Dtype Blob<Dtype>::sumsq_diff() const {
Dtype sumsq;
const Dtype* diff;
if (!diff_) { return 0; }
switch (diff_->head()) {
case SyncedMemory::HEAD_AT_CPU:
diff = cpu_diff();
sumsq = caffe_cpu_dot(count_, diff, diff);
break;
case SyncedMemory::HEAD_AT_GPU:
case SyncedMemory::SYNCED:
#ifndef CPU_ONLY
diff = gpu_diff();
caffe_gpu_dot(count_, diff, diff, &sumsq);
break;
#else
NO_GPU;
#endif
case SyncedMemory::UNINITIALIZED:
return 0;
default:
LOG(FATAL) << "Unknown SyncedMemory head state: " << data_->head();
}
return sumsq;
}
Dtype Blob<Dtype>::sumsq_data() const {
Dtype sumsq;
const Dtype* data;
if (!data_) { return 0; }
switch (data_->head()) {
case SyncedMemory::SYNCED_PRV:
case SyncedMemory::HEAD_AT_PRV:
data = prv_data();
sumsq = caffe_cpu_dot(prv_data_count(), data, data);
break;
case SyncedMemory::HEAD_AT_CPU:
data = cpu_data();
sumsq = caffe_cpu_dot(count_, data, data);
break;
case SyncedMemory::HEAD_AT_GPU:
case SyncedMemory::SYNCED:
#ifndef CPU_ONLY
data = gpu_data();
caffe_gpu_dot(count_, data, data, &sumsq);
#else
NO_GPU;
#endif
break;
case SyncedMemory::UNINITIALIZED:
return 0;
default:
LOG(FATAL) << "Unknown SyncedMemory head state: " << data_->head();
}
return sumsq;
}
inline Dtype Layer<Dtype>::Forward(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top) {
Dtype loss = 0;
Reshape(bottom, top);
switch (Caffe::mode()) {
case Caffe::CPU:
Forward_cpu(bottom, top);
for (int top_id = 0; top_id < top.size(); ++top_id) {
if (!this->loss(top_id)) { continue; }
const int count = top[top_id]->count();
const Dtype* data = top[top_id]->cpu_data();
const Dtype* loss_weights = top[top_id]->cpu_diff();
loss += caffe_cpu_dot(count, data, loss_weights);
}
break;
case Caffe::GPU:
Forward_gpu(bottom, top);
#ifndef CPU_ONLY
for (int top_id = 0; top_id < top.size(); ++top_id) {
if (!this->loss(top_id)) { continue; }
const int count = top[top_id]->count();
const Dtype* data = top[top_id]->gpu_data();
const Dtype* loss_weights = top[top_id]->gpu_diff();
Dtype blob_loss = 0;
caffe_gpu_dot(count, data, loss_weights, &blob_loss);
loss += blob_loss;
}
#endif
break;
default:
LOG(FATAL) << "Unknown caffe mode.";
}
return loss;
}
Dtype Tensor<Dtype>::DotPFrom(const Tensor& source) {
if (source.count() != count_) {
ASSERT(false, "Trying to dot blobs of different counts: "
<< source.count() << " != " << count_);
}
Dtype result;
switch (mode()) {
case Caffe::CPU:
result = caffe_cpu_dot(count_,
source.cpu_mem(),
this->cpu_mem());
break;
case Caffe::GPU:
#ifndef CPU_ONLY
caffe_gpu_dot(count_,
source.gpu_mem(),
this->gpu_mem(),
&result);
#else
NO_GPU;
#endif
break;
default:
ASSERT(false, "Unknown caffe mode.");
}
return result;
}
Dtype Tensor<Dtype>::sumsq() const {
Dtype sumsq;
const Dtype* data;
if (!mem_) { return 0; }
switch (mem_->head()) {
case SyncedMemory::HEAD_AT_CPU:
data = cpu_mem();
sumsq = caffe_cpu_dot(count_, data, data);
break;
case SyncedMemory::HEAD_AT_GPU:
case SyncedMemory::SYNCED:
#ifndef CPU_ONLY
data = gpu_mem();
caffe_gpu_dot(count_, data, data, &sumsq);
#else
NO_GPU;
#endif
break;
case SyncedMemory::UNINITIALIZED:
return 0;
default:
LOG(FATAL) << "Unknown SyncedMemory head state: " << mem_->head();
}
return sumsq;
}
inline Dtype Layer<Dtype>::Forward(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top) {
// Lock during forward to ensure sequential forward
Lock();
Dtype loss = 0;
Reshape(bottom, top);
switch (Caffe::mode()) {
case Caffe::CPU:
Forward_cpu(bottom, top);
for (int top_id = 0; top_id < top.size(); ++top_id) {
if (!this->loss(top_id)) {
continue;
}
const int count = top[top_id]->count();
const Dtype* data = top[top_id]->cpu_data();
const Dtype* loss_weights = top[top_id]->cpu_diff();
loss += caffe_cpu_dot(count, data, loss_weights);
}
break;
case Caffe::GPU:
Forward_gpu(bottom, top);
#ifndef CPU_ONLY
if (device_->backend() == BACKEND_CUDA) {
#ifdef USE_CUDA
for (int top_id = 0; top_id < top.size(); ++top_id) {
if (!this->loss(top_id)) {
continue;
}
const int count = top[top_id]->count();
const Dtype* data = top[top_id]->gpu_data();
const Dtype* loss_weights = top[top_id]->gpu_diff();
Dtype blob_loss = 0;
caffe_gpu_dot(count, data, loss_weights, &blob_loss);
