PaddleClas/ppcls/configs/ImageNet/MobileViT/MobileViT_XS.yaml

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YAML

# global configs
Global:
checkpoints: null
pretrained_model: null
output_dir: ./output/
device: gpu
save_interval: 1
eval_during_train: True
eval_interval: 1
epochs: 300
print_batch_step: 10
use_visualdl: False
# used for static mode and model export
image_shape: [3, 256, 256]
save_inference_dir: ./inference
use_dali: False
# model architecture
Arch:
name: MobileViT_XS
class_num: 1000
# loss function config for traing/eval process
Loss:
Train:
- CELoss:
weight: 1.0
epsilon: 0.1
Eval:
- CELoss:
weight: 1.0
Optimizer:
name: AdamW
beta1: 0.9
beta2: 0.999
epsilon: 1e-8
weight_decay: 0.01
no_weight_decay_name: .bias norm
one_dim_param_no_weight_decay: True
lr:
# for 8 cards
name: Cosine
learning_rate: 0.002
eta_min: 0.0002
warmup_epoch: 5
warmup_start_lr: 0.0002
# data loader for train and eval
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: ./dataset/ILSVRC2012/
cls_label_path: ./dataset/ILSVRC2012/train_list.txt
transform_ops:
- DecodeImage:
to_rgb: True
channel_first: False
- RandCropImage:
size: 256
interpolation: bilinear
backend: pil
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 1.0/255.0
mean: [0.0, 0.0, 0.0]
std: [1.0, 1.0, 1.0]
order: ''
sampler:
name: DistributedBatchSampler
batch_size: 128
drop_last: False
shuffle: True
loader:
num_workers: 8
use_shared_memory: True
Eval:
dataset:
name: ImageNetDataset
image_root: ./dataset/ILSVRC2012/
cls_label_path: ./dataset/ILSVRC2012/val_list.txt
transform_ops:
- DecodeImage:
to_rgb: False
channel_first: False
- ResizeImage:
resize_short: 292
interpolation: bilinear
backend: pil
- CropImage:
size: 256
- NormalizeImage:
scale: 1.0/255.0
mean: [0.0, 0.0, 0.0]
std: [1.0, 1.0, 1.0]
order: ''
sampler:
name: DistributedBatchSampler
batch_size: 64
drop_last: False
shuffle: False
loader:
num_workers: 4
use_shared_memory: True
Infer:
infer_imgs: docs/images/inference_deployment/whl_demo.jpg
batch_size: 10
transforms:
- DecodeImage:
to_rgb: True
channel_first: False
- ResizeImage:
resize_short: 292
- CropImage:
size: 256
- NormalizeImage:
scale: 1.0/255.0
mean: [0.0, 0.0, 0.0]
std: [1.0, 1.0, 1.0]
order: ''
- ToCHWImage:
PostProcess:
name: Topk
topk: 5
class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
Metric:
Train:
- TopkAcc:
topk: [1, 5]
Eval:
- TopkAcc:
topk: [1, 5]