已合并
【PR】: fix: 修复融合pass编译失败 #3787
hugo111创建于 6月30日
【PR】: fix: 修复融合pass编译失败 #3787
已合并
共 4 个文件变更+8-28
| @@ -191,7 +191,7 @@ GraphUniqPtr Replacement(const std::unique_ptr<MatchResult> &match_result) overr | |||
| 191 | } | 191 | } |
| 192 | ``` | 192 | ``` |
| 193 | 193 | ||
| 194 | -如果 pass 注册在 InferShape 后，replacement 中新建节点的 shape 信息需要自行处理。需要对 replacement 做 shape 推导时，可参考现有样例中对 `GeUtils::InferShape` 的使用。 | 194 | +如果 pass 注册在 InferShape 后，replacement 中新建节点的 shape 信息需要自行处理。需要对 replacement 做 shape 推导时，可参考现有样例中对 `InferShapeUtil::InferShape` 的使用。 |
| 195 | 195 | ||
| 196 | ## 6. CaptureTensor：读取 pattern 中的关键 Tensor | 196 | ## 6. CaptureTensor：读取 pattern 中的关键 Tensor |
| 197 | 197 | ||
| @@ -191,7 +191,7 @@ GraphUniqPtr Replacement(const std::unique_ptr<MatchResult> &match_result) overr | |||
| 191 | } | 191 | } |
| 192 | ``` | 192 | ``` |
| 193 | 193 | ||
| 194 | -If the pass is registered after InferShape, shape information for new nodes in the replacement needs to be handled manually. Refer to existing examples for using `GeUtils::InferShape` when shape inference is needed for replacement. | 194 | +If the pass is registered after InferShape, shape information for new nodes in the replacement needs to be handled manually. Refer to existing examples for using `InferShapeUtil::InferShape` when shape inference is needed for replacement. |
| 195 | 195 | ||
| 196 | ## 6. CaptureTensor: Read Key Tensors in Pattern | 196 | ## 6. CaptureTensor: Read Key Tensors in Pattern |
| 197 | 197 | ||
| @@ -100,24 +100,14 @@ class DecomposeGroupedConvToSplitedPass : public DecomposePass { | |||
| 100 | auto res = es::Concat(replacement_graph_builder.CreateScalar(1), convs, groups); | 100 | auto res = es::Concat(replacement_graph_builder.CreateScalar(1), convs, groups); |
| 101 | auto replace_graph = replacement_graph_builder.BuildAndReset({res}); | 101 | auto replace_graph = replacement_graph_builder.BuildAndReset({res}); |
| 102 | // 当前pass注册在after infershape阶段，需要自行保证替换部分的shape连续 | 102 | // 当前pass注册在after infershape阶段，需要自行保证替换部分的shape连续 |
| 103 | - if (!InferShape(matched_node, *replace_graph)) { | 103 | + // 使用 ge::fusion::InferShapeUtil 提供的 InferShape 接口做 shape/dtype 推导 |
| 104 | + // 该接口会自动从 matched_node 边界获取输入 tensor desc（shape/dtype/format） | ||
| 105 | + if (InferShapeUtil::InferShape(*replace_graph, matched_node) != SUCCESS) { | ||
| 106 | + std::cout << "InferShapeUtil::InferShape failed" << std::endl; | ||
| 104 | return nullptr; | 107 | return nullptr; |
| 105 | } | 108 | } |
| 106 | return replace_graph; | 109 | return replace_graph; |
| 107 | } | 110 | } |
| 108 | - | ||
| 109 | - private: | ||
| 110 | - // 因为pass会被重复执行，不建议使用私有成员 | ||
| 111 | - // 如果使用，需要保证pass对象的可重入性 | ||
| 112 | - bool InferShapeAndCheckSupport(const GNode &matched_node, const Graph &graph) { | ||
| 113 | - // 使用 ge::fusion::InferShapeUtil 提供的 InferShape 接口做 shape/dtype 推导 | ||
| 114 | - // 该接口会自动从 matched_node 边界获取输入 tensor desc（shape/dtype/format） | ||
| 115 | - if (InferShapeUtil::InferShape(graph, matched_node) != SUCCESS) { | ||
| 116 | - std::cout << "InferShapeUtil::InferShape failed" << std::endl; | ||
| 117 | - return false; | ||
| 118 | - } | ||
| 119 | - return true; | ||
| 120 | - } | ||
| 121 | }; | 111 | }; |
| 122 | 112 | ||
| 123 | REG_DECOMPOSE_PASS(DecomposeGroupedConvToSplitedPass, {"Conv2D"}).Stage(CustomPassStage::kAfterInferShape); | 113 | REG_DECOMPOSE_PASS(DecomposeGroupedConvToSplitedPass, {"Conv2D"}).Stage(CustomPassStage::kAfterInferShape); |
| @@ -13,7 +13,7 @@ | |||
| 13 | 13 | ||
| 14 | 14 | ||
| 15 | 15 | ||
| 16 | -#include "ge/ge_utils.h" | 16 | +#include "ge/fusion/infer_shape_util.h" |
| 17 | 17 | ||
| 18 | using namespace ge; | 18 | using namespace ge; |
| 19 | using namespace fusion; | 19 | using namespace fusion; |
| @@ -262,17 +262,7 @@ class BatchMatmulFlattenPass : public PatternFusionPass { | |||
| 262 | } | 262 | } |
| 263 | 263 | ||
| 264 | bool InferShapeAndCheckSupport(const GNode &matched_node, const Graph &graph) { | 264 | bool InferShapeAndCheckSupport(const GNode &matched_node, const Graph &graph) { |
| 265 | - std::vector<ge::Shape> input_shapes; | 265 | + if (InferShapeUtil::InferShape(graph, matched_node) != SUCCESS) { |
| 266 | - auto input_size = matched_node.GetInputsSize(); | ||
| 267 | - for (size_t i = 0; i < input_size; i++) { | ||
| 268 | - TensorDesc tensor_desc; | ||
| 269 | - if (matched_node.GetInputDesc(i, tensor_desc) != SUCCESS) { | ||
| 270 | - return false; | ||
| 271 | - } | ||
| 272 | - input_shapes.emplace_back(tensor_desc.GetShape()); | ||
| 273 | - } | ||
| 274 | - | ||
| 275 | - if (GeUtils::InferShape(graph, input_shapes) != SUCCESS) { | ||
| 276 | std::cout << "InferShape failed" << std::endl; | 266 | std::cout << "InferShape failed" << std::endl; |
| 277 | return false; | 267 | return false; |
| 278 | } | 268 | } |