dnn test

recommend-model-produce/src/main/python/models/dnn/config.yaml

@@ -35,8 +35,8 @@ runner:
   #use inference save model
   # model_init_path: "output_model_dnn/2" # init model
   use_inference: True
-  save_inference_feed_varnames: ["1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20","21","22","23","24","25","26","dense_input"]
-  save_inference_fetch_varnames: ["1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20","21","22","23","24","25","26","dense_input","label", "SparseFeatFactors"]
+  save_inference_feed_varnames: ["1"]
+  save_inference_fetch_varnames: ["1", "label"]
 
   # distribute_config
   sync_mode: "async"

recommend-model-service/src/main/java/com/tzld/piaoquan/recommend/model/service/model/DNNModel.java

@@ -27,6 +27,7 @@ public class DNNModel implements Model {
         String inNames = predictor.getInputNameById(0);
         Tensor inHandle = predictor.getInputHandle(inNames);
         log.info("predictor2 inNames={}", inNames);
+        inHandle.reshape(4, new int[]{1, 3, 224, 224});
         float[] inData = new float[39];
         inHandle.copyFromCpu(inData);
         predictor.run();