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import paddle.v2 as paddle
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import numpy as np
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paddle.init(use_gpu=False)
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x = paddle.layer.data(name='x', type=paddle.data_type.dense_vector(2))
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y_predict = paddle.layer.fc(input=x, size=1, act=paddle.activation.Linear())
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# loading the model which generated by training
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with open('params_pass_90.tar', 'r') as f:
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parameters = paddle.parameters.Parameters.from_tar(f)
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# Input multiple sets of data,Output the infer result in a array.
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i = [[[1, 2]], [[3, 4]], [[5, 6]]]
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print paddle.infer(output_layer=y_predict, parameters=parameters, input=i)
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# Will print:
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# [[ -3.24491572]
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# [ -6.94668722]
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# [-10.64845848]]
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