loss += blob_loss;
}
#endif // USE_CUDA
} else {
#ifdef USE_GREENTEA
for (int top_id = 0; top_id < top.size(); ++top_id) {
if (!this->loss(top_id)) {
continue;
}
const int count = top[top_id]->count();
cl_mem data = (cl_mem) (top[top_id]->gpu_data());
cl_mem loss_weights = (cl_mem) (top[top_id]->gpu_diff());
Dtype blob_loss = 0;
greentea_gpu_dot(this->device_->id(), count, data, 0,
loss_weights, 0, &blob_loss);
loss += blob_loss;
}
#endif // USE_GREENTEA
}
#endif
break;
default:
LOG(FATAL)<< "Unknown caffe mode.";
}
Unlock();
return loss;
}
inline Dtype Layer<Dtype>::Forward(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top) {
// Lock during forward to ensure sequential forward
Lock();
Dtype loss = 0;
double tempdouble = 0;
int tempint = 0;
//if (bottom.size() != 0)
// tempint = bottom[0]->count();
Reshape(bottom, top);
switch (Caffe::mode()) {
case Caffe::CPU:
Forward_cpu(bottom, top);
for (int top_id = 0; top_id < top.size(); ++top_id) {
if (!this->loss(top_id)) { continue; }
const int count = top[top_id]->count();
const Dtype* data = top[top_id]->cpu_data();
//const Dtype* label = bottom[0]->cpu_data();
//for (int i = 0; i < 10; i++)
//{
//
// printf("%lf\t", data[i]);
// /*if ((i + 1) % 10 == 0)
// {
// printf("\n");
// }*/
//
//}
//for (int i = 0; i < 10; i++)
// printf("%lf\t", label[i]);
const Dtype* loss_weights = top[top_id]->cpu_diff();
loss += caffe_cpu_dot(count, data, loss_weights);
}
break;
case Caffe::GPU:
Forward_gpu(bottom, top);
#ifndef CPU_ONLY
for (int top_id = 0; top_id < top.size(); ++top_id) {
if (!this->loss(top_id)) { continue; }
const int count = top[top_id]->count();
const Dtype* data = top[top_id]->gpu_data();
const Dtype* loss_weights = top[top_id]->gpu_diff();
Dtype blob_loss = 0;
caffe_gpu_dot(count, data, loss_weights, &blob_loss);
loss += blob_loss;
}
#endif
break;
default:
LOG(FATAL) << "Unknown caffe mode.";
}
Unlock();
return loss;
}
void EuclideanLossLayer<Dtype>::Forward_gpu(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top) {
int count = bottom[0]->count();
caffe_gpu_sub(
count,
bottom[0]->gpu_data(),
bottom[1]->gpu_data(),
diff_.mutable_gpu_data());
Dtype dot;
caffe_gpu_dot(count, diff_.gpu_data(), diff_.gpu_data(), &dot);
Dtype loss = dot / bottom[0]->num() / Dtype(2);
top[0]->mutable_cpu_data()[0] = loss;
}
inline Dtype Layer<Dtype>::Forward(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top) {
// Lock during forward to ensure sequential forward
for(int i=0; i<bottom.size(); i++)
{
LOG(INFO) << bottom[i]->shape_string();
}
Lock();
Dtype loss = 0;
Reshape(bottom, top);
switch (Caffe::mode()) {
/* case Caffe::CPU:
Forward_cpu(bottom, top);
for (int top_id = 0; top_id < top.size(); ++top_id) {
if (!this->loss(top_id)) { continue; }
const int count = top[top_id]->count();
const Dtype* data = top[top_id]->cpu_data();
const Dtype* loss_weights = top[top_id]->cpu_diff();
loss += caffe_cpu_dot(count, data, loss_weights);
}
break;*/
case Caffe::GPU:
Forward_gpu(bottom, top);
#ifndef CPU_ONLY
for (int top_id = 0; top_id < top.size(); ++top_id) {
if (!this->loss(top_id)) { continue; }
const int count = top[top_id]->count();
const Dtype* data = top[top_id]->gpu_data();
const Dtype* loss_weights = top[top_id]->gpu_diff();
Dtype blob_loss = 0;
caffe_gpu_dot(count, data, loss_weights, &blob_loss);
loss += blob_loss;
}
#endif
break;
default:
LOG(FATAL) << "Unknown caffe mode.";
}
Unlock();
return loss;
}
Dtype Blob<Dtype>::sumsq_diff() const {
Dtype sumsq;
const Dtype* diff;
if (!diff_) {
return 0;
}
switch (diff_->head()) {
case SyncedMemory::HEAD_AT_CPU: {
diff = cpu_diff();
sumsq = caffe_cpu_dot(count_, diff, diff);
break;
}
case SyncedMemory::HEAD_AT_GPU:
case SyncedMemory::SYNCED: {
#ifndef CPU_ONLY
diff = gpu_diff();
if (device_->backend() == Backend::BACKEND_CUDA) {
#ifdef USE_CUDA
caffe_gpu_dot(count_, diff, diff, &sumsq);
#endif
} else {
#ifdef USE_GREENTEA
greentea_gpu_dot(device_->id(), count_, (cl_mem) diff, 0,
(cl_mem) diff, 0, &sumsq);
#endif
}
#else
NO_GPU;
#endif
break;
}
case SyncedMemory::UNINITIALIZED:
return 0;
default:
LOG(FATAL)<< "Unknown SyncedMemory head state: " << data_->head();
}
return sumsq;
}
