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!30361 Fix master code warning 

Merge pull request !30361 from LiangZhibo/master_warning
This commit is contained in:
i-robot 2022-02-22 02:56:06 +00:00 committed by Gitee
parent b38bd363cd 5c746186ef
commit 384aecbbbe
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GPG Key ID: 173E9B9CA92EEF8F
6 changed files with 15 additions and 19 deletions
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21
mindspore/ccsrc/backend/graph_compiler/backend.cc
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@ -293,7 +293,7 @@ std::vector<tensor::TensorPtr> GetRealValueNodeTensorFromGraph(
auto value = value_node->value();
MS_EXCEPTION_IF_NULL(value);
auto tensor = value->cast<tensor::TensorPtr>();
value_node_pos.emplace(i, tensor);
(void)value_node_pos.emplace(i, tensor);
}
}
@ -301,10 +301,10 @@ std::vector<tensor::TensorPtr> GetRealValueNodeTensorFromGraph(
for (size_t i = 0; i < input_num; ++i) {
auto iter = value_node_pos.find(i);
if (iter == value_node_pos.end()) {
new_input_tensors.emplace_back(tensors_without_value_node[cur_input_tensor_index]);
(void)new_input_tensors.emplace_back(tensors_without_value_node[cur_input_tensor_index]);
cur_input_tensor_index++;
} else {
new_input_tensors.emplace_back(iter->second);
(void)new_input_tensors.emplace_back(iter->second);
}
}
MS_LOG(DEBUG) << "new input tensor size:" << new_input_tensors.size();
@ -647,7 +647,7 @@ void ConvertPyObjectToTensor(const py::object &input_object, std::vector<tensor:
MS_EXCEPTION(TypeError) << "Unreasonable data type: " << input_object.get_type() << ".";
}
MS_EXCEPTION_IF_NULL(tensor_ptr);
tensors->emplace_back(tensor_ptr);
(void)tensors->emplace_back(tensor_ptr);
}
void RunControlOperator(const std::shared_ptr<GraphCompiler> &graph_compiler, const KernelGraphPtr &graph,
@ -770,7 +770,7 @@ void FlatValueTupleValue(const ValuePtrList &value, ValuePtrList *flatted_value)
auto value_element = value[i];
MS_EXCEPTION_IF_NULL(value_element);
if (utils::isa<tensor::TensorPtr>(value_element)) {
flatted_value->emplace_back(value_element);
(void)flatted_value->emplace_back(value_element);
} else if (utils::isa<ValueTuplePtr>(value_element)) {
auto value_tuple_element = value_element->cast<ValueTuplePtr>();
MS_EXCEPTION_IF_NULL(value_tuple_element);
@ -1203,10 +1203,8 @@ void MindRTBackend::EraseSingleOpCache(const ActorInfo &actor_info, const Kernel
actor_to_graph_compiler_info_.erase(actor_info);
}
void MindRTBackend::RunSingleOpGraph(const KernelGraphPtr &graph,
const std::vector<session::KernelWithIndex> &output_nodes,
const OpRunInfo &op_run_info, const GraphCompilerInfo *graph_compiler_info,
DeviceContext *device_context) {
void MindRTBackend::RunSingleOpGraph(const KernelGraphPtr &graph, const OpRunInfo &op_run_info,
const GraphCompilerInfo *graph_compiler_info) {
// Erase value node tensor.
std::vector<tensor::TensorPtr> tensors_without_value_node;
const auto &input_tensors = op_run_info.input_tensors;
@ -1309,8 +1307,7 @@ void MindRTBackend::LazyExecuteTaskCallback() {
auto &op_run_task = op_run_tasks.front();
const auto &context = op_run_task->context();
ms_context->set_param<bool>(MS_CTX_ENABLE_PYNATIVE_INFER, context->is_pynative_infer());
RunSingleOpGraph(context->graph(), context->output_nodes(), context->op_run_info(),
context->graph_compiler_info(), context->device_context());
RunSingleOpGraph(context->graph(), context->op_run_info(), context->graph_compiler_info());
ClearGraphDeviceAddress(context->graph(), context->device_context(), context->op_run_info().is_gradient_out);
UpdateInputDeviceAddress(context->graph());
@ -1365,7 +1362,7 @@ void MindRTBackend::RunOpInternal(bool single_op_cache_hit, GraphCompilerInfo *g
if (!single_op_cache_hit) {
CompileSingleOpGraph(graph, device_context, graph_compiler_info);
}
RunSingleOpGraph(graph, output_nodes, *op_run_info, graph_compiler_info, device_context);
RunSingleOpGraph(graph, *op_run_info, graph_compiler_info);
UpdateOutput(output_nodes, outputs);
ClearGraphDeviceAddress(graph, device_context, op_run_info->is_gradient_out);
UpdateInputDeviceAddress(graph);

