caffe 运行过程中如何显示更新梯度信息 solver.cpp

在solver.cpp中。。。

包含文件变动如下：

#include <cstdio>

#include <algorithm>

#include <string>

#include <vector>

#include <iomanip>

#include "caffe/net.hpp"

#include "caffe/proto/caffe.pb.h"

#include "caffe/solver.hpp"

#include "caffe/util/io.hpp"

#include "caffe/util/math_functions.hpp"

#include "caffe/util/upgrade_proto.hpp"

using std::max;

using std::min;

using std::setw;

using std::scientific;

using std::left;

正文cpp文件中，void Solver<Dtype>::Solve(const char* resume_file) {

中变动如下：

if (display) {

LOG(INFO) << "Iteration " << iter_ << ", loss = " << loss;

const vector<Blob<Dtype>*>& result = net_->output_blobs();

int score_index = 0;

for (int j = 0; j < result.size(); ++j) {

const Dtype* result_vec = result[j]->cpu_data();

const string& output_name =

net_->blob_names()[net_->output_blob_indices()[j]];

const Dtype loss_weight =

net_->blob_loss_weights()[net_->output_blob_indices()[j]];

for (int k = 0; k < result[j]->count(); ++k) {

ostringstream loss_msg_stream;

if (loss_weight) {

loss_msg_stream << " (* " << loss_weight

<< " = " << loss_weight * result_vec[k] << " loss)";

}

LOG(INFO) << " Train net output #"

<< score_index++ << ": " << output_name << " = "

<< result_vec[k] << loss_msg_stream.str();

}

}

//add by me

int max_len = 0;

for (int l = 0; l < net_->layers().size(); ++l) {

Layer<Dtype>& layer = *net_->layers()[l].get();

if (layer.blobs().size() > 0 && layer.layer_param().name().length()

> max_len)

max_len = layer.layer_param().name().length();

}

for (int l = 0; l < net_->layers().size(); ++l) {

Layer<Dtype>& layer = *net_->layers()[l].get();

for (int b = 0; b < layer.blobs().size(); ++b) {

Blob<Dtype>& blob = *layer.blobs()[b].get();

const Dtype* blob_cpu_data = blob.cpu_data();

const Dtype* blob_cpu_diff = blob.cpu_diff();

Dtype data_sum = 0;

Dtype diff_sum = 0;

for (int i = 0; i < blob.count(); ++i) {

data_sum += (blob_cpu_data[i] > Dtype(0.)) ? blob_cpu_data[i]

: - blob_cpu_data[i];

diff_sum += (blob_cpu_diff[i] > Dtype(0.)) ? blob_cpu_diff[i]

: - blob_cpu_diff[i];

}

data_sum /= blob.count();

diff_sum /= blob.count();

LOG(INFO) << std::left << std::setw(max_len + 1) << std::setfill(' ')

<< layer.layer_param().name()

<< " blob" << b << ": " << std::scientific

<< data_sum << " [" << diff_sum << "]";

}

}

//end revised by me

}