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Star934
1856
已合并
fix: softmax_grad_ext fusion pass 代码审查修复（memcpy_s 安全函数）、quant_update_scatter 原型重构、leaky_relu mask 调整、tiling 告警消除及 classify_rule 测试分类调整 #9190
yuanbin_22创建于 17 天前
fix: softmax_grad_ext fusion pass 代码审查修复（memcpy_s 安全函数）、quant_update_scatter 原型重构、leaky_relu mask 调整、tiling 告警消除及 classify_rule 测试分类调整 #9190
已合并
yuanbin_22创建于 17 天前
从yuanbin_22/ops-nnfix/softmax-grad-ext-code-review合入到cann/ops-nnmaster
共 6 个文件变更+150-184
Mactivation/leaky_relu/op_kernel/arch35/leaky_relu_dag.h+2-3
@@ -35,7 +35,6 @@ struct LeakyReluCustom : public Vec::ElemwiseBinaryOP<T, T, float> {
35 {35 {
36#ifdef __CCE_AICORE__36#ifdef __CCE_AICORE__
37 uint32_t dtypeSize = sizeof(float);37 uint32_t dtypeSize = sizeof(float);
38- constexpr uint64_t VECTOR_REG_WIDTH = 256UL;
39 uint32_t vl = VECTOR_REG_WIDTH / dtypeSize;38 uint32_t vl = VECTOR_REG_WIDTH / dtypeSize;
40 uint16_t loopNum = (count + vl - 1) / vl;39 uint16_t loopNum = (count + vl - 1) / vl;
41 uint32_t vlSize = vl;40 uint32_t vlSize = vl;
@@ -53,8 +52,8 @@ struct LeakyReluCustom : public Vec::ElemwiseBinaryOP<T, T, float> {
53 __VEC_SCOPE__52 __VEC_SCOPE__
54 {53 {
55 Reg::Duplicate(vregZero, 0.0f);54 Reg::Duplicate(vregZero, 0.0f);
56- mask = Reg::UpdateMask<float, Reg::RegTraitNumOne>(count);
57 for (uint16_t loopIdx = 0; loopIdx < loopNum; loopIdx++) {55 for (uint16_t loopIdx = 0; loopIdx < loopNum; loopIdx++) {
56+ mask = Reg::UpdateMask<float, Reg::RegTraitNumOne>(count);
58 Reg::LoadAlign<T, Reg::LoadDist::DIST_NORM>(vregInputfloat,57 Reg::LoadAlign<T, Reg::LoadDist::DIST_NORM>(vregInputfloat,
59 (__ubuf__ T*)(srcAddr + loopIdx * vlSize));58 (__ubuf__ T*)(srcAddr + loopIdx * vlSize));
60 Reg::Muls(vregNegPart, vregInputfloat, negativeSlope, mask);59 Reg::Muls(vregNegPart, vregInputfloat, negativeSlope, mask);
@@ -70,8 +69,8 @@ struct LeakyReluCustom : public Vec::ElemwiseBinaryOP<T, T, float> {
70 __VEC_SCOPE__69 __VEC_SCOPE__
71 {70 {
72 Reg::Duplicate(vregZero, 0.0f);71 Reg::Duplicate(vregZero, 0.0f);
73- mask = Reg::UpdateMask<float, Reg::RegTraitNumOne>(count);
74 for (uint16_t loopIdx = 0; loopIdx < loopNum; loopIdx++) {72 for (uint16_t loopIdx = 0; loopIdx < loopNum; loopIdx++) {
73+ mask = Reg::UpdateMask<float, Reg::RegTraitNumOne>(count);
75 Reg::LoadAlign<T, Reg::LoadDist::DIST_UNPACK_B16>(vregInputT,74 Reg::LoadAlign<T, Reg::LoadDist::DIST_UNPACK_B16>(vregInputT,
76 (__ubuf__ T*)(srcAddr + loopIdx * vlSize));75 (__ubuf__ T*)(srcAddr + loopIdx * vlSize));
77 Reg::Cast<float, T, castTrait0>(vregInputfloat, vregInputT, mask);76 Reg::Cast<float, T, castTrait0>(vregInputfloat, vregInputT, mask);
Mactivation/softmax_grad_ext/op_graph/fusion_pass/softmax_grad_ext_fusion_pass.cpp+49-28
@@ -7,6 +7,7 @@
7 * INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.7 * INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
8 * See LICENSE in the root of the software repository for the full text of the License.8 * See LICENSE in the root of the software repository for the full text of the License.
