forked from mindspore-Ecosystem/mindspore
replace trandata with transpose
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890a949b4a
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bc4f35ce4d
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@ -1137,6 +1137,7 @@ constexpr auto kAttrPreKernelGraph = "pre_kernel_graph";
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constexpr auto kAttrNeedInline = "need_inline";
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constexpr auto kAttrNeedInline = "need_inline";
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constexpr auto kAttrOriFusionName = "ori_fusion_name";
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constexpr auto kAttrOriFusionName = "ori_fusion_name";
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constexpr auto kAttrDynamicLenName = "is_dynamic_len";
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constexpr auto kAttrDynamicLenName = "is_dynamic_len";
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constexpr auto kAttrForFormatChange = "for_format_change";
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// FuncGraph Flags
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// FuncGraph Flags
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constexpr auto kFlagIsPynativeBpropGraph = "is_pynative_bprop_graph";
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constexpr auto kFlagIsPynativeBpropGraph = "is_pynative_bprop_graph";
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@ -187,6 +187,7 @@
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#include "plugin/device/ascend/optimizer/optimizer_factory.h"
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#include "plugin/device/ascend/optimizer/optimizer_factory.h"
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#include "plugin/device/ascend/hal/common/ascend_utils.h"
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#include "plugin/device/ascend/hal/common/ascend_utils.h"
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#include "plugin/device/ascend/optimizer/ir_fission/ascend_convert_tuple_input_to_dynamic_input.h"
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#include "plugin/device/ascend/optimizer/ir_fission/ascend_convert_tuple_input_to_dynamic_input.h"
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#include "plugin/device/ascend/optimizer/format_type/replace_transdata_with_transpose.h"
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namespace mindspore {
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namespace mindspore {
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namespace opt {
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namespace opt {
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@ -313,6 +314,7 @@ void AscendDataLayout(const std::shared_ptr<session::KernelGraph> &kernel_graph)
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data_layout_pm->AddPass(std::make_shared<CommonSubexpressionElimination>());
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data_layout_pm->AddPass(std::make_shared<CommonSubexpressionElimination>());
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data_layout_pm->AddPass(std::make_shared<RemoveReshapePair>());
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data_layout_pm->AddPass(std::make_shared<RemoveReshapePair>());
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data_layout_pm->AddPass(std::make_shared<EliminateRedundantOp>());
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data_layout_pm->AddPass(std::make_shared<EliminateRedundantOp>());
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data_layout_pm->AddPass(std::make_shared<ReplaceTransDataWithTranspose>());
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if (kernel_graph->has_flag(kFlagPyNativeRunInGraph)) {
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if (kernel_graph->has_flag(kFlagPyNativeRunInGraph)) {
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data_layout_pm->AddPass(std::make_shared<EliminateGraphOutputTransdata>());
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data_layout_pm->AddPass(std::make_shared<EliminateGraphOutputTransdata>());
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}
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}
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@ -0,0 +1,155 @@
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/**
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* Copyright 2023 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "plugin/device/ascend/optimizer/format_type/replace_transdata_with_transpose.h"
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#include <string>
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#include <memory>
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#include <set>
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#include <vector>
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#include "backend/common/optimizer/optimizer.h"
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#include "backend/common/optimizer/helper.h"
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#include "plugin/device/ascend/optimizer/ascend_helper.h"
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namespace mindspore {
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namespace opt {
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namespace {
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const size_t kTransDataInputIndex = 1;
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bool CheckTransDataSupport(const AnfNodePtr &node) {
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MS_EXCEPTION_IF_NULL(node);
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if (!common::AnfAlgo::IsDynamicShape(node)) {
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return true;
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}
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static std::set<string> format_list = {kOpFormat_DEFAULT, kOpFormat_NCHW, kOpFormat_CHWN, kOpFormat_HWCN,
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kOpFormat_NHWC};
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auto input_format = AnfAlgo::GetInputFormat(node, 0);
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auto output_format = AnfAlgo::GetOutputFormat(node, 0);
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auto input_shape = AnfAlgo::GetInputDeviceShape(node, 0);
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auto output_shape = AnfAlgo::GetOutputDeviceShape(node, 0);
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return format_list.find(input_format) == format_list.end() || format_list.find(output_format) == format_list.end() ||
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input_shape.size() != kDim4 || output_shape.size() != kDim4;
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}
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std::vector<int64_t> GetTransposePerm(const AnfNodePtr &node) {
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MS_EXCEPTION_IF_NULL(node);
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auto input_format = AnfAlgo::GetInputFormat(node, 0);
