add some new configs

ppcls/configs/slim/GeneralRecognition_PPLCNet_x2_5_quantization.yaml

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+# global configs
+Global:
+ checkpoints: null
+ pretrained_model: https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/models/pretrain/general_PPLCNet_x2_5_pretrained_v1.0.pdparams
+ output_dir: ./output/
+ device: gpu
+ save_interval: 1
+ eval_during_train: True
+ eval_interval: 1
+ epochs: 30
+ print_batch_step: 10
+ use_visualdl: False
+ # 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
+
+# for quantizaiton or prune model
+Slim:
+ ## for prune
+ quant:
+ name: pact
+
+# model architecture
+Arch:
+ name: RecModel
+ infer_output_key: features
+ infer_add_softmax: False
+
+ Backbone: 
+ name: PPLCNet_x2_5
+ pretrained: False
+ use_ssld: True
+ BackboneStopLayer:
+ name: flatten_0
+ Neck:
+ name: FC
+ embedding_size: 1280
+ class_num: 512
+ Head:
+ name: ArcMargin 
+ embedding_size: 512
+ class_num: 185341
+ margin: 0.2
+ scale: 30
+
+# loss function config for traing/eval process
+Loss:
+ Train:
+ - CELoss:
+ weight: 1.0
+ Eval:
+ - CELoss:
+ weight: 1.0
+
+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: ./dataset/
+ cls_label_path: ./dataset/train_reg_all_data.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: 128
+ drop_last: False
+ shuffle: True
+ loader:
+ num_workers: 4
+ use_shared_memory: True
+
+ Eval:
+ Query:
+ dataset: 
+ name: VeriWild
+ image_root: ./dataset/Aliproduct/
+ cls_label_path: ./dataset/Aliproduct/val_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: ./dataset/Aliproduct/
+ cls_label_path: ./dataset/Aliproduct/val_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]

ppcls/configs/slim/PPLCNet_x1_0_quantization.yaml

@@ -0,0 +1,138 @@
+# global configs
+Global:
+ checkpoints: null
+ pretrained_model: null
+ output_dir: ./output/
+ device: gpu
+ save_interval: 1
+ eval_during_train: True
+ eval_interval: 1
+ epochs: 60
+ print_batch_step: 10
+ use_visualdl: False
+ # used for static mode and model export
+ image_shape: [3, 224, 224]
+ save_inference_dir: ./inference
+
+# for quantalization or prune model 
+Slim:
+ ## for quantization
+ quant:
+ name: pact
+
+# model architecture
+Arch:
+ name: PPLCNet_x1_0
+ class_num: 1000
+ pretrained: True
+
+# loss function config for traing/eval process
+Loss:
+ Train:
+ - CELoss:
+ weight: 1.0
+ epsilon: 0.1
+ Eval:
+ - CELoss:
+ weight: 1.0
+
+
+Optimizer:
+ name: Momentum
+ momentum: 0.9
+ lr:
+ name: Cosine
+ learning_rate: 0.02
+ warmup_epoch: 0
+ regularizer:
+ name: 'L2'
+ coeff: 0.00003
+
+
+# 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
+ - RandFlipImage:
+ flip_code: 1
+ - AutoAugment:
+ - 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: 128
+ drop_last: False
+ shuffle: True
+ loader:
+ num_workers: 4
+ 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: 256
+ - CropImage:
+ size: 224
+ - 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: False
+ loader:
+ num_workers: 4
+ use_shared_memory: True
+
+Infer:
+ infer_imgs: docs/images/whl/demo.jpg
+ batch_size: 10
+ transforms:
+ - DecodeImage:
+ to_rgb: True
+ channel_first: False
+ - ResizeImage:
+ resize_short: 256
+ - 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: Topk
+ topk: 5
+ class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
+
+Metric:
+ Train:
+ - TopkAcc:
+ topk: [1, 5]
+ Eval:
+ - TopkAcc:
+ topk: [1, 5]