update

microsoft · Nov 5, 2023 · 93f9fbb · 93f9fbb
1 parent 9631f73
commit 93f9fbb
Showing 1 changed file with 4 additions and 4 deletions.
diff --git a/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.cc b/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.cc
@@ -3003,7 +3003,7 @@ Status TensorrtExecutionProvider::CreateNodeComputeFromOrtGraph(const GraphViewe
         engine_file.seekg(0, std::ios::beg);
         std::unique_ptr<char[]> engine_buf{new char[engine_size]};
         engine_file.read((char*)engine_buf.get(), engine_size);
-        trt_engine = std::unique_ptr<nvinfer1::ICudaEngine>(runtime_->deserializeCudaEngine(engine_buf.get(), engine_size, nullptr));
+        trt_engine = std::unique_ptr<nvinfer1::ICudaEngine>(runtime_->deserializeCudaEngine(engine_buf.get(), engine_size));
         LOGS_DEFAULT(VERBOSE) << "[TensorRT EP] DeSerialized " + engine_cache_path;
         if (trt_engine == nullptr) {
           return ORT_MAKE_STATUS(ONNXRUNTIME, EP_FAIL,
@@ -3022,7 +3022,7 @@ Status TensorrtExecutionProvider::CreateNodeComputeFromOrtGraph(const GraphViewe
                                  "TensorRT EP could not call engine decryption function decrypt");
         }
         // Deserialize engine
-        trt_engine = std::unique_ptr<nvinfer1::ICudaEngine>(runtime_->deserializeCudaEngine(engine_buf.get(), engine_size, nullptr));
+        trt_engine = std::unique_ptr<nvinfer1::ICudaEngine>(runtime_->deserializeCudaEngine(engine_buf.get(), engine_size));
         LOGS_DEFAULT(VERBOSE) << "[TensorRT EP] Decrypted and DeSerialized " + encrypted_engine_cache_path;
         if (trt_engine == nullptr) {
           return ORT_MAKE_STATUS(ONNXRUNTIME, EP_FAIL,
@@ -3268,7 +3268,7 @@ Status TensorrtExecutionProvider::CreateNodeComputeFromOrtGraph(const GraphViewe
         // https://docs.nvidia.com/deeplearning/tensorrt/developer-guide/index.html#threading
         trt_state->engine->reset();
         *(trt_state->engine) = std::unique_ptr<nvinfer1::ICudaEngine>(
-            trt_state->runtime->deserializeCudaEngine(engine_buf.get(), engine_size, nullptr));
+            trt_state->runtime->deserializeCudaEngine(engine_buf.get(), engine_size));
         if (!(*(trt_state->engine))) {
           return ORT_MAKE_STATUS(ONNXRUNTIME, EP_FAIL, "TensorRT EP Failed to Build Engine.");
         }
@@ -3293,7 +3293,7 @@ Status TensorrtExecutionProvider::CreateNodeComputeFromOrtGraph(const GraphViewe
         // Note: Deserializing an engine from a TensorRT runtime is thread safe per TRT doc
         // https://docs.nvidia.com/deeplearning/tensorrt/developer-guide/index.html#threading
         trt_state->engine->reset();
-        *(trt_state->engine) = std::unique_ptr<nvinfer1::ICudaEngine>(trt_state->runtime->deserializeCudaEngine(engine_buf.get(), engine_size, nullptr));
+        *(trt_state->engine) = std::unique_ptr<nvinfer1::ICudaEngine>(trt_state->runtime->deserializeCudaEngine(engine_buf.get(), engine_size));
         if (!(*(trt_state->engine))) {
           return ORT_MAKE_STATUS(ONNXRUNTIME, EP_FAIL,
                                  "TensorRT EP could not deserialize engine from encrypted cache: " + encrypted_engine_cache_path);