void BasePrefetchingDataLayer<Ftype, Btype>::InternalThreadEntryN(size_t thread_id) {
#ifndef CPU_ONLY
const bool use_gpu_transform = this->is_gpu_transform();
#endif
static thread_local bool iter0 = this->phase_ == TRAIN;
if (iter0 && this->net_inititialized_flag_ != nullptr) {
this->net_inititialized_flag_->wait();
} else { // nothing to wait -> initialize and start pumping
std::lock_guard<std::mutex> lock(mutex_in_);
InitializePrefetch();
start_reading();
iter0 = false;
}
try {
while (!must_stop(thread_id)) {
const size_t qid = this->queue_id(thread_id);
#ifndef CPU_ONLY
shared_ptr<Batch<Ftype>> batch = prefetches_free_[qid]->pop();
CHECK_EQ((size_t) -1, batch->id());
load_batch(batch.get(), thread_id, qid);
if (Caffe::mode() == Caffe::GPU) {
if (!use_gpu_transform) {
batch->data_.async_gpu_push();
}
if (this->output_labels_) {
batch->label_.async_gpu_push();
}
CUDA_CHECK(cudaStreamSynchronize(Caffe::th_stream_aux(Caffe::STREAM_ID_ASYNC_PUSH)));
}
prefetches_full_[qid]->push(batch);
#else
shared_ptr<Batch<Ftype>> batch = prefetches_free_[qid]->pop();
load_batch(batch.get(), thread_id, qid);
prefetches_full_[qid]->push(batch);
#endif
if (iter0) {
if (this->net_iteration0_flag_ != nullptr) {
this->net_iteration0_flag_->wait();
}
std::lock_guard<std::mutex> lock(mutex_out_);
if (this->net_inititialized_flag_ != nullptr) {
this->net_inititialized_flag_ = nullptr; // no wait on the second round
InitializePrefetch();
start_reading();
}
if (this->auto_mode_) {
break;
} // manual otherwise, thus keep rolling
iter0 = false;
}
}
} catch (boost::thread_interrupted&) {
}
}
void BasePrefetchingDataLayer<Dtype>::InternalThreadEntry() {
#ifndef CPU_ONLY
cudaStream_t stream;
if (Caffe::mode() == Caffe::GPU) {
CUDA_CHECK(cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking));
}
#endif
try {
while (!must_stop()) {
Batch<Dtype>* batch = prefetch_free_.pop();
load_batch(batch);
#ifndef CPU_ONLY
if (Caffe::mode() == Caffe::GPU) {
batch->data_.data().get()->async_gpu_push(stream);
CUDA_CHECK(cudaStreamSynchronize(stream));
}
#endif
prefetch_full_.push(batch);
}
} catch (boost::thread_interrupted&) {
// Interrupted exception is expected on shutdown
}
#ifndef CPU_ONLY
if (Caffe::mode() == Caffe::GPU) {
CUDA_CHECK(cudaStreamDestroy(stream));
}
#endif
}
void BasePrefetchingDataLayer<Dtype>::InternalThreadEntry() {
#ifndef CPU_ONLY
cudaStream_t stream;//创建CUDA stream，非阻塞类型
if (Caffe::mode() == Caffe::GPU) {
CUDA_CHECK(cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking));
}
#endif
try {
while (!must_stop()) { //循环载入批量数据
Batch<Dtype>* batch = prefetch_free_.pop();//拿到一个空闲batch
load_batch(batch);//载入批量数据
#ifndef CPU_ONLY
if (Caffe::mode() == Caffe::GPU) {
batch->data_.data().get()->async_gpu_push(stream);
if (this->output_labels_) {
batch->label_.data().get()->async_gpu_push(stream);
}
CUDA_CHECK(cudaStreamSynchronize(stream));//同步到GPU
}
#endif
prefetch_full_.push(batch);//加入到带负载的Batch队列中
}
} catch (boost::thread_interrupted&) {//捕获异常，退出while循环
// Interrupted exception is expected on shutdown
}
#ifndef CPU_ONLY
if (Caffe::mode() == Caffe::GPU) {
CUDA_CHECK(cudaStreamDestroy(stream));//销毁CUDA stream
}
#endif
}
void TransformingFastHDF5InputLayer<Dtype>::InternalThreadEntry() {
try {
while (!must_stop()) {
Batch* batch = prefetch_free_.pop();
load_batch(batch);
prefetch_full_.push(batch);
}
} catch (boost::thread_interrupted&) {
// Interrupted exception is expected on shutdown
}
}
void change_batch() {
if (! loaded_batch && ! inited_batch)
load_batch ();
if (! loaded_batch && ! inited_batch ) {
init_batch ();
return;
}
big_menu (0);
big_menu (1);
inited_batch = saved_batch = 0, loaded_batch = 1;
big_menu (0);
}
void run_sas() {
register i;
struct wordb word;
union word W_0;
if (! loaded_sas)
if (! pt_load (&word.left, &word.right, 0x3E010l, &word.tag, 1)) {
if ((word.left & 0xFFFFF000l) != 0x03B3E000l)
load_sas ();
else
loaded_sas = 1;
} else
load_sas ();
if (! loaded_batch) {
if (is_name)
load_batch ();
else
change_batch ();
}
if (! loaded_batch)
return ;
if (stopped == 0) /* Процессор работает */
if (! ask_are_you_shure (" Процессор работает !") )
return ;
stop ();
stopped = 4;
/* Запись в память параметров для САС */
for (i = 0; i < 10; i++)
pt_store (batch_w[i].l[1], batch_w[i].l[0], 0x3E000l + i, 0, 1);
zero ();
/* Установка регистра РКП */
pt_sendl (0x0183E010l, BCMD);
/* Установка регистра РК (РК := РКП) */
pt_send (04, BBUTTON1);
memcpy (W_0.c, CAC_Name, 8);
/* Имя САС.tst ==> в 0 слово */
pt_store (W_0.l[1], W_0.l[0], 0x0l, 0, 1);
pt_store (W_0.l[1], W_0.l[0], 0x36l, 0, 1);
run ();
}
// Perform the classification (this calls into the functions from cnn.c
double run_classification(int* samples, int n, double** keep_output) {
fprintf(stderr, "Making network...\n");
network_t* net = load_cnn_snapshot();
fprintf(stderr, "Loading batches...\n");
for (int i = 0; i < n; i++) {
int batch = samples[i]/10000;
if (batches[batch] == NULL) {
batches[batch] = load_batch(batch);
}
}
vol_t** input = (vol_t**)malloc(sizeof(vol_t*)*n);
double* output = (double*)malloc(sizeof(double)*n);
for (int i = 0; i < n; i++) {
input[i] = batches[samples[i]/10000][samples[i]%10000];
}
fprintf(stderr, "Running classification...\n");
uint64_t start_time = timestamp_us();
net_classify_cats(net, input, output, n);
uint64_t end_time = timestamp_us();
for (int i = 0; i < n; i++) {
samples[i] = (output[i] > 0.5) ? 0 : -1;
}
double dt = (double)(end_time-start_time) / 1000.0;
fprintf(stderr, "TIME: %lf ms\n", dt);
free_network(net);
free(input);
if (keep_output == NULL)
free(output);
else
*keep_output = output;
return dt;
}