3.1 KiB
MobileNetV2 Example
Description
This is an example of training MobileNetV2 with ImageNet2012 dataset in MindSpore.
Requirements
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Install MindSpore.
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Download the dataset ImageNet2012.
Unzip the ImageNet2012 dataset to any path you want and the folder structure should be as follows:
. ├── train # train dataset └── val # infer dataset
Example structure
.
├── config.py # parameter configuration
├── dataset.py # data preprocessing
├── eval.py # infer script
├── launch.py # launcher for distributed training
├── lr_generator.py # generate learning rate for each step
├── run_infer.sh # launch infering
├── run_train.sh # launch training
└── train.py # train script
Parameter configuration
Parameters for both training and inference can be set in 'config.py'.
"num_classes": 1000, # dataset class num
"image_height": 224, # image height
"image_width": 224, # image width
"batch_size": 256, # training or infering batch size
"epoch_size": 200, # total training epochs, including warmup_epochs
"warmup_epochs": 4, # warmup epochs
"lr": 0.4, # base learning rate
"momentum": 0.9, # momentum
"weight_decay": 4e-5, # weight decay
"loss_scale": 1024, # loss scale
"save_checkpoint": True, # whether save checkpoint
"save_checkpoint_epochs": 1, # the epoch interval between two checkpoints
"keep_checkpoint_max": 200, # only keep the last keep_checkpoint_max checkpoint
"save_checkpoint_path": "./checkpoint" # path to save checkpoint
Running the example
Train
Usage
Usage: sh run_train.sh [DEVICE_NUM] [SERVER_IP(x.x.x.x)] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH]
Launch
# training example
sh run_train.sh 8 192.168.0.1 0,1,2,3,4,5,6,7 ~/imagenet
Result
Training result will be stored in the example path. Checkpoints will be stored at . /checkpoint by default, and training log will be redirected to ./train/train.log like followings.
epoch: [ 0/200], step:[ 624/ 625], loss:[5.258/5.258], time:[140412.236], lr:[0.100]
epoch time: 140522.500, per step time: 224.836, avg loss: 5.258
epoch: [ 1/200], step:[ 624/ 625], loss:[3.917/3.917], time:[138221.250], lr:[0.200]
epoch time: 138331.250, per step time: 221.330, avg loss: 3.917
Infer
Usage
Usage: sh run_infer.sh [DATASET_PATH] [CHECKPOINT_PATH]
Launch
# infer example
sh run_infer.sh ~/imagenet ~/train/mobilenet-200_625.ckpt
checkpoint can be produced in training process.
Result
Inference result will be stored in the example path, you can find result like the followings in val.log.
result: {'acc': 0.71976314102564111} ckpt=/path/to/checkpoint/mobilenet-200_625.ckpt