!4923 fix dts bug

Merge pull request !4923 from cjh9368/dts-0718

mindspore/lite/src/ir/tensor.cc

@@ -75,6 +75,7 @@ Tensor::~Tensor() {
     } else {
       free(this->data_);
     }
+    this->data_ = nullptr;
   }
 }
 

mindspore/lite/src/runtime/thread_pool.cc

@@ -27,6 +27,7 @@ namespace mindspore {
 namespace predict {
 constexpr int kDefaultBigCount = 2;
 constexpr int kDefaultMidCount = 2;
+constexpr uint32_t kDefaultSpinCount = 300000;
 constexpr int kSmallCpuNum = 4;
 constexpr int kBigMidCpuNum = 4;
 constexpr int kDefaultThreadNum = 1;
@@ -97,6 +98,11 @@ void LiteThreadBind::InitSortedCpuId() {
 #else
   numCores = static_cast<int>(std::thread::hardware_concurrency());
 #endif  // MS_COMPILE_IOS
+  if (numCores < 0) {
+    MS_LOG(ERROR) << "get numCores return invalid value: " << numCores;
+    sortedCpuIds.clear();
+    return;
+  }
   if (numCores < kBigMidCpuNum) {
     bigCore = 0;
     midCore = numCores;
@@ -259,6 +265,7 @@ void ThreadPool::AddNewThread(int newNums) {
     auto queue = std::make_shared<LiteQueue>();
     threadList.emplace_back([this, i, active, queue]() {
       ThreadPoolTask *task = nullptr;
+      uint32_t spin_count = 0;
       while (!exitRun) {
         while (*active) {
           if (queue->Dequeue(&task)) {
@@ -267,6 +274,15 @@ void ThreadPool::AddNewThread(int newNums) {
               errorInfo.emplace_back(std::make_pair(i + 1, std::make_pair(false, ret)));
             }
             queue->taskSize--;
+            spin_count = 0;
+          } else {
+            ++spin_count;
+          }
+          if (spin_count == kDefaultSpinCount) {
+            *(activateList[i]) = false;
+            --curThreadRunNums;
+            spin_count = 0;
+            break;
           }
           std::this_thread::yield();
         }

mindspore/lite/tools/converter/parser/caffe/CMakeLists.txt

@@ -20,6 +20,7 @@ add_library(caffe_parser_mid OBJECT
         ${CMAKE_CURRENT_SOURCE_DIR}/caffe_power_parser.cc
         ${CMAKE_CURRENT_SOURCE_DIR}/caffe_prelu_parser.cc
         ${CMAKE_CURRENT_SOURCE_DIR}/caffe_relu_parser.cc
+        ${CMAKE_CURRENT_SOURCE_DIR}/caffe_relu6_parser.cc
         ${CMAKE_CURRENT_SOURCE_DIR}/caffe_reshape_parser.cc
         ${CMAKE_CURRENT_SOURCE_DIR}/caffe_scale_parser.cc
         ${CMAKE_CURRENT_SOURCE_DIR}/caffe_sigmoid_parser.cc

mindspore/lite/tools/converter/parser/caffe/caffe_relu6_parser.cc

@@ -0,0 +1,43 @@
+/**
+ * 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 <memory>
+#include "mindspore/lite/tools/converter/parser/caffe/caffe_relu6_parser.h"
+
+namespace mindspore {
+namespace lite {
+STATUS CaffeRelu6Parser::Parse(const caffe::LayerParameter &proto, const caffe::LayerParameter &weight,
+                               schema::CNodeT *op, std::vector<schema::TensorT *> *weightVec) {
+  std::unique_ptr<schema::ActivationT> attr(new schema::ActivationT());
+  attr->type = schema::ActivationType_RELU6;
+  // relu: negative_slope = 0, no parameter;
+  // leakyrelu: negative_slope != 0;
+  if (proto.has_relu_param() && proto.relu_param().has_negative_slope()) {
+    float negative_slope = proto.relu_param().negative_slope();
+    if (0 != negative_slope) {
+      attr->type = schema::ActivationType_LEAKY_RELU;
+      attr->alpha = negative_slope;
+    }
+  }
+  op->primitive = std::make_unique<schema::PrimitiveT>();
+  op->primitive->value.value = attr.release();
+  op->primitive->value.type = schema::PrimitiveType_Activation;
+  return RET_OK;
+}
+
+CaffeNodeRegistrar g_caffeRelu6Parser("ReLU6", new CaffeRelu6Parser());
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/tools/converter/parser/caffe/caffe_relu6_parser.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 MINDSPORE_CCSRC_TOOLS_LITE_CONVERTER_PARSER_CAFFE_CAFFE_RELU6_PARSER_H_
+#define MINDSPORE_CCSRC_TOOLS_LITE_CONVERTER_PARSER_CAFFE_CAFFE_RELU6_PARSER_H_
+
+#include <vector>
+#include "mindspore/lite/tools/converter/parser/caffe/caffe_node_parser.h"
+#include "mindspore/lite/tools/converter/parser/caffe/caffe_node_parser_registry.h"
+
+namespace mindspore {
+namespace lite {
+class CaffeRelu6Parser : public CaffeNodeParser {
+ public:
+  CaffeRelu6Parser() : CaffeNodeParser("relu6") {}
+
+  STATUS Parse(const caffe::LayerParameter &proto, const caffe::LayerParameter &weight, schema::CNodeT *op,
+               std::vector<schema::TensorT *> *weightVec) override;
+};
+}  // namespace lite
+}  // namespace mindspore
+
+#endif  // MINDSPORE_CCSRC_TOOLS_LITE_CONVERTER_PARSER_CAFFE_CAFFE_RELU_PARSER_H_

mindspore/lite/tools/converter/parser/onnx/onnx_pool_parser.cc

@@ -53,6 +53,9 @@ STATUS OnnxPoolParser::Parse(const onnx::GraphProto &onnx_graph,
   } else if (pool_type == "GlobalAveragePool") {
     attr->poolingMode = schema::PoolMode_MEAN_POOLING;
     attr->global = true;
+  } else if (pool_type == "Int8AveragePool") {
+    attr->poolingMode = schema::PoolMode_MEAN_POOLING;
+    attr->global = false;
   } else {
     MS_LOG(ERROR) << "Pooling param`s PoolingMode is not MAX either AVE. MindSpore support MAX and AVE only.";
     return RET_ERROR;
@@ -105,5 +108,6 @@ OnnxNodeRegistrar g_onnxMaxPoolParser("MaxPool", new OnnxPoolParser());
 OnnxNodeRegistrar g_onnxAveragePoolParser("AveragePool", new OnnxPoolParser());
 OnnxNodeRegistrar g_onnxGlobalAveragePoolParser("GlobalAveragePool", new OnnxPoolParser());
 OnnxNodeRegistrar g_onnxGlobalMaxPoolParser("GlobalMaxPool", new OnnxPoolParser());
+OnnxNodeRegistrar g_onnxInt8AveragePoolParser("Int8AveragePool", new OnnxPoolParser());
 }  // namespace lite
 }  // namespace mindspore