forked from mindspore-Ecosystem/mindspore
15ccc5c56e | ||
---|---|---|
.. | ||
README.md | ||
config.py | ||
dataset.py | ||
eval.py | ||
train.py |
README.md
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.
-
Download the MNIST dataset at http://yann.lecun.com/exdb/mnist/. 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
# train LeNet, hyperparameter setting in config.py
python train.py --data_path MNIST_Data
You will get the loss value of each step as following:
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, evaluate LeNet according to network model
# evaluate 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
Here are some optional parameters:
--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.