9 */9 */
10+#include "securec.h"
10#include "common/inc/error_util.h"11#include "common/inc/error_util.h"
11#include "softmax_grad_ext_fusion_pass.h"12#include "softmax_grad_ext_fusion_pass.h"
12#include "es_nn_ops.h"13#include "es_nn_ops.h"
@@ -29,11 +30,22 @@ const int64_t kSubgraphInputGrad = 0;
29const int64_t kSubgraphInputX1 = 1;30const int64_t kSubgraphInputX1 = 1;
30const int64_t kSubgraphInputX2 = 2;31const int64_t kSubgraphInputX2 = 2;
31const int32_t kReduceSumAxesInputIdx = 1;32const int32_t kReduceSumAxesInputIdx = 1;
33+const size_t kMinSubgraphInputCount = 3;
34+ 
35+const int64_t kUnknownShapeDim = -1;
36+const int64_t kReduceLastAxis = -1;
37+const int64_t kAxesShapeDim = 1;
38+const int32_t kPatternV2VariantCount = 4;
39+const int32_t kBinaryInputX1Idx = 0;
40+const int32_t kBinaryInputX2Idx = 1;
41+const int32_t kReduceSumInputXIdx = 0;
42+const int32_t kNodeOutputIdx = 0;
43+const std::string kTargetSocVersion = "Ascend950";
32 44 
33bool IsUnknownShape(const std::vector<int64_t>& dims)45bool IsUnknownShape(const std::vector<int64_t>& dims)
34{46{
35 for (auto dim : dims) {47 for (auto dim : dims) {
36- if (dim == -1) {48+ if (dim == kUnknownShapeDim) {
37 return true;49 return true;
38 }50 }
39 }51 }
@@ -49,8 +61,8 @@ bool IsTargetPlatform()
49 false, kPassName.c_str(), "Get platform_info failed.");61 false, kPassName.c_str(), "Get platform_info failed.");
50 const std::string soc = platform_info.str_info.short_soc_version;62 const std::string soc = platform_info.str_info.short_soc_version;
51 OPS_LOG_D(kPassName.c_str(), "Platform short soc: %s", soc.c_str());63 OPS_LOG_D(kPassName.c_str(), "Platform short soc: %s", soc.c_str());
52- if (soc != "Ascend950") {64+ if (soc != kTargetSocVersion) {
53- OPS_LOG_D(kPassName.c_str(), "Platform is not support, only support Ascend950.");65+ OPS_LOG_D(kPassName.c_str(), "Platform is not support, only support %s.", kTargetSocVersion.c_str());
54 return false;66 return false;
55 }67 }
56 return true;68 return true;
@@ -108,9 +120,15 @@ bool GetAxisFromReduceSum(const GNode& sum_node, int64_t& axis_value, bool& keep
108 return false;120 return false;
109 }121 }
110 if (dtype == DT_INT64) {122 if (dtype == DT_INT64) {
111- axis_value = static_cast<int64_t>(*reinterpret_cast<const int64_t*>(data));123+ int64_t tmp = 0;
124+ auto memRet = memcpy_s(&tmp, sizeof(int64_t), data, sizeof(int64_t));
125+ OP_LOGE_IF(memRet != EOK, false, kPassName.c_str(), "memcpy_s for int64 axes failed, ret=%d.", memRet);
126+ axis_value = tmp;
112 } else if (dtype == DT_INT32) {127 } else if (dtype == DT_INT32) {
113- axis_value = static_cast<int64_t>(*reinterpret_cast<const int32_t*>(data));128+ int32_t tmp = 0;
129+ auto memRet = memcpy_s(&tmp, sizeof(int32_t), data, sizeof(int32_t));
130+ OP_LOGE_IF(memRet != EOK, false, kPassName.c_str(), "memcpy_s for int32 axes failed, ret=%d.", memRet);
131+ axis_value = tmp;
114 } else {132 } else {
115 OPS_LOG_D(kPassName.c_str(), "ReduceSum axes dtype %d is not supported.", static_cast<int32_t>(dtype));133 OPS_LOG_D(kPassName.c_str(), "ReduceSum axes dtype %d is not supported.", static_cast<int32_t>(dtype));
116 return false;134 return false;
@@ -120,7 +138,7 @@ bool GetAxisFromReduceSum(const GNode& sum_node, int64_t& axis_value, bool& keep
120 OPS_LOG_D(kPassName.c_str(), "Failed to get keep_dims attr from ReduceSum.");138 OPS_LOG_D(kPassName.c_str(), "Failed to get keep_dims attr from ReduceSum.");
121 return false;139 return false;
122 }140 }
123- OPS_LOG_D(kPassName.c_str(), "ReduceSum axis=%ld, keep_dims=%d.", axis_value, static_cast<int32_t>(keep_dims));141+ OPS_LOG_D(kPassName.c_str(), "ReduceSum axis=%lld, keep_dims=%d.", axis_value, static_cast<int32_t>(keep_dims));
124 return true;142 return true;
125}143}
126 144 
@@ -199,15 +217,17 @@ es::EsTensorHolder BuildBinaryNode(es::EsGraphBuilder& graph_builder, const es::
199 .IrDefOutputs({{"y", es::CompliantNodeBuilder::kEsIrOutputRequired, ""}})217 .IrDefOutputs({{"y", es::CompliantNodeBuilder::kEsIrOutputRequired, ""}})
200 .Build();218 .Build();
201#endif219#endif
202- es::AddEdgeAndUpdatePeerDesc(*graph, *input0.GetProducer(), input0.GetProducerOutIndex(), node, 0);220+ ES_ASSERT_GRAPH_SUCCESS(es::AddEdgeAndUpdatePeerDesc(*graph, *input0.GetProducer(), input0.GetProducerOutIndex(),
203- es::AddEdgeAndUpdatePeerDesc(*graph, *input1.GetProducer(), input1.GetProducerOutIndex(), node, 1);221+ node, kBinaryInputX1Idx));
204- return es::EsTensorHolder(c_builder->GetTensorHolderFromNode(node, 0));222+ ES_ASSERT_GRAPH_SUCCESS(es::AddEdgeAndUpdatePeerDesc(*graph, *input1.GetProducer(), input1.GetProducerOutIndex(),
223+ node, kBinaryInputX2Idx));
224+ return es::EsTensorHolder(c_builder->GetTensorHolderFromNode(node, kNodeOutputIdx));
205}225}
206 226 
207// Build a ReduceSum node used inside a pattern. axes is an internal Const node (CreateConst).227// Build a ReduceSum node used inside a pattern. axes is an internal Const node (CreateConst).