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auto output_format = AnfAlgo::GetOutputFormat(node, 0);
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if (input_format == kOpFormat_DEFAULT) {
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input_format = kOpFormat_NCHW;
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}
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if (output_format == kOpFormat_DEFAULT) {
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output_format = kOpFormat_NCHW;
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}
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std::vector<int64_t> perm_value;
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for (size_t i = 0; i < output_format.size(); i++) {
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auto index = input_format.find((output_format[i]));
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if (index == std::string::npos) {
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MS_LOG(EXCEPTION) << "Can not find output dim [" << output_format[i] << "] in input format [" << input_format
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<< "].";
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}
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perm_value.emplace_back(index);
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}
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return perm_value;
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}
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ValueNodePtr CreatePermValueNode(const FuncGraphPtr &graph, const AnfNodePtr &node) {
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MS_EXCEPTION_IF_NULL(node);
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auto perm = GetTransposePerm(node);
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auto perm_value = std::make_shared<tensor::Tensor>(perm, kInt64);
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auto perm_node = NewValueNode(perm_value);
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MS_EXCEPTION_IF_NULL(perm_node);
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auto value_abstract = perm_value->ToAbstract();
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perm_node->set_abstract(value_abstract);
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auto kernel_info = std::make_shared<device::KernelInfo>();
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MS_EXCEPTION_IF_NULL(kernel_info);
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perm_node->set_kernel_info(kernel_info);
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kernel::KernelBuildInfo::KernelBuildInfoBuilder builder;
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builder.SetOutputsFormat({kOpFormat_DEFAULT});
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builder.SetOutputsDeviceType({kNumberTypeInt64});
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builder.SetOutputsKernelObjectType({kernel::KernelObjectType::TENSOR});
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AnfAlgo::SetSelectKernelBuildInfo(builder.Build(), perm_node.get());
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auto kernel_graph = graph->cast<KernelGraphPtr>();
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MS_EXCEPTION_IF_NULL(kernel_graph);
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kernel_graph->AddValueNodeToGraph(perm_node);
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return perm_node;
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}
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void SetKernelBuildInfo(const AnfNodePtr &transdata, const AnfNodePtr &transpose) {
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MS_EXCEPTION_IF_NULL(transpose);
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MS_EXCEPTION_IF_NULL(transdata);
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kernel::KernelBuildInfo::KernelBuildInfoBuilder selected_kernel_builder;
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selected_kernel_builder.SetInputsFormat({AnfAlgo::GetInputFormat(transdata, 0), kOpFormat_DEFAULT});
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selected_kernel_builder.SetInputsDeviceType(
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{AnfAlgo::GetInputDeviceDataType(transdata, 0), TypeId::kNumberTypeInt64});
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selected_kernel_builder.SetOutputsFormat({AnfAlgo::GetOutputFormat(transdata, 0)});
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selected_kernel_builder.SetOutputsDeviceType({AnfAlgo::GetOutputDeviceDataType(transdata, 0)});
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selected_kernel_builder.SetInputsKernelObjectType(
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{kernel::KernelObjectType::TENSOR, kernel::KernelObjectType::TENSOR});
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selected_kernel_builder.SetOutputsKernelObjectType({kernel::KernelObjectType::TENSOR});
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selected_kernel_builder.SetInputsReshapeType({"", ""});
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selected_kernel_builder.SetOutputsReshapeType({""});
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selected_kernel_builder.SetProcessor(kernel::Processor::AICORE);
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selected_kernel_builder.SetKernelType(KernelType::TBE_KERNEL);
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AnfAlgo::SetSelectKernelBuildInfo(selected_kernel_builder.Build(), transpose.get());
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}
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AnfNodePtr CreateNewTranspose(const FuncGraphPtr &func_graph, const AnfNodePtr &node, const PatternProcessPass &pass) {
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MS_EXCEPTION_IF_NULL(func_graph);
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MS_EXCEPTION_IF_NULL(node);
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auto cnode = node->cast<CNodePtr>();
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MS_EXCEPTION_IF_NULL(cnode);
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auto perm_node = CreatePermValueNode(func_graph, node);
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std::vector<AnfNodePtr> inputs = {NewValueNode(std::make_shared<Primitive>(kTransposeOpName)),
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cnode->input(kTransDataInputIndex), perm_node};
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auto transpose = pass.NewCNode(inputs, func_graph);
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MS_EXCEPTION_IF_NULL(transpose);
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SetKernelBuildInfo(node, transpose);
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std::vector<std::string> input_names = {"x", "perm"};
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std::vector<std::string> output_names = {"output"};
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common::AnfAlgo::SetNodeAttr(kAttrInputNames, MakeValue(input_names), transpose);
