diff --git a/ppcls/configs/quick_start/professional/MobileNetV3_large_x1_0_CIFAR100_finetune.yaml b/ppcls/configs/quick_start/professional/MobileNetV3_large_x1_0_CIFAR100_finetune.yaml index 8222f5a80..6cc50c98f 100644 --- a/ppcls/configs/quick_start/professional/MobileNetV3_large_x1_0_CIFAR100_finetune.yaml +++ b/ppcls/configs/quick_start/professional/MobileNetV3_large_x1_0_CIFAR100_finetune.yaml @@ -1,76 +1,127 @@ -mode: 'train' -ARCHITECTURE: - name: 'MobileNetV3_large_x1_0' +# global configs +Global: + checkpoints: null + pretrained_model: null + output_dir: "./output/" + device: "gpu" + class_num: 100 + save_interval: 1 + eval_during_train: True + eval_interval: 1 + epochs: 50 + print_batch_step: 10 + use_visualdl: False + # used for static mode and model export + image_shape: [3, 32, 32] + save_inference_dir: "./inference" -checkpoints: "" -pretrained_model: "./pretrained/MobileNetV3_large_x1_0_pretrained" -model_save_dir: "./output/" -classes_num: 100 -total_images: 50000 -save_interval: 1 -validate: True -valid_interval: 1 -epochs: 100 -topk: 5 -image_shape: [3, 32, 32] -use_mix: False - -LEARNING_RATE: - function: 'Cosine' - params: - lr: 0.04 - -OPTIMIZER: - function: 'Momentum' - params: - momentum: 0.9 - regularizer: - function: 'L2' - factor: 0.0001 - -TRAIN: - batch_size: 1024 - num_workers: 4 - file_list: "./dataset/CIFAR100/train_list.txt" - data_dir: "./dataset/CIFAR100/" - shuffle_seed: 0 - transforms: - - DecodeImage: - to_rgb: True - channel_first: False - - RandCropImage: - size: 32 - - RandFlipImage: - flip_code: 1 - - NormalizeImage: - scale: 1./255. - mean: [0.485, 0.456, 0.406] - std: [0.229, 0.224, 0.225] - order: '' - - ToCHWImage: - - mix: - - MixupOperator: - alpha: 0.2 +# model architecture +Arch: + name: "MobileNetV3_large_x1_0" + +# loss function config for traing/eval process +Loss: + Train: + - CELoss: + weight: 1.0 + epsilon: 0.1 + Eval: + - CELoss: + weight: 1.0 -VALID: - batch_size: 256 - num_workers: 0 - file_list: "./dataset/CIFAR100/test_list.txt" - data_dir: "./dataset/CIFAR100/" - shuffle_seed: 0 - transforms: - - DecodeImage: - to_rgb: True - channel_first: False - - ResizeImage: - resize_short: 36 - - CropImage: - size: 32 - - NormalizeImage: - scale: 1.0/255.0 - mean: [0.485, 0.456, 0.406] - std: [0.229, 0.224, 0.225] - order: '' - - ToCHWImage: +Optimizer: + name: Momentum + momentum: 0.9 + lr: + name: Cosine + learning_rate: 0.04 + regularizer: + name: 'L2' + coeff: 0.0001 + + +# data loader for train and eval +DataLoader: + Train: + dataset: + name: ImageNetDataset + image_root: "./dataset/CIFAR100/" + cls_label_path: "./dataset/CIFAR100/train_list.txt" + transform_ops: + - RandCropImage: + size: 32 + scale: [0.5, 1] + ratio: [1, 1] + - RandFlipImage: + flip_code: 1 + - NormalizeImage: + scale: 0.00392157 + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: '' + + sampler: + name: DistributedBatchSampler + batch_size: 1000 + drop_last: False + shuffle: True + loader: + num_workers: 6 + use_shared_memory: False + + Eval: + # TOTO: modify to the latest trainer + dataset: + name: ImageNetDataset + image_root: "./dataset/CIFAR100/" + cls_label_path: "./dataset/CIFAR100/test_list.txt" + transform_ops: + - ResizeImage: + resize_short: 36 + - CropImage: + size: 32 + - NormalizeImage: + scale: 0.00392157 + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: '' + sampler: + name: DistributedBatchSampler + batch_size: 1000 + drop_last: False + shuffle: False + loader: + num_workers: 6 + use_shared_memory: False + +Infer: + infer_imgs: "docs/images/whl/demo.jpg" + batch_size: 10 + transforms: + - DecodeImage: + to_rgb: True + channel_first: False + - ResizeImage: + resize_short: 36 + - CropImage: + size: 32 + - 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: + - Topk: + k: [1, 5] + Eval: + - Topk: + k: [1, 5] +