forked from mindspore-Ecosystem/mindspore
!1505 Add some checks in ConstToAttr[StridedSliceGrad] pass
Merge pull request !1505 from huanghui/stride-slice
This commit is contained in:
commit
c086d91aaf
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@ -21,6 +21,7 @@
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#include "pre_activate/pass/convert_tuple_output_to_maketuple.h"
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#include "pre_activate/pass/convert_const_input_to_tensor_input.h"
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#include "pre_activate/pass/convert_tuple_input_to_dynamic_input.h"
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#include "pre_activate/pass/const_to_attr_strided_slice_grad.h"
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#include "utils/context/ms_context.h"
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#include "debug/anf_ir_dump.h"
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@ -42,6 +43,7 @@ void BackendCommonOptimization(const std::shared_ptr<session::KernelGraph> &kern
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auto optimizer = std::make_shared<GraphOptimizer>();
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auto common_pm = std::make_shared<PassManager>("common_pm");
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common_pm->AddPass(std::make_shared<ConvertConstInputToAttr>());
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common_pm->AddPass(std::make_shared<ConstToAttrStridedSliceGradPass>());
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common_pm->AddPass(std::make_shared<ConvertConstInputToTensorInput>());
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common_pm->AddPass(std::make_shared<ConvertTupleInputToDynamicInput>());
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common_pm->AddPass(std::make_shared<ConvertTupleOutputToMaketuple>());
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@ -687,7 +687,7 @@ bool IsSameNode(const EquivPtr &equiv1, const EquivPtr &equiv2, const VarPtr &va
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MS_EXCEPTION_IF_NULL(equiv1_node);
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auto equiv2_node = GetAnfNodeByVar(equiv2, var_node);
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MS_EXCEPTION_IF_NULL(equiv2_node);
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return equiv1_node == equiv2_node;
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return *equiv1_node == *equiv2_node;
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}
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AnfNodePtr GetAnfNodeByVar(const EquivPtr &equiv, const VarPtr &var_node) {
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@ -52,7 +52,6 @@ ConstInputToAttrInfoRegistry::ConstInputToAttrInfoRegistry() {
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Register(kScatterNdOpName, {2});
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Register(kStridedSliceAssignOpName, {1, 2, 3});
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Register(kStridedSliceOpName, {1, 2, 3});
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Register(kStridedSliceGradOpName, {1, 2, 3, 4});
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Register(kFlattenGradOpName, {1});
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Register(kExpandDimsOpName, {1});
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Register(kSplitOpName, {0});
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@ -0,0 +1,132 @@
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/**
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* Copyright 2020 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 "pre_activate/pass/const_to_attr_strided_slice_grad.h"
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#include <memory>
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#include <vector>
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#include "session/anf_runtime_algorithm.h"
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#include "ir/primitive.h"
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#include "utils/utils.h"
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#include "pipeline/static_analysis/abstract_value.h"
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#include "pre_activate/common/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 strides_index = 5;
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bool GetStridesValues(const CNodePtr &strided_slice_grad, ValuePtrList *strides_values) {
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MS_EXCEPTION_IF_NULL(strided_slice_grad);
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if (strided_slice_grad->size() < 6) {
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MS_LOG(DEBUG) << "Op strided_slice_grad's inputs size less than 6, graph not changed";
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return false;
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}
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auto strides_input = strided_slice_grad->input(strides_index);
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MS_EXCEPTION_IF_NULL(strides_input);
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auto strides_value_node = strides_input->cast<ValueNodePtr>();
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if (strides_value_node == nullptr) {
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MS_LOG(DEBUG) << "strides is not a value node.";
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return false;
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}
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auto value = strides_value_node->value();
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if (value == nullptr) {
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MS_LOG(DEBUG) << "strides has no value.";
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return false;
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}
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auto value_tuple = value->cast<ValueTuplePtr>();
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if (value_tuple == nullptr) {
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MS_LOG(DEBUG) << "strides is not a value tuple.";
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return false;
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}
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*strides_values = value_tuple->value();
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return true;
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}
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bool CheckValues(const ValuePtrList &strides_values) {
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if (strides_values.empty()) {
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MS_LOG(DEBUG) << "strides_values is empty";
