| # 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. |
| |
| # pylint: skip-file |
| from data import mnist_iterator |
| import mxnet as mx |
| import numpy as np |
| import logging |
| |
| data = mx.symbol.Variable('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=10) |
| mlp = mx.symbol.SoftmaxOutput(data = fc3, name = 'softmax') |
| |
| # data |
| |
| train, val = mnist_iterator(batch_size=100, input_shape = (784,)) |
| |
| # train |
| |
| logging.basicConfig(level=logging.DEBUG) |
| |
| model = mx.model.FeedForward( |
| ctx = mx.cpu(), symbol = mlp, num_epoch = 20, |
| learning_rate = 0.1, momentum = 0.9, wd = 0.00001) |
| |
| def norm_stat(d): |
| return mx.nd.norm(d)/np.sqrt(d.size) |
| mon = mx.mon.Monitor(100, norm_stat) |
| model.fit(X=train, eval_data=val, monitor=mon, |
| batch_end_callback = mx.callback.Speedometer(100, 100)) |
| |
