[JitLayer]Pybind Fucniton and hide ExecutorEngine and PEEngine (#44984)

* Pybind Fucniton and hide ExecutorEngine and PEEngine

* Remove FunctionNames in compilation_unit

paddle/fluid/jit/function_utils.cc

@@ -73,12 +73,17 @@ void ShareIntoScope(const std::vector<std::string> &ordered_input_names,
 void ShareParamsIntoScope(const std::vector<std::string> &param_names,
                           const Name2VariableMap &params_dict,
                           framework::Scope *scope) {
-  VLOG(3) << "param_names size: " << param_names.size();
   for (size_t i = 0; i < param_names.size(); ++i) {
     std::string name = param_names[i];
+    PADDLE_ENFORCE_EQ(params_dict.count(name),
+                      1,
+                      phi::errors::InvalidArgument(
+                          "Parameter named %s is not exist in param_names. "
+                          "Please check that your model was saved correctly",
+                          name));
+
     auto &param = params_dict.find(name)->second;
     auto &dense_tensor = param->Get<DenseTensor>();
-    VLOG(3) << "share into scope: " << name;
     auto *var = scope->Var(name);
     auto *dst_tensor = var->GetMutable<DenseTensor>();
     *dst_tensor = dense_tensor;

paddle/fluid/jit/layer.cc

@@ -68,6 +68,14 @@ const std::shared_ptr<jit::FunctionInfo>& Layer::FunctionInfo(
   return info_map_.at(name);
 }
 
+std::vector<std::string> Layer::FunctionNames() const {
+  std::vector<std::string> names;
+  for (auto it = info_map_.begin(); it != info_map_.end(); ++it) {
+    names.emplace_back(it->first);
+  }
+  return names;
+}
+
 #define PD_SPECIALZE_ATTRIBUTE_TYPE(T)                                \
   template <>                                                         \
   T Layer::Attribute<T>(const std::string& name) const {              \

paddle/fluid/jit/layer.h

@@ -70,6 +70,8 @@ class Layer {
   const std::shared_ptr<jit::FunctionInfo>& FunctionInfo(
       const std::string& name) const;
 
+  std::vector<std::string> FunctionNames() const;
+
  private:
   Name2VariableMap params_map_;
   Name2VariableMap attrs_map_;

paddle/fluid/pybind/eager_functions.cc

@@ -372,8 +372,9 @@ static PyObject* eager_api_jit_function_call(PyObject* self,
                                              PyObject* args,
                                              PyObject* kwargs) {
   EAGER_TRY
-  std::shared_ptr<jit::BaseEngine> function =
-      CastPyArg2BaseEngine(PyTuple_GET_ITEM(args, 0), 0);
+
+  std::shared_ptr<jit::Function> function =
+      CastPyArg2JitFunction(PyTuple_GET_ITEM(args, 0), 0);
   std::vector<paddle::experimental::Tensor> ins =
       CastPyArg2VectorOfTensor(PyTuple_GET_ITEM(args, 1), 1);
   std::vector<paddle::experimental::Tensor> outs = (*function)(ins);

paddle/fluid/pybind/eager_utils.cc

@@ -22,8 +22,7 @@ limitations under the License. */
 #include "paddle/fluid/framework/convert_utils.h"
 #include "paddle/fluid/framework/scope.h"
 #include "paddle/fluid/framework/scope_guard.h"
-#include "paddle/fluid/jit/engine/executor_engine.h"
-#include "paddle/fluid/jit/engine/pe_engine.h"
+#include "paddle/fluid/jit/function.h"
 #include "paddle/fluid/memory/allocation/allocator.h"
 #include "paddle/fluid/operators/py_func_op.h"
 #include "paddle/fluid/operators/utils.h"
@@ -54,8 +53,7 @@ extern PyTypeObject* g_customplace_pytype;
 extern PyTypeObject* g_framework_tensor_pytype;
 extern PyTypeObject* g_framework_lodtensorarray_pytype;
 extern PyTypeObject* g_custom_op_kernel_ctx_pytype;
-extern PyTypeObject* g_executor_engine_pytype;
-extern PyTypeObject* g_pe_engine_pytype;
+extern PyTypeObject* g_jit_function_pytype;
 
 int TensorDtype2NumpyDtype(phi::DataType dtype) {
   switch (dtype) {
@@ -232,14 +230,11 @@ std::shared_ptr<imperative::VarBase> CastPyArg2VarBase(PyObject* obj,
   return py::cast<std::shared_ptr<imperative::VarBase>>(obj);
 }
 