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return false;
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}
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for (auto &value : strides_values) {
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MS_EXCEPTION_IF_NULL(value);
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if (value->isa<Scalar>()) {
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auto scalar = value->cast<ScalarPtr>();
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MS_EXCEPTION_IF_NULL(scalar);
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if (!scalar->isa<Int32Imm>()) {
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MS_LOG(DEBUG) << "strides value is not a Integer";
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return false;
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}
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if (GetValue<int>(scalar) != 1) {
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MS_LOG(DEBUG) << "StridedSliceGrad has no 1 value";
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return false;
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}
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} else {
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MS_LOG(DEBUG) << "The value " << value << "of tuple is not a scalar";
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return false;
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}
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}
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return true;
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}
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bool CheckAttrs(const CNodePtr &strided_slice_grad) {
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MS_EXCEPTION_IF_NULL(strided_slice_grad);
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if (!AnfAlgo::HasNodeAttr(kAttrNewAxisMask, strided_slice_grad) ||
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!AnfAlgo::HasNodeAttr(kAttrShrinkAxisMask, strided_slice_grad)) {
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MS_LOG(INFO) << "new_axis_mask or shrink_axis_mask not exist in cnode[" + strided_slice_grad->DebugString() + "]";
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return false;
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}
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auto new_axis_mask = AnfAlgo::GetNodeAttr<int>(strided_slice_grad, kAttrNewAxisMask);
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auto shrink_axis_mask = AnfAlgo::GetNodeAttr<int>(strided_slice_grad, kAttrShrinkAxisMask);
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if (new_axis_mask != 0 || shrink_axis_mask != 0) {
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MS_LOG(INFO) << "new_axis_mask or shrink_axis_mask not equal 0";
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return false;
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}
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return true;
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}
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} // namespace
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const BaseRef ConstToAttrStridedSliceGradPass::DefinePattern() const {
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VarPtr Xs = std::make_shared<SeqVar>();
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auto strided_slice_grad_prim = std::make_shared<Primitive>(kStridedSliceGradOpName);
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return VectorRef({strided_slice_grad_prim, Xs});
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}
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const AnfNodePtr ConstToAttrStridedSliceGradPass::Process(const FuncGraphPtr &graph, const AnfNodePtr &node,
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const EquivPtr &) const {
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MS_EXCEPTION_IF_NULL(graph);
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MS_EXCEPTION_IF_NULL(node);
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auto strided_slice_grad = node->cast<CNodePtr>();
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MS_EXCEPTION_IF_NULL(strided_slice_grad);
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if (!CheckAttrs(strided_slice_grad)) {
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MS_LOG(INFO) << "Check strided_slice_grad's attrs failed, graph not changed";
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return nullptr;
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}
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ValuePtrList strides_values;
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if (!GetStridesValues(strided_slice_grad, &strides_values)) {
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return nullptr;
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}
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if (!CheckValues(strides_values)) {
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MS_LOG(INFO) << "Check strides' values failed, graph not changed";
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return nullptr;
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}
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ConstInputToAttr(strided_slice_grad, {1, 2, 3, 4});
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return nullptr;
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}
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} // namespace opt
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} // namespace mindspore
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@ -0,0 +1,34 @@
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/**
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* Copyright 2020 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_PRE_ACTIVATE_PASS_CONST_TO_ATTR_STRIDED_SLICE_GRAD_H_
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#define MINDSPORE_CCSRC_PRE_ACTIVATE_PASS_CONST_TO_ATTR_STRIDED_SLICE_GRAD_H_
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#include <memory>
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#include "pre_activate/common/optimizer.h"
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namespace mindspore {
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namespace opt {
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class ConstToAttrStridedSliceGradPass : public PatternProcessPass {
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public:
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explicit ConstToAttrStridedSliceGradPass(bool multigraph = true)
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: PatternProcessPass("const_to_attr_strided_slice_grad_", multigraph) {}
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~ConstToAttrStridedSliceGradPass() 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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};
