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| author | Jeff Donahue <jeff.donahue@gmail.com> | 2014-07-11 01:55:17 -0700 |
|---|---|---|
| committer | Jeff Donahue <jeff.donahue@gmail.com> | 2014-08-13 13:22:04 -0700 |
| commit | 512a626fc71c69ed4460024b31c5fe8dff1e668c (patch) | |
| tree | f3d11beb593a4e64e779a99b82538ceee7fae21a /src/caffe/layers/euclidean_loss_layer.cpp | |
| parent | 7a3ed9b8edf43895770b63cb4d9f5cacf0dba047 (diff) | |
| download | caffeonacl-512a626fc71c69ed4460024b31c5fe8dff1e668c.tar.gz caffeonacl-512a626fc71c69ed4460024b31c5fe8dff1e668c.tar.bz2 caffeonacl-512a626fc71c69ed4460024b31c5fe8dff1e668c.zip | |
Generalize loss by allowing any top blob to be used as a loss in which
its elements are summed with a scalar coefficient.
Forward for layers no longer returns a loss; instead all loss layers must have
top blobs. Existing loss layers are given a top blob automatically by
Net::Init, with an associated top_loss_weight of 1 (set in
LossLayer::FurtherSetUp). Due to the increased amount of common SetUp logic,
the SetUp interface is modified such that all subclasses should normally
override FurtherSetUp only, which is called by SetUp.
Diffstat (limited to 'src/caffe/layers/euclidean_loss_layer.cpp')
| -rw-r--r-- | src/caffe/layers/euclidean_loss_layer.cpp | 13 |
1 files changed, 6 insertions, 7 deletions
diff --git a/src/caffe/layers/euclidean_loss_layer.cpp b/src/caffe/layers/euclidean_loss_layer.cpp index 17180d40..be83601f 100644 --- a/src/caffe/layers/euclidean_loss_layer.cpp +++ b/src/caffe/layers/euclidean_loss_layer.cpp @@ -8,8 +8,9 @@ namespace caffe { template <typename Dtype> -void EuclideanLossLayer<Dtype>::FurtherSetUp( +void EuclideanLossLayer<Dtype>::LayerSetUp( const vector<Blob<Dtype>*>& bottom, vector<Blob<Dtype>*>* top) { + LossLayer<Dtype>::LayerSetUp(bottom, top); CHECK_EQ(bottom[0]->channels(), bottom[1]->channels()); CHECK_EQ(bottom[0]->height(), bottom[1]->height()); CHECK_EQ(bottom[0]->width(), bottom[1]->width()); @@ -18,7 +19,7 @@ void EuclideanLossLayer<Dtype>::FurtherSetUp( } template <typename Dtype> -Dtype EuclideanLossLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom, +void EuclideanLossLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom, vector<Blob<Dtype>*>* top) { int count = bottom[0]->count(); caffe_sub( @@ -28,10 +29,7 @@ Dtype EuclideanLossLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom, diff_.mutable_cpu_data()); Dtype dot = caffe_cpu_dot(count, diff_.cpu_data(), diff_.cpu_data()); Dtype loss = dot / bottom[0]->num() / Dtype(2); - if (top->size() == 1) { - (*top)[0]->mutable_cpu_data()[0] = loss; - } - return loss; + (*top)[0]->mutable_cpu_data()[0] = loss; } template <typename Dtype> @@ -40,9 +38,10 @@ void EuclideanLossLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top, for (int i = 0; i < 2; ++i) { if (propagate_down[i]) { const Dtype sign = (i == 0) ? 1 : -1; + const Dtype alpha = sign * top[0]->cpu_diff()[0] / (*bottom)[i]->num(); caffe_cpu_axpby( (*bottom)[i]->count(), // count - sign / (*bottom)[i]->num(), // alpha + alpha, // alpha diff_.cpu_data(), // a Dtype(0), // beta (*bottom)[i]->mutable_cpu_diff()); // b |