提交 f5dc9ead 编写于 作者: Z zhushuang02

Add refer code to get started

上级 72bcf7b3
import paddle.v2 as paddle
import numpy as np
paddle.init(use_gpu=False)
x = paddle.layer.data(name='x', type=paddle.data_type.dense_vector(2))
y_predict = paddle.layer.fc(input=x, size=1, act=paddle.activation.Linear())
# loading the model which generated by training
with open('hello_params_pass_90.tar', 'r') as f:
parameters = paddle.parameters.Parameters.from_tar(f)
i = [[[1, 2]]]
print paddle.infer(output_layer=y_predict, parameters=parameters, input=i)
...@@ -26,6 +26,11 @@ def event_handler(event): ...@@ -26,6 +26,11 @@ def event_handler(event):
if event.batch_id % 1 == 0: if event.batch_id % 1 == 0:
print "Pass %d, Batch %d, Cost %f" % (event.pass_id, event.batch_id, print "Pass %d, Batch %d, Cost %f" % (event.pass_id, event.batch_id,
event.cost) event.cost)
# product model every 10 pass
if isinstance(event, paddle.event.EndPass):
if event.pass_id % 10 == 0:
with open('params_pass_%d.tar' % event.pass_id, 'w') as f:
trainer.save_parameter_to_tar(f)
# define training dataset reader # define training dataset reader
......
...@@ -147,4 +147,9 @@ PaddlePaddle支持不同类型的输入数据,主要包括四种类型,和 ...@@ -147,4 +147,9 @@ PaddlePaddle支持不同类型的输入数据,主要包括四种类型,和
.. literalinclude:: src/train.py .. literalinclude:: src/train.py
:linenos: :linenos:
使用以上训练好的模型进行预测的例子:
.. literalinclude:: src/infer.py
:linenos:
有关线性回归的实际应用,可以参考PaddlePaddle book的 `第一章节 <http://book.paddlepaddle.org/index.html>`_。 有关线性回归的实际应用,可以参考PaddlePaddle book的 `第一章节 <http://book.paddlepaddle.org/index.html>`_。
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