29 lines
817 B
Python
29 lines
817 B
Python
# Refers to https://pytorch.org/blog/ml-models-torchvision-v0.9/#classification
|
|
|
|
_base_ = [
|
|
'../_base_/models/mobilenet_v3/mobilenet_v3_small_imagenet.py',
|
|
'../_base_/datasets/imagenet_bs128_mbv3.py',
|
|
'../_base_/default_runtime.py',
|
|
]
|
|
|
|
# schedule settings
|
|
optim_wrapper = dict(
|
|
optimizer=dict(
|
|
type='RMSprop',
|
|
lr=0.064,
|
|
alpha=0.9,
|
|
momentum=0.9,
|
|
eps=0.0316,
|
|
weight_decay=1e-5))
|
|
|
|
param_scheduler = dict(type='StepLR', by_epoch=True, step_size=2, gamma=0.973)
|
|
|
|
train_cfg = dict(by_epoch=True, max_epochs=600, val_interval=1)
|
|
val_cfg = dict()
|
|
test_cfg = dict()
|
|
|
|
# NOTE: `auto_scale_lr` is for automatically scaling LR
|
|
# based on the actual training batch size.
|
|
# base_batch_size = (8 GPUs) x (128 samples per GPU)
|
|
auto_scale_lr = dict(base_batch_size=1024)
|