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common::AnfAlgo::SetNodeAttr(kAttrOutputNames, MakeValue(output_names), transpose);
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common::AnfAlgo::SetNodeAttr(kAttrForFormatChange, MakeValue(true), transpose);
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transpose->set_abstract(node->abstract());
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transpose->set_scope(node->scope());
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return transpose;
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}
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} // namespace
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const BaseRef ReplaceTransDataWithTranspose::DefinePattern() const {
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VarPtr x1 = std::make_shared<Var>();
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return VectorRef({prim::kPrimTransData, x1});
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}
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const AnfNodePtr ReplaceTransDataWithTranspose::Process(const FuncGraphPtr &func_graph, const AnfNodePtr &node,
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const EquivPtr &) const {
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MS_EXCEPTION_IF_NULL(func_graph);
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MS_EXCEPTION_IF_NULL(node);
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MS_LOG(DEBUG) << "Process node: " << node->fullname_with_scope();
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if (CheckTransDataSupport(node)) {
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MS_LOG(DEBUG) << "TransData is support, no need replace. node: " << node->fullname_with_scope();
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return nullptr;
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}
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auto transpose = CreateNewTranspose(func_graph, node, *this);
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MS_EXCEPTION_IF_NULL(transpose);
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MS_LOG(DEBUG) << "TransData is not supported from input format " << AnfAlgo::GetInputFormat(node, 0)
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<< " to output format " << AnfAlgo::GetOutputFormat(node, 0)
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<< " in dynamic shape scenario, replace TransData with Transpose."
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<< " Origin TransData: " << node->fullname_with_scope()
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<< ", New Transpose: " << transpose->fullname_with_scope();
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return transpose;
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}
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} // namespace opt
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} // namespace mindspore
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@ -0,0 +1,38 @@
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/**
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* Copyright 2023 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_CCSRC_BACKEND_OPTIMIZER_ASCEND_FORMAT_TYPE_REPLACE_TRANSDATA_WITH_TRANSPOSE_H
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#define MINDSPORE_CCSRC_BACKEND_OPTIMIZER_ASCEND_FORMAT_TYPE_REPLACE_TRANSDATA_WITH_TRANSPOSE_H
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#include <string>
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#include <memory>
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#include "backend/common/optimizer/optimizer.h"
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#include "backend/common/optimizer/helper.h"
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#include "plugin/device/ascend/optimizer/ascend_helper.h"
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namespace mindspore {
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namespace opt {
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class ReplaceTransDataWithTranspose : public PatternProcessPass {
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public:
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explicit ReplaceTransDataWithTranspose(bool multigraph = true)
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: PatternProcessPass("replace_transdata_with_transpose", multigraph) {}
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~ReplaceTransDataWithTranspose() override = default;
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const BaseRef DefinePattern() const override;
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const AnfNodePtr Process(const FuncGraphPtr &func_graph, const AnfNodePtr &node, const EquivPtr &) const override;
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};
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} // namespace opt
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} // namespace mindspore
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#endif // MINDSPORE_REPLACE_TRANSDATA_WITH_TRANSPOSE_H
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@ -82,6 +82,11 @@ class TransposeInfer : public abstract::OpInferBase {
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CheckAndConvertUtils::CheckInputArgs(input_args, kEqual, kInputNum, op_name);
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CheckAndConvertUtils::CheckInputArgs(input_args, kEqual, kInputNum, op_name);
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auto x_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[0]->BuildShape())[kShape];
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auto x_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[0]->BuildShape())[kShape];
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(void)CheckAndConvertUtils::CheckInteger("input_x size", SizeToLong(x_shape.size()), kGreaterThan, 0, op_name);
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(void)CheckAndConvertUtils::CheckInteger("input_x size", SizeToLong(x_shape.size()), kGreaterThan, 0, op_name);
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auto for_format_change_value = primitive->GetAttr(kAttrForFormatChange);
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if (for_format_change_value != nullptr && GetValue<bool>(for_format_change_value)) {
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return std::make_shared<abstract::Shape>(x_shape);
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}
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ShapeVector p_value;
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ShapeVector p_value;
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if (x_shape[0] == 0) {
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if (x_shape[0] == 0) {
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MS_EXCEPTION(ValueError) << "For 'Transpose', first dim of input_x's shape can not be 0, but got 0.";
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MS_EXCEPTION(ValueError) << "For 'Transpose', first dim of input_x's shape can not be 0, but got 0.";
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