add assert for GetOutput

Author: NHZlX

paddle/fluid/inference/tensorrt/convert/ut_helper.h

@@ -139,11 +139,11 @@ class TRTConvertValidation {
     cudaStreamSynchronize(*engine_->stream());
 
     ASSERT_FALSE(op_desc_->OutputArgumentNames().empty());
-    const size_t output_space_size = 200;
+    const size_t output_space_size = 2000;
     for (const auto& output : op_desc_->OutputArgumentNames()) {
       std::vector<float> fluid_out;
       std::vector<float> trt_out(output_space_size);
-      engine_->GetOutputInCPU(output, &trt_out[0]);
+      engine_->GetOutputInCPU(output, &trt_out[0], output_space_size);
       cudaStreamSynchronize(*engine_->stream());
 
       auto* var = scope_.FindVar(output);

paddle/fluid/inference/tensorrt/engine.cc

@@ -1,7 +1,7 @@
 /* Copyright (c) 2018 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.
+Licensed under the Apache License, Version 2.0 (the "License"); you may not use
+this file except in compliance with the License.
 You may obtain a copy of the License at
 
 http://www.apache.org/licenses/LICENSE-2.0
@@ -149,7 +149,8 @@ void *TensorRTEngine::GetOutputInGPU(const std::string &name) {
   return buffer(name).buffer;
 }
 
-void TensorRTEngine::GetOutputInGPU(const std::string &name, void *dst) {
+void TensorRTEngine::GetOutputInGPU(const std::string &name, void *dst,
+                                    size_t max_size) {
   // determine data size
   auto *output = TensorRTEngine::GetITensor(name);
   nvinfer1::Dims dims = output->getDimensions();
@@ -161,14 +162,16 @@ void TensorRTEngine::GetOutputInGPU(const std::string &name, void *dst) {
   PADDLE_ENFORCE(it != buffer_sizes_.end());
   PADDLE_ENFORCE_GT(it->second, 0);
   PADDLE_ENFORCE_LE(dst_size, it->second);
+  PADDLE_ENFORCE_GE(max_size, dst_size);
   auto &buf = buffer(name);
   PADDLE_ENFORCE_NOT_NULL(buf.buffer, "buffer should be allocated before");
   PADDLE_ENFORCE_EQ(cudaMemcpyAsync(dst, buf.buffer, dst_size,
                                     cudaMemcpyDeviceToDevice, *stream_),
                     0);
 }
 
-void TensorRTEngine::GetOutputInCPU(const std::string &name, void *dst) {
+void TensorRTEngine::GetOutputInCPU(const std::string &name, void *dst,
+                                    size_t max_size) {
   // determine data size
 
   auto *output = TensorRTEngine::GetITensor(name);
@@ -180,6 +183,7 @@ void TensorRTEngine::GetOutputInCPU(const std::string &name, void *dst) {
   PADDLE_ENFORCE(it != buffer_sizes_.end());
   PADDLE_ENFORCE_GT(it->second, 0);
   PADDLE_ENFORCE_LE(dst_size, it->second);
+  PADDLE_ENFORCE_GE(max_size, dst_size);
   auto &buf = buffer(name);
   PADDLE_ENFORCE_NOT_NULL(buf.buffer, "buffer should be allocated before");
   PADDLE_ENFORCE_EQ(0, cudaMemcpyAsync(dst, buf.buffer, dst_size,

paddle/fluid/inference/tensorrt/engine.h

@@ -106,10 +106,10 @@ class TensorRTEngine : public EngineBase {
   // Return the output's GPU memory address without copy.
   void* GetOutputInGPU(const std::string& name);
   // Copy data into dst inside the GPU device.
-  void GetOutputInGPU(const std::string& name, void* dst);
+  void GetOutputInGPU(const std::string& name, void* dst, size_t max_size);
   // LOW EFFICENCY! Get output to CPU, this will trigger a memory copy from GPU
   // to CPU.
-  void GetOutputInCPU(const std::string& name, void* dst);
+  void GetOutputInCPU(const std::string& name, void* dst, size_t max_size);
   // Fill an ITensor into map itensor_map_.
   void SetITensor(const std::string& name, nvinfer1::ITensor* tensor);
   // Get an ITensor called name.

paddle/fluid/inference/tensorrt/test_engine.cc

@@ -71,7 +71,7 @@ TEST_F(TensorRTEngineTest, add_layer) {
 
   LOG(INFO) << "to get output";
   float y_cpu;
-  engine_->GetOutputInCPU("y", &y_cpu);
+  engine_->GetOutputInCPU("y", &y_cpu, 1 * sizeof(float));
 
   LOG(INFO) << "to checkout output";
   ASSERT_EQ(y_cpu, x_v * 2 + 3);
@@ -108,7 +108,7 @@ TEST_F(TensorRTEngineTest, add_layer_multi_dim) {
   ASSERT_EQ(dims.nbDims, 3);
   ASSERT_EQ(dims.d[0], 2);
   ASSERT_EQ(dims.d[1], 1);
-  engine_->GetOutputInCPU("y", &y_cpu[0]);
+  engine_->GetOutputInCPU("y", &y_cpu[0], 2 * sizeof(float));
   ASSERT_EQ(y_cpu[0], 4.5);
   ASSERT_EQ(y_cpu[1], 14.5);
 }
@@ -141,7 +141,7 @@ TEST_F(TensorRTEngineTest, test_conv2d_temp) {
 
   LOG(INFO) << "to get output";
   float* y_cpu = new float[18];
-  engine_->GetOutputInCPU("y", &y_cpu[0]);
+  engine_->GetOutputInCPU("y", &y_cpu[0], 18 * sizeof(float));
   ASSERT_EQ(y_cpu[0], 4.0);
   ASSERT_EQ(y_cpu[1], 6.0);
 }

paddle/fluid/operators/tensorrt_engine_op.h

@@ -100,8 +100,11 @@ class TensorRTEngineKernel : public framework::OpKernel<T> {
       // tensor.
       // if (platform::is_cpu_place(fluid_t->place())) {
       // TODO(Superjomn) change this float to dtype size.
-      engine->GetOutputInCPU(
-          y, fluid_t->mutable_data<float>(platform::CPUPlace()));
+      auto size = inference::analysis::AccuDims(dims.d, dims.nbDims) *
+                  FLAGS_tensorrt_engine_batch_size;
+      engine->GetOutputInCPU(y,
+                             fluid_t->mutable_data<float>(platform::CPUPlace()),
+                             size * sizeof(float));
       //} else {
       // engine->GetOutputInGPU(
       // y, fluid_t->mutable_data<float>(platform::CUDAPlace()),