208es::EsTensorHolder BuildPatternReduceSum(es::EsGraphBuilder& graph_builder, const es::EsTensorHolder& input)228es::EsTensorHolder BuildPatternReduceSum(es::EsGraphBuilder& graph_builder, const es::EsTensorHolder& input)
209{229{
210- auto axes = graph_builder.CreateConst(std::vector<int64_t>{-1}, std::vector<int64_t>{1});230+ auto axes = graph_builder.CreateConst(std::vector<int64_t>{kReduceLastAxis}, std::vector<int64_t>{kAxesShapeDim});
211 auto* c_builder = graph_builder.GetCGraphBuilder();231 auto* c_builder = graph_builder.GetCGraphBuilder();
212 auto* graph = c_builder->GetGraph();232 auto* graph = c_builder->GetGraph();
213#if NN_HAS_V2_IR_API233#if NN_HAS_V2_IR_API
@@ -235,20 +255,20 @@ es::EsTensorHolder BuildPatternReduceSum(es::EsGraphBuilder& graph_builder, cons
235 es::CreateFrom(true)}})255 es::CreateFrom(true)}})
236 .Build();256 .Build();
237#endif257#endif
238- es::AddEdgeAndUpdatePeerDesc(*graph, *input.GetProducer(), input.GetProducerOutIndex(), node, 0);258+ ES_ASSERT_GRAPH_SUCCESS(es::AddEdgeAndUpdatePeerDesc(*graph, *input.GetProducer(), input.GetProducerOutIndex(),
239- es::AddEdgeAndUpdatePeerDesc(*graph, *axes.GetProducer(), axes.GetProducerOutIndex(), node, 1);259+ node, kReduceSumInputXIdx));
240- return es::EsTensorHolder(c_builder->GetTensorHolderFromNode(node, 0));260+ ES_ASSERT_GRAPH_SUCCESS(es::AddEdgeAndUpdatePeerDesc(*graph, *axes.GetProducer(), axes.GetProducerOutIndex(), node,
261+ kReduceSumAxesInputIdx));
262+ return es::EsTensorHolder(c_builder->GetTensorHolderFromNode(node, kNodeOutputIdx));
241}263}
242 264 
243-// v1 pattern:265+// Pattern: output = x2 * x1 * (grad - ReduceSum(grad * x1))
244-// mul = Mul(input0, input1); sum = ReduceSum(mul); sub = Sub(input0, sum);
245-// mul1 = Mul(input2, input1); mulGrad = Mul(mul1, sub)
246PatternUniqPtr MakePatternSoftmaxGradExt(const std::string& pass_name)266PatternUniqPtr MakePatternSoftmaxGradExt(const std::string& pass_name)
247{267{
248 auto graph_builder = es::EsGraphBuilder(pass_name.c_str());268 auto graph_builder = es::EsGraphBuilder(pass_name.c_str());
249- auto input0 = graph_builder.CreateInput(0, "grad");269+ auto input0 = graph_builder.CreateInput(kSubgraphInputGrad, "grad");
250- auto input1 = graph_builder.CreateInput(1, "x1");270+ auto input1 = graph_builder.CreateInput(kSubgraphInputX1, "x1");
251- auto input2 = graph_builder.CreateInput(2, "x2");271+ auto input2 = graph_builder.CreateInput(kSubgraphInputX2, "x2");
252 272 
253 auto mul = BuildBinaryNode(graph_builder, input0, input1, "Mul");273 auto mul = BuildBinaryNode(graph_builder, input0, input1, "Mul");
254 auto sum = BuildPatternReduceSum(graph_builder, mul);274 auto sum = BuildPatternReduceSum(graph_builder, mul);
@@ -258,7 +278,7 @@ PatternUniqPtr MakePatternSoftmaxGradExt(const std::string& pass_name)
258 278 
259 auto graph = graph_builder.BuildAndReset({mul_grad});279 auto graph = graph_builder.BuildAndReset({mul_grad});
260 auto pattern = std::make_unique<Pattern>(std::move(*graph));280 auto pattern = std::make_unique<Pattern>(std::move(*graph));
