refactor: reduce duplicated code and fix tensor dump error

lite/kernels/mlu/bridges/graph.h

@@ -150,6 +150,23 @@ class Graph {
     CNML_CALL(cnmlCompileFusionOp_V2(fusion_op_));
   }
 
+#define MEASURE_HWTIME_START(que)                       \
+  do {                                                  \
+    CNRT_CALL(cnrtPlaceNotifier(notifier_start_, que)); \
+  } while (0)
+
+#define MEASURE_HWTIME_END(que)                                                \
+  do {                                                                         \
+    thread_local float hw_time;                                                \
+    CNRT_CALL(cnrtPlaceNotifier(notifier_end_, que));                          \
+    CNRT_CALL(cnrtSyncQueue(que));                                             \
+    CNRT_CALL(cnrtNotifierDuration(notifier_start_, notifier_end_, &hw_time)); \
+    hw_time /= 1000.0f;                                                        \
+    DLOG(INFO) << "cnml hardware time " << hw_time << "ms" << std::endl;       \
+    std::lock_guard<std::mutex> lk(time_mut_);                                 \
+    time_log_.push_back(hw_time);                                              \
+  } while (0)
+
   void Compute(cnrtInvokeFuncParam_t forward_param, cnrtQueue_t que) {
     input_addrs_.resize(input_tensors_.size());
     output_addrs_.resize(output_tensors_.size());
@@ -161,8 +178,7 @@ class Graph {
     }
 
 #if PRINT_HW_TIME
-    thread_local float hw_time;
-    CNRT_CALL(cnrtPlaceNotifier(notifier_start_, que));
+    MEASURE_HWTIME_START(que);
 #endif
     CNML_CALL(cnmlComputeFusionOpForward_V3(fusion_op_,
                                             input_addrs_.data(),
@@ -172,18 +188,11 @@ class Graph {
                                             &forward_param,
                                             que));
 #if PRINT_HW_TIME
-    CNRT_CALL(cnrtPlaceNotifier(notifier_end_, que));
-    CNRT_CALL(cnrtSyncQueue(que));
-    CNRT_CALL(cnrtNotifierDuration(notifier_start_, notifier_end_, &hw_time));
-    hw_time /= 1000.0f;
-    DLOG(INFO) << "cnml hardware time " << hw_time << "ms" << std::endl;
-    std::lock_guard<std::mutex> lk(time_mut_);
-    time_log_.push_back(hw_time);
+    MEASURE_HWTIME_END(que);
 #endif
   }
 
-  void Compute(cnrtInvokeFuncParam_t forward_param,
-               cnrtQueue_t que,
+  void Compute(cnrtQueue_t que,
                const std::vector<std::shared_ptr<MLUTensor>>& in,
                const std::vector<std::shared_ptr<MLUTensor>>& out) {
     std::vector<cnmlTensor_t> in_tensor;
@@ -200,8 +209,7 @@ class Graph {
     }
 
 #if PRINT_HW_TIME
-    thread_local float hw_time;
-    CNRT_CALL(cnrtPlaceNotifier(notifier_start_, que));
+    MEASURE_HWTIME_START(que);
 #endif
     /* Because of using cnmlSetTensorDimMutable, cnmlComputeFusionOpForward_V3
      * -> cnmlComputeFusionOpForward_V4 */
@@ -215,15 +223,11 @@ class Graph {
                                             que,
                                             NULL));
 #if PRINT_HW_TIME
-    CNRT_CALL(cnrtPlaceNotifier(notifier_end_, que));
-    CNRT_CALL(cnrtSyncQueue(que));
-    CNRT_CALL(cnrtNotifierDuration(notifier_start_, notifier_end_, &hw_time));
-    hw_time /= 1000.0f;
-    DLOG(INFO) << "cnml hardware time " << hw_time << "ms" << std::endl;
-    std::lock_guard<std::mutex> lk(time_mut_);
-    time_log_.push_back(hw_time);
+    MEASURE_HWTIME_END(que);
 #endif
   }
+#undef MEASURE_HWTIME_START
+#undef MEASURE_HWTIME_END
 
   template <typename T>
   void* RegisterConstData(size_t len) {

lite/kernels/mlu/bridges/test_helper.cc

@@ -56,12 +56,6 @@ void LaunchOp(const std::shared_ptr<lite::OpLite> op,
   CNRT_CALL(cnrtInit(0));
   lite::SetMluDevice(0);
   cnrtQueue_t queue_;
-  cnrtInvokeFuncParam_t forward_param;
-  u32_t affinity = 1;
-  int data_param = 1;
-  forward_param.data_parallelism = &data_param;
-  forward_param.affinity = &affinity;
-  forward_param.end = CNRT_PARAM_END;
   CNRT_CALL(cnrtCreateQueue(&queue_));
   cnrtDev_t dev_handle;
   CNRT_CALL(cnrtGetDeviceHandle(&dev_handle, 0));
@@ -113,10 +107,7 @@ void LaunchOp(const std::shared_ptr<lite::OpLite> op,
   }
 
