提交 ad92e521 编写于 作者: C cuicheng01

add res2net200_vd_distill_pphgnet_base.yaml

上级 713dd6f9
# global configs
Global:
checkpoints: null
pretrained_model: null
output_dir: "./output/"
device: "gpu"
save_interval: 1
eval_during_train: True
eval_interval: 1
epochs: 360
print_batch_step: 10
use_visualdl: False
# used for static mode and model export
image_shape: [3, 224, 224]
save_inference_dir: "./inference"
use_dali: false
# mixed precision training
AMP:
scale_loss: 128.0
use_dynamic_loss_scaling: True
# O1: mixed fp16
level: O1
# model architecture
Arch:
name: "DistillationModel"
class_num: &class_num 1000
# if not null, its lengths should be same as models
pretrained_list:
# if not null, its lengths should be same as models
freeze_params_list:
- True
- False
models:
- Teacher:
name: Res2Net200_vd_26w_4s
class_num: *class_num
pretrained: True
use_ssld: True
- Student:
name: PPHGNet_base
class_num: *class_num
pretrained: False
infer_model_name: "Student"
# loss function config for traing/eval process
Loss:
Train:
- DistillationCELoss:
weight: 1.0
model_name_pairs:
- ["Student", "Teacher"]
Eval:
- DistillationGTCELoss:
weight: 1.0
model_names: ["Student"]
Optimizer:
name: Momentum
momentum: 0.9
lr:
name: Cosine
learning_rate: 0.5
warmup_epoch: 5
regularizer:
name: 'L2'
coeff: 0.00004
# 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: 224
interpolation: bicubic
backend: pil
- RandFlipImage:
flip_code: 1
- TimmAutoAugment:
config_str: rand-m7-mstd0.5-inc1
interpolation: bicubic
img_size: 224
- NormalizeImage:
scale: 0.00392157
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
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: True
channel_first: False
- ResizeImage:
resize_short: 236
interpolation: bicubic
backend: pil
- CropImage:
size: 224
- NormalizeImage:
scale: 0.00392157
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
sampler:
name: DistributedBatchSampler
batch_size: 128
drop_last: False
shuffle: False
loader:
num_workers: 8
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: 236
- CropImage:
size: 224
- NormalizeImage:
scale: 1.0/255.0
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
- ToCHWImage:
PostProcess:
name: DistillationPostProcess
func: Topk
topk: 5
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
Metric:
Train:
- DistillationTopkAcc:
model_key: "Student"
topk: [1, 5]
Eval:
- DistillationTopkAcc:
model_key: "Student"
topk: [1, 5]
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册