# LeNet Example ## Description Training LeNet with MNIST dataset in MindSpore. This is the simple and basic tutorial for constructing a network in MindSpore. ## Requirements - Install [MindSpore](https://www.mindspore.cn/install/en). - Download the MNIST dataset at . The directory structure is as follows: ``` └─MNIST_Data ├─test │ t10k-images.idx3-ubyte │ t10k-labels.idx1-ubyte │ └─train train-images.idx3-ubyte train-labels.idx1-ubyte ``` ## Running the example ```python # train LeNet, hyperparameter setting in config.py python train.py --data_path MNIST_Data ``` You can get loss with each step similar to this: ```bash epoch: 1 step: 1, loss is 2.3040335 ... epoch: 1 step: 1739, loss is 0.06952668 epoch: 1 step: 1740, loss is 0.05038793 epoch: 1 step: 1741, loss is 0.05018193 ... ``` Then, test LeNet according to network model ```python # test LeNet, after 1 epoch training, the accuracy is up to 96.5% python eval.py --data_path MNIST_Data --mode test --ckpt_path checkpoint_lenet-1_1875.ckpt ``` ## Note There are some optional arguments: ```bash -h, --help show this help message and exit --device_target {Ascend,GPU,CPU} device where the code will be implemented (default: Ascend) --data_path DATA_PATH path where the dataset is saved --dataset_sink_mode DATASET_SINK_MODE dataset_sink_mode is False or True ``` You can run ```python train.py -h``` or ```python eval.py -h``` to get more information.