fix build warning
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564f6089c6
commit
d3a67a0233
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@ -97,7 +97,7 @@ class MS_API DelegateModel {
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/// \brief Get the ms model version.
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///
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/// \return The schema version for the primitives map.
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const SchemaVersion GetVersion() { return version_; }
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SchemaVersion GetVersion() const { return version_; }
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protected:
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std::vector<kernel::Kernel *> *kernels_;
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@ -17,7 +17,7 @@
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#include <stdlib.h>
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#include <string.h>
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#include "nnacl/infer/infer_register.h"
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#include "plugin/device/cpu/kernel/nnacl/op_base.h"
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#include "nnacl/op_base.h"
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#ifndef CONTROLFLOW_TENSORLIST_CLIP
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int MallocTensorListData(TensorListC *tensor_list, TypeIdC dtype, const vvector *tensor_shape) {
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@ -66,7 +66,7 @@ class MessageBase {
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inline void SetTo(const AID &aTo) { to = aTo; }
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inline const Type GetType() const { return type; }
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inline Type GetType() const { return type; }
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inline void SetType(Type eType) { type = eType; }
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@ -619,7 +619,7 @@ if(MSLITE_ENABLE_TOOLS)
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endif()
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endif()
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if(NOT WIN32 AND MSLITE_ENABLE_TESTCASES AND NOT MSLITE_MINDDATA_IMPLEMENT STREQUAL "off")
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if(NOT WIN32 AND MSLITE_ENABLE_TESTCASES)
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add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/test)
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endif()
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@ -75,7 +75,7 @@ struct Context {
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Vector<int> affinity_core_list_; /**< explicitly specify the core to be bound. priority use affinity core list */
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AllocatorPtr allocator = nullptr;
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#ifndef NOT_USE_STL
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DeviceContextVector device_list_ = {{DT_CPU, {false, MID_CPU}}};
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DeviceContextVector device_list_ = {{DT_CPU, {{false, MID_CPU}}}};
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#else
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DeviceContextVector device_list_;
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#endif // NOT_USE_STL
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@ -41,8 +41,6 @@ class ModelC {
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MSTensor::Impl **GetInputs(size_t *input_num);
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MSTensor::Impl **GetOutputs(size_t *output_num);
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MSTensor::Impl *GetInputByTensorName(const std::string &name);
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MSTensor::Impl *GetOutputByTensorName(const std::string &name);
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private:
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std::shared_ptr<lite::LiteSession> session_ = nullptr;
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@ -284,24 +282,6 @@ MSTensor::Impl **ModelC::GetOutputs(size_t *output_num) {
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});
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return outputs_.data();
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}
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MSTensor::Impl *ModelC::GetInputByTensorName(const std::string &name) {
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if (session_ == nullptr) {
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MS_LOG(ERROR) << "Session is null.";
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return nullptr;
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}
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auto tensor = session_->GetInputsByTensorName(name);
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return TensorToTensorImpl(tensor);
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}
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MSTensor::Impl *ModelC::GetOutputByTensorName(const std::string &name) {
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if (session_ == nullptr) {
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MS_LOG(ERROR) << "Session is null.";
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return nullptr;
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}
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auto tensor = session_->GetOutputByTensorName(name);
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return TensorToTensorImpl(tensor);
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}
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} // namespace mindspore
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MSModelHandle MSModelCreate() {
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@ -36,7 +36,7 @@ namespace mindspore::lite {
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class ControlFlowScheduler {
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public:
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ControlFlowScheduler(InnerContext *ctx, const mindspore::Context *ms_ctx, std::vector<Tensor *> *src_tensors)
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: context_(ctx), ms_context_(ms_ctx), src_tensors_(src_tensors) {}
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: context_(ctx), src_tensors_(src_tensors) {}
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~ControlFlowScheduler() = default;
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int Schedule(std::vector<kernel::LiteKernel *> *dst_kernels);
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void SetSubgraphForPartialNode(std::unordered_map<kernel::LiteKernel *, size_t> *partial_kernel_subgraph_index_map,
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@ -91,7 +91,6 @@ class ControlFlowScheduler {
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private:
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InnerContext *context_ = nullptr;
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const mindspore::Context *ms_context_ = nullptr;
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int schema_version_ = SCHEMA_VERSION::SCHEMA_CUR;
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std::vector<Tensor *> *src_tensors_ = nullptr;
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std::queue<kernel::LiteKernel *> to_process_q_{};
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@ -139,7 +139,7 @@ lite::InnerContext *ContextUtils::Convert(const ContextC *context_c) {
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Status ret = kLiteError;
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for (auto &device_info_c : device_list) {
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MS_CHECK_TRUE_RET(device_info_c != nullptr, nullptr);
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lite::DeviceInfo device_info = {0};
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lite::DeviceInfo device_info = {{0}};
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if (device_info_c->device_type == kMSDeviceTypeCPU) {
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if (device_info_c->allocator == nullptr) {
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device_info_c->allocator = Allocator::Create();
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@ -14,7 +14,7 @@
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* limitations under the License.
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*/
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#include "src/ops/populate/populate_register.h"
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#include "plugin/device/cpu/kernel/nnacl/op_base.h"
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#include "nnacl/op_base.h"
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using mindspore::schema::PrimitiveType_Adam;
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namespace mindspore {
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@ -83,13 +83,13 @@ class NMSBox {
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return score_ < box.score_ || (std::abs(score_ - box.score_) < FLT_EPSILON && index_ > box.index_);
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}
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const float get_score() const { return score_; }
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const int get_index() const { return index_; }
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const float get_y1() const { return y1_; }
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const float get_y2() const { return y2_; }
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const float get_x1() const { return x1_; }
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const float get_x2() const { return x2_; }
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const float get_area() const { return area_; }
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float get_score() const { return score_; }
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int get_index() const { return index_; }
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float get_y1() const { return y1_; }
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float get_y2() const { return y2_; }
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float get_x1() const { return x1_; }
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float get_x2() const { return x2_; }
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float get_area() const { return area_; }
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private:
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float score_;
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@ -145,7 +145,10 @@ target_compile_options(gmock_tests PRIVATE -fno-rtti)
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target_link_libraries(lite-test gmock_tests)
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if(MSLITE_ENABLE_TRAIN)
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target_link_libraries(lite-test mindspore-lite-train minddata-lite)
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target_link_libraries(lite-test mindspore-lite-train)
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if(NOT MSLITE_MINDDATA_IMPLEMENT STREQUAL "off")
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target_link_libraries(lite-test minddata-lite)
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endif()
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endif()
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if(PLATFORM_ARM)
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