-std::shared_ptr<jit::BaseEngine> CastPyArg2BaseEngine(PyObject* obj,
+std::shared_ptr<jit::Function> CastPyArg2JitFunction(PyObject* obj,
                                                      ssize_t arg_pos) {
-  if (PyObject_IsInstance(
-          obj, reinterpret_cast<PyObject*>(g_executor_engine_pytype))) {
-    return ::pybind11::handle(obj).cast<std::shared_ptr<jit::ExecutorEngine>>();
-  } else if (PyObject_IsInstance(
-                 obj, reinterpret_cast<PyObject*>(g_pe_engine_pytype))) {
-    return ::pybind11::handle(obj).cast<std::shared_ptr<jit::PEEngine>>();
+  if (PyObject_IsInstance(obj,
+                          reinterpret_cast<PyObject*>(g_jit_function_pytype))) {
+    return ::pybind11::handle(obj).cast<std::shared_ptr<jit::Function>>();
   } else {
     PADDLE_THROW(platform::errors::InvalidArgument(
         "argument (position %d) must be "

paddle/fluid/pybind/eager_utils.h

@@ -20,7 +20,7 @@ typedef SSIZE_T ssize_t;
 #include "paddle/fluid/eager/hooks.h"
 #include "paddle/fluid/framework/lod_tensor.h"
 #include "paddle/fluid/framework/tensor.h"
-#include "paddle/fluid/jit/engine/base_engine.h"
+#include "paddle/fluid/jit/function.h"
 #include "paddle/fluid/platform/place.h"
 #include "paddle/phi/common/backend.h"
 #include "paddle/phi/common/data_type.h"
@@ -75,7 +75,7 @@ framework::proto::VarType::Type CastPyArg2ProtoType(PyObject* obj,
 std::unordered_map<std::wstring, int> CastPyArg2Vocab(PyObject* obj,
                                                       ssize_t arg_pos);
 std::vector<std::string> CastPyArg2Strings(PyObject* obj, ssize_t arg_pos);
-std::shared_ptr<jit::BaseEngine> CastPyArg2BaseEngine(PyObject* obj,
+std::shared_ptr<jit::Function> CastPyArg2JitFunction(PyObject* obj,
                                                      ssize_t arg_pos);
 
 PyObject* ToPyObject(int value);

paddle/fluid/pybind/jit.cc

@@ -18,8 +18,7 @@ limitations under the License. */
 #include "paddle/fluid/imperative/layer.h"
 #include "paddle/fluid/platform/place.h"
 
-#include "paddle/fluid/jit/engine/executor_engine.h"
-#include "paddle/fluid/jit/engine/pe_engine.h"
+#include "paddle/fluid/jit/function.h"
 #include "paddle/fluid/jit/function_schema.h"
 #include "paddle/fluid/jit/layer.h"
 #include "paddle/fluid/jit/serializer.h"
@@ -29,26 +28,18 @@ namespace py = pybind11;
 namespace paddle {
 namespace pybind {
 
-PyTypeObject *g_executor_engine_pytype = nullptr;
-PyTypeObject *g_pe_engine_pytype = nullptr;
+PyTypeObject *g_jit_function_pytype = nullptr;
 using Variable = paddle::framework::Variable;
 
 void BindJit(pybind11::module *m) {
   py::class_<jit::Layer>(*m, "Layer", R"DOC(Layer Class.)DOC")
-      .def("function_dict",
-           &jit::Layer::EngineMap,
-           py::return_value_policy::reference);
+      .def("function_names", &jit::Layer::FunctionNames)
+      .def("function", &jit::Layer::Function)
+      .def("function_info", &jit::Layer::FunctionInfo);
 
-  py::class_<jit::ExecutorEngine, std::shared_ptr<jit::ExecutorEngine>>
-      executor_engine(*m, "ExecutorEngine", R"DOC(ExecutorEngine Class.)DOC");
-  g_executor_engine_pytype =
-      reinterpret_cast<PyTypeObject *>(executor_engine.ptr());
-  executor_engine.def("info", &jit::ExecutorEngine::Info);
-
-  py::class_<jit::PEEngine, std::shared_ptr<jit::PEEngine>> pe_engine(
-      *m, "PEEngine", R"DOC(PEEngine Class.)DOC");
-  g_pe_engine_pytype = reinterpret_cast<PyTypeObject *>(pe_engine.ptr());
-  pe_engine.def("info", &jit::PEEngine::Info);
+  py::class_<jit::Function, std::shared_ptr<jit::Function>> function(
+      *m, "Function", R"DOC(Function Class.)DOC");
+  g_jit_function_pytype = reinterpret_cast<PyTypeObject *>(function.ptr());
 
   py::class_<jit::FunctionInfo, std::shared_ptr<jit::FunctionInfo>>(
       *m, "FunctionInfo", R"DOC(FunctionInfo Class.)DOC")

python/paddle/jit/layer.py

@@ -26,18 +26,19 @@ class Layer(object):
 
     def load(self, load_path, place):
         self.cpp_layer = Load(load_path, place)
-        function_dict = self.cpp_layer.function_dict()
 
-        for name, function in function_dict.items():
-            self.functions[name] = Function(function)
+        for name in self.cpp_layer.function_names():
+            function = self.cpp_layer.function(name)
+            info = self.cpp_layer.function_info(name)
+            self.functions[name] = Function(function, info)
             setattr(self, name, self.functions[name])
 
 
 class Function():
 
-    def __init__(self, function):
+    def __init__(self, function, info):
         self.function = function
-        self.info = FunctionInfo(function.info())
+        self.info = FunctionInfo(info)
 
     def __call__(self, *args):
         return core.eager.jit_function_call(self.function, args)