local_train.py

# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed 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: disable=doc-string-missing

import sys
import paddle
import paddle.fluid as fluid

train_reader = paddle.batch(
    paddle.reader.shuffle(
        paddle.dataset.uci_housing.train(), buf_size=500),
    batch_size=16)

test_reader = paddle.batch(
    paddle.reader.shuffle(
        paddle.dataset.uci_housing.test(), buf_size=500),
    batch_size=16)

x = fluid.data(name='x', shape=[None, 13], dtype='float32')
y = fluid.data(name='y', shape=[None, 1], dtype='float32')

y_predict = fluid.layers.fc(input=x, size=1, act=None)
cost = fluid.layers.square_error_cost(input=y_predict, label=y)
avg_loss = fluid.layers.mean(cost)
sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.01)
sgd_optimizer.minimize(avg_loss)

place = fluid.CPUPlace()
feeder = fluid.DataFeeder(place=place, feed_list=[x, y])
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())

import paddle_serving_client.io as serving_io

for pass_id in range(30):
    for data_train in train_reader():
        avg_loss_value, = exe.run(fluid.default_main_program(),
                                  feed=feeder.feed(data_train),
                                  fetch_list=[avg_loss])

serving_io.save_model("uci_housing_model", "uci_housing_client", {"x": x},
                      {"price": y_predict}, fluid.default_main_program())