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[Bug Fix] Improve error handling and compatibility in TensorRT engine tests #75948

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Merged
YuanRisheng merged 4 commits into from
Oct 22, 2025
Merged

[Bug Fix] Improve error handling and compatibility in TensorRT engine tests #75948

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7b10a49
[Bug Fix] Improve error handling and compatibility in TensorRT engine…
youge325 Oct 19, 2025
b2960fa
Merge branch 'PaddlePaddle:develop' into tensorrt
youge325 Oct 20, 2025
8dc79e9
Merge branch 'PaddlePaddle:develop' into tensorrt
youge325 Oct 21, 2025
d06e8ff
Merge branch 'PaddlePaddle:develop' into tensorrt
youge325 Oct 21, 2025
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93 changes: 82 additions & 11 deletions test/cpp/inference/tensorrt/test_tensorrt_engine_instruction.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -85,20 +85,79 @@ TEST(TensorRTEngineInstructionTest, test_tensorrt_engine_instruction) {
nvinfer1::DataType::kFLOAT, raw_bias, size);
auto *x = engine->DeclareInput(
"x", nvinfer1::DataType::kFLOAT, nvinfer1::Dims4{-1, 1, 1, 1});
auto *fc_layer = TRT_ENGINE_ADD_LAYER(
engine, FullyConnected, *x, size, weight.get(), bias.get());
PADDLE_ENFORCE_NOT_NULL(fc_layer,
common::errors::InvalidArgument(
"TRT fully connected layer building failed."));
auto *flatten_layer = engine->network()->addShuffle(*x);
PADDLE_ENFORCE_NOT_NULL(
flatten_layer,
common::errors::InvalidArgument(
"Unable to build the TensorRT shuffle layer for the input tensor "
"'x'. "
"This usually indicates the TensorRT network failed to allocate the "
"intermediate reshape layer."));
flatten_layer->setReshapeDimensions(nvinfer1::Dims2{-1, 1});

auto *weight_layer = TRT_ENGINE_ADD_LAYER(
engine, Constant, nvinfer1::Dims2{1, 1}, weight.get());
PADDLE_ENFORCE_NOT_NULL(
weight_layer,
common::errors::InvalidArgument("TensorRT failed to create the constant "
"layer for parameter 'weight'. "
"Please confirm the TensorRT builder "
"supports constant initialisation "
"for the provided weight shape."));

auto *bias_layer =
TRT_ENGINE_ADD_LAYER(engine, Constant, nvinfer1::Dims2{1, 1}, bias.get());
PADDLE_ENFORCE_NOT_NULL(
bias_layer,
common::errors::InvalidArgument(
"TensorRT failed to create the constant layer for parameter 'bias'. "
"Check whether the provided bias data matches the expected shape."));

auto *matmul_layer = TRT_ENGINE_ADD_LAYER(engine,
MatrixMultiply,
*flatten_layer->getOutput(0),
nvinfer1::MatrixOperation::kNONE,
*weight_layer->getOutput(0),
nvinfer1::MatrixOperation::kNONE);
PADDLE_ENFORCE_NOT_NULL(
matmul_layer,
common::errors::InvalidArgument(
"TensorRT returned a null matrix-multiply layer while fusing the "
"fully-connected op. Verify the network input ranks and TensorRT "
"version."));

auto *add_layer = TRT_ENGINE_ADD_LAYER(engine,
ElementWise,
*matmul_layer->getOutput(0),
*bias_layer->getOutput(0),
nvinfer1::ElementWiseOperation::kSUM);
PADDLE_ENFORCE_NOT_NULL(
add_layer,
common::errors::InvalidArgument(
"TensorRT could not construct the elementwise-add layer for bias "
"fusion. Ensure the bias tensor uses broadcastable dimensions."));

engine->DeclareOutput(fc_layer, 0, "y");
auto *reshape_layer = engine->network()->addShuffle(*add_layer->getOutput(0));
PADDLE_ENFORCE_NOT_NULL(
reshape_layer,
common::errors::InvalidArgument(
"TensorRT could not emit the final shuffle layer to restore the "
"output shape. Confirm the shape tensor and inferred dimensions are "
"valid."));
reshape_layer->setReshapeDimensions(nvinfer1::Dims4{-1, 1, 1, 1});

engine->DeclareOutput(reshape_layer, 0, "y");
std::vector<std::string> input_names = {"x", ""};
std::vector<std::string> output_names = {"y"};
std::vector<std::vector<int64_t>> outputs_shape = {{1}};
std::vector<phi::DataType> outputs_dtype = {phi::DataType::FLOAT32};
LOG(INFO) << "freeze network";
engine->FreezeNetwork();
#if IS_TRT_VERSION_GE(8600)
ASSERT_EQ(engine->engine()->getNbIOTensors(), 2);
#else
ASSERT_EQ(engine->engine()->getNbBindings(), 2);
#endif
nvinfer1::IHostMemory *serialized_engine_data = engine->Serialize();

std::ofstream outFile("engine_serialized_data.bin", std::ios::binary);
Expand Down Expand Up @@ -220,7 +279,10 @@ TEST(TensorRTEngineInstructionTest, test_tensorrt_engine_instruction_dynamic) {
layer->setInput(1, *shape);
PADDLE_ENFORCE_NOT_NULL(
layer,
common::errors::InvalidArgument("TRT shuffle layer building failed."));
common::errors::InvalidArgument(
"TensorRT failed to construct the dynamic shuffle layer that "
"consumes the runtime shape tensor. Please check the provided "
"shape binding."));
engine->DeclareOutput(layer, 0, "y");
engine->FreezeNetwork();

Expand Down Expand Up @@ -401,14 +463,19 @@ TEST(PluginTest, test_generic_plugin) {
creator->createPlugin("pir_generic_plugin", plugin_collection.get());
PADDLE_ENFORCE_NOT_NULL(
generic_plugin,
common::errors::InvalidArgument("TRT create generic plugin failed."));
common::errors::InvalidArgument(
"TensorRT plugin registry returned nullptr while creating "
"'pir_generic_plugin'. Verify the plugin has been registered before "
"building the engine."));
std::vector<nvinfer1::ITensor *> plugin_inputs;
plugin_inputs.emplace_back(x);
auto plugin_layer = engine->network()->addPluginV2(
plugin_inputs.data(), plugin_inputs.size(), *generic_plugin);
PADDLE_ENFORCE_NOT_NULL(plugin_layer,
common::errors::InvalidArgument(
"TRT generic plugin layer building failed."));
PADDLE_ENFORCE_NOT_NULL(
plugin_layer,
common::errors::InvalidArgument(
"TensorRT failed to add the generic plugin layer to the network. "
"Ensure the plugin inputs match the expected TensorRT types."));

engine->DeclareOutput(plugin_layer, 0, "y");
std::vector<std::string> input_names = {"x"};
Expand All @@ -417,7 +484,11 @@ TEST(PluginTest, test_generic_plugin) {
std::vector<phi::DataType> outputs_dtype = {phi::DataType::FLOAT32};
LOG(INFO) << "freeze network";
engine->FreezeNetwork();
#if IS_TRT_VERSION_GE(8600)
ASSERT_EQ(engine->engine()->getNbIOTensors(), 2);
#else
ASSERT_EQ(engine->engine()->getNbBindings(), 2);
#endif
nvinfer1::IHostMemory *serialized_engine_data = engine->Serialize();
std::ofstream outFile("engine_serialized_data.bin", std::ios::binary);
outFile.write(static_cast<const char *>(serialized_engine_data->data()),
Expand Down
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