mindspore/example/alexnet_cifar10/README.md

# AlexNet Example

## Description

Training AlexNet with CIFAR-10 dataset in MindSpore.

This is the simple tutorial for training AlexNet in MindSpore.

## Requirements

- Install [MindSpore](https://www.mindspore.cn/install/en).

- Download the CIFAR-10 dataset at <http://www.cs.toronto.edu/~kriz/cifar-10-binary.tar.gz>. The directory structure is as follows:

```
├─cifar-10-batches-bin
│
└─cifar-10-verify-bin
```

## Running the example

```python
# train AlexNet, hyperparameter setting in config.py
python train.py --data_path cifar-10-batches-bin
```

You can get loss with each step similar to this:

```bash
epoch: 1 step: 1, loss is 2.2791853
...
epoch: 1 step: 1536, loss is 1.9366643
epoch: 1 step: 1537, loss is 1.6983616
epoch: 1 step: 1538, loss is 1.0221305
...
```

Then, test AlexNet according to network model
```python
# test AlexNet, 1 epoch training accuracy is up to 51.1%; 10 epoch training accuracy is up to 81.2%
python eval.py --data_path cifar-10-verify-bin --mode test --ckpt_path checkpoint_alexnet-1_1562.ckpt
```

## Note
There are some optional arguments:

```bash
-h, --help           show this help message and exit
--device_target {Ascend,GPU}
                     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.