261- pattern->CaptureTensor({*sum.GetProducer(), 0});281+ pattern->CaptureTensor({*sum.GetProducer(), kNodeOutputIdx});
262 return pattern;282 return pattern;
263}283}
264 284 
@@ -271,9 +291,9 @@ PatternUniqPtr MakePatternSoftmaxGradExtV2(const std::string& pass_name, int32_t
271{291{
272 std::string builder_name = pass_name + "_" + std::to_string(variant);292 std::string builder_name = pass_name + "_" + std::to_string(variant);
273 auto graph_builder = es::EsGraphBuilder(builder_name.c_str());293 auto graph_builder = es::EsGraphBuilder(builder_name.c_str());
274- auto input0 = graph_builder.CreateInput(0, "grad");294+ auto input0 = graph_builder.CreateInput(kSubgraphInputGrad, "grad");
275- auto input1 = graph_builder.CreateInput(1, "x1");295+ auto input1 = graph_builder.CreateInput(kSubgraphInputX1, "x1");
276- auto input2 = graph_builder.CreateInput(2, "x2");296+ auto input2 = graph_builder.CreateInput(kSubgraphInputX2, "x2");
277 297 
278 auto mul = BuildBinaryNode(graph_builder, input0, input1, "Mul");298 auto mul = BuildBinaryNode(graph_builder, input0, input1, "Mul");
279 auto sum = BuildPatternReduceSum(graph_builder, mul);299 auto sum = BuildPatternReduceSum(graph_builder, mul);
@@ -302,7 +322,7 @@ PatternUniqPtr MakePatternSoftmaxGradExtV2(const std::string& pass_name, int32_t
302 322 
303 auto graph = graph_builder.BuildAndReset({mul_grad});323 auto graph = graph_builder.BuildAndReset({mul_grad});
304 auto pattern = std::make_unique<Pattern>(std::move(*graph));324 auto pattern = std::make_unique<Pattern>(std::move(*graph));
305- pattern->CaptureTensor({*sum.GetProducer(), 0});325+ pattern->CaptureTensor({*sum.GetProducer(), kNodeOutputIdx});
306 return pattern;326 return pattern;
307}327}
308 328 
@@ -322,12 +342,13 @@ GraphUniqPtr SoftmaxGradExtReplacementCommon(const std::unique_ptr<MatchResult>&
322 342 
323 std::vector<SubgraphInput> subgraph_inputs;343 std::vector<SubgraphInput> subgraph_inputs;
324 match_result->ToSubgraphBoundary()->GetAllInputs(subgraph_inputs);344 match_result->ToSubgraphBoundary()->GetAllInputs(subgraph_inputs);
325- OP_LOGE_IF(subgraph_inputs.size() < 3UL, nullptr, pass_name.c_str(), "Subgraph inputs size %zu is less than 3.",345+ OP_LOGE_IF(subgraph_inputs.size() < kMinSubgraphInputCount, nullptr, pass_name.c_str(),
326- subgraph_inputs.size());346+ "Subgraph inputs size %zu is less than %zu.", subgraph_inputs.size(), kMinSubgraphInputCount);
327 347 
328 auto graph_builder = es::EsGraphBuilder("replacement");348 auto graph_builder = es::EsGraphBuilder("replacement");
329 auto replacement_inputs = CreateReplacementInputs(graph_builder, subgraph_inputs);349 auto replacement_inputs = CreateReplacementInputs(graph_builder, subgraph_inputs);
330- OP_LOGE_IF(replacement_inputs.size() < 3UL, nullptr, pass_name.c_str(), "Create replacement inputs failed.");350+ OP_LOGE_IF(replacement_inputs.size() < kMinSubgraphInputCount, nullptr, pass_name.c_str(),
351+ "Create replacement inputs failed.");
331 352 
332 // SoftmaxGradExt(grad, x1, x2): grad=input0, x1=input1, x2=input2.353 // SoftmaxGradExt(grad, x1, x2): grad=input0, x1=input1, x2=input2.
