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@ -181,7 +181,7 @@ images = data_layer(name='pixel', dims=[BATCH_SIZE, 784])
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labels = data_layer(name='label', dims=[BATCH_SIZE])
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fc1 = fc_layer(net=forward_net, input=images, size=100, act="sigmoid")
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fc2 = fc_layer(net=forward_net, input=fc1, size=100, act="sigmoid")
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predict = fc_layer(net=forward_net, input=fc2, size=100, act="softmax")
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predict = fc_layer(net=forward_net, input=fc2, size=10, act="softmax")
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cost = cross_entropy_layer(net=forward_net, input=predict, label=labels)
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init_net.complete_add_op(True)
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@ -223,7 +223,7 @@ def test(cost_name):
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sum(error) / float(len(error))))
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PASS_NUM = 1
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PASS_NUM = 10
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init_net.run(scope, dev_ctx)
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for pass_id in range(PASS_NUM):
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