Nigel
/
mindspore
forked from mindspore-Ecosystem/mindspore
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

!2370 modify alexnet shell def get_lr args 

Merge pull request !2370 from changzherui/mod_alexnet
This commit is contained in:
mindspore-ci-bot 2020-06-20 10:54:57 +08:00 committed by Gitee
parent e8639ad91e 6c324b58d6
commit 8d34c65592
2 changed files with 6 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
model_zoo/alexnet/eval.py
View File

@ -45,7 +45,7 @@ if __name__ == "__main__":
loss = nn.SoftmaxCrossEntropyWithLogits(is_grad=False, sparse=True, reduction="mean")
repeat_size = cfg.epoch_size
opt = nn.Momentum(network.trainable_params(), cfg.learning_rate, cfg.momentum)
model = Model(network, loss, opt, metrics={"Accuracy": Accuracy()}) # test
model = Model(network, loss, opt, metrics={"Accuracy": Accuracy()})
print("============== Starting Testing ==============")
param_dict = load_checkpoint(args.ckpt_path)

12
model_zoo/alexnet/train.py
View File

@ -43,19 +43,17 @@ if __name__ == "__main__":
context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target)
ds_train = create_dataset_mnist(args.data_path, cfg.batch_size, cfg.epoch_size)
network = AlexNet(cfg.num_classes)
loss = nn.SoftmaxCrossEntropyWithLogits(is_grad=False, sparse=True, reduction="mean")
lr = Tensor(get_lr(0, cfg.learning_rate, cfg.epoch_size, cfg.save_checkpoint_steps))
lr = Tensor(get_lr(0, cfg.learning_rate, cfg.epoch_size, ds_train.get_dataset_size()))
opt = nn.Momentum(network.trainable_params(), lr, cfg.momentum)
model = Model(network, loss, opt, metrics={"Accuracy": Accuracy()}) # test
print("============== Starting Training ==============")
ds_train = create_dataset_mnist(args.data_path,
cfg.batch_size,
cfg.epoch_size)
model = Model(network, loss, opt, metrics={"Accuracy": Accuracy()})
time_cb = TimeMonitor(data_size=ds_train.get_dataset_size())
config_ck = CheckpointConfig(save_checkpoint_steps=cfg.save_checkpoint_steps,
keep_checkpoint_max=cfg.keep_checkpoint_max)
ckpoint_cb = ModelCheckpoint(prefix="checkpoint_alexnet", directory=args.ckpt_path, config=config_ck)
print("============== Starting Training ==============")
model.train(cfg.epoch_size, ds_train, callbacks=[time_cb, ckpoint_cb, LossMonitor()],
dataset_sink_mode=args.dataset_sink_mode)