333 auto softmax_grad_ext = es::SoftmaxGradExt(replacement_inputs[kSubgraphInputGrad],354 auto softmax_grad_ext = es::SoftmaxGradExt(replacement_inputs[kSubgraphInputGrad],
@@ -376,7 +397,7 @@ std::vector<PatternUniqPtr> SoftmaxGradExtV2FusionPass::Patterns()
376{397{
377 OPS_LOG_D(kPassNameV2.c_str(), "Enter Patterns for SoftmaxGradExtV2FusionPass.");398 OPS_LOG_D(kPassNameV2.c_str(), "Enter Patterns for SoftmaxGradExtV2FusionPass.");
378 std::vector<PatternUniqPtr> patterns;399 std::vector<PatternUniqPtr> patterns;
379- for (int32_t i = 0; i < 4; ++i) {400+ for (int32_t i = 0; i < kPatternV2VariantCount; ++i) {
380 patterns.emplace_back(MakePatternSoftmaxGradExtV2(kPassNameV2, i));401 patterns.emplace_back(MakePatternSoftmaxGradExtV2(kPassNameV2, i));
381 }402 }
382 return patterns;403 return patterns;
Mclassify_rule.yaml+45-88
@@ -594,36 +594,16 @@ activation-c@ops-nn:
594 test_code:594 test_code:
595 - ops/ops-nn/activation/celu_v2/tests/595 - ops/ops-nn/activation/celu_v2/tests/
596 - ops/ops-nn/activation/celu_v2/examples/596 - ops/ops-nn/activation/celu_v2/examples/
597- - ops/ops-nn/activation/elu/tests/
598- - ops/ops-nn/activation/elu/examples/
599- - ops/ops-nn/activation/elu_grad_v2/tests/
600- - ops/ops-nn/activation/elu_grad_v2/examples/
601 - ops/ops-nn/activation/erfinv/tests/597 - ops/ops-nn/activation/erfinv/tests/
602 - ops/ops-nn/activation/erfinv/examples/598 - ops/ops-nn/activation/erfinv/examples/
603- - ops/ops-nn/activation/fast_gelu/examples/
604- - ops/ops-nn/activation/fast_gelu_grad/examples/
605 - ops/ops-nn/activation/fatrelu_mul/tests/599 - ops/ops-nn/activation/fatrelu_mul/tests/
606 - ops/ops-nn/activation/fatrelu_mul/examples/600 - ops/ops-nn/activation/fatrelu_mul/examples/
607 - ops/ops-nn/activation/clipped_swiglu/tests/601 - ops/ops-nn/activation/clipped_swiglu/tests/
608 - ops/ops-nn/activation/clipped_swiglu/examples/602 - ops/ops-nn/activation/clipped_swiglu/examples/
609 - ops/ops-nn/activation/clipped_swiglu_grad/tests/603 - ops/ops-nn/activation/clipped_swiglu_grad/tests/
610 - ops/ops-nn/activation/clipped_swiglu_grad/examples/604 - ops/ops-nn/activation/clipped_swiglu_grad/examples/
611- - ops/ops-nn/activation/ge_glu_grad_v2/tests/
612- - ops/ops-nn/activation/ge_glu_grad_v2/examples/
613- - ops/ops-nn/activation/ge_glu_v2/tests/
614- - ops/ops-nn/activation/ge_glu_v2/examples/
615- - ops/ops-nn/activation/gelu/tests/
616- - ops/ops-nn/activation/gelu/examples/
617- - ops/ops-nn/activation/gelu_grad/tests/
618- - ops/ops-nn/activation/gelu_grad/examples/
619- - ops/ops-nn/activation/gelu_grad_v2/tests/
620- - ops/ops-nn/activation/gelu_grad_v2/examples/
621 - ops/ops-nn/activation/gelu_mul/tests/605 - ops/ops-nn/activation/gelu_mul/tests/
622 - ops/ops-nn/activation/gelu_mul/examples/606 - ops/ops-nn/activation/gelu_mul/examples/
623- - ops/ops-nn/activation/gelu_quant/tests/
624- - ops/ops-nn/activation/gelu_quant/examples/
625- - ops/ops-nn/activation/gelu_v2/tests/
626- - ops/ops-nn/activation/gelu_v2/examples/
627 - ops/ops-nn/activation/glu/examples/607 - ops/ops-nn/activation/glu/examples/
628 - ops/ops-nn/activation/glu/tests/608 - ops/ops-nn/activation/glu/tests/
629 - ops/ops-nn/activation/hard_shrink/tests/609 - ops/ops-nn/activation/hard_shrink/tests/
@@ -640,14 +620,8 @@ activation-c@ops-nn:
640 - ops/ops-nn/activation/hard_swish_grad/examples/620 - ops/ops-nn/activation/hard_swish_grad/examples/
641 - ops/ops-nn/activation/hard_swish_grad_v2/tests/621 - ops/ops-nn/activation/hard_swish_grad_v2/tests/
