!45184 Fix clean code warning
Merge pull request !45184 from 胡彬/clean-code-master
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commit
f7168c8ee7
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@ -62,6 +62,7 @@ void EliminateDuplicatedTupleGetItem(const FuncGraphPtr &graph, const FuncGraphM
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continue;
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}
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auto getitem_cnode = node->cast<CNodePtr>();
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MS_EXCEPTION_IF_NULL(getitem_cnode);
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KernelWithIndex input_with_index{getitem_cnode->input(kRealInputNodeIndexInTupleGetItem),
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GetGetitemIndex(getitem_cnode)};
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if (getitem_dup_map.count(input_with_index) == 0) {
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@ -105,6 +106,8 @@ bool BackendCSE::CheckEqualKernelBuildInfo(const AnfNodePtr &main, const AnfNode
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}
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bool BackendCSE::CheckEqualCnodeInputs(const AnfNodePtr &main, const AnfNodePtr &node) const {
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MS_EXCEPTION_IF_NULL(main);
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MS_EXCEPTION_IF_NULL(node);
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auto c_main = main->cast<CNodePtr>();
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MS_EXCEPTION_IF_NULL(c_main);
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auto c_node = node->cast<CNodePtr>();
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@ -35,6 +35,7 @@ const AnfNodePtr ConvertDynamicBroadcastTo::Process(const FuncGraphPtr &func_gra
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auto input_x = common::AnfAlgo::GetInputNode(ori_cnode, 0);
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CNodePtr broadcast_to_node =
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opt::NewCNode({NewValueNode(std::make_shared<Primitive>(broadcast_to_op_name)), input_x}, func_graph, {node});
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MS_EXCEPTION_IF_NULL(broadcast_to_node);
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broadcast_to_node->set_abstract(node->abstract());
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auto shape_ptr = node->abstract()->BuildShape()->cast<abstract::ShapePtr>();
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MS_EXCEPTION_IF_NULL(shape_ptr);
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@ -22,6 +22,7 @@
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namespace mindspore {
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namespace opt {
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bool ConvertUnusedTupleParaToMakeTuple::Run(const FuncGraphPtr &func_graph) {
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MS_EXCEPTION_IF_NULL(func_graph);
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auto kernel_graph = dyn_cast<session::KernelGraph>(func_graph);
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MS_EXCEPTION_IF_NULL(kernel_graph);
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for (auto &input : kernel_graph->inputs()) {
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@ -67,7 +67,7 @@ CNodePtr NewConcatNode(const FuncGraphPtr &func_graph, const std::pair<std::vect
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size_t input_num = node_info.first.size() - 1;
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common::AnfAlgo::SetNodeAttr(kAttrAxis, MakeValue<int64_t>(0), concat_node);
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common::AnfAlgo::SetNodeAttr(kAttrInputNums, MakeValue<int64_t>(static_cast<int64_t>(input_num)), concat_node);
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common::AnfAlgo::SetNodeAttr(kAttrInputNums, MakeValue<int64_t>(UlongToLong(input_num)), concat_node);
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std::vector<int64_t> dyn_input_size{UlongToLong(input_num)};
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common::AnfAlgo::SetNodeAttr(kAttrDynInputSizes, MakeValue(dyn_input_size), concat_node);
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return concat_node;
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@ -40,6 +40,7 @@ bool GradientsAllReduceDependLastSend::Run(const FuncGraphPtr &graph) {
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continue;
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}
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auto cnode = node->cast<CNodePtr>();
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MS_EXCEPTION_IF_NULL(cnode);
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if (IsPrimitiveCNode(cnode, prim::kPrimAllReduce) && common::AnfAlgo::IsFusion(cnode)) {
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auto last_input = cnode->inputs().back();
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if (IsPrimitiveCNode(last_input, prim::kPrimTensorMove)) {
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@ -66,6 +67,7 @@ bool GradientsAllReduceDependLastSend::InsertDependBetweenAllReduceAndSend(const
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const CNodePtr &last_send) const {
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bool changed = false;
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FuncGraphManagerPtr manager = graph->manager();
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MS_EXCEPTION_IF_NULL(manager);
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for (auto &addn : addn_list) {
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std::vector<AnfNodePtr> inputs = {NewValueNode(std::make_shared<Primitive>(prim::kPrimDepend->name())), addn,
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last_send};
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@ -22,10 +22,12 @@
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namespace mindspore {
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namespace opt {
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namespace {
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const int axis_input_index = 2;
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constexpr int axis_input_index = 2;
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} // namespace
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AnfNodePtr ReduceSumOptimizer::NewRankOp(const AnfNodePtr &cnode, const KernelGraphPtr &kernel_graph) const {
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MS_EXCEPTION_IF_NULL(cnode);
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MS_EXCEPTION_IF_NULL(kernel_graph);
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std::vector<AnfNodePtr> rank_inputs;
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auto prim = std::make_shared<Primitive>(prim::kPrimRank->name());
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rank_inputs.push_back(NewValueNode(prim));
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@ -38,6 +40,8 @@ AnfNodePtr ReduceSumOptimizer::NewRankOp(const AnfNodePtr &cnode, const KernelGr
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}
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AnfNodePtr ReduceSumOptimizer::NewRangeOp(const AnfNodePtr &rank_op, const KernelGraphPtr &kernel_graph) const {
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MS_EXCEPTION_IF_NULL(rank_op);
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MS_EXCEPTION_IF_NULL(kernel_graph);
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std::vector<AnfNodePtr> range_inputs;
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auto prim = std::make_shared<Primitive>(prim::kPrimRange->name());
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range_inputs.push_back(NewValueNode(prim));
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