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GeneralRecognition_PPLCNet_x2_5_dml_002.yaml
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GeneralRecognition_PPLCNet_x2_5_dml_002.yaml
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# global configs
Global:
checkpoints: null
pretrained_model: null
output_dir: ./output/
device: gpu
save_interval: 1
eval_during_train: true
eval_interval: 1
epochs: 400
print_batch_step: 10
use_visualdl: True
# used for static mode and model export
image_shape: [3, 224, 224]
save_inference_dir: ./inference
eval_mode: retrieval
use_dali: False
to_static: False
# model architecture
Arch:
name: "DistillationModel"
infer_output_key: features
infer_add_softmax: False
is_rec: True
infer_model_name: "Student"
# 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:
- False
- False
models:
- Teacher:
name: RecModel
infer_output_key: features
infer_add_softmax: False
Backbone:
name: PPLCNet_x2_5
pretrained: True
use_ssld: True
BackboneStopLayer:
name: "flatten"
Neck:
name: FC
embedding_size: 1280
class_num: 512
Head:
name: ArcMargin
embedding_size: 512
class_num: 358
margin: 0.2
scale: 30
- Student:
name: RecModel
infer_output_key: features
infer_add_softmax: False
Backbone:
name: PPLCNet_x2_5
pretrained: True
use_ssld: True
BackboneStopLayer:
name: "flatten"
Neck:
name: FC
embedding_size: 1280
class_num: 512
Head:
name: ArcMargin
embedding_size: 512
class_num: 358
margin: 0.2
scale: 30
# loss function config for traing/eval process
Loss:
Train:
- DistillationGTCELoss:
weight: 1.0
key: "logits"
model_names: ["Student", "Teacher"]
- DistillationDMLLoss:
weight: 1.0
key: "logits"
model_name_pairs:
- ["Student", "Teacher"]
Eval:
- DistillationGTCELoss:
weight: 1.0
model_names: ["Student"]
Optimizer:
name: Momentum
momentum: 0.9
lr:
name: Cosine
learning_rate: 0.002
warmup_epoch: 5
regularizer:
name: 'L2'
coeff: 0.00001
# data loader for train and eval
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: /root/paddlejob/workspace/code/PaddleClas/dataset
cls_label_path: /root/paddlejob/workspace/code/PaddleClas/dataset/train_list.txt
transform_ops:
- DecodeImage:
to_rgb: True
channel_first: False
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 1.0/255.0
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
sampler:
name: DistributedBatchSampler
batch_size: 64
drop_last: False
shuffle: True
loader:
num_workers: 4
use_shared_memory: True
Eval:
Query:
dataset:
name: VeriWild
image_root: /root/paddlejob/workspace/code/PaddleClas/dataset
cls_label_path: /root/paddlejob/workspace/code/PaddleClas/dataset/test_list.txt
transform_ops:
- DecodeImage:
to_rgb: True
channel_first: False
- ResizeImage:
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: 64
drop_last: False
shuffle: False
loader:
num_workers: 4
use_shared_memory: True
Gallery:
dataset:
name: VeriWild
image_root: /root/paddlejob/workspace/code/PaddleClas/dataset
cls_label_path: /root/paddlejob/workspace/code/PaddleClas/dataset/test_list.txt
transform_ops:
- DecodeImage:
to_rgb: True
channel_first: False
- ResizeImage:
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: 64
drop_last: False
shuffle: False
loader:
num_workers: 4
use_shared_memory: True
Metric:
Eval:
- Recallk:
topk: [1, 5]