feat(//core): New API to register arbitrary TRT engines in TorchScript

Modules Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com>
pytorch · Apr 21, 2021 · 3ec836e · 3ec836e
1 parent bbf997e
commit 3ec836e
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Showing 5 changed files with 62 additions and 0 deletions.
diff --git a/core/compiler.cpp b/core/compiler.cpp
@@ -173,6 +173,20 @@ torch::jit::script::Module CompileGraph(const torch::jit::script::Module& mod, C
   return new_mod;
 }
 
+torch::jit::script::Module EmbedEngineInNewModule(std::string& engine) {
+  std::ostringstream engine_id;
+  engine_id << reinterpret_cast<int*>(&engine);
+  torch::jit::script::Module new_mod("tensorrt_engine_mod_" + engine_id.str());
+  auto new_g = std::make_shared<torch::jit::Graph>();
+  AddEngineToGraph(new_mod, new_g, engine);
+  auto new_method = new_mod._ivalue()->compilation_unit()->create_function("forward", new_g);
+  auto schema = GenerateGraphSchema(new_mod, new_method->name(), new_g);
+  new_mod.type()->addMethod(new_method);
+  new_method->setSchema(schema);
+
+  return new_mod;
+}
+
 void set_device(const int gpu_id) {
   TRTORCH_ASSERT(cudaSetDevice(gpu_id) == cudaSuccess, "Unable to set CUDA device: " << gpu_id);
 }

diff --git a/core/compiler.h b/core/compiler.h
@@ -19,6 +19,8 @@ std::string ConvertGraphToTRTEngine(const torch::jit::script::Module& mod, std::
 
 torch::jit::script::Module CompileGraph(const torch::jit::script::Module& module, CompileSpec cfg);
 
+torch::jit::script::Module EmbedEngineInNewModule(std::string& engine);
+
 void set_device(const int gpu_id);
 
 } // namespace core

diff --git a/cpp/api/include/trtorch/trtorch.h b/cpp/api/include/trtorch/trtorch.h
@@ -480,6 +480,20 @@ TRTORCH_API std::string ConvertGraphToTRTEngine(
     const torch::jit::Module& module,
     std::string method_name,
     CompileSpec info);
+
+/**
+ * @brief Take a previously created TensorRT engine and embed it in
+ * in a TorchScript module
+ *
+ * @param engine: std::string - Precompiled serialized TensorRT engine
+ *
+ * Takes a prebuilt serialized TensorRT engine and embeds it in a TorchScript
+ * graph. Registers the engine as the forward method of the module
+ *
+ * @return: A new module trageting a TensorRT engine
+ */
+TRTORCH_API torch::jit::Module EmbedEngineInNewModule(std::string& engine);
+
 /**
  * @brief Set gpu device id
  *

diff --git a/cpp/api/src/trtorch.cpp b/cpp/api/src/trtorch.cpp
@@ -31,6 +31,10 @@ torch::jit::script::Module CompileGraph(const torch::jit::script::Module& module
   return core::CompileGraph(module, to_internal_compile_spec(info));
 }
 
+torch::jit::Module EmbedEngineInNewModule(std::string& engine) {
+  return core::EmbedEngineInNewModule(engine);
+}
+
 std::string get_build_info() {
   auto info = core::util::get_build_info();
   return std::string("TRTorch Version: ") + TRTORCH_VERSION + '\n' + info;

diff --git a/tests/modules/test_modules_as_engines.cpp b/tests/modules/test_modules_as_engines.cpp
@@ -16,6 +16,34 @@ TEST_P(ModuleTests, ModuleAsEngineIsClose) {
   ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt_results[0].reshape_as(jit_results[0]), 2e-5));
 }
 
+TEST_P(ModuleTests, ModuleToModuleIsClose) {
+  std::vector<at::Tensor> inputs;
+  std::vector<torch::jit::IValue> inputs_ivalues;
+  for (auto in_shape : input_shapes) {
+    inputs.push_back(at::randint(5, in_shape, {at::kCUDA}));
+    inputs_ivalues.push_back(inputs[inputs.size() - 1].clone());
+  }
+
+  torch::jit::IValue jit_results_ivalues = trtorch::tests::util::RunModuleForward(mod, inputs_ivalues);
+  std::vector<at::Tensor> jit_results;
+  jit_results.push_back(jit_results_ivalues.toTensor());
+
+  auto forward_graph = mod.get_method("forward");
+  std::vector<c10::ArrayRef<int64_t>> input_ranges;
+  for (auto in : inputs) {
+    input_ranges.push_back(in.sizes());
+  }
+
+  auto engine = trtorch::ConvertGraphToTRTEngine(mod, "forward", input_ranges);
+  auto trt_mod = trtorch::EmbedEngineInNewModule(engine);
+
+  torch::jit::IValue trt_results_ivalues = trtorch::tests::util::RunModuleForward(mod, inputs_ivalues);
+  std::vector<at::Tensor> trt_results;
+  trt_results.push_back(trt_results_ivalues.toTensor());
+
+  ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt_results[0].reshape_as(jit_results[0]), 2e-5));
+}
+
 INSTANTIATE_TEST_SUITE_P(
     ModuleAsEngineForwardIsCloseSuite,
     ModuleTests,