[TIPC] * benchamrk use cocomini dataset (#7995)

* benchamrk set run 5m finish
* static train pop data['image_file']

ppdet/engine/trainer.py

@@ -487,6 +487,9 @@ class Trainer(object):
                 profiler.add_profiler_step(profiler_options)
                 self._compose_callback.on_step_begin(self.status)
                 data['epoch_id'] = epoch_id
+                if self.cfg.get('to_static',
+                                False) and 'image_file' in data.keys():
+                    data.pop('image_file')
 
                 if self.use_amp:
                     if isinstance(

test_tipc/benchmark_train.sh

@@ -243,7 +243,7 @@ for batch_size in ${batch_size_list[*]}; do
                         --run_mode ${run_mode} \
                         --fp_item ${precision} \
                         --keyword ips: \
-                        --skip_steps 2 \
+                        --skip_steps 4 \
                         --device_num ${device_num} \
                         --speed_unit images/s \
                         --convergence_key loss: "
@@ -279,7 +279,7 @@ for batch_size in ${batch_size_list[*]}; do
                         --run_mode ${run_mode} \
                         --fp_item ${precision} \
                         --keyword ips: \
-                        --skip_steps 2 \
+                        --skip_steps 4 \
                         --device_num ${device_num} \
                         --speed_unit images/s \
                         --convergence_key loss: "

test_tipc/configs/deformable_detr/deformable_detr_r50_1x_coco_train_infer_python.txt

@@ -53,6 +53,6 @@ inference:./deploy/python/infer.py
 batch_size:2
 fp_items:fp32|fp16
 epoch:1
-repeat:2
+repeat:1
 --profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
 flags:null
\ No newline at end of file

test_tipc/configs/dino/dino_r50_4scale_1x_coco_train_infer_python.txt

@@ -53,7 +53,7 @@ inference:./deploy/python/infer.py
 batch_size:2
 fp_items:fp32|fp16
 epoch:1
-repeat:2
+repeat:1
 --profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
 flags:null
 ===========================infer_benchmark_params===========================

test_tipc/configs/fcos/fcos_r50_fpn_1x_coco_train_infer_python.txt

@@ -53,7 +53,7 @@ inference:./deploy/python/infer.py
 batch_size:2|8
 fp_items:fp32|fp16
 epoch:1
-repeat:3
+repeat:1
 --profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
 flags:null
 ===========================infer_benchmark_params===========================

test_tipc/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco_train_infer_python.txt

@@ -53,7 +53,7 @@ inference:./deploy/python/infer.py
 batch_size:2|4
 fp_items:fp32|fp16
 epoch:1
-repeat:2
+repeat:1
 --profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
 flags:null
 ===========================infer_benchmark_params===========================

test_tipc/configs/picodet/picodet_s_320_coco_lcnet_train_infer_python.txt

@@ -53,7 +53,7 @@ null:null
 batch_size:64
 fp_items:fp32|fp16
 epoch:1
-repeat:25
+repeat:1
 --profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
 flags:null
 ===========================infer_benchmark_params===========================

test_tipc/configs/ppyoloe/ppyoloe_crn_s_300e_coco_train_infer_python.txt

@@ -53,8 +53,10 @@ inference:./deploy/python/infer.py
 batch_size:8
 fp_items:fp32|fp16
 epoch:1
-repeat:12
+repeat:1
 --profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
 flags:null
 ===========================infer_benchmark_params===========================
 numpy_infer_input:3x640x640_2.npy
+===========================to_static_train_benchmark_params===========================
+to_static_train:--to_static

test_tipc/configs/yolov3/yolov3_darknet53_270e_coco_train_infer_python.txt

@@ -53,7 +53,7 @@ null:null
 batch_size:8
 fp_items:fp32|fp16
 epoch:1
-repeat:3
+repeat:1
 --profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
 flags:null
 ===========================infer_benchmark_params===========================

test_tipc/prepare.sh

@@ -99,9 +99,9 @@ elif [ ${MODE} = "benchmark_train" ];then
         cd ../../
     else
         # prepare lite benchmark coco data
-        wget -nc -P ./dataset/coco/ https://paddledet.bj.bcebos.com/data/coco_benchmark.tar --no-check-certificate
-        cd ./dataset/coco/ && tar -xf coco_benchmark.tar
-        mv -u coco_benchmark/* ./
+        wget -nc -P ./dataset/coco/ https://bj.bcebos.com/v1/paddledet/data/cocomini.zip --no-check-certificate
+        cd ./dataset/coco/ && unzip cocomini.zip
+        mv -u cocomini/* ./
         ls ./
         cd ../../
         # prepare lite benchmark mot data

test_tipc/test_train_inference_python.sh

@@ -311,7 +311,7 @@ else
                 fi
                 # run train
                 train_log_path="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}_nodes_${nodes}.log"
-                eval "${cmd} > ${train_log_path} 2>&1"
+                eval "timeout 5m ${cmd} > ${train_log_path} 2>&1"
                 last_status=$?
                 cat ${train_log_path}
                 status_check $last_status "${cmd}" "${status_log}" "${model_name}" "${train_log_path}"