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} // namespace opt
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} // namespace mindspore
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#endif // MINDSPORE_CCSRC_PRE_ACTIVATE_PASS_CONST_TO_ATTR_STRIDED_SLICE_GRAD_H_
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@ -193,6 +193,8 @@ constexpr auto kAttrIsTraining = "is_training";
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constexpr auto kAttrFusionId = "fusion_id";
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constexpr auto kAttrLabelIndex = "label_index";
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constexpr auto kAttrLabelSwitchList = "label_switch_list";
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constexpr auto kAttrNewAxisMask = "new_axis_mask";
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constexpr auto kAttrShrinkAxisMask = "shrink_axis_mask";
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// attr value
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constexpr auto kValueTargetSwitch = "target_switch";
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@ -0,0 +1,77 @@
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/**
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* Copyright 2020 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 "common/backend_common_test.h"
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#include "operator/ops.h"
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#include "debug/anf_ir_dump.h"
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#include "common/py_func_graph_fetcher.h"
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#include "session/anf_runtime_algorithm.h"
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#include "pre_activate/common/optimizer.h"
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#include "pre_activate/common/pass_manager.h"
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#include "pre_activate/pass/const_to_attr_strided_slice_grad.h"
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#include "utils/utils.h"
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#include "common/utils.h"
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namespace mindspore {
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namespace opt {
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class TestHWConstToAttrStridedSliceGrad : public BackendCommon {
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public:
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TestHWConstToAttrStridedSliceGrad() : getPyFun_("gtest_input.pre_activate.const_to_attr_strided_slice_grad", true) {}
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~TestHWConstToAttrStridedSliceGrad() override = default;
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public:
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UT::PyFuncGraphFetcher getPyFun_;
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};
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TEST_F(TestHWConstToAttrStridedSliceGrad, test_strided_slice_grad) {
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FuncGraphPtr g = getPyFun_.CallAndParseRet("test_const_to_attr_strided_slice_grad", "before");
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ASSERT_TRUE(g != nullptr);
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FuncGraphPtr g_after = getPyFun_.CallAndParseRet("test_const_to_attr_strided_slice_grad", "after");
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ASSERT_TRUE(g_after != nullptr);
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auto ret = g->get_return();
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ASSERT_TRUE(ret != nullptr);
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EXPECT_NE(ret->input(1), nullptr);
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EXPECT_NE(ret->input(1)->cast<CNodePtr>(), nullptr);
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auto cnode = ret->input(1)->cast<CNodePtr>();
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EXPECT_FALSE(AnfAlgo::HasNodeAttr("shapex", cnode));
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EXPECT_FALSE(AnfAlgo::HasNodeAttr("begin", cnode));
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EXPECT_FALSE(AnfAlgo::HasNodeAttr("end", cnode));
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EXPECT_FALSE(AnfAlgo::HasNodeAttr("strides", cnode));
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EXPECT_FALSE(CheckEqualGraph(g, g_after));
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std::vector<int> shp_x{16, 1, 1024};
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auto x_abstract = std::make_shared<abstract::AbstractTensor>(kFloat32, shp_x);
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AbstractBasePtrList args_spec_list{x_abstract};
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auto kg = GetKernelGraph(g, args_spec_list);
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ASSERT_TRUE(kg != nullptr);
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ret = kg->get_return();
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ASSERT_TRUE(ret != nullptr);
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EXPECT_NE(ret->input(1), nullptr);
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EXPECT_NE(ret->input(1)->cast<CNodePtr>(), nullptr);
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auto make_tuple = ret->input(1)->cast<CNodePtr>();
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ASSERT_TRUE(make_tuple != nullptr);
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EXPECT_NE(make_tuple->input(1), nullptr);
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EXPECT_NE(make_tuple->input(1)->cast<CNodePtr>(), nullptr);
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cnode = make_tuple->input(1)->cast<CNodePtr>();
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EXPECT_TRUE(AnfAlgo::HasNodeAttr("shapex", cnode));
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EXPECT_TRUE(AnfAlgo::HasNodeAttr("begin", cnode));
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EXPECT_TRUE(AnfAlgo::HasNodeAttr("end", cnode));
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EXPECT_TRUE(AnfAlgo::HasNodeAttr("strides", cnode));
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EXPECT_TRUE(CheckEqualGraph(kg, g_after));
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}
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} // namespace opt
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} // namespace mindspore
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@ -109,44 +109,5 @@ TEST_F(TestHWConstInputToAttr, test_onehot) {
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EXPECT_TRUE(AnfAlgo::HasNodeAttr("depth", cnode));
