forked from mindspore-Ecosystem/mindspore
commit
e06649fc51
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@ -201,6 +201,7 @@ Status MultiProcess::ReceiveMsg(const CreateBufferCall &create_buffer_call) {
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msg_len = receive_msg_->msg_total_len;
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msg_buffer = create_buffer_call(msg_len);
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}
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MS_EXCEPTION_IF_NULL(msg_buffer);
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auto ret = memcpy_s(msg_buffer + cur_offset, msg_len - cur_offset, shmat_data_addr_, receive_msg_->msg_len);
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if (ret != EOK) {
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MS_LOG(INFO) << "memcpy_s failed, ret = " << ret;
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@ -39,7 +39,7 @@ class AscendMemAdapter {
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uint8_t *MallocStaticDevMem(size_t size, const std::string &tag = "");
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uint8_t *MallocDynamicDevMem(size_t size, const std::string &tag = "");
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bool FreeStaticDevMem(void *devPtr) const { return true; }
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bool FreeStaticDevMem(void *) const { return true; }
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void ResetDynamicMemory();
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[[nodiscard]] uint64_t FreeDevMemSize() const { return static_mem_offset_ - max_dynamic_mem_offset_; }
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@ -41,7 +41,7 @@ void AscendMemoryPool::Init() {
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if (task_sink) {
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SetMemAllocUintSize(ASCEND_COMMON_POOL_ALLOC_UNIT_SIZE_FOR_GRAPH, ASCEND_COMMON_POOL_ALLOC_UNIT_SIZE_FOR_GRAPH);
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} else {
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SetMemAllocUintSize(total_size * kCommonMemoryRatio, total_size * kPersistMemoryRatio);
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SetMemAllocUintSize(FloatToSize(total_size * kCommonMemoryRatio), FloatToSize(total_size * kPersistMemoryRatio));
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}
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}
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}
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@ -32,7 +32,7 @@ int MpiPycc::GetDeviceID() { return GetDeviceId(); }
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int MpiPycc::GetRankId(const std::string &group) { return GetRankIdByGroup(group); }
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int MpiPycc::GetRankSize(const std::string &group) { return GetGroupSize(group); }
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void MpiPycc::CreateGroup(const std::string &group, const std::vector<unsigned int> &ranks) {
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CreateCommForGroup(group, ranks);
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(void)CreateCommForGroup(group, ranks);
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}
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// cppcheck-suppress syntaxError
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@ -99,7 +99,7 @@ bool AicpuExtInfoHandler::ParseExtShapeType(AicpuExtInfo *aicpu_ext_info) {
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auto type = reinterpret_cast<const int32_t *>(aicpu_ext_info->infoMsg);
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if (*type != unknown_type_) {
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if (*type != static_cast<int32_t>(unknown_type_)) {
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MS_LOG(ERROR) << "Node:" << node_name_ << " parse ext shape type failed as need:" << unknown_type_
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<< " but got:" << *type;
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return false;
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@ -230,8 +230,9 @@ bool AicpuExtInfoHandler::UpdateShapeAndType(const std::vector<int64_t> &shape,
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return true;
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}
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void AicpuExtInfoHandler::GetShapeAndType(NotNull<const AicpuShapeAndType *> shape_and_type,
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NotNull<std::vector<int64_t> *> shape, NotNull<TypeId *> data_type) {
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void AicpuExtInfoHandler::GetShapeAndType(const NotNull<const AicpuShapeAndType *> &shape_and_type,
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const NotNull<std::vector<int64_t> *> &shape,
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const NotNull<TypeId *> &data_type) {
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for (int64_t tmpDim : shape_and_type->dims) {
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if (tmpDim == kDimEndFlag) {
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break;
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@ -69,8 +69,8 @@ class AicpuExtInfoHandler {
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[[nodiscard]] static bool UpdateShapeAndType(const std::vector<int64_t> &shape,
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NotNull<AicpuShapeAndType *> shape_and_type);
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static void GetShapeAndType(NotNull<const AicpuShapeAndType *> shape_and_type, NotNull<std::vector<int64_t> *> shape,
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NotNull<TypeId *> data_type);
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static void GetShapeAndType(const NotNull<const AicpuShapeAndType *> &shape_and_type,
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const NotNull<std::vector<int64_t> *> &shape, const NotNull<TypeId *> &data_type);
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const std::string node_name_;
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const uint32_t input_num_;
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@ -23,7 +23,7 @@ namespace mindspore::kernel {
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using ANodeFusionDataTypeMap = std::map<const AnfNodePtr, tbe::FusionDataType>;
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class FusionBuildTbeJsonCreator : public TbeJsonCreator {
