[TIPC] add pp_mobileseg_base_ade20k_512x512_80k to train benchmark (#3221)

Co-authored-by: root <[email protected]>

Author: TingquanGao

test_tipc/configs/pp_mobileseg/pp_mobileseg_base_ade20k_512x512_80k.yml

@@ -0,0 +1,71 @@
+_base_: '../_base_/ade20k.yml'
+
+batch_size: 16  # total batch size is 32
+iters: 80000
+
+train_dataset:
+  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:
+  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: MixedLoss
+      losses:
+        - type: CrossEntropyLoss
+        - type: LovaszSoftmaxLoss
+      coef: [0.8, 0.2]
+  coef: [1]
+
+
+model:
+  type: PPMobileSeg
+  num_classes: 150
+  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

test_tipc/configs/pp_mobileseg/train_infer_python.txt

@@ -0,0 +1,63 @@
+===========================train_params===========================
+model_name:pp_mobileseg
+python:python3.7
+gpu_list:0|0,1
+Global.use_gpu:null|null
+--precision:null
+--iters:lite_train_lite_infer=20|lite_train_whole_infer=20|whole_train_whole_infer=1000
+--save_dir:
+--batch_size:lite_train_lite_infer=2|lite_train_whole_infer=2|whole_train_whole_infer=3
+--model_path:null
+train_model_name:best_model/model.pdparams
+train_infer_img_dir:test_tipc/data/cityscapes/cityscapes_val_5.list
+--profiler_options:null
+##
+trainer:norm_train
+norm_train:tools/train.py --config test_tipc/configs/pp_mobileseg/pp_mobileseg_base_ade20k_512x512_80k.yml --device gpu --save_interval 500 --seed 100 --num_workers 8
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:null
+null:null
+##
+===========================export_params===========================
+--save_dir:
+--model_path:
+norm_export:tools/export.py --config test_tipc/configs/pp_mobileseg/pp_mobileseg_base_ade20k_512x512_80k.yml
+quant_export:null
+fpgm_export:null
+distill_export:null
+export1:null
+export2:null
+===========================infer_params===========================
+infer_model:./test_tipc/output/pp_mobileseg/model.pdparams
+infer_export:tools/export.py --config test_tipc/configs/pp_mobileseg/pp_mobileseg_base_ade20k_512x512_80k.yml
+infer_quant:False
+inference:deploy/python/infer.py --save_dir ./test_tipc/output/pp_mobileseg/
+--device:cpu|gpu
+--enable_mkldnn:True
+--cpu_threads:6
+--batch_size:1
+--use_trt:False
+--precision:fp32
+--config:
+--image_path:./test_tipc/data/cityscapes/cityscapes_val_5.list
+--save_log_path:null
+--benchmark:True
+--save_dir:
+--model_name:pp_mobileseg
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,1024,1024]}]
+===========================to_static_train_benchmark_params===========================
+to_static_train:--opts to_static_training=True
+===========================train_benchmark_params==========================
+batch_size:4
+fp_items:fp32|fp16
+epoch:400
+--profiler_options:'batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile'
+flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096;FLAGS_cudnn_deterministic=False
+log_iters:15;repeats:500

test_tipc/prepare.sh

@@ -175,7 +175,7 @@ if [ ${MODE} = "benchmark_train" ]; then
         rm -rf ./test_tipc/data/coco
         wget -nc -P ./test_tipc/data/ https://paddleseg.bj.bcebos.com/tipc/data/mini_coco.zip --no-check-certificate
         cd ./test_tipc/data/ && unzip mini_coco.zip && cd -
-    elif [ ${model_name} = 'vit_adapter' ]; then
+    elif [ ${model_name} = 'vit_adapter' ] || [ ${model_name} = 'pp_mobileseg' ]; then
         rm -rf ./test_tipc/data/ADEChallengeData2016
         wget -nc -P ./test_tipc/data/ https://paddleseg.bj.bcebos.com/dataset/ADEChallengeData2016.zip --no-check-certificate
         cd ./test_tipc/data/ && unzip ADEChallengeData2016.zip && cd -