//input from console and output the result predict by the model
void AspectTool::realTest(string model_file)
{
//initialize word vector tool
Word2VecTool word_vec_tool("../res/glove.42B.300d.txt", false);
//word_vec_tool.initWordIndexDict();
word_vec_tool.loadWordDict("word_index_dictionary");
cout << "Please input the test sectence : " << endl;
string sentence;
getline(cin, sentence);
cout << sentence << endl;
StringTool st;
vector<string> word_token = st.tokenize(sentence);
MatrixXd *p_input_data = new MatrixXd(word_vec_tool.getVectorLength(), word_token.size());
for (int i = 0; i < word_token.size(); ++i)
{
MatrixXd temp_matrix(word_vec_tool.getVectorLength(), 1);
word_vec_tool.getWrodVect(word_token[i], temp_matrix);
p_input_data -> col(i) = temp_matrix;
}
vector<MatrixXd*> input_datas;
input_datas.push_back(p_input_data);
//cout << *p_input_data << endl;
LSTM lstm(model_file);
vector<MatrixXd*> predict_labels = lstm.predict(input_datas);
MatrixXd temp_label = *(predict_labels[0]);
cout << temp_label << endl;
string aspect_term = "";
for (int i = 0; i < temp_label.cols(); ++i)
{
if (temp_label(1, i) == 1)
{
aspect_term = aspect_term + " " + word_token[i];
}
else if (temp_label(2, i) == 1 && aspect_term.size() > 0)
{
aspect_term = aspect_term + " " + word_token[i];
}
else if (temp_label(0, i) == 1)
{
if (aspect_term.size() > 0)
{
cout << "Aspect Term : " << aspect_term << endl;
}
aspect_term = "";
}
}
if (aspect_term.size() > 0)
{
cout << "Aspect Term : " << aspect_term << endl;
}
return;
}
void function_labeltemp(function_t *func, const char *name) {
temp_t *tmp = function_findtemp(func,name);
temp_label(tmp);
}