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EXPECT_TRUE(CheckEqualGraph(func_graph, g_after));
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}
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TEST_F(TestHWConstInputToAttr, test_strided_slice_grad) {
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FuncGraphPtr g = getPyFun_.CallAndParseRet("test_convert_strided_slice_grad_input_to_attr", "before");
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ASSERT_TRUE(g != nullptr);
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FuncGraphPtr g_after = getPyFun_.CallAndParseRet("test_convert_strided_slice_grad_input_to_attr", "after");
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ASSERT_TRUE(g_after != nullptr);
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auto ret = g->get_return();
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ASSERT_TRUE(ret != nullptr);
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EXPECT_NE(ret->input(1), nullptr);
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EXPECT_NE(ret->input(1)->cast<CNodePtr>(), nullptr);
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auto cnode = ret->input(1)->cast<CNodePtr>();
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EXPECT_FALSE(AnfAlgo::HasNodeAttr("shapex", cnode));
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EXPECT_FALSE(AnfAlgo::HasNodeAttr("begin", cnode));
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EXPECT_FALSE(AnfAlgo::HasNodeAttr("end", cnode));
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EXPECT_FALSE(AnfAlgo::HasNodeAttr("strides", cnode));
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EXPECT_FALSE(CheckEqualGraph(g, g_after));
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std::vector<int> shp_x{16, 1, 1024};
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auto x_abstract = std::make_shared<abstract::AbstractTensor>(kFloat32, shp_x);
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AbstractBasePtrList args_spec_list{x_abstract};
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auto func_graph = GetKernelGraph(g, args_spec_list);
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ASSERT_TRUE(func_graph != nullptr);
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ret = func_graph->get_return();
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ASSERT_TRUE(ret != nullptr);
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EXPECT_NE(ret->input(1), nullptr);
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EXPECT_NE(ret->input(1)->cast<CNodePtr>(), nullptr);
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auto make_tuple = ret->input(1)->cast<CNodePtr>();
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ASSERT_TRUE(make_tuple != nullptr);
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EXPECT_NE(make_tuple->input(1), nullptr);
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EXPECT_NE(make_tuple->input(1)->cast<CNodePtr>(), nullptr);
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cnode = make_tuple->input(1)->cast<CNodePtr>();
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EXPECT_TRUE(AnfAlgo::HasNodeAttr("shapex", cnode));
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EXPECT_TRUE(AnfAlgo::HasNodeAttr("begin", cnode));
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EXPECT_TRUE(AnfAlgo::HasNodeAttr("end", cnode));
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EXPECT_TRUE(AnfAlgo::HasNodeAttr("strides", cnode));
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EXPECT_TRUE(CheckEqualGraph(func_graph, g_after));
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}
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} // namespace opt
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} // namespace mindspore
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@ -0,0 +1,46 @@
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# Copyright 2020 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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from mindspore.ops import Primitive
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from mindspore.ops.operations import _grad_ops as G
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stridedslicegrad = G.StridedSliceGrad()
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backend_stridedslicegrad = Primitive('StridedSliceGrad')
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make_tuple = Primitive('make_tuple')
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class FnDict:
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def __init__(self):
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self.fnDict = {}
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def __call__(self, fn):
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self.fnDict[fn.__name__] = fn
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def __getitem__(self, name):
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return self.fnDict[name]
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def test_const_to_attr_strided_slice_grad(tag):
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fns = FnDict()
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@fns
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def before(x):
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return stridedslicegrad(x, (16, 128, 1024), (0, 0, 0), (16, 1, 1024), (1, 1, 1))
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@fns
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def after(x):
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res = backend_stridedslicegrad(x)
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return make_tuple(res)
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return fns[tag]
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@ -110,21 +110,6 @@ def test_convert_onehot_input_to_attr(tag):
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return fns[tag]
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def test_convert_strided_slice_grad_input_to_attr(tag):
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fns = FnDict()
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@fns
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def before(x):
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return stridedslicegrad(x, (16, 128, 1024), (0, 0, 0), (16, 1, 1024), (1, 1, 1))
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@fns
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def after(x):
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res = backend_stridedslicegrad(x)
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return make_tuple(res)
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return fns[tag]
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def test_convert_onehot_input_to_tensor1(tag):
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fns = FnDict()
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