5
mindspore/ccsrc/backend/graph_compiler/backend.h
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@ -163,9 +163,8 @@ class MindRTBackend : public Backend {
void EraseSingleOpCache(const ActorInfo &actor_info, const KernelGraphPtr &graph);
// Run op immediately when the single_op_cache hit and the queue of OpLazyBuilder is empty in PyNative mode.
void RunSingleOpGraph(const KernelGraphPtr &graph, const std::vector<session::KernelWithIndex> &output_nodes,
const OpRunInfo &op_run_info, const GraphCompilerInfo *graph_compiler_info,
DeviceContext *device_context);
void RunSingleOpGraph(const KernelGraphPtr &graph, const OpRunInfo &op_run_info,
const GraphCompilerInfo *graph_compiler_info);
// Execute OpBuildTask and OpRunTask when the OpLazyBuilder queue is full in PyNative mode.
void LazyExecuteTaskCallback();

2
mindspore/ccsrc/backend/graph_compiler/segment_runner.cc
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@ -140,7 +140,7 @@ std::tuple<FuncGraphPtr, AnfNodePtrList, AnfNodePtrList> TransformSegmentToAnfGr
}
mindspore::HashSet<AnfNodePtr> eqv_keys;
for (auto &e : eqv) {
eqv_keys.emplace(e.first);
(void)eqv_keys.emplace(e.first);
}
auto mgr = lst[0]->func_graph()->manager();
MS_EXCEPTION_IF_NULL(mgr);

2
mindspore/ccsrc/backend/graph_compiler/transform.cc
View File

@ -396,7 +396,7 @@ int64_t CompileGraph::AddCall(const FuncGraphPtr &graph, const CNodePtr &node) {
for (size_t i = size - 1; i > 0; i--) {
const auto iter = slots_.find(inputs[i]);
if (iter != slots_.end() && iter->second >= height_) {
slots_.erase(inputs[i]);
(void)slots_.erase(inputs[i]);
}
}
return RET_SUCCESS;

2
mindspore/ccsrc/pipeline/jit/static_analysis/static_analysis.cc
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@ -1087,7 +1087,7 @@ AbstractBasePtr ToAbstract(const ValuePtr &value, const AnalysisContextPtr &cont
if (anf_node != nullptr) {
SetSequenceNodeElementsUseFlags(anf_node, std::make_shared<std::vector<bool>>(sequence_abs->elements().size()));
std::shared_ptr<AnfNodeWeakPtrList> sequence_nodes = std::make_shared<AnfNodeWeakPtrList>();
sequence_nodes->emplace_back(AnfNodeWeakPtr(anf_node));
(void)sequence_nodes->emplace_back(AnfNodeWeakPtr(anf_node));
sequence_abs->set_sequence_nodes(sequence_nodes);
}
return abs;

2
mindspore/core/abstract/abstract_value.cc
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@ -251,7 +251,7 @@ void CollectSequenceNodes(const AnfNodeWeakPtrList &source_sequence_nodes, AnfNo
sequence_nodes.begin(), sequence_nodes.end(),
[&source_sequence_node](const AnfNodeWeakPtr &weak_node) { return source_sequence_node == weak_node.lock(); });
if (this_iter == sequence_nodes.end()) {
sequence_nodes.emplace_back(AnfNodeWeakPtr(source_sequence_node));
(void)sequence_nodes.emplace_back(AnfNodeWeakPtr(source_sequence_node));
}
}
}