Merge pull request #6646 from memorycancel/add-refer-code-to-getstarted

Add refer code to get started ~
del_some_in_makelist
Tao Luo 7 years ago committed by GitHub
commit 8a24915d39
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@ -0,0 +1,18 @@
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('params_pass_90.tar', 'r') as f:
parameters = paddle.parameters.Parameters.from_tar(f)
# Input multiple sets of dataOutput the infer result in a array.
i = [[[1, 2]], [[3, 4]], [[5, 6]]]
print paddle.infer(output_layer=y_predict, parameters=parameters, input=i)
# Will print:
# [[ -3.24491572]
# [ -6.94668722]
# [-10.64845848]]

@ -26,6 +26,11 @@ def event_handler(event):
if event.batch_id % 1 == 0:
print "Pass %d, Batch %d, Cost %f" % (event.pass_id, event.batch_id,
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

@ -147,4 +147,9 @@ PaddlePaddle支持不同类型的输入数据主要包括四种类型
.. literalinclude:: src/train.py
:linenos:
使用以上训练好的模型进行预测取其中一个模型params_pass_90.tar输入需要预测的向量组然后打印输出
.. 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>`_

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