642 - ops/ops-nn/activation/hard_swish_grad_v2/examples/622 - ops/ops-nn/activation/hard_swish_grad_v2/examples/
643- - ops/ops-nn/activation/hardtanh_grad/tests/
644- - ops/ops-nn/activation/hardtanh_grad/examples/
645 - ops/ops-nn/activation/heaviside/tests/623 - ops/ops-nn/activation/heaviside/tests/
646 - ops/ops-nn/activation/heaviside/examples/624 - ops/ops-nn/activation/heaviside/examples/
647- - ops/ops-nn/activation/leaky_relu/tests/
648- - ops/ops-nn/activation/leaky_relu/examples/
649- - ops/ops-nn/activation/leaky_relu_grad/tests/
650- - ops/ops-nn/activation/leaky_relu_grad/examples/
651 - ops/ops-nn/activation/log_sigmoid/tests/625 - ops/ops-nn/activation/log_sigmoid/tests/
652 - ops/ops-nn/activation/log_sigmoid/examples/626 - ops/ops-nn/activation/log_sigmoid/examples/
653 - ops/ops-nn/activation/logsigmoid_grad/tests/627 - ops/ops-nn/activation/logsigmoid_grad/tests/
@@ -660,14 +634,8 @@ activation-c@ops-nn:
660 - ops/ops-nn/activation/mish/examples/634 - ops/ops-nn/activation/mish/examples/
661 - ops/ops-nn/activation/mish_grad/tests/635 - ops/ops-nn/activation/mish_grad/tests/
662 - ops/ops-nn/activation/mish_grad/examples/636 - ops/ops-nn/activation/mish_grad/examples/
663- - ops/ops-nn/activation/p_relu/tests/
664- - ops/ops-nn/activation/p_relu/examples/
665 - ops/ops-nn/activation/prelu_grad_update/tests/637 - ops/ops-nn/activation/prelu_grad_update/tests/
666 - ops/ops-nn/activation/prelu_grad_update/examples/638 - ops/ops-nn/activation/prelu_grad_update/examples/
667- - ops/ops-nn/activation/relu/tests/
668- - ops/ops-nn/activation/relu/examples/
669- - ops/ops-nn/activation/relu_grad/tests/
670- - ops/ops-nn/activation/relu_grad/examples/
671 - ops/ops-nn/activation/relu_grad_v2/tests/639 - ops/ops-nn/activation/relu_grad_v2/tests/
672 - ops/ops-nn/activation/relu_grad_v2/examples/640 - ops/ops-nn/activation/relu_grad_v2/examples/
673 - ops/ops-nn/activation/selu/tests/641 - ops/ops-nn/activation/selu/tests/
@@ -676,12 +644,6 @@ activation-c@ops-nn:
676 - ops/ops-nn/activation/selu_grad/examples/644 - ops/ops-nn/activation/selu_grad/examples/
677 - ops/ops-nn/activation/shrink/tests/645 - ops/ops-nn/activation/shrink/tests/
678 - ops/ops-nn/activation/shrink/examples/646 - ops/ops-nn/activation/shrink/examples/
679- - ops/ops-nn/activation/sigmoid/tests/
680- - ops/ops-nn/activation/sigmoid/examples/
681- - ops/ops-nn/activation/sigmoid_grad/tests/
682- - ops/ops-nn/activation/sigmoid_grad/examples/
683- - ops/ops-nn/activation/silu_grad/tests/
684- - ops/ops-nn/activation/silu_grad/examples/
685 - ops/ops-nn/activation/situ_glu/tests/647 - ops/ops-nn/activation/situ_glu/tests/
686 - ops/ops-nn/activation/situ_glu/examples/648 - ops/ops-nn/activation/situ_glu/examples/
687 - ops/ops-nn/activation/situ_glu_grad/tests/649 - ops/ops-nn/activation/situ_glu_grad/tests/
@@ -704,12 +666,6 @@ activation-c@ops-nn:
704 - ops/ops-nn/activation/squared_relu/examples/666 - ops/ops-nn/activation/squared_relu/examples/
705 - ops/ops-nn/activation/swi_glu/tests/667 - ops/ops-nn/activation/swi_glu/tests/
706 - ops/ops-nn/activation/swi_glu/examples/668 - ops/ops-nn/activation/swi_glu/examples/
707- - ops/ops-nn/activation/swi_glu_grad/tests/
708- - ops/ops-nn/activation/swi_glu_grad/examples/
709- - ops/ops-nn/activation/swish/tests/
710- - ops/ops-nn/activation/swish/examples/
711- - ops/ops-nn/activation/swish_grad/tests/
712- - ops/ops-nn/activation/swish_grad/examples/
