[buaa]【Error Message No.32 No.33】rewrite error message (#66957)

crazyxiaoxi · web-flow · commit c8f5017f3f59 · 2024-08-09T14:47:56.000+08:00
* first try

fix

fix

* phi

* fix

* fix equal

* fix equal

* unchase test_custom_op_plugin.h

* Update test_custom_op_plugin.h
diff --git a/paddle/fluid/framework/hogwild_worker.cc b/paddle/fluid/framework/hogwild_worker.cc
@@ -991,7 +991,10 @@ void HogwildWorker::CreateThreadScope(const ProgramDesc &program) {
       ++persist_total;
       if (stat_var_name_map_.find(name) != stat_var_name_map_.end()) {
         Variable *root_var = root_scope_->FindVar(name);
-        CHECK(root_var != nullptr);
+        PADDLE_ENFORCE_NOT_NULL(
+            root_var,
+            common::errors::NotFound("Root scope should contain variable."));
+
         auto root_tensor = root_var->Get<phi::DenseTensor>();
         if (root_tensor.place() == place_) {
           continue;
@@ -1060,12 +1063,18 @@ void HogwildWorker::CreateThreadScope(const ProgramDesc &program) {
                            holder->ptr(),
                            holder->size(),
                            stream);
-              CHECK(phi::is_gpu_place(root_tensor->place()));
+              PADDLE_ENFORCE_EQ(phi::is_gpu_place(root_tensor->place()),
+                                true,
+                                common::errors::InvalidArgument(
+                                    "The place of root tensor should be GPU."));
               ++persist_reset;
             }
           } else {
             auto *ptr = thread_scope_->Var(name);
-            CHECK(proto::VarType::LOD_TENSOR == var->GetType());
+            PADDLE_ENFORCE_EQ(proto::VarType::LOD_TENSOR,
+                              var->GetType(),
+                              common::errors::InvalidArgument(
+                                  "The type of var should be LOD_TENSOR."));
             InitializeVariable(ptr, var->GetType());
             phi::DenseTensor *thread_tensor =
                 ptr->GetMutable<phi::DenseTensor>();
diff --git a/paddle/fluid/inference/analysis/dot.h b/paddle/fluid/inference/analysis/dot.h
@@ -67,7 +67,10 @@ class Dot {
 
     std::string repr() const {
       std::stringstream ss;
-      CHECK(!name.empty());
+      PADDLE_ENFORCE_EQ(
+          !name.empty(),
+          true,
+          common::errors::InvalidArgument("Sorry,but name is empty"));
       ss << id_;
       if (attrs.empty()) {
         ss << "[label=" << '"' << name << '"' << "]";
@@ -99,8 +102,14 @@ class Dot {
 
     std::string repr() const {
       std::stringstream ss;
-      CHECK(!source.empty());
-      CHECK(!target.empty());
+      PADDLE_ENFORCE_EQ(
+          !source.empty(),
+          true,
+          common::errors::InvalidArgument("Sorry,but source is empty"));
+      PADDLE_ENFORCE_EQ(
+          !target.empty(),
+          true,
+          common::errors::InvalidArgument("Sorry,but target is empty"));
       ss << source << "->" << target;
       for (size_t i = 0; i < attrs.size(); i++) {
         if (i == 0) {
@@ -121,7 +130,10 @@ class Dot {
                const std::vector<Attr>& attrs,
                std::string label = "",
                bool use_local_id = false) {
-    CHECK(!nodes_.count(id)) << "duplicate Node '" << id << "'";
+    PADDLE_ENFORCE_EQ(
+        !nodes_.count(id),
+        true,
+        common::errors::InvalidArgument("Sorry,but duplicate Node"));
     if (label.empty()) label = id;
     if (use_local_id) {
       nodes_.emplace(id, Node{label, attrs, local_node_counter_++});
@@ -133,8 +145,14 @@ class Dot {
   void AddEdge(const std::string& source,
                const std::string& target,
                const std::vector<Attr>& attrs) {
-    CHECK(!source.empty());
-    CHECK(!target.empty());
+    PADDLE_ENFORCE_EQ(
+        !source.empty(),
+        true,
+        common::errors::InvalidArgument("Sorry,but source is empty"));
+    PADDLE_ENFORCE_EQ(
+        !target.empty(),
+        true,
+        common::errors::InvalidArgument("Sorry,but target is empty"));
     auto sid = nodes_.at(source).id();
     auto tid = nodes_.at(target).id();
     edges_.emplace_back(sid, tid, attrs);
diff --git a/paddle/fluid/inference/api/demo_ci/custom_pass_demo.cc b/paddle/fluid/inference/api/demo_ci/custom_pass_demo.cc
@@ -60,10 +60,18 @@ std::vector<float> GetOutputData(const std::shared_ptr<Predictor> &predictor) {
     input_tensor.set_name(input_name);
     inputs.emplace_back(std::move(input_tensor));
   }
-  CHECK(predictor->Run(inputs, &outputs));
-
-  CHECK(outputs[0].place() == paddle::GPUPlace{});
-  CHECK(outputs[0].dtype() == paddle::DataType::FLOAT32);
+  PADDLE_ENFORCE_EQ(
+      predictor->Run(inputs, &outputs),
+      true,
+      common::errors::ExecutionTimeout("Sorry, predictor run failed"));
+  PADDLE_ENFORCE_EQ(outputs[0].place(),
+                    paddle::GPUPlace{},
+                    common::errors::InvalidArgument(
+                        "Sorry, output tensor place is not GPUPlace"));
+  PADDLE_ENFORCE_EQ(outputs[0].dtype(),
+                    paddle::DataType::FLOAT32,
+                    common::errors::InvalidArgument(
+                        "Sorry, output tensor dtype is not FLOAT32"));
   auto output = outputs[0].copy_to(paddle::CPUPlace{}, true);
 
