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[TIPC] Add TIPC Benchmarks of SFNet and MobileSeg-MV3 (#2505)
* Add TIPC chains of SFNet and MobileSeg-MV3 * Fix SegFormer initialization bug * Update benchmark statistics of OCRNet_HRNetW18 and PPMatting * Update SegFormer configs
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test_tipc/configs/mobileseg_mv3/mobileseg_mobilenetv3_cityscapes_1024x512_80k.yml
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_base_: '../_base_/cityscapes.yml' | ||
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batch_size: 4 | ||
iters: 80000 | ||
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optimizer: | ||
weight_decay: 5.0e-4 | ||
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lr_scheduler: | ||
warmup_iters: 1000 | ||
warmup_start_lr: 1.0e-5 | ||
learning_rate: 0.005 | ||
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loss: | ||
types: | ||
- type: OhemCrossEntropyLoss | ||
min_kept: 130000 | ||
- type: OhemCrossEntropyLoss | ||
min_kept: 130000 | ||
- type: OhemCrossEntropyLoss | ||
min_kept: 130000 | ||
coef: [1, 1, 1] | ||
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train_dataset: | ||
transforms: | ||
- type: ResizeStepScaling | ||
min_scale_factor: 0.5 | ||
max_scale_factor: 2.0 | ||
scale_step_size: 0.25 | ||
- type: RandomPaddingCrop | ||
crop_size: [1024, 512] | ||
- type: RandomHorizontalFlip | ||
- type: RandomDistort | ||
brightness_range: 0.5 | ||
contrast_range: 0.5 | ||
saturation_range: 0.5 | ||
- type: Normalize | ||
mode: train | ||
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model: | ||
type: MobileSeg | ||
backbone: | ||
type: MobileNetV3_large_x1_0 # out channels: [24, 40, 112, 160] | ||
pretrained: https://paddleseg.bj.bcebos.com/dygraph/backbone/mobilenetv3_large_x1_0_ssld.tar.gz | ||
cm_bin_sizes: [1, 2, 4] | ||
cm_out_ch: 128 | ||
arm_out_chs: [32, 64, 128] | ||
seg_head_inter_chs: [32, 32, 32] |
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===========================train_params=========================== | ||
model_name:mobileseg_mv3 | ||
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=4 | ||
--model_path:null | ||
train_model_name:best_model/model.pdparams | ||
train_infer_img_dir:test_tipc/data/cityscapes/cityscapes_val_5.list | ||
null:null | ||
## | ||
trainer:norm | ||
norm_train:train.py --config test_tipc/configs/mobileseg_mv3/mobileseg_mobilenetv3_cityscapes_1024x512_80k.yml --save_interval 500 --seed 100 --num_workers 8 | ||
pact_train:null | ||
fpgm_train:null | ||
distill_train:null | ||
null:null | ||
null:null | ||
## | ||
===========================eval_params=========================== | ||
eval:val.py --config test_tipc/configs/mobileseg_mv3/mobileseg_mobilenetv3_cityscapes_1024x512_80k.yml --num_workers 8 | ||
null:null | ||
## | ||
===========================export_params=========================== | ||
--save_dir: | ||
--model_path: | ||
norm_export:export.py --config test_tipc/configs/mobileseg_mv3/mobileseg_mobilenetv3_cityscapes_1024x512_80k.yml | ||
quant_export:null | ||
fpgm_export:null | ||
distill_export:null | ||
export1:null | ||
export2:null | ||
===========================infer_params=========================== | ||
infer_model:./test_tipc/output/mobileseg_mv3/model.pdparams | ||
infer_export:export.py --config test_tipc/configs/mobileseg_mv3/mobileseg_mobilenetv3_cityscapes_1024x512_80k.yml | ||
infer_quant:False | ||
inference:deploy/python/infer.py | ||
--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:mobileseg_mv3 | ||
===========================infer_benchmark_params========================== | ||
random_infer_input:[{float32,[3,1024,512]}] | ||
===========================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;set_cv_threads:true;skip_iters:2;repeats:500 |
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