713 - ops/ops-nn/activation/swiglu_group_quant/tests/669 - ops/ops-nn/activation/swiglu_group_quant/tests/
714 - ops/ops-nn/activation/swiglu_group_quant/examples/670 - ops/ops-nn/activation/swiglu_group_quant/examples/
715 - ops/ops-nn/activation/threshold/tests/671 - ops/ops-nn/activation/threshold/tests/
@@ -2115,55 +2071,56 @@ VC1@ops-nn:
2115 kernel_style: null2071 kernel_style: null
2116 unrelease:2072 unrelease:
2117 test_code:2073 test_code:
2118- #- ops/ops-nn/activation/elu/examples/2074+ - ops/ops-nn/activation/elu/examples/
2119- #- ops/ops-nn/activation/elu/tests/2075+ - ops/ops-nn/activation/elu/tests/
2120 - ops/ops-nn/activation/elu_grad/examples/2076 - ops/ops-nn/activation/elu_grad/examples/
2121 - ops/ops-nn/activation/elu_grad/tests/2077 - ops/ops-nn/activation/elu_grad/tests/
2122- #- ops/ops-nn/activation/elu_grad_v2/examples/2078+ - ops/ops-nn/activation/elu_grad_v2/examples/
2123- #- ops/ops-nn/activation/elu_grad_v2/tests/2079+ - ops/ops-nn/activation/elu_grad_v2/tests/
2124- #- ops/ops-nn/activation/fast_gelu/examples/2080+ - ops/ops-nn/activation/fast_gelu/examples/
2125- #- ops/ops-nn/activation/fast_gelu/tests/2081+ - ops/ops-nn/activation/fast_gelu/tests/
2126- #- ops/ops-nn/activation/fast_gelu_grad/examples/2082+ - ops/ops-nn/activation/fast_gelu_grad/examples/
2127 - ops/ops-nn/activation/fast_gelu_grad/tests/2083 - ops/ops-nn/activation/fast_gelu_grad/tests/
2128- #- ops/ops-nn/activation/ge_glu_grad_v2/examples/2084+ - ops/ops-nn/activation/ge_glu_grad_v2/examples/
2129- #- ops/ops-nn/activation/ge_glu_grad_v2/tests/2085+ - ops/ops-nn/activation/ge_glu_grad_v2/tests/
2130- #- ops/ops-nn/activation/ge_glu_v2/examples/2086+ - ops/ops-nn/activation/ge_glu_v2/examples/
2131- #- ops/ops-nn/activation/ge_glu_v2/tests/2087+ - ops/ops-nn/activation/ge_glu_v2/tests/
2132- #- ops/ops-nn/activation/gelu/examples/2088+ - ops/ops-nn/activation/gelu/examples/
2133- #- ops/ops-nn/activation/gelu/tests/2089+ - ops/ops-nn/activation/gelu/tests/
2134- #- ops/ops-nn/activation/gelu_grad/examples/2090+ - ops/ops-nn/activation/gelu_grad/examples/
2135- #- ops/ops-nn/activation/gelu_grad/tests/2091+ - ops/ops-nn/activation/gelu_grad/tests/
2136- #- ops/ops-nn/activation/gelu_grad_v2/examples/2092+ - ops/ops-nn/activation/gelu_grad_v2/examples/
2137- #- ops/ops-nn/activation/gelu_grad_v2/tests/2093+ - ops/ops-nn/activation/gelu_grad_v2/tests/
2138- #- ops/ops-nn/activation/gelu_quant/examples/2094+ - ops/ops-nn/activation/gelu_quant/examples/
2139- #- ops/ops-nn/activation/gelu_quant/tests/2095+ - ops/ops-nn/activation/gelu_quant/tests/
2140- #- ops/ops-nn/activation/gelu_v2/examples/2096+ - ops/ops-nn/activation/gelu_v2/examples/
2141- #- ops/ops-nn/activation/gelu_v2/tests/2097+ - ops/ops-nn/activation/gelu_v2/tests/
2142- #- ops/ops-nn/activation/hardtanh_grad/examples/2098+ - ops/ops-nn/activation/hardtanh_grad/examples/
2143- #- ops/ops-nn/activation/hardtanh_grad/tests/2099+ - ops/ops-nn/activation/hardtanh_grad/tests/
2144- #- ops/ops-nn/activation/leaky_relu/examples/2100+ - ops/ops-nn/activation/leaky_relu/examples/
2145- #- ops/ops-nn/activation/leaky_relu/tests/2101+ - ops/ops-nn/activation/leaky_relu/tests/
2146- #- ops/ops-nn/activation/leaky_relu_grad/examples/2102+ - ops/ops-nn/activation/leaky_relu_grad/examples/
2147- #- ops/ops-nn/activation/leaky_relu_grad/tests/2103+ - ops/ops-nn/activation/leaky_relu_grad/tests/
2148- #- ops/ops-nn/activation/prelu/examples/2104+ - ops/ops-nn/activation/p_relu/examples/