   graph.Compile(CNML_MLU270, 1);
-  graph.Compute(forward_param,
-                queue_,
-                *(graph.MutableInputs()),
-                *(graph.MutableOutputs()));
+  graph.Compute(queue_, *(graph.MutableInputs()), *(graph.MutableOutputs()));
   CNRT_CALL(cnrtSyncQueue(queue_));
 
   for (auto& output_name : output_var_names) {

lite/kernels/mlu/subgraph_compute.h

@@ -330,12 +330,6 @@ class SubgraphEngine : public subgraph::Engine {
     // prepare input and output memory
     auto& mlu_context = this->ctx_->template As<MLUContext>();
     auto exec_queue = mlu_context.exec_queue();
-    u32_t affinity = mlu_context.affinity();
-    cnrtInvokeFuncParam_t forward_param = mlu_context.forward_param();
-    int data_param = 1;
-    forward_param.data_parallelism = &data_param;
-    forward_param.affinity = &affinity;
-    forward_param.end = CNRT_PARAM_END;
 
     auto graph = shape_graph_map_[inputs_shape_];
     auto* graph_input = graph->MutableInputs();
@@ -402,7 +396,7 @@ class SubgraphEngine : public subgraph::Engine {
         }
         shape_tensor_map_out_[all_inputs_shape_] = graph_out;
       }
-      graph->Compute(forward_param, exec_queue, graph_in, graph_out);
+      graph->Compute(exec_queue, graph_in, graph_out);
     } else {
       for (size_t i = 0; i < origin_itensors_.size(); ++i) {
         graph_input->at(i)->set_mlu_ptr(
@@ -413,36 +407,49 @@ class SubgraphEngine : public subgraph::Engine {
         graph_output->at(i)->set_mlu_ptr(
             GetOutputDataPtr(origin_otensors_[i], !disable_mlu_cast));
       }
+      // only cnmlComputeFusionOpForward_V3 need cnrtInvokeFuncParam_t
+      cnrtInvokeFuncParam_t forward_param = mlu_context.forward_param();
+      int data_param = 1;
+      forward_param.data_parallelism = &data_param;
+      u32_t affinity = mlu_context.affinity();
+      forward_param.affinity = &affinity;
+      forward_param.end = CNRT_PARAM_END;
       graph->Compute(forward_param, exec_queue);
+
+#ifdef MLU_DUMP_SUBGRAPH_IO
+      // Graph node store compile-time tensor while batchsize mutable is set.
+      // Only batchsize mutable is disabled, data exists in graph node at
+      // runtime
+      // =========== DUMP ===================
+      for (auto input_name : input_names_) {
+        auto input_tensor =
+            shape_graph_map_[inputs_shape_]->GetNode(input_name);
+        auto dump_name = input_name;
+        while (dump_name.find("/") != std::string::npos) {
+          dump_name = dump_name.replace(dump_name.find("/"), 1, "_");
+        }
+        VLOG(6) << "dump_name: " << dump_name;
+        input_tensor->ToFile(dump_name);
+      }
+      for (auto output_name : output_names_) {
+        if (shape_graph_map_[inputs_shape_]->HasNode(output_name)) {
+          auto output_tensor =
+              shape_graph_map_[inputs_shape_]->GetNode(output_name);
+          auto dump_name = output_name;
+          while (dump_name.find("/") != std::string::npos) {
+            dump_name = dump_name.replace(dump_name.find("/"), 1, "_");
+          }
+          VLOG(6) << "dump_name: " << dump_name;
+          output_tensor->ToFile(dump_name);
+        } else {
+          VLOG(6) << "graph does not have " << output_name << " as output"
+                  << std::endl;
+        }
+      }
+#endif
+      // =========== DUMP END ================
     }
 
-    // // =========== DUMP ===================
-    // for (auto input_name : input_names_) {
-    //   auto input_tensor =
-    //   shape_graph_map_[inputs_shape_]->GetNode(input_name);
-    //   auto dump_name = input_name;
-    //   while (dump_name.find("/") != std::string::npos) {
-    //     dump_name = dump_name.replace(dump_name.find("/"), 1, "_");
-    //   }
-    //   VLOG(6) << "dump_name: " << dump_name;
-    //   input_tensor->ToFile(dump_name);
-    // }
-    // for (auto output_name : output_names_) {
-    //   if (shape_graph_map_[inputs_shape_]->HasNode(output_name)) {
-    //     auto output_tensor =
-    //     shape_graph_map_[inputs_shape_]->GetNode(output_name);
-    //     auto dump_name = output_name;
-    //     while (dump_name.find("/") != std::string::npos) {
-    //       dump_name = dump_name.replace(dump_name.find("/"), 1, "_");
-    //     }
-    //     VLOG(6) << "dump_name: " << dump_name;
-    //     output_tensor->ToFile(dump_name);
-    //   } else {
-    //     VLOG(6) << "graph does not have " << output_name << " as output"
-    //             << std::endl;
-    //   }
-    // }
-    // // =========== DUMP END ================
     return 0;
   }