Update ResNet50_retrieval.yml
-a
+# global configs
+Global:
+ checkpoints: null
+ pretrained_model: null
+ output_dir: "./output/"
+ device: "gpu"
+ class_num: 1000
+ save_interval: 1
+ eval_during_train: True
+ eval_interval: 1
+ epochs: 120
+ print_batch_step: 10
+ use_visualdl: False
+ image_shape: [3, 224, 224]
+ infer_imgs:
+
+# model architecture
+Arch:
+ name: "RecModel"
+ Backbone:
+ name: "ResNet50"
+ Stoplayer:
+ name: "flatten_0"
+ output_dim: 2048
+ embedding_size: 512
+ Head:
+ name: "ArcMargin"
+ margin: 0.5
+ scale: 80
+
+# 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: Piecewise
+ learning_rate: 0.1
+ decay_epochs: [30, 60, 90]
+ values: [0.1, 0.01, 0.001, 0.0001]
+ regularizer:
+ name: 'L2'
+ coeff: 0.0001
+
+# data loader for train and eval
+DataLoader:
+ Train:
+ # Dataset:
+ # Sampler:
+ # Loader:
+ batch_size: 256
+ num_workers: 4
+ file_list: "./dataset/ILSVRC2012/train_list.txt"
+ data_dir: "./dataset/ILSVRC2012/"
+ shuffle_seed: 0
+ transforms:
+ - DecodeImage:
+ to_rgb: True
+ channel_first: False
+ - RandCropImage:
+ size: 224
+ - RandFlipImage:
+ flip_code: 1
+ - NormalizeImage:
+ scale: 1./255.
+ mean: [0.485, 0.456, 0.406]
+ std: [0.229, 0.224, 0.225]
+ order: ''
+ - ToCHWImage:
+ Eval:
+ # TOTO: modify to the latest trainer
+ # Dataset:
+ # Sampler:
+ # Loader:
+ batch_size: 128
+ num_workers: 4
+ file_list: "./dataset/ILSVRC2012/val_list.txt"
+ data_dir: "./dataset/ILSVRC2012/"
+ shuffle_seed: 0
+ 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:
+
+Metric:
+ Train:
+ - Topk:
+ k: [1, 5]
+ Eval:
+ - Topk:
+ k: [1, 5]
