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91 lines
2.8 KiB
91 lines
2.8 KiB
import unittest
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import numpy as np
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import paddle.v2.fluid.core as core
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import paddle.v2.fluid.executor as executor
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import paddle.v2.fluid.layers as layers
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import paddle.v2.fluid.optimizer as optimizer
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from paddle.v2.fluid.framework import Program
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from paddle.v2.fluid.io import save_inference_model, load_inference_model
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class TestBook(unittest.TestCase):
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def test_fit_line_inference_model(self):
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MODEL_DIR = "./tmp/inference_model"
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init_program = Program()
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program = Program()
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x = layers.data(
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name='x',
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shape=[2],
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dtype='float32',
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main_program=program,
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startup_program=init_program)
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y = layers.data(
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name='y',
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shape=[1],
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dtype='float32',
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main_program=program,
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startup_program=init_program)
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y_predict = layers.fc(input=x,
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size=1,
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act=None,
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main_program=program,
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startup_program=init_program)
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cost = layers.square_error_cost(
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input=y_predict,
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label=y,
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main_program=program,
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startup_program=init_program)
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avg_cost = layers.mean(
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x=cost, main_program=program, startup_program=init_program)
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sgd_optimizer = optimizer.SGDOptimizer(learning_rate=0.001)
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sgd_optimizer.minimize(avg_cost, init_program)
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place = core.CPUPlace()
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exe = executor.Executor(place)
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exe.run(init_program, feed={}, fetch_list=[])
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for i in xrange(100):
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tensor_x = np.array(
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[[1, 1], [1, 2], [3, 4], [5, 2]]).astype("float32")
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tensor_y = np.array([[-2], [-3], [-7], [-7]]).astype("float32")
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exe.run(program,
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feed={'x': tensor_x,
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'y': tensor_y},
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fetch_list=[avg_cost])
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save_inference_model(MODEL_DIR, ["x", "y"], [avg_cost], exe, program)
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expected = exe.run(program,
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feed={'x': tensor_x,
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'y': tensor_y},
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fetch_list=[avg_cost])[0]
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reload(executor) # reload to build a new scope
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exe = executor.Executor(place)
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[infer_prog, feed_var_names, fetch_vars] = load_inference_model(
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MODEL_DIR, exe)
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outs = exe.run(
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infer_prog,
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feed={feed_var_names[0]: tensor_x,
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feed_var_names[1]: tensor_y},
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fetch_list=fetch_vars)
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actual = outs[0]
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self.assertEqual(feed_var_names, ["x", "y"])
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self.assertEqual(len(fetch_vars), 1)
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self.assertEqual(str(fetch_vars[0]), str(avg_cost))
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self.assertEqual(expected, actual)
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if __name__ == '__main__':
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unittest.main()
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