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public:
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FusionBuildTbeJsonCreator() : optional_index_(0) {}
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FusionBuildTbeJsonCreator() : TbeJsonCreator(), optional_index_(0) {}
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~FusionBuildTbeJsonCreator() override = default;
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bool GenJson(const FusionScopeInfo &fusion_scope_info, nlohmann::json *fusion_json) override;
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@ -16,6 +16,8 @@
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#ifndef MINDSPORE_CCSRC_BACKEND_OPTIMIZER_ASCEND_BUFFER_FUSION_PASS_BATCHMATMUL_DROPOUTDOMASKV3_FUSION_PASS_H_
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#define MINDSPORE_CCSRC_BACKEND_OPTIMIZER_ASCEND_BUFFER_FUSION_PASS_BATCHMATMUL_DROPOUTDOMASKV3_FUSION_PASS_H_
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#include <utility>
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#include "utils/hash_set.h"
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#include "plugin/device/ascend/optimizer/buffer_fusion/fusion_base_pass.h"
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#include "ir/anf.h"
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@ -30,7 +32,7 @@ namespace opt {
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class BatchMatmulDropoutDoMaskV3FusionPass : public FusionBasePass {
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public:
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explicit BatchMatmulDropoutDoMaskV3FusionPass(FusionIdAllocatorPtr idAllocator)
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: FusionBasePass("BatchMatmulDropoutDoMaskV3FusionPass", idAllocator) {}
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: FusionBasePass("BatchMatmulDropoutDoMaskV3FusionPass", std::move(idAllocator)) {}
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~BatchMatmulDropoutDoMaskV3FusionPass() override = default;
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void MatchSingleFusionPattern(const session::KernelGraph &kernel_graph, FusedNodeRecord *candidate_fusion) override;
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@ -16,6 +16,8 @@
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#ifndef MINDSPORE_CCSRC_BACKEND_OPTIMIZER_ASCEND_BUFFER_FUSION_PASS_DEPTHWISECONV_ELTWISE_FUSION_PASS_H_
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#define MINDSPORE_CCSRC_BACKEND_OPTIMIZER_ASCEND_BUFFER_FUSION_PASS_DEPTHWISECONV_ELTWISE_FUSION_PASS_H_
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#include <utility>
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#include "utils/hash_set.h"
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#include "plugin/device/ascend/optimizer/buffer_fusion/fusion_base_pass.h"
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#include "ir/anf.h"
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@ -30,7 +32,7 @@ namespace opt {
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class DepthwiseConvEltwiseFusionPass : public FusionBasePass {
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public:
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explicit DepthwiseConvEltwiseFusionPass(FusionIdAllocatorPtr idAllocator)
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: FusionBasePass("DepthwiseConvEltwiseFusionPass", idAllocator) {}
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: FusionBasePass("DepthwiseConvEltwiseFusionPass", std::move(idAllocator)) {}
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~DepthwiseConvEltwiseFusionPass() override = default;
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void MatchSingleFusionPattern(const session::KernelGraph &kernel_graph, FusedNodeRecord *candidate_fusion) override;
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@ -25,7 +25,7 @@ namespace mindspore {
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namespace opt {
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class BnSplit : public PatternProcessPass {
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public:
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explicit BnSplit(string name = "bn_split", bool multigraph = true) : PatternProcessPass(name, multigraph) {}
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explicit BnSplit(const string &name = "bn_split", bool multigraph = true) : PatternProcessPass(name, multigraph) {}
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~BnSplit() override = default;
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const BaseRef DefinePattern() const override;
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const AnfNodePtr Process(const FuncGraphPtr &, const AnfNodePtr &, const EquivPtr &) const override;
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@ -27,7 +27,7 @@
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namespace mindspore {
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namespace opt {
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namespace {
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bool NeedFusion(const AnfNodePtr &sum_anf, const AnfNodePtr &input0, const AnfNodePtr &input1) {
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bool NeedFusion(const AnfNodePtr &sum_anf, const AnfNodePtr &input0, const AnfNodePtr &) {
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if (sum_anf == nullptr || !sum_anf->isa<CNode>()) {
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MS_LOG(WARNING) << "Matched ReduceSum is not a CNode!";
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return false;
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@ -49,7 +49,7 @@ class InputToOutputRegistry {
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void Register(const InputToOutputRegister ®);
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void Register(
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const std::string &op_name, const std::vector<size_t> &input_indices,
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const PreCheckFunc &pre_check_func = [](const CNodePtr &node) { return true; });
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const PreCheckFunc &pre_check_func = [](const CNodePtr &) { return true; });
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bool GetRegisterByOpName(const std::string &op_name, InputToOutputRegister *reg) const;
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private:
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