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fix lite window vs compile.

This commit is contained in:
wangpingan2 2023-03-02 16:11:11 +08:00
parent ad98167a6c
commit 3acec368ce
7 changed files with 30 additions and 14 deletions
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5
mindspore/lite/CMakeLists.txt
View File

@ -444,6 +444,11 @@ endif()
if(MSVC)
set(MSLITE_ENABLE_CONVERTER off)
if(MSLITE_ENABLE_RUNTIME_GLOG)
add_definitions(-DNOMINMAX)
add_definitions(-DNOGDI)
set(MSLITE_DEPS_DIRENT on)
endif()
endif()
if(MSLITE_GPU_BACKEND STREQUAL cuda)

4
mindspore/lite/cmake/lite_dependences.cmake
View File

@ -70,4 +70,8 @@ endif()
if(MSLITE_DEPS_OPENSSL)
include(${TOP_DIR}/cmake/external_libs/openssl.cmake)
endif()
if(MSLITE_DEPS_DIRENT)
include(${TOP_DIR}/cmake/external_libs/dirent.cmake)
endif()

6
mindspore/lite/src/CMakeLists.txt
View File

@ -429,6 +429,12 @@ if(NOT MSLITE_ENABLE_COREML)
${CMAKE_CURRENT_SOURCE_DIR}/litert/delegate/coreml/stub/coreml_delegate_stub.cc)
endif()
if(MSVC)
set(LITE_SRC ${LITE_SRC}
${EXPRESSION_SRC}
${CMAKE_CURRENT_SOURCE_DIR}/common/storage.cc)
endif()
add_subdirectory(litert/kernel/cpu)
add_library(lite_src_mid OBJECT ${LITE_SRC})

2
mindspore/lite/src/expression/param.cc
View File

@ -36,7 +36,7 @@ int Param::Fill(Mode mode) {
constexpr float scale = 0.01;
std::normal_distribution<float> n{0, 1};
std::generate_n(data.begin(), size_, [&]() { return n(engine); });
(void)std::transform(data.begin(), data.end(), data.begin(), [](float x) { return x * scale; });
(void)std::transform(data.begin(), data.end(), data.begin(), [=](float x) { return x * scale; });
break;
}
case UNIFORM: {

4
mindspore/lite/src/litert/cxx_api/expression/net_impl.cc
View File

@ -87,13 +87,13 @@ NetImpl::NetImpl(std::shared_ptr<Net> p) { pnet_ = p; }
NetImpl::NetImpl(Graph *g) { pnet_ = g->net_data_->net(); }
std::vector<lite::EXPR *> MS_API NetImpl::construct(const std::vector<lite::EXPR *> &inputs) {
std::vector<lite::EXPR *> NetImpl::construct(const std::vector<lite::EXPR *> &inputs) {
auto in = Expr::convert(inputs);
auto out = pnet_->construct(in);
return Expr::convert(out);
}
Net *MS_API NetImpl::Connect(std::shared_ptr<Net> net, lite::Net *lnet) {
Net *NetImpl::Connect(std::shared_ptr<Net> net, lite::Net *lnet) {
auto impl = GetImpl(net.get());
if (impl == nullptr) {
MS_LOG(ERROR) << "missing implementation";

