonpub-downloads
#read: https://pjreddie.com/darknet/imagenet/
mkdir -p labelled mkdir -p labelled
wd=`pwd` wd=`pwd`

2
src/avgpool_layer.c
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@ -4,7 +4,7 @@
avgpool_layer make_avgpool_layer(int batch, int w, int h, int c) avgpool_layer make_avgpool_layer(int batch, int w, int h, int c)
{ {
fprintf(stderr, "avg %4d x%4d x%4d -> %4d\n", w, h, c, c); fprintf(stderr, "avg %4d x%4d x%4d -> %4d\n", w, h, c, c);
avgpool_layer l = { (LAYER_TYPE)0 }; avgpool_layer l = { (LAYER_TYPE)0 };
l.type = AVGPOOL; l.type = AVGPOOL;
l.batch = batch; l.batch = batch;

6
src/convolutional_layer.c
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@ -552,13 +552,13 @@ convolutional_layer make_convolutional_layer(int batch, int steps, int h, int w,
else if (l.xnor) fprintf(stderr, "convX "); else if (l.xnor) fprintf(stderr, "convX ");
else fprintf(stderr, "conv "); else fprintf(stderr, "conv ");
if(groups > 1) fprintf(stderr, "%5d/%3d ", n, groups); if(groups > 1) fprintf(stderr, "%5d/%4d ", n, groups);
else fprintf(stderr, "%5d ", n); else fprintf(stderr, "%5d ", n);
if(dilation > 1) fprintf(stderr, "%2d x%2d/%2d(%1d)", size, size, stride, dilation); if(dilation > 1) fprintf(stderr, "%2d x%2d/%2d(%1d)", size, size, stride, dilation);
else fprintf(stderr, "%2d x%2d/%2d ", size, size, stride); else fprintf(stderr, "%2d x%2d/%2d ", size, size, stride);
fprintf(stderr, "%4d x%4d x%4d -> %4d x%4d x%4d %5.3f BF\n", w, h, c, l.out_w, l.out_h, l.out_c, l.bflops); fprintf(stderr, "%4d x%4d x%4d -> %4d x%4d x%4d %5.3f BF\n", w, h, c, l.out_w, l.out_h, l.out_c, l.bflops);
//fprintf(stderr, "%5d/%2d %2d x%2d /%2d(%d)%4d x%4d x%4d -> %4d x%4d x%4d %5.3f BF\n", n, groups, size, size, stride, dilation, w, h, c, l.out_w, l.out_h, l.out_c, l.bflops); //fprintf(stderr, "%5d/%2d %2d x%2d /%2d(%d)%4d x%4d x%4d -> %4d x%4d x%4d %5.3f BF\n", n, groups, size, size, stride, dilation, w, h, c, l.out_w, l.out_h, l.out_c, l.bflops);

2
src/dropout_layer.c
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@ -21,7 +21,7 @@ dropout_layer make_dropout_layer(int batch, int inputs, float probability)
l.backward_gpu = backward_dropout_layer_gpu; l.backward_gpu = backward_dropout_layer_gpu;
l.rand_gpu = cuda_make_array(l.rand, inputs*batch); l.rand_gpu = cuda_make_array(l.rand, inputs*batch);
#endif #endif
fprintf(stderr, "dropout p = %.2f %4d -> %4d\n", probability, inputs, inputs); fprintf(stderr, "dropout p = %.2f %4d -> %4d\n", probability, inputs, inputs);
return l; return l;
} }

2
src/maxpool_layer.c
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@ -78,7 +78,7 @@ maxpool_layer make_maxpool_layer(int batch, int h, int w, int c, int size, int s
#endif // GPU #endif // GPU
l.bflops = (l.size*l.size*l.c * l.out_h*l.out_w) / 1000000000.; l.bflops = (l.size*l.size*l.c * l.out_h*l.out_w) / 1000000000.;
fprintf(stderr, "max %d x %d/%2d %4d x%4d x%4d -> %4d x%4d x%4d %5.3f BF\n", size, size, stride, w, h, c, l.out_w, l.out_h, l.out_c, l.bflops); fprintf(stderr, "max %d x %d/%2d %4d x%4d x%4d -> %4d x%4d x%4d %5.3f BF\n", size, size, stride, w, h, c, l.out_w, l.out_h, l.out_c, l.bflops);
return l; return l;
} }

2
src/reorg_layer.c
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@ -23,7 +23,7 @@ layer make_reorg_layer(int batch, int w, int h, int c, int stride, int reverse)
l.out_c = c*(stride*stride); l.out_c = c*(stride*stride);
} }
l.reverse = reverse; l.reverse = reverse;
fprintf(stderr, "reorg /%2d %4d x%4d x%4d -> %4d x%4d x%4d\n", stride, w, h, c, l.out_w, l.out_h, l.out_c); fprintf(stderr, "reorg /%2d %4d x%4d x%4d -> %4d x%4d x%4d\n", stride, w, h, c, l.out_w, l.out_h, l.out_c);
l.outputs = l.out_h * l.out_w * l.out_c; l.outputs = l.out_h * l.out_w * l.out_c;
l.inputs = h*w*c; l.inputs = h*w*c;
int output_size = l.out_h * l.out_w * l.out_c * batch; int output_size = l.out_h * l.out_w * l.out_c * batch;

4
src/upsample_layer.c
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@ -36,8 +36,8 @@ layer make_upsample_layer(int batch, int w, int h, int c, int stride)
l.delta_gpu = cuda_make_array(l.delta, l.outputs*batch); l.delta_gpu = cuda_make_array(l.delta, l.outputs*batch);
l.output_gpu = cuda_make_array(l.output, l.outputs*batch); l.output_gpu = cuda_make_array(l.output, l.outputs*batch);
#endif #endif
if(l.reverse) fprintf(stderr, "downsample %2dx %4d x%4d x%4d -> %4d x%4d x%4d\n", stride, w, h, c, l.out_w, l.out_h, l.out_c); if(l.reverse) fprintf(stderr, "downsample %2dx %4d x%4d x%4d -> %4d x%4d x%4d\n", stride, w, h, c, l.out_w, l.out_h, l.out_c);
else fprintf(stderr, "upsample %2dx %4d x%4d x%4d -> %4d x%4d x%4d\n", stride, w, h, c, l.out_w, l.out_h, l.out_c); else fprintf(stderr, "upsample %2dx %4d x%4d x%4d -> %4d x%4d x%4d\n", stride, w, h, c, l.out_w, l.out_h, l.out_c);
return l; return l;
} }