ThreadTrainer.py

# Copyright (c) 2016, NVIDIA CORPORATION. All rights reserved.
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from threading import Thread
import numpy as np

from Config import Config


class ThreadTrainer(Thread):
    def __init__(self, server, id):
        super(ThreadTrainer, self).__init__()
        self.setDaemon(True)

        self.id = id
        self.server = server
        self.exit_flag = False

    def run(self):
        while not self.exit_flag:
            batch_size = 0
            while batch_size <= Config.TRAINING_MIN_BATCH_SIZE:
                x_, r_, a_ = self.server.training_q.get()
                if batch_size == 0:
                    x__ = x_; r__ = r_; a__ = a_
                else:
                    x__ = np.concatenate((x__, x_))
                    r__ = np.concatenate((r__, r_))
                    a__ = np.concatenate((a__, a_))
                batch_size += x_.shape[0]
            
            if Config.TRAIN_MODELS:
                self.server.train_model(x__, r__, a__, self.id)