| # 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. |
| |
| """ |
| a simple multilayer perceptron |
| """ |
| import mxnet as mx |
| |
| def get_symbol(num_classes=10, **kwargs): |
| data = mx.symbol.Variable('data') |
| data = mx.sym.Flatten(data=data) |
| fc1 = mx.symbol.FullyConnected(data = data, name='fc1', num_hidden=128) |
| act1 = mx.symbol.Activation(data = fc1, name='relu1', act_type="relu") |
| fc2 = mx.symbol.FullyConnected(data = act1, name = 'fc2', num_hidden = 64) |
| act2 = mx.symbol.Activation(data = fc2, name='relu2', act_type="relu") |
| fc3 = mx.symbol.FullyConnected(data = act2, name='fc3', num_hidden=num_classes) |
| mlp = mx.symbol.SoftmaxOutput(data = fc3, name = 'softmax') |
| return mlp |
