change skip-layernorm to adapt a new method (#52456)

* change skip-layernorm to adapt a new method

* fix review problem and add vlog

* fix review problem

paddle/fluid/framework/ir/trt_skip_layernorm_fuse_pass.cc

@@ -181,6 +181,11 @@ void TrtSkipLayerNormFusePass::ApplyImpl(ir::Graph *graph) const {
                        layer_norm->Op()->GetAttr("out_threshold"));
     }
 
+    if (layer_norm->Op()->HasAttr("smooth_scale")) {
+      new_desc.SetAttr("smooth_scale",
+                       layer_norm->Op()->GetAttr("smooth_scale"));
+    }
+
     // outputs
     new_desc.SetOutput("Out", {layer_norm_out->Name()});
 

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

@@ -50,6 +50,15 @@ class SkipLayerNormOpConverter : public OpConverter {
     if (op_desc.HasAttr("enable_int8")) {
       enable_int8 = PADDLE_GET_CONST(bool, op_desc.GetAttr("enable_int8"));
     }
+
+    std::vector<float> smooth_scale;
+    bool use_smooth = false;
+    if (op_desc.HasAttr("smooth_scale")) {
+      smooth_scale =
+          PADDLE_GET_CONST(std::vector<float>, op_desc.GetAttr("smooth_scale"));
+      use_smooth = true;
+    }
+
     auto bias_weight = GetWeight("Bias").get();
     auto scale_weight = GetWeight("Scale").get();
     nvinfer1::ILayer* layer = nullptr;
@@ -121,7 +130,7 @@ class SkipLayerNormOpConverter : public OpConverter {
                             "in CustomSkipLayerNormPluginDynamic hidden "
                             "dimension should > 0"));
 
-      const std::vector<nvinfer1::PluginField> fields{
+      std::vector<nvinfer1::PluginField> fields{
           {"type_id", &type, nvinfer1::PluginFieldType::kINT32, 1},
           {"ld", &hidden_size, nvinfer1::PluginFieldType::kINT32, 1},
           {"beta",
@@ -133,6 +142,15 @@ class SkipLayerNormOpConverter : public OpConverter {
            GetPluginFieldType(scale_weight.type),
            static_cast<int32_t>(scale_weight.count)},
       };
+
+      if (use_smooth) {
+        VLOG(4) << "using special method, make sure you have correct version "
+                   "of tensorrt";
+        type = static_cast<int32_t>(nvinfer1::DataType::kINT8);
+        fields.push_back({"smooth_scale",
+                          smooth_scale.data(),
+                          nvinfer1::PluginFieldType::kFLOAT32,
+                          static_cast<int32_t>(smooth_scale.size())});
         nvinfer1::PluginFieldCollection* pluginPtr =
             static_cast<nvinfer1::PluginFieldCollection*>(
                 malloc(sizeof(nvinfer1::PluginFieldCollection) +
@@ -141,8 +159,32 @@ class SkipLayerNormOpConverter : public OpConverter {
         pluginPtr->nbFields = static_cast<int32_t>(fields.size());
         pluginPtr->fields = fields.data();
 
-      auto pluginObj =
-          creator->createPlugin("CustomSkipLayerNormPluginDynamic", pluginPtr);
+        auto pluginObj = creator->createPlugin(
+            "CustomSkipLayerNormPluginDynamicWithSmooth", pluginPtr);
+
+        free(pluginPtr);
+
+        auto plugin_layer = engine_->network()->addPluginV2(
+            inputs.data(), inputs.size(), *pluginObj);
+
+        PADDLE_ENFORCE_NE(
+            plugin_layer,
+            nullptr,
+            platform::errors::InvalidArgument(
+                "fail to add CustomSkipLayerNormPluginDynamicWithSmooth "
+                "layer"));
+        layer = plugin_layer;
+      } else {
+        nvinfer1::PluginFieldCollection* pluginPtr =
+            static_cast<nvinfer1::PluginFieldCollection*>(
+                malloc(sizeof(nvinfer1::PluginFieldCollection) +
+                       fields.size() *
+                           sizeof(nvinfer1::PluginField)));  // remember to free
+        pluginPtr->nbFields = static_cast<int32_t>(fields.size());
+        pluginPtr->fields = fields.data();
+
+        auto pluginObj = creator->createPlugin(
+            "CustomSkipLayerNormPluginDynamic", pluginPtr);
 
         free(pluginPtr);
 
@@ -156,6 +198,7 @@ class SkipLayerNormOpConverter : public OpConverter {
                 "fail to add CustomSkipLayerNormPluginDynamic layer"));
         layer = plugin_layer;
       }
+    }
     auto output_name = op_desc.Output("Out")[0];
     RreplenishLayerAndOutput(layer, "skip_layernorm", {output_name}, test_mode);
   }