Add partition logic and torch backend integration

Signed-off-by: Arvind Sridhar <[email protected]>
pytorch · Aug 20, 2021 · b96087b · b96087b
1 parent b4feb49
commit b96087b
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Showing 10 changed files with 23 additions and 7 deletions.
diff --git a/core/compiler.cpp b/core/compiler.cpp
@@ -119,7 +119,7 @@ void AddEngineToGraph(
 }
 
 bool CheckMethodOperatorSupport(const torch::jit::script::Module& mod, std::string method_name) {
-  // Go through Lowering to simplify graph
+  // Go through Lowering to simplify graph and extract weight parameters
   auto graph_and_parameters = lowering::Lower(mod, method_name, lowering::LowerInfo());
 
   auto g = graph_and_parameters.first;

diff --git a/core/compiler.h b/core/compiler.h
@@ -19,7 +19,7 @@ struct CompileSpec {
   partitioning::PartitionInfo partition_info;
 };
 
-bool CheckMethodOperatorSupport(const torch::jit::script::Module& mod, std::string method_name, CompileSpec cfg);
+bool CheckMethodOperatorSupport(const torch::jit::script::Module& mod, std::string method_name);
 
 std::string ConvertGraphToTRTEngine(const torch::jit::script::Module& mod, std::string method_name, CompileSpec cfg);
 

diff --git a/core/partitioning/partitioning.cpp b/core/partitioning/partitioning.cpp
@@ -274,7 +274,8 @@ std::vector<SegmentedBlock> segment_graph(torch::jit::Block* block, const Partit
     }
 
     std::string node_string(n->kind().toQualString());
-    if (conversion::OpSupported(n) && !forced_fallback_operators.count(node_string)) {
+    auto has_compile_attribute = n->hasAttribute(c10::Symbol::attr("to_compile"));
+    if (conversion::OpSupported(n) && !forced_fallback_operators.count(node_string) && (!has_compile_attribute || n->i(c10::Symbol::attr("to_compile")) == (int64_t) true)) {
       tensorrt_nodes.push_back(n);
       if (tensorrt_nodes.size() >= min_block_size && !pytorch_nodes.empty()) {
         segmented_blocks.emplace_back(SegmentedBlock::kTorch, pytorch_nodes);

diff --git a/cpp/api/include/trtorch/trtorch.h b/cpp/api/include/trtorch/trtorch.h
@@ -784,7 +784,7 @@ TRTORCH_API void dump_build_info();
  *
  * @returns bool: Method is supported by TRTorch
  */
-TRTORCH_API bool CheckMethodOperatorSupport(const torch::jit::Module& module, std::string method_name, CompileSpec info);
+TRTORCH_API bool CheckMethodOperatorSupport(const torch::jit::Module& module, std::string method_name);
 
 /**
  * @brief Compile a TorchScript module for NVIDIA GPUs using TensorRT

diff --git a/cpp/api/src/trtorch.cpp b/cpp/api/src/trtorch.cpp
@@ -11,8 +11,8 @@ namespace trtorch {
 core::CompileSpec to_internal_compile_spec(CompileSpec external);
 core::runtime::CudaDevice to_internal_cuda_device(CompileSpec::Device device);
 
-bool CheckMethodOperatorSupport(const torch::jit::script::Module& module, std::string method_name, CompileSpec info) {
-  return core::CheckMethodOperatorSupport(module, method_name, to_internal_compile_spec(info));
+bool CheckMethodOperatorSupport(const torch::jit::script::Module& module, std::string method_name) {
+  return core::CheckMethodOperatorSupport(module, method_name);
 }
 
 std::string ConvertGraphToTRTEngine(

diff --git a/py/trtorch/_compile_spec.py b/py/trtorch/_compile_spec.py
@@ -148,6 +148,10 @@ def _parse_torch_fallback(fallback_info: Dict[str, Any]) -> trtorch._C.TorchFall
         assert isinstance(fallback_info["forced_fallback_ops"], list)
         info.forced_fallback_operators = fallback_info["forced_fallback_ops"]
 
+    if "forced_fallback_modules" in fallback_info:
+        assert isinstance(fallback_info["forced_fallback_modules"], list)
+        info.forced_fallback_modules = fallback_info["forced_fallback_modules"]
+
     return info
 
