From 168097fd61e1249f78a363325f2ea0879ee16319 Mon Sep 17 00:00:00 2001 From: cuicheng01 <45199522+cuicheng01@users.noreply.github.com> Date: Mon, 30 Oct 2023 20:21:52 +0800 Subject: [PATCH] remove PP-HGNetV2_B7 config (#3024) --- .../ImageNet/PPHGNetV2/PPHGNetV2_B7.yaml | 164 ------------------ 1 file changed, 164 deletions(-) delete mode 100644 ppcls/configs/ImageNet/PPHGNetV2/PPHGNetV2_B7.yaml diff --git a/ppcls/configs/ImageNet/PPHGNetV2/PPHGNetV2_B7.yaml b/ppcls/configs/ImageNet/PPHGNetV2/PPHGNetV2_B7.yaml deleted file mode 100644 index 5ce0601a2..000000000 --- a/ppcls/configs/ImageNet/PPHGNetV2/PPHGNetV2_B7.yaml +++ /dev/null @@ -1,164 +0,0 @@ -## Note: This config is only used for finetune training. The ImageNet metrics in PaddleClas are not trained through this config. -# global configs -Global: - checkpoints: null - pretrained_model: null - output_dir: ./output/ - device: gpu - save_interval: 1 - eval_during_train: True - eval_interval: 1 - epochs: 200 - print_batch_step: 10 - use_visualdl: False - # used for static mode and model export - image_shape: [3, 224, 224] - save_inference_dir: ./inference - # training model under @to_static - to_static: False - use_dali: False - -# mixed precision training -AMP: - use_amp: True - use_fp16_test: False - scale_loss: 128.0 - use_dynamic_loss_scaling: True - use_promote: False - # O1: mixed fp16, O2: pure fp16 - level: O1 - -# model architecture -Arch: - name: PPHGNetV2_B7 - class_num: 1000 - pretrained: True # ssld pretrained - -# 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 - # for global bs 1024, when finetune training, you need to reduce learning_rate manually - learning_rate: 0.5 - warmup_epoch: 5 - regularizer: - name: 'L2' - coeff: 0.00002 - - -# 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: 1.0/255.0 - mean: [0.485, 0.456, 0.406] - std: [0.229, 0.224, 0.225] - order: '' - - RandomErasing: - EPSILON: 0.25 - sl: 0.02 - sh: 1.0/3.0 - r1: 0.3 - attempt: 10 - use_log_aspect: True - mode: pixel - - sampler: - name: DistributedBatchSampler - batch_size: 128 - drop_last: False - shuffle: True - loader: - num_workers: 16 - 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: 232 - interpolation: bicubic - backend: pil - - 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: 128 - drop_last: False - shuffle: False - loader: - num_workers: 16 - 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: 232 - interpolation: bicubic - backend: pil - - 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]