load_dygraph

paddle.fluid.dygraph.checkpoint. load_dygraph ( model_path, **configs ) [source]
Api_attr

imperative

Load parameter state dict from disk.

Note

Due to some historical reasons, if you load state_dict from the saved result of paddle.static.save_inference_model, the structured variable name will cannot be restored. You need to set the argument use_structured_name=False when using Layer.set_state_dict later.

Parameters

  • model_path (str) – The file prefix store the state_dict. (The path should Not contain suffix ‘.pdparams’)

  • **configs (dict, optional) – Other load configuration options for compatibility. We do not recommend using these configurations, if not necessary, DO NOT use them. Default None. The following options are currently supported: (1) model_filename (str): The inference model file name of the paddle 1.x save_inference_model save format. Default file name is __model__ . (2) params_filename (str): The persistable variables file name of the paddle 1.x save_inference_model save format. No default file name, save variables separately by default.

Returns

the dict store the state_dict

Return type

state_dict(dict)

Examples

import paddle
import paddle.fluid as fluid

paddle.disable_static()

emb = paddle.nn.Embedding(10, 10)

state_dict = emb.state_dict()
fluid.save_dygraph(state_dict, "paddle_dy")

scheduler = paddle.optimizer.lr.NoamDecay(
    d_model=0.01, warmup_steps=100, verbose=True)
adam = paddle.optimizer.Adam(
    learning_rate=scheduler,
    parameters=emb.parameters())
state_dict = adam.state_dict()
fluid.save_dygraph(state_dict, "paddle_dy")

para_state_dict, opti_state_dict = fluid.load_dygraph("paddle_dy")