[Hackathon NO.75] 为 Paddle-TRT 添加 expend_as_v2 算子

paddle/fluid/inference/api/analysis_predictor.cc

@@ -2685,6 +2685,7 @@ USE_TRT_CONVERTER(tanh_shrink)
 USE_TRT_CONVERTER(logsigmoid)
 USE_TRT_CONVERTER(lookup_table)
 USE_TRT_CONVERTER(expand_v2)
+USE_TRT_CONVERTER(expand_as_v2)
 USE_TRT_CONVERTER(take_along_axis)
 USE_TRT_CONVERTER(skip_groupnorm_act)
 USE_TRT_CONVERTER(preln_groupnorm_act)

paddle/fluid/inference/tensorrt/convert/expand_v2_op.cc

@@ -1,4 +1,4 @@
-/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+/* Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -18,12 +18,12 @@ namespace paddle {
 namespace inference {
 namespace tensorrt {
 
-class ExpandV2OpConverter : public OpConverter {
+class ExpandOpConverter : public OpConverter {
  public:
   void operator()(const framework::proto::OpDesc& op,
                   const framework::Scope& scope,
                   bool test_mode) override {
-    VLOG(3) << "convert a expand_v2 op to trt expand layer.";
+    VLOG(3) << "convert a paddle " << op_type_ << " op to trt expand layer.";
     framework::OpDesc op_desc(op, nullptr);
     auto* input = engine_->GetITensor(op_desc.Input("X")[0]);
     auto inputs = op_desc.Inputs();
@@ -33,25 +33,40 @@ class ExpandV2OpConverter : public OpConverter {
 
     nvinfer1::ITensor* shape_tensor = nullptr;
     int32_t shape_rank = 0;
-    if (inputs.find("Shape") != inputs.end() &&
-        op_desc.Input("Shape").size() >= 1) {
-      shape_tensor = engine_->GetITensor(op_desc.Input("Shape")[0]);
-      shape_rank = shape_tensor->getDimensions().d[0];
-    } else if (inputs.find("expand_shapes_tensor") != inputs.end() &&
-               op_desc.Input("expand_shapes_tensor").size() >= 1) {
-      int shape_size = op_desc.Input("expand_shapes_tensor").size();
-      std::vector<nvinfer1::ITensor*> shape_tensors;
-      for (int i = 0; i < shape_size; ++i) {
-        shape_tensors.push_back(
-            engine_->GetITensor(op_desc.Input("expand_shapes_tensor")[i]));
+
+    if (op_type_ == "expand_v2") {
+      if (inputs.find("Shape") != inputs.end() &&
+          op_desc.Input("Shape").size() >= 1) {
+        shape_tensor = engine_->GetITensor(op_desc.Input("Shape")[0]);
+        shape_rank = shape_tensor->getDimensions().nbDims;
+      } else if (inputs.find("expand_shapes_tensor") != inputs.end() &&
+                 op_desc.Input("expand_shapes_tensor").size() >= 1) {
+        int shape_size = op_desc.Input("expand_shapes_tensor").size();
+        std::vector<nvinfer1::ITensor*> shape_tensors;
+        for (int i = 0; i < shape_size; ++i) {
+          shape_tensors.push_back(
+              engine_->GetITensor(op_desc.Input("expand_shapes_tensor")[i]));
+        }
+        shape_tensor = Concat(shape_tensors);
+        shape_rank = shape_size;
+      } else {
+        std::vector<int32_t> shape =
+            PADDLE_GET_CONST(std::vector<int32_t>, op_desc.GetAttr("shape"));
+        shape_tensor =
+            Add1DConstantLayer(shape, output_name + "_shape_tensor_");
+        shape_rank = shape.size();
+      }
+    } else if (op_type_ == "expand_as_v2") {
+      if (inputs.find("Y") != inputs.end()) {
+        shape_tensor = engine_->GetITensor(op_desc.Input("Y")[0]);
+        shape_rank = shape_tensor->getDimensions().nbDims;
+      } else {
+        std::vector<int32_t> shape = PADDLE_GET_CONST(
+            std::vector<int32_t>, op_desc.GetAttr("target_shape"));
+        shape_tensor =
+            Add1DConstantLayer(shape, output_name + "_target_shape_tensor_");
+        shape_rank = shape.size();
       }
-      shape_tensor = Concat(shape_tensors);
-      shape_rank = shape_size;
-    } else {
-      std::vector<int32_t> shape =
-          PADDLE_GET_CONST(std::vector<int32_t>, op_desc.GetAttr("shape"));
-      shape_tensor = Add1DConstantLayer(shape, output_name + "_shape_tensor_");
-      shape_rank = shape.size();
     }
 
     nvinfer1::ITensor* input_shape_tensor;
@@ -68,8 +83,7 @@ class ExpandV2OpConverter : public OpConverter {
       input_shape_tensor = Shape(input);
     }
 