 
@@ -338,6 +342,7 @@ def TensorRTCompileSpec(compile_spec: Dict[str, Any]) -> torch.classes.tensorrt.
     torch_fallback._set_enabled(parsed_spec.torch_fallback.enabled)
     torch_fallback._set_min_block_size(parsed_spec.torch_fallback.min_block_size)
     torch_fallback._set_forced_fallback_operators(parsed_spec.torch_fallback.forced_fallback_operators)
+    torch_fallback._set_forced_fallback_modules(parsed_spec.torch_fallback.forced_fallback_modules)
 
     backend_spec._set_device(d)
     backend_spec._set_torch_fallback(torch_fallback)

diff --git a/py/trtorch/csrc/register_tensorrt_classes.cpp b/py/trtorch/csrc/register_tensorrt_classes.cpp
@@ -37,6 +37,7 @@ void RegisterTRTCompileSpec() {
   ADD_FIELD_GET_SET_REGISTRATION(TRTFallbackTSRegistration, trtorch::pyapi::TorchFallback, enabled);
   ADD_FIELD_GET_SET_REGISTRATION(TRTFallbackTSRegistration, trtorch::pyapi::TorchFallback, min_block_size);
   ADD_FIELD_GET_SET_REGISTRATION(TRTFallbackTSRegistration, trtorch::pyapi::TorchFallback, forced_fallback_operators);
+  ADD_FIELD_GET_SET_REGISTRATION(TRTFallbackTSRegistration, trtorch::pyapi::TorchFallback, forced_fallback_modules);
 
   static auto TRTORCH_UNUSED TRTCompileSpecTSRegistration =
       torch::class_<trtorch::pyapi::CompileSpec>("tensorrt", "CompileSpec")

diff --git a/py/trtorch/csrc/tensorrt_classes.cpp b/py/trtorch/csrc/tensorrt_classes.cpp
@@ -166,6 +166,11 @@ std::string TorchFallback::to_str() {
     ss << "            " << i << ',' << std::endl;
   }
   ss << "        ]" << std::endl;
+  ss << "        \"forced_fallback_modules\": [" << std::endl;
+  for (auto i : forced_fallback_modules) {
+    ss << "            " << i << ',' << std::endl;
+  }
+  ss << "        ]" << std::endl;
   ss << "    }" << std::endl;
   return ss.str();
 }
@@ -203,6 +208,7 @@ core::CompileSpec CompileSpec::toInternalCompileSpec() {
   info.partition_info.enabled = torch_fallback.enabled;
   info.partition_info.min_block_size = torch_fallback.min_block_size;
   info.partition_info.forced_fallback_operators = torch_fallback.forced_fallback_operators;
+  info.lower_info.forced_fallback_modules = torch_fallback.forced_fallback_modules;
   info.convert_info.engine_settings.truncate_long_and_double = truncate_long_and_double;
 
   info.convert_info.engine_settings.capability = toTRTEngineCapability(capability);

diff --git a/py/trtorch/csrc/tensorrt_classes.h b/py/trtorch/csrc/tensorrt_classes.h
@@ -90,11 +90,13 @@ struct TorchFallback : torch::CustomClassHolder {
   bool enabled;
   int64_t min_block_size;
   std::vector<std::string> forced_fallback_operators;
+  std::vector<std::string> forced_fallback_modules;
   TorchFallback() : enabled(false), min_block_size(1) {}
 
   ADD_FIELD_GET_SET(enabled, bool);
   ADD_FIELD_GET_SET(min_block_size, int64_t);
   ADD_FIELD_GET_SET(forced_fallback_operators, std::vector<std::string>);
+  ADD_FIELD_GET_SET(forced_fallback_modules, std::vector<std::string>);
 
   std::string to_str();
 };

diff --git a/py/trtorch/csrc/trtorch_py.cpp b/py/trtorch/csrc/trtorch_py.cpp
@@ -281,7 +281,8 @@ PYBIND11_MODULE(_C, m) {
       .def("__str__", &trtorch::pyapi::TorchFallback::to_str)
       .def_readwrite("enabled", &TorchFallback::enabled)
       .def_readwrite("min_block_size", &TorchFallback::min_block_size)
-      .def_readwrite("forced_fallback_operators", &TorchFallback::forced_fallback_operators);
+      .def_readwrite("forced_fallback_operators", &TorchFallback::forced_fallback_operators)
+      .def_readwrite("forced_fallback_modules", &TorchFallback::forced_fallback_modules);
 
   m.doc() =
       "TRTorch Internal C Bindings: Ahead of Time compilation for PyTorch JIT. A tool to convert PyTorch JIT to TensorRT";