ModelCheckpoint
class paddle.callbacks.ModelCheckpoint
( save_freq=1, save_dir=None )
ModelCheckpoint
是一个日志回调类。
参数:
save_freq (int,可选) - 间隔多少个epoch保存模型。默认值:1。
save_dir (int,可选) - 保存模型的文件夹。如果不设定,将不会保存模型。默认值:None。
代码示例:
import paddle
import paddle.vision.transforms as T
from paddle.static import InputSpec
inputs = [InputSpec([-1, 1, 28, 28], 'float32', 'image')]
labels = [InputSpec([None, 1], 'int64', 'label')]
transform = T.Compose([
T.Transpose(),
T.Normalize([127.5], [127.5])
])
train_dataset = paddle.vision.datasets.MNIST(mode='train', transform=transform)
lenet = paddle.vision.LeNet()
model = paddle.Model(lenet,
inputs, labels)
optim = paddle.optimizer.Adam(0.001, parameters=lenet.parameters())
model.prepare(optimizer=optim,
loss=paddle.nn.CrossEntropyLoss(),
metrics=paddle.metric.Accuracy())
callback = paddle.callbacks.ModelCheckpoint(save_dir='./temp')
model.fit(train_dataset, batch_size=64, callbacks=callback)