add tensor name

mindspore/lite/schema/model.fbs

@@ -54,6 +54,7 @@ table Tensor {
     data: [ubyte];
     quantParams: [QuantParam];
     quantClusters: [float];
+    name: string;
 }
 
 union PrimitiveType {

mindspore/lite/tools/converter/graphdef_transform.cc

@@ -34,6 +34,7 @@
 #include "tools/converter/legacy_optimizer/graph/dropout_node_remove_pass.h"
 #include "tools/converter/legacy_optimizer/graph/topological_sort_pass.h"
 #include "tools/converter/legacy_optimizer/graph/tensor_quant_pass.h"
+#include "tools/converter/legacy_optimizer/graph/tensor_name_pass.h"
 #include "tools/converter/legacy_optimizer/graph/infer_quant_param_pass.h"
 #include "tools/converter/legacy_optimizer/graph/set_unused_quant_param_to_default_pass.h"
 
@@ -183,6 +184,17 @@ int GraphDefTransform::Transform(const converter::Flags &ctx) {
       return status;
     }
   }
+
+  // tensor name
+  {
+    Optimizer nameOptimizer;
+    nameOptimizer.AddPass(new (std::nothrow) TensorNamePass());
+    status = nameOptimizer.Run(graphDefT);
+    if (status != RET_OK && status != RET_NO_CHANGE) {
+      MS_LOG(ERROR) << "Run nameOptimizer graphPasses Failed";
+      return status;
+    }
+  }
   return RET_OK;
 }
 }  // namespace mindspore::lite

mindspore/lite/tools/converter/legacy_optimizer/graph/CMakeLists.txt

@@ -14,6 +14,7 @@ file(GLOB GRAPH_PASS
         ${CMAKE_CURRENT_SOURCE_DIR}/infer_quant_param_pass.cc
         ${CMAKE_CURRENT_SOURCE_DIR}/global_format_transform_pass.cc
         ${CMAKE_CURRENT_SOURCE_DIR}/set_unused_quant_param_to_default_pass.cc
+        ${CMAKE_CURRENT_SOURCE_DIR}/tensor_name_pass.cc
         )
 set_property(SOURCE ${GRAPH_PASS} PROPERTY COMPILE_DEFINITIONS SUBMODULE_ID=mindspore::SubModuleId::SM_LITE)
 add_library(graph_pass_mid OBJECT ${GRAPH_PASS})

mindspore/lite/tools/converter/legacy_optimizer/graph/tensor_name_pass.cc

@@ -0,0 +1,77 @@
+/**
+ * Copyright 2019 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "tools/converter/legacy_optimizer/graph/tensor_name_pass.h"
+#include "tools/converter/converter_context.h"
+#include "tools/converter/quantizer/quantize_util.h"
+#include "tools/common/tensor_util.h"
+
+namespace mindspore::lite {
+STATUS TensorNamePass::Run(schema::MetaGraphT *graph) {
+  MS_ASSERT(graph != nullptr);
+
+  for (int i = 0; i < static_cast<int>(graph->inputIndex.size()); i++) {
+    auto tensor_id = graph->inputIndex.at(i);
+    auto &tensor = graph->allTensors.at(tensor_id);
+    tensor->name = "graph_input-" + std::to_string(i);
+  }
+
+  for (auto &node : graph->nodes) {
+    if (node == nullptr || node->primitive == nullptr) {
+      MS_LOG(ERROR) << " node or node->primitive is nullptr";
+      return RET_ERROR;
+    }
+
+    for (int i = 0; i < static_cast<int>(node->outputIndex.size()); i++) {
+      auto tensor_id = node->outputIndex.at(i);
+      auto &tensor = graph->allTensors.at(tensor_id);
+      if (tensor->name.empty()) {
+        tensor->name = node->name + "/output-" + std::to_string(i);
+      }
+    }
+
+    auto type = node->primitive->value.type;
+    if (type == PrimitiveType_Conv2D || type == PrimitiveType_DeConv2D || type == PrimitiveType_DepthwiseConv2D ||
+        type == PrimitiveType_DeDepthwiseConv2D || type == PrimitiveType_FullConnection) {
+      auto input_size = node->inputIndex.size();
+      if (input_size > 1) {
+        auto weight_tensor_id = node->inputIndex.at(1);
+        auto &weight_tensor = graph->allTensors.at(weight_tensor_id);
+        if (weight_tensor->name.empty()) {
+          weight_tensor->name = node->name + "/weight";
+        }
+
+        if (input_size > 2) {
+          auto bias_tensor_id = node->inputIndex.at(2);
+          auto &bias_tensor = graph->allTensors.at(bias_tensor_id);
+          if (bias_tensor->name.empty()) {
+            bias_tensor->name = node->name + "/bias";
+          }
+        }
+      }
+    } else {
+      for (int i = 0; i < static_cast<int>(node->inputIndex.size()); i++) {
+        auto tensor_id = node->inputIndex.at(i);
+        auto &tensor = graph->allTensors.at(tensor_id);
+        if (tensor->name.empty()) {
+          tensor->name = node->name + "/input-" + std::to_string(i);
+        }
+      }
+    }
+  }
+  return RET_OK;
+}
+}  // namespace mindspore::lite

mindspore/lite/tools/converter/legacy_optimizer/graph/tensor_name_pass.h

@@ -0,0 +1,35 @@
+/**
+ * Copyright 2019 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#ifndef LITE_NAME_TENSOR_PASS_H
+#define LITE_NAME_TENSOR_PASS_H
+
+#include <memory>
+#include "tools/converter/optimizer.h"
+#include "tools/common/graph_util.h"
+
+namespace mindspore {
+namespace lite {
+class TensorNamePass : public GraphPass {
+ public:
+  TensorNamePass() {}
+
+  ~TensorNamePass() override = default;
+
+  STATUS Run(schema::MetaGraphT *graph) override;
+};
+}  // namespace lite
+}  // namespace mindspore
+#endif  // LITE_NAME_TENSOR_PASS_H