remove PP-HGNetV2_B7 config (#3024)

ppcls/configs/ImageNet/PPHGNetV2/PPHGNetV2_B7.yaml

@@ -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]