debug

test_tipc/config/PPHGNet/PPHGNet_small_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
 trainer:amp_train
-amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPHGNet_small.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 pact_train:null
 fpgm_train:null
 distill_train:null
@@ -21,19 +21,19 @@ null:null
 null:null
 ##
 ===========================eval_params===========================
-eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPHGNet_small.yaml
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml
 null:null
 ##
 ===========================infer_params==========================
 -o Global.save_inference_dir:./inference
 -o Global.pretrained_model:
-norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPHGNet_small.yaml
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml
 quant_export:null
 fpgm_export:null
 distill_export:null
 kl_quant:null
 export2:null
-pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x2_5_pretrained.pdparams
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNet_small_pretrained.pdparams
 infer_model:../inference/
 infer_export:True
 infer_quant:Fasle

test_tipc/config/PPHGNet/PPHGNet_tiny_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu copy.txt → test_tipc/config/PPHGNet/PPHGNet_tiny_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
 trainer:amp_train
-amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPHGNet_tiny.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 pact_train:null
 fpgm_train:null
 distill_train:null
@@ -21,19 +21,19 @@ null:null
 null:null
 ##
 ===========================eval_params===========================
-eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPHGNet_tiny.yaml
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml
 null:null
 ##
 ===========================infer_params==========================
 -o Global.save_inference_dir:./inference
 -o Global.pretrained_model:
-norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPHGNet_tiny.yaml
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml
 quant_export:null
 fpgm_export:null
 distill_export:null
 kl_quant:null
 export2:null
-pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x2_5_pretrained.pdparams
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNet_tiny_pretrained.pdparams
 infer_model:../inference/
 infer_export:True
 infer_quant:Fasle

test_tipc/config/PPLCNetV2/PPLCNetV2_base_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -6,14 +6,14 @@ gpu_list:0|0,1
 -o Global.auto_cast:null
 -o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
 -o Global.output_dir:./output/
--o DataLoader.Train.sampler.batch_size:8
+-o DataLoader.Train.sampler.batch_size:null
 -o Global.pretrained_model:null
 train_model_name:latest
 train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
 trainer:amp_train
-amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNetV2_base.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+amp_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml -o Global.seed=1234 -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 pact_train:null
 fpgm_train:null
 distill_train:null
@@ -21,13 +21,13 @@ null:null
 null:null
 ##
 ===========================eval_params===========================
-eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNetV2_base.yaml
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml
 null:null
 ##
 ===========================infer_params==========================
 -o Global.save_inference_dir:./inference
 -o Global.pretrained_model:
-norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNetV2_base.yaml
+norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml
 quant_export:null
 fpgm_export:null
 distill_export:null

test_tipc/config/ResNet/ResNet50_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -13,7 +13,7 @@ train_infer_img_dir:./dataset/ILSVRC2012/val
 null:null
 ##
 trainer:amp_train
-amp_train:tools/train.py -c ppcls/configs/ImageNet/ResNet/ResNet50_amp_O1.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
+amp_train:tools/train.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=65536 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2
 pact_train:null
 fpgm_train:null
 distill_train:null