fix bugs

configs/pp_mobileseg_multilabel/pp_mobileseg_multilabel_base_coco2017_512x512_80k.yml

@@ -0,0 +1,72 @@
+_base_: '../_base_/coco_instance_multilabel.yml'
+
+batch_size: 16  # total batch size is 32
+iters: 80000
+
+train_dataset:
+  image_dir: val2017/
+  anno_path: annotations/instances_val2017.json
+  allow_overlap: True
+  add_background: True
+  transforms:
+    - type: ResizeStepScaling
+      min_scale_factor: 0.5
+      max_scale_factor: 2.0
+      scale_step_size: 0.25
+    - type: RandomPaddingCrop
+      crop_size: [512, 512]
+    - type: RandomHorizontalFlip
+    - type: RandomDistort
+      brightness_range: 0.4
+      contrast_range: 0.4
+      saturation_range: 0.4
+    - type: Normalize
+      mean: [0.485, 0.456, 0.406]
+      std: [0.229, 0.224, 0.225]
+
+val_dataset:
+  allow_overlap: True
+  add_background: True
+  transforms:
+    - type: Resize
+      target_size: [2048, 512]
+      keep_ratio: True
+      size_divisor: 32
+    - type: Normalize
+      mean: [0.485, 0.456, 0.406]
+      std: [0.229, 0.224, 0.225]
+
+optimizer:
+  _inherited_: False
+  type: AdamW
+  weight_decay: 0.01
+  custom_cfg:
+  - name: pos_embed
+    weight_decay_mult: 0.0
+  - name: head
+    lr_multi: 10.0
+  - name: bn
+    weight_decay_mult: 0.0
+
+lr_scheduler:
+  type: PolynomialDecay
+  learning_rate: 0.0006
+  end_lr: 0
+  power: 1.0
+  warmup_iters: 1500
+  warmup_start_lr: 1.0e-6
+
+loss:
+  types:
+    - type: MultiLabelCategoricalCrossEntropyLoss
+  coef: [1]
+
+model:
+  type: PPMobileSeg
+  num_classes: 81
+  backbone:
+    type: MobileSeg_Base
+    inj_type: AAMSx8
+    out_feat_chs: [64, 128, 192] 
+    pretrained: https://bj.bcebos.com/paddleseg/dygraph/ade20k/pp_mobileseg/pretrain/model.pdparams
+  upsample: intepolate # During exportation, you need to change it to vim for using VIM

configs/pp_mobileseg_multilabel/pp_mobileseg_multilabel_tiny_coco2017_512x512_80k.yml

@@ -0,0 +1,15 @@
+_base_: './pp_mobileseg_multilabel_base_coco2017_512x512_80k.yml'
+
+batch_size: 2  # total batch size is 32
+iters: 80000
+
+model:
+  type: PPMobileSeg
+  num_classes: 81
+  backbone:
+    type: MobileSeg_Tiny
+    inj_type: AAM
+    out_feat_chs: [32, 64, 128]
+    pretrained: https://bj.bcebos.com/paddleseg/dygraph/ade20k/pp_mobileseg_tiny_pretrain/model.pdparams
+  upsample: intepolate  # During exportation, you need to change it to vim for using VIM
+