# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. """ The mxnet symbol of Nature DQN Reference: Mnih, Volodymyr, et al. "Human-level control through deep reinforcement learning." Nature 518.7540 (2015): 529. """ import mxnet as mx def get_symbol(num_action=18): data = mx.sym.Variable(name='data') net = mx.sym.Convolution(data, kernel=(8, 8), stride=(4, 4), num_filter=32, name='conv1') net = mx.sym.Activation(net, act_type='relu', name='relu1') net = mx.sym.Convolution(net, kernel=(4, 4), stride=(2, 2), num_filter=64, name='conv2') net = mx.sym.Activation(net, act_type='relu', name='relu2') net = mx.sym.Convolution(net, kernel=(3, 3), stride=(1, 1), num_filter=64, name='conv3') net = mx.sym.Activation(net, act_type='relu', name='relu3') net = mx.sym.FullyConnected(net, num_hidden=512, name='fc4') net = mx.sym.Activation(net, act_type='relu', name='relu4') net = mx.sym.FullyConnected(net, num_hidden=num_action, name='fc5', flatten=False) return net