-    auto* shuffle = TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *input);
-    shuffle->setInput(1, *input_shape_tensor);
+    auto* newInputTensor = Reshape(input, input_shape_tensor);
 
     std::vector<int32_t> start_vec(shape_rank, 0);
     nvinfer1::Dims start;
@@ -91,17 +105,31 @@ class ExpandV2OpConverter : public OpConverter {
     auto strides_tensor = Min(one_tensor, input_sub_tensor);
 
     auto layer = TRT_ENGINE_ADD_LAYER(
-        engine_, Slice, *shuffle->getOutput(0), start, size, stride);
+        engine_, Slice, *newInputTensor, start, size, stride);
     layer->setInput(1, *starts_tensor);
     layer->setInput(2, *sizes_tensor);
     layer->setInput(3, *strides_tensor);
 
-    RreplenishLayerAndOutput(layer, "expand_v2", {output_name}, test_mode);
+    RreplenishLayerAndOutput(layer, op_type_, {output_name}, test_mode);
   }
+
+ protected:
+  std::string op_type_;
+};
+
+class ExpandV2OpConverter : public ExpandOpConverter {
+ public:
+  ExpandV2OpConverter() { op_type_ = "expand_v2"; }
+};
+
+class ExpandAsV2OpConverter : public ExpandOpConverter {
+ public:
+  ExpandAsV2OpConverter() { op_type_ = "expand_as_v2"; }
 };
 
 }  // namespace tensorrt
 }  // namespace inference
 }  // namespace paddle
 
 REGISTER_TRT_OP_CONVERTER(expand_v2, ExpandV2OpConverter);
+REGISTER_TRT_OP_CONVERTER(expand_as_v2, ExpandAsV2OpConverter);

paddle/fluid/inference/tensorrt/op_teller.cc

@@ -2654,11 +2654,35 @@ struct SimpleOpTypeSetTeller : public Teller {
       }
     }
 
-    if (op_type == "expand_v2") {
+    if (op_type == "expand_as_v2" || op_type == "expand_v2") {
       if (!with_dynamic_shape) {
+        VLOG(3) << "the " << op_type
+                << "does not support "
+                   "static shape yet";
         return false;
       }
-      if (!desc.HasAttr("shape")) {
+
+      auto inputs = desc.Inputs();
+      if (op_type == "expand_as_v2") {
+        if (!desc.HasAttr("target_shape") && inputs.find("Y") == inputs.end()) {
+          VLOG(3)
+              << "expand_as_v2 op need have input(Y) or attr(target_shape). ";
+          return false;
+        }
+      } else if (op_type == "expand_v2") {
+        if (!desc.HasAttr("shape") && inputs.find("Shape") == inputs.end() &&
+            inputs.find("expand_shapes_tensor") == inputs.end()) {
+          VLOG(3) << "expand_v2 op need have input(Shape) or "
+                     "input(expand_shapes_tensor) or attr(shape) . ";
+          return false;
+        }
+      }
+
+      auto* block = desc.Block();
+      if (block == nullptr) {
+        VLOG(3) << "The block desc is nullptr, we can't continue to analyze. "
+                   "Developers need to check whether block_desc is passed in "
+                   "the pass.";
         return false;
       }
     }
@@ -2921,6 +2945,7 @@ struct SimpleOpTypeSetTeller : public Teller {
       "skip_merge_layernorm",
       "lookup_table_v2",
       "expand_v2",
+      "expand_as_v2",
       "fuse_eleadd_transpose",
       "skip_groupnorm_act",
       "preln_groupnorm_act",
@@ -3080,6 +3105,7 @@ struct SimpleOpTypeSetTeller : public Teller {
       "lookup_table",
       "lookup_table_v2",
       "expand_v2",
+      "expand_as_v2",
       "fuse_eleadd_transpose",
       "skip_groupnorm_act",
       "preln_groupnorm_act",