fix bugs

deploy/python/predict_cls.py

@@ -48,18 +48,21 @@ class ClsPredictor(Predictor):
             import os
             pid = os.getpid()
             self.auto_log = auto_log.AutoLogger(
-                model_name='cls',
+                model_name=config["Global"].get("model_name", "cls"),
                 model_precision='fp16'
                 if config["Global"]["use_fp16"] else 'fp32',
-                batch_size=1,
+                batch_size=config["Global"].get("batch_size", 1),
                 data_shape=[3, 224, 224],
-                save_path="../output/auto_log.lpg",
-                inference_config=None,
+                save_path=config["Global"].get("save_log_path",
+                                               "./auto_log.log"),
+                inference_config=self.config,
                 pids=pid,
                 process_name=None,
                 gpu_ids=None,
-                time_keys=['preprocess_time', 'inference_time'],
-                warmup=10)
+                time_keys=[
+                    'preprocess_time', 'inference_time', 'postprocess_time'
+                ],
+                warmup=2)
 
     def predict(self, images):
         input_names = self.paddle_predictor.get_input_names()
@@ -99,8 +102,8 @@ def main(config):
         output = cls_predictor.postprocess(output, [image_file])
         if cls_predictor.benchmark:
             cls_predictor.auto_log.times.end(stamp=True)
-            cls_predictor.auto_log.report()
         print(output)
+    cls_predictor.auto_log.report()
     return
 
 

deploy/test.sh

-python3.7 python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu=True -o Global.use_tensorrt=False -o Global.use_fp16=False -o Global.inference_model_dir=.././test/output/ResNet50_vd_gpus_0,1/inference -o Global.batch_size=1 -o Global.infer_imgs=.././dataset/chain_dataset/val -o Global.save_log_path=.././test/output/ResNet50_vd_infer_gpu_usetrt_True_precision_False_batchsize_1.log -o benchmark=True

deploy/utils/predictor.py

@@ -28,7 +28,7 @@ class Predictor(object):
         if args.use_fp16 is True:
             assert args.use_tensorrt is True
         self.args = args
-        self.paddle_predictor = self.create_paddle_predictor(
+        self.paddle_predictor, self.config = self.create_paddle_predictor(
             args, inference_model_dir)
 
     def predict(self, image):
@@ -66,4 +66,4 @@ class Predictor(object):
         config.switch_use_feed_fetch_ops(False)
         predictor = create_predictor(config)
 
-        return predictor
+        return predictor, config

test/test.sh

@@ -92,7 +92,7 @@ function func_inference(){
                 for threads in ${cpu_threads_list[*]}; do
                     for batch_size in ${batch_size_list[*]}; do
                         _save_log_path="${_log_path}/${_model_name}_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_batchsize_${batch_size}.log"
-                        command="${_python} ${_script} -o ${use_gpu_key}=${use_gpu} -o ${use_mkldnn_key}=${use_mkldnn} -o ${cpu_threads_key}=${threads} -o ${infer_model_key}=${_model_dir} -o ${batch_size_key}=${batch_size} -o ${image_dir_key}=${_img_dir} -o ${save_log_key}=${_save_log_path} -o benchmark=True"
+                        command="${_python} ${_script} -o ${use_gpu_key}=${use_gpu} -o ${use_mkldnn_key}=${use_mkldnn} -o ${cpu_threads_key}=${threads} -o ${infer_model_key}=${_model_dir} -o ${batch_size_key}=${batch_size} -o ${image_dir_key}=${_img_dir} -o ${save_log_key}=${_save_log_path} -o benchmark=True -o Global.model_name=${_model_name}"
                         eval $command
                         status_check $? "${command}" "${status_log}"
                     done
@@ -106,7 +106,7 @@ function func_inference(){
                     fi
                     for batch_size in ${batch_size_list[*]}; do
                         _save_log_path="${_log_path}/${_model_name}_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
-                        command="${_python} ${_script} -o ${use_gpu_key}=${use_gpu} -o ${use_trt_key}=${use_trt} -o ${precision_key}=${precision} -o ${infer_model_key}=${_model_dir} -o ${batch_size_key}=${batch_size} -o ${image_dir_key}=${_img_dir} -o ${save_log_key}=${_save_log_path}  -o benchmark=True"
+                        command="${_python} ${_script} -o ${use_gpu_key}=${use_gpu} -o ${use_trt_key}=${use_trt} -o ${precision_key}=${precision} -o ${infer_model_key}=${_model_dir} -o ${batch_size_key}=${batch_size} -o ${image_dir_key}=${_img_dir} -o ${save_log_key}=${_save_log_path}  -o benchmark=True -o Global.model_name=${_model_name}"
                         eval $command
                         status_check $? "${command}" "${status_log}"
                     done