Method train_batch

include/core/solver.h:1525–1557

Train a single batch */

    /** Train a single batch */
    virtual void train_batch(int batch_id) {
        Timer batch_timer("Train Batch", log_frequency);
        if (batch_id % log_frequency == 0)
            LOG(INFO) << "Batch id: " << batch_id << " / " << solver->num_batch;
        batch.to_device_async();
        // Sampling
        {
            Timer timer("Sampling", log_frequency);
            int num_sample = batch_size * num_negative;
            {
                Timer timer("Random", log_frequency);
                CURAND_CHECK(curandGenerateUniformDouble(generator, random.device_ptr, num_sample * 2));
                negative_sampler.device_sample(random, &negative_batch);
            }
            CUDA_CHECK(cudaStreamSynchronize(sample_stream));
        }
        // Loss (last batch)
        if (batch_id % log_frequency == 0){
            Timer timer("Loss", log_frequency);
            loss.to_host();
            Float batch_loss = 0;
            for (int i = 0; i < batch_size; i++)
                batch_loss += loss[i];
            LOG(INFO) << "loss = " << batch_loss / batch_size;
        }
        // Train
        {
            Timer timer("Train Kernel", log_frequency);
            optimizer.apply_schedule(batch_id, solver->num_batch);
            CHECK(train_dispatch())
                    << "Can't find a training kernel for `" << solver->model << "` with " << optimizer.type;
        }
    }

    /**
     * @brief Predict on samples in the sample block