diff --git a/model_zoo/alexnet/eval.py b/model_zoo/alexnet/eval.py index 4190451632..6a091aedd8 100644 --- a/model_zoo/alexnet/eval.py +++ b/model_zoo/alexnet/eval.py @@ -20,7 +20,7 @@ python eval.py --data_path /YourDataPath --ckpt_path Your.ckpt import argparse from src.config import alexnet_cfg as cfg -from src.dataset import create_dataset_mnist +from src.dataset import create_dataset_cifar10 from src.alexnet import AlexNet import mindspore.nn as nn from mindspore import context @@ -50,8 +50,8 @@ if __name__ == "__main__": print("============== Starting Testing ==============") param_dict = load_checkpoint(args.ckpt_path) load_param_into_net(network, param_dict) - ds_eval = create_dataset_mnist(args.data_path, - cfg.batch_size, - status="test") + ds_eval = create_dataset_cifar10(args.data_path, + cfg.batch_size, + status="test") acc = model.eval(ds_eval, dataset_sink_mode=args.dataset_sink_mode) print("============== {} ==============".format(acc)) diff --git a/model_zoo/alexnet/src/dataset.py b/model_zoo/alexnet/src/dataset.py index 6e9f310bed..651c76d6e3 100644 --- a/model_zoo/alexnet/src/dataset.py +++ b/model_zoo/alexnet/src/dataset.py @@ -23,7 +23,7 @@ from mindspore.common import dtype as mstype from .config import alexnet_cfg as cfg -def create_dataset_mnist(data_path, batch_size=32, repeat_size=1, status="train"): +def create_dataset_cifar10(data_path, batch_size=32, repeat_size=1, status="train"): """ create dataset for train or test """ diff --git a/model_zoo/alexnet/train.py b/model_zoo/alexnet/train.py index 184290c26c..df038d62a2 100644 --- a/model_zoo/alexnet/train.py +++ b/model_zoo/alexnet/train.py @@ -20,7 +20,7 @@ python train.py --data_path /YourDataPath import argparse from src.config import alexnet_cfg as cfg -from src.dataset import create_dataset_mnist +from src.dataset import create_dataset_cifar10 from src.generator_lr import get_lr from src.alexnet import AlexNet import mindspore.nn as nn @@ -43,7 +43,7 @@ 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) + ds_train = create_dataset_cifar10(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, ds_train.get_dataset_size()))