dpn98_ascend.yaml

# system
mode: 0
distribute: True
num_parallel_workers: 8
val_while_train: True

# dataset
dataset: 'imagenet'
data_dir: 'path/to/imagenet'
shuffle: True
dataset_download: False
batch_size: 32
drop_remainder: True

# augmentation
image_resize: 224
scale: [0.08, 1.0]
ratio: [0.75, 1.333]
hflip: 0.5
vflip: 0.0
interpolation: 'bilinear'
crop_pct: 0.875

# model
model: 'dpn98'
num_classes: 1000
pretrained: False
ckpt_path: ''
keep_checkpoint_max: 10
ckpt_save_dir: './ckpt'
epoch_size: 200
dataset_sink_mode: True
amp_level: 'O2'

# loss
loss: 'CE'
label_smoothing: 0.1

# lr scheduler
scheduler: 'cosine_decay'
min_lr: 1e-6
lr: 0.05
warmup_epochs: 0
decay_epochs: 200

# optimizer
opt: 'SGD'
momentum: 0.9
weight_decay: 0.0001
loss_scale: 1024
use_nesterov: False