   std::vector<float> output_data;
@@ -92,7 +100,9 @@ int main(int argc, char **argv) {
   auto base_data = GetOutputData(InitPredictor(false));
   auto custom_data = GetOutputData(InitPredictor(true));
 
-  CHECK(AreEqual(base_data, custom_data, 1e-3));
-
+  PADDLE_ENFORCE_EQ(AreEqual(base_data, custom_data, 1e-3),
+                    true,
+                    common::errors::InvalidArgument(
+                        "Sorry, base_data and custom_data are not equal"));
   return 0;
 }
diff --git a/paddle/fluid/inference/tensorrt/convert/generic_and_custom_plugin_creater.cc b/paddle/fluid/inference/tensorrt/convert/generic_and_custom_plugin_creater.cc
@@ -55,7 +55,9 @@ class CustomPluginCreater : public OpConverter {
     }
     auto creator =
         GetPluginRegistry()->getPluginCreator(plugin_name.c_str(), "1");
-    CHECK(creator);
+    PADDLE_ENFORCE_NOT_NULL(creator,
+                            common::errors::PreconditionNotMet(
+                                "The op's plugin should be PluginV2."));
 
     // set attrs
     std::vector<nvinfer1::PluginField> plugin_datas;
@@ -132,7 +134,8 @@ class CustomPluginCreater : public OpConverter {
         plugin_data.type = nvinfer1::PluginFieldType::kINT32;
         plugin_data.length = ints_attrs.back().size();
       } else {
-        CHECK(false) << "UNKNOWN PluginFieldType.";
+        PADDLE_THROW(
+            common::errors::PreconditionNotMet("UNKNOWN PluginFieldType."));
       }
       plugin_datas.push_back(plugin_data);
     }
@@ -141,7 +144,8 @@ class CustomPluginCreater : public OpConverter {
                                               plugin_datas.data()};
 
     auto *plugin = creator->createPlugin(op_desc.Type().c_str(), &plugin_fc);
-    CHECK(plugin);
+    PADDLE_ENFORCE_NOT_NULL(
+        plugin, common::errors::NotFound("Sorry,create plugin failed."));
 
     if (engine_->with_dynamic_shape()) {
       layer =
@@ -153,8 +157,8 @@ class CustomPluginCreater : public OpConverter {
           inputs.data(), inputs.size(), (plugin::PluginTensorRT *)plugin);
     }
 
-    CHECK(layer);
-
+    PADDLE_ENFORCE_NOT_NULL(
+        layer, common::errors::NotFound("Sorry, add plugin layer failed."));
     // set outputs
     auto &op_output_names = OpMetaInfoHelper::GetOutputs(op_info);
     std::vector<std::string> output_names;
@@ -175,7 +179,9 @@ class GenericPluginCreater : public OpConverter {
     framework::OpDesc op_desc(op, nullptr);
     VLOG(3) << "convert " << op_desc.Type() << " op to generic plugin layer";
 
-    CHECK(block_);
+    PADDLE_ENFORCE_NOT_NULL(
+        block_,
+        common::errors::NotFound("The block is null, can not find the block."));
     const framework::BlockDesc block_desc(
         nullptr, const_cast<framework::proto::BlockDesc *>(block_));
 
@@ -261,8 +267,9 @@ class CustomGenericPluginCreater : public OpConverter {
 
     nvinfer1::ILayer *layer = nullptr;
     std::vector<nvinfer1::ITensor *> inputs;
-
-    CHECK(block_);
+    PADDLE_ENFORCE_NOT_NULL(
+        block_,
+        common::errors::NotFound("The block is null, can not find the block."));
     const framework::BlockDesc block_desc(
         nullptr, const_cast<framework::proto::BlockDesc *>(block_));
 
@@ -326,12 +333,12 @@ class CustomGenericPluginCreater : public OpConverter {
     }
 
     auto *plugin = new plugin::CustomGenericPlugin(op, in_out_info, with_fp16);
-    CHECK(plugin);
-
+    PADDLE_ENFORCE_NOT_NULL(
+        plugin, common::errors::NotFound("Sorry,create plugin failed."));
     layer = engine_->AddDynamicPlugin(
         inputs.data(), inputs.size(), (plugin::DynamicPluginTensorRT *)plugin);
-    CHECK(layer);
-
+    PADDLE_ENFORCE_NOT_NULL(
+        layer, common::errors::NotFound("Sorry,add plugin layer failed."));
     ReplenishLayerAndOutput(layer, op_desc.Type(), outputs, test_mode);
   }
 };
