import paddle
import numpy as np

paddle.enable_static()

# 构建模型
startup_prog = paddle.static.default_startup_program()
main_prog = paddle.static.default_main_program()
with paddle.static.program_guard(main_prog, startup_prog):
    image = paddle.static.data(name="img", shape=[64, 784])
    w = paddle.create_parameter(shape=[784, 200], dtype='float32')
    b = paddle.create_parameter(shape=[200], dtype='float32')
    hidden_w = paddle.matmul(x=image, y=w)
    hidden_b = paddle.add(hidden_w, b)
exe = paddle.static.Executor(paddle.CPUPlace())
exe.run(startup_prog)

# 保存预测模型
path_prefix = "./infer_model"
paddle.static.save_inference_model(path_prefix, [image], [hidden_b], exe)

[inference_program, feed_target_names, fetch_targets] = (
    paddle.static.load_inference_model(path_prefix, exe))
tensor_img = np.array(np.random.random((64, 784)), dtype=np.float32)
results = exe.run(inference_program,
              feed={feed_target_names[0]: tensor_img},
              fetch_list=fetch_targets)

# 在上述示例中，inference program 被保存在 "./infer_model.pdmodel" 文件中，
# 参数被保存在 "./infer_model.pdiparams" 文件中。
# 加载 inference program 后， executor可使用 fetch_targets 和 feed_target_names,
# 执行Program，并得到预测结果。