21
mindspore/lite/src/litert/sub_graph_split.cc
View File

@ -100,7 +100,7 @@ bool SearchSubGraph::CheckIsParallelSubGraph(const std::vector<Subgraph> &subgra
// 1. check head_node's input is SplitOverlap node
for (const auto &input : head_node->input_indices_) {
if (tensors_.at(input).type_ == CONST) {
if (tensors_.at(input).type_ == CONSTANT) {
continue;
}
auto input_node_index = tensors_.at(input).out_nodes_.front();
@ -112,7 +112,7 @@ bool SearchSubGraph::CheckIsParallelSubGraph(const std::vector<Subgraph> &subgra
// 2. check end_node's output is concat node
for (const auto &output : end_node->output_indices_) {
if (tensors_.at(output).type_ == CONST) {
if (tensors_.at(output).type_ == CONSTANT) {
continue;
}
auto output_node_index = tensors_.at(output).in_nodes_.front();
@ -276,7 +276,7 @@ void SearchSubGraph::ConvertSubGraphToModel(std::vector<Subgraph> *sub_graphs) {
LiteGraph::Node *head_node = model_->graph_.all_nodes_[head_index];
std::vector<uint32_t> inputs = head_node->input_indices_;
for (auto input : inputs) {
if (tensors_[input].type_ == CONST) {
if (tensors_[input].type_ == CONSTANT) {
continue;
}
if (std::find(new_sub_graph->input_indices_.begin(), new_sub_graph->input_indices_.end(), input) !=
@ -359,8 +359,9 @@ void SearchSubGraph::SearchMultyInNodes(std::vector<uint32_t> *multy_in_nodes) {
if (IsPartialNode(node->primitive_, model_->GetSchemaVersion())) {
continue;
}
int input_count = std::count_if(node->input_indices_.begin(), node->input_indices_.end(),
[&](uint32_t in_tensor_index) { return tensors_[in_tensor_index].type_ != CONST; });
int input_count =
std::count_if(node->input_indices_.begin(), node->input_indices_.end(),
[&](uint32_t in_tensor_index) { return tensors_[in_tensor_index].type_ != CONSTANT; });
if (input_count > 1) {
multy_in_nodes->push_back(node_index);
}
@ -373,7 +374,7 @@ void SearchSubGraph::RemoveConstNode(std::vector<uint32_t> *nodes) {
while (!stop_search) {
stop_search = true;
for (size_t i = 0; i < nodes->size(); i++) {
if (tensors_[nodes->at(i)].type_ == CONST) {
if (tensors_[nodes->at(i)].type_ == CONSTANT) {
VectorErase(nodes, nodes->at(i));
stop_search = false;
break;
@ -596,7 +597,7 @@ void SearchSubGraph::InitMiddleSubgraph(const std::vector<uint32_t> *multy_in_no
LiteGraph::Node *node = node_list_[node_index];
for (uint32_t input_tensor_index : node->input_indices_) {
Tensor *tensor = &tensors_[input_tensor_index];
if (tensor->type_ == CONST || tensor->type_ == INPUT) continue;
if (tensor->type_ == CONSTANT || tensor->type_ == INPUT) continue;
std::vector<uint32_t> input_nodes = tensor->out_nodes_;
if (input_nodes.empty()) continue;
@ -662,7 +663,7 @@ void SearchSubGraph::InitSearchTensor() {
}
auto category = TensorCategory(*src_tensor);
if (category == mindspore::lite::Category::CONST_TENSOR || category == mindspore::lite::Category::CONST_SCALAR) {
tensors_[i].type_ = CONST;
tensors_[i].type_ = CONSTANT;
}
}
std::vector<uint32_t> graph_input = model_->graph_.sub_graphs_[0]->input_indices_;
@ -867,7 +868,7 @@ void SearchSubGraph::SubGraphSplitByOffLineParallel() {
std::vector<Subgraph> node_subs;
for (uint32_t input_tensor_index : node->input_indices_) {
Tensor *tensor = &tensors_[input_tensor_index];
if (tensor->type_ == CONST) continue;
if (tensor->type_ == CONSTANT) continue;
std::vector<uint32_t> input_nodes = tensor->out_nodes_;
Subgraph sub;
sub.ends_.push_back(input_nodes[0]);
@ -971,7 +972,7 @@ void SearchSubGraph::InsertParallelNode(uint32_t index, Subgraph *subgraph) {
/* remove const node */
for (int i = static_cast<int>(input.size()) - 1; i >= 0; i--) {
if (tensors_[input[i]].type_ == CONST) {
if (tensors_[input[i]].type_ == CONSTANT) {
VectorErase(&input, input[i]);
}
}

2
mindspore/lite/src/litert/sub_graph_split.h
View File

@ -40,7 +40,7 @@ constexpr int kMinSubgraphCost = 50;
constexpr double kDefaultGpu = 0.5;
class SearchSubGraph {
public:
enum TensorType { NORMAL, CONST, INPUT };
enum TensorType { NORMAL, CONSTANT, INPUT };
struct Tensor {
std::vector<uint32_t> in_nodes_; /* used current tensor as input */