2149- #- ops/ops-nn/activation/prelu/tests/2105+ - ops/ops-nn/activation/p_relu/tests/
2150- #- ops/ops-nn/activation/relu/examples/2106+ - ops/ops-nn/activation/relu/examples/
2151- #- ops/ops-nn/activation/relu/tests/2107+ - ops/ops-nn/activation/relu/tests/
2108+ - ops/ops-nn/activation/relu_grad/examples/
2109+ - ops/ops-nn/activation/relu_grad/tests/
2152 - ops/ops-nn/activation/relu_v2/examples/2110 - ops/ops-nn/activation/relu_v2/examples/
2153 - ops/ops-nn/activation/relu_v2/tests/2111 - ops/ops-nn/activation/relu_v2/tests/
2154- #- ops/ops-nn/activation/sigmoid/examples/2112+ - ops/ops-nn/activation/sigmoid/examples/
2155- #- ops/ops-nn/activation/sigmoid/tests/2113+ - ops/ops-nn/activation/sigmoid/tests/
2156- #- ops/ops-nn/activation/sigmoid_grad/examples/2114+ - ops/ops-nn/activation/sigmoid_grad/examples/
2157- #- ops/ops-nn/activation/sigmoid_grad/tests/2115+ - ops/ops-nn/activation/sigmoid_grad/tests/
2158- #- ops/ops-nn/activation/silu_grad/examples/2116+ - ops/ops-nn/activation/silu_grad/examples/
2159- #- ops/ops-nn/activation/silu_grad/tests/2117+ - ops/ops-nn/activation/silu_grad/tests/
2160- #- ops/ops-nn/activation/swi_glu_grad/examples/2118+ - ops/ops-nn/activation/swi_glu_grad/examples/
2161- #- ops/ops-nn/activation/swi_glu_grad/tests/2119+ - ops/ops-nn/activation/swi_glu_grad/tests/
2162- #- ops/ops-nn/activation/swish/examples/2120+ - ops/ops-nn/activation/swish/examples/
2163- #- ops/ops-nn/activation/swish/tests/2121+ - ops/ops-nn/activation/swish/tests/
2164- #- ops/ops-nn/activation/swish_grad/examples/2122+ - ops/ops-nn/activation/swish_grad/examples/
2165- #- ops/ops-nn/activation/swish_grad/tests/2123+ - ops/ops-nn/activation/swish_grad/tests/
2166- - ops/ops-nn/quant/ascend_quant/examples/
2167 - ops/ops-nn/quant/ascend_quant/tests/2124 - ops/ops-nn/quant/ascend_quant/tests/
2168 - ops/ops-nn/quant/ascend_quant_v2/examples/2125 - ops/ops-nn/quant/ascend_quant_v2/examples/
2169 - ops/ops-nn/quant/ascend_quant_v2/tests/2126 - ops/ops-nn/quant/ascend_quant_v2/tests/
Mindex/quant_update_scatter/op_host/quant_update_scatter_def.cpp+46-63文件内容审核中，请稍后刷新重试
Mquant/dynamic_block_quant/op_host/dynamic_block_quant_tiling.cpp+4-1
@@ -670,7 +670,10 @@ ge::graphStatus Tiling4DynamicBlockQuant(gert::TilingContext* context)
670 return ge::GRAPH_SUCCESS;670 return ge::GRAPH_SUCCESS;
671}671}
672 672 
673-ge::graphStatus TilingPrepare4DynamicBlockQuant(gert::TilingParseContext* context) { return ge::GRAPH_SUCCESS; }673+ge::graphStatus TilingPrepare4DynamicBlockQuant([[maybe_unused]] gert::TilingParseContext* context)
674+{
675+ return ge::GRAPH_SUCCESS;
676+}
674 677 
675// register tiling interface of the DynamicBlockQuant op.678// register tiling interface of the DynamicBlockQuant op.
676IMPL_OP_OPTILING(DynamicBlockQuant)679IMPL_OP_OPTILING(DynamicBlockQuant)
Mquant/dynamic_mx_quant/op_host/arch35/dynamic_mx_quant_tiling_arch35.cpp+4-1
@@ -754,7 +754,10 @@ ge::graphStatus Tiling4DynamicMxQuant(gert::TilingContext* context)
754 return ge::GRAPH_SUCCESS;754 return ge::GRAPH_SUCCESS;
755}755}
756 756 
757-ge::graphStatus TilingPrepare4DynamicMxQuant(gert::TilingParseContext* context) { return ge::GRAPH_SUCCESS; }757+ge::graphStatus TilingPrepare4DynamicMxQuant([[maybe_unused]] gert::TilingParseContext* context)
758+{
759+ return ge::GRAPH_SUCCESS;
760+}
758 761 
759// register tiling interface of the DynamicMxQuant op.762// register tiling interface of the DynamicMxQuant op.
760IMPL_OP_OPTILING(DynamicMxQuant)763IMPL_OP_OPTILING(DynamicMxQuant)