Question on the matrix norm

[gpengzhi]

Great Work!

When you discuss the norm of the source embedding of the NMT model, are you talking about the Frobenius norm or the spectral norm?

[lkfo415579]

should be like this....

[gpengzhi]

should be like this....

X should be a matrix, right?

[lkfo415579]

should be like this....

X should be a matrix, right?

Yes. and you can review code in data/gap_training.h#L360

float get_mod_from_emb(size_t step) override {
      // graph is not been created, using mini value
      if (graphs_.empty() || graphs_[0]->params()->size() == 0)
        return 10.;
      int dimSrcVoc = options_->get<std::vector<int>>("dim-vocabs")[0];
      int dimEmb = options_->get<int>("dim-emb");

      //auto enc_emb = graphs_[0]->param("encoder_Wemb", {dimSrcVoc, dimEmb}, inits::glorot_uniform);
      auto enc_emb = graphs_[0]->get("encoder_Wemb");
      std::vector<float> values;
      if (!enc_emb->val())
        graphs_[0]->forward();
      enc_emb->val()->get(values);
      graph = New<ExpressionGraph>();
      graph->setDevice(graphs_[0]->getDeviceId());
      auto new_enc_emb = graph->param("encoder_Wemb" + std::to_string(runner_++), {dimSrcVoc, dimEmb}, inits::from_vector(values));
      auto enc_mod = square(new_enc_emb);
      enc_mod = sum(enc_mod, -1);
      enc_mod = sqrt(enc_mod, 0);
      enc_mod = sum(enc_mod, 0);
      //enc_mod->debug("enc_mod sqrt");
      graph->forward();
      //std::string str = enc_mod->graphviz();
      values.clear();
      enc_mod->val()->get(values);
      if (init_mod == 0.){
        init_mod = values[0] - 10;
        LOG(info,"[CL-MOD] step:{}, initial_mod:{}", step, init_mod);
      }
      LOG(info,"[CL-MOD] step:{}, enc_emb_mod_avg:{}", step, values[0]);
      return values[0] - init_mod;
    }