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90 lines
3.3 KiB
90 lines
3.3 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import paddle.v2 as paddle
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import paddle.v2.dataset.uci_housing as uci_housing
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import paddle.v2.master as master
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import os
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import cPickle as pickle
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from paddle.v2.reader.creator import cloud_reader
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etcd_ip = os.getenv("MASTER_IP", "127.0.0.1")
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etcd_endpoints = "http://" + etcd_ip + ":2379"
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print "etcd endpoints: ", etcd_endpoints
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def main():
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# init
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paddle.init(use_gpu=False, trainer_count=1)
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# network config
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x = paddle.layer.data(name='x', type=paddle.data_type.dense_vector(13))
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y_predict = paddle.layer.fc(input=x,
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param_attr=paddle.attr.Param(name='w'),
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size=1,
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act=paddle.activation.Linear(),
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bias_attr=paddle.attr.Param(name='b'))
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y = paddle.layer.data(name='y', type=paddle.data_type.dense_vector(1))
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cost = paddle.layer.mse_cost(input=y_predict, label=y)
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# create parameters
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parameters = paddle.parameters.create(cost)
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# create optimizer of new remote updater to pserver
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optimizer = paddle.optimizer.Momentum(momentum=0, learning_rate=1e-3)
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trainer = paddle.trainer.SGD(cost=cost,
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parameters=parameters,
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update_equation=optimizer,
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is_local=False,
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pserver_spec=etcd_endpoints,
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use_etcd=True)
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# event_handler to print training and testing info
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def event_handler(event):
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if isinstance(event, paddle.event.EndIteration):
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# FIXME: for cloud data reader, pass number is managed by master
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# should print the server side pass number
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if event.batch_id % 100 == 0:
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print "Pass %d, Batch %d, Cost %f" % (
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event.pass_id, event.batch_id, event.cost)
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if isinstance(event, paddle.event.EndPass):
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if (event.pass_id + 1) % 10 == 0:
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result = trainer.test(
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reader=paddle.batch(
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uci_housing.test(), batch_size=2),
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feeding={'x': 0,
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'y': 1})
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print "Test %d, %.2f" % (event.pass_id, result.cost)
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# training
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# NOTE: use uci_housing.train() as reader for non-paddlecloud training
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trainer.train(
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reader=paddle.batch(
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paddle.reader.shuffle(
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cloud_reader(
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["/pfs/dlnel/public/dataset/uci_housing/uci_housing*"],
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etcd_endpoints),
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buf_size=500),
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batch_size=2),
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feeding={'x': 0,
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'y': 1},
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event_handler=event_handler,
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num_passes=30)
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if __name__ == '__main__':
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main()
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