serialize_persistables

paddle.static. serialize_persistables ( feed_vars, fetch_vars, executor, **kwargs ) [源代码] 

根据指定的 feed_vars，fetch_vars 和 executor，序列化模型参数。

参数

feed_vars (Variable | list[Variable]) – 模型的输入变量。

fetch_vars (Variable | list[Variable]) – 模型的输出变量。

executor (Executor) - 用于保存预测模型的 executor，详见执行器。

kwargs - 支持的 key 包括 program。(注意：kwargs 主要是用来做反向兼容的)。

program - 指定想要序列化的 program，默认使用 default_main_program。

返回

参数序列化之后的字节数组。

代码示例

          >>> import paddle
>>> paddle.enable_static()
>>> with paddle.pir_utils.OldIrGuard():
...     path_prefix = "./infer_model"
...
...     # User defined network, here a softmax regression example
...     image = paddle.static.data(name='img', shape=[None, 28, 28], dtype='float32')
...     label = paddle.static.data(name='label', shape=[None, 1], dtype='int64')
...     predict = paddle.static.nn.fc(image, 10, activation='softmax')
...
...     loss = paddle.nn.functional.cross_entropy(predict, label)
...
...     exe = paddle.static.Executor(paddle.CPUPlace())
...     exe.run(paddle.static.default_startup_program())
...
...     # serialize parameters to bytes.
...     serialized_params = paddle.static.serialize_persistables([image], [predict], exe)
...
...     # deserialize bytes to parameters.
...     main_program = paddle.static.default_main_program()
...     deserialized_params = paddle.static.deserialize_persistables(main_program, serialized_params, exe)

         