Polish JitLayer in Python

paddle/fluid/jit/compilation_unit.cc

@@ -42,5 +42,9 @@ std::vector<std::string> CompilationUnit::FunctionNames() const {
   return names;
 }
 
+const FunctionMap &CompilationUnit::FunctionDict() const {
+  return function_dict_;
+}
+
 }  // namespace jit
 }  // namespace paddle

paddle/fluid/jit/compilation_unit.h

@@ -21,6 +21,8 @@
 
 namespace paddle {
 namespace jit {
+using FunctionMap =
+    std::unordered_map<std::string, std::shared_ptr<BaseFunction>>;
 
 class CompilationUnit {
  public:
@@ -34,8 +36,10 @@ class CompilationUnit {
 
   std::vector<std::string> FunctionNames() const;
 
+  const FunctionMap &FunctionDict() const;
+
  private:
-  std::unordered_map<std::string, std::shared_ptr<BaseFunction>> function_dict_;
+  FunctionMap function_dict_;
 };
 
 }  // namespace jit

paddle/fluid/jit/layer.cc

@@ -46,5 +46,7 @@ std::vector<std::string> Layer::FunctionNames() const {
   return unit_.FunctionNames();
 }
 
+const FunctionMap& Layer::FunctionDict() const { return unit_.FunctionDict(); }
+
 }  // namespace jit
 }  // namespace paddle

paddle/fluid/jit/layer.h

@@ -52,6 +52,8 @@ class Layer {
 
   std::vector<std::string> FunctionNames() const;
 
+  const FunctionMap& FunctionDict() const;
+
  private:
   // internal::Object obj_;
   Name2VariableMap params_dict_;

paddle/fluid/pybind/CMakeLists.txt

@@ -122,7 +122,8 @@ set(PYBIND_SRCS
     io.cc
     generator_py.cc
     communication.cc
-    cuda_streams_py.cc)
+    cuda_streams_py.cc
+    jit.cc)
 
 if(WITH_CUSTOM_DEVICE)
   set(PYBIND_DEPS ${PYBIND_DEPS} phi_capi)

paddle/fluid/pybind/jit.cc

@@ -0,0 +1,83 @@
+/* Copyright (c) 2022 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.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/fluid/pybind/jit.h"
+
+#include "paddle/fluid/framework/variable.h"
+#include "paddle/fluid/imperative/layer.h"
+#include "paddle/fluid/platform/place.h"
+
+#include "paddle/fluid/jit/executor_function.h"
+#include "paddle/fluid/jit/function_schema.h"
+#include "paddle/fluid/jit/layer.h"
+#include "paddle/fluid/jit/serializer.h"
+
+namespace py = pybind11;
+
+namespace paddle {
+namespace pybind {
+
+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::FunctionDict);
+
+  py::class_<jit::ExecutorFunction, std::shared_ptr<jit::ExecutorFunction>>(
+      *m, "ExectorFunction", R"DOC(ExectorFunction Class.)DOC")
+      .def("__call__",
+           [](jit::ExecutorFunction &self,
+              const std::vector<std::shared_ptr<imperative::VarBase>>
+                  &tensor_inputs) {
+             std::vector<Variable> var_inputs;
+             for (auto &tensor : tensor_inputs) {
+               var_inputs.emplace_back(tensor->Var());
+             }
+             auto var_outputs = self(var_inputs);
+
+             std::vector<std::shared_ptr<imperative::VarBase>> tensor_outputs;
+             auto output_names = self.Info()->OutputArgNames();
+             for (size_t i = 0; i < var_outputs.size(); ++i) {
+               auto var = var_outputs[i];
+               std::string name = output_names[i];
+               imperative::VariableWrapper var_wrapper(name, var);
+               auto shared_wrapper =
+                   std::make_shared<imperative::VariableWrapper>(var_wrapper);
+               auto shared_varbase =
+                   std::make_shared<imperative::VarBase>(shared_wrapper);
+               tensor_outputs.emplace_back(shared_varbase);
+             }
+             return tensor_outputs;
+           })
+      .def("info", &jit::ExecutorFunction::Info);
+
+  py::class_<jit::FunctionInfo, std::shared_ptr<jit::FunctionInfo>>(
+      *m, "FunctionInfo", R"DOC(FunctionInfo Class.)DOC")
+      .def("name", &jit::FunctionInfo::FunctionName)
+      .def("input_names", &jit::FunctionInfo::InputArgNames)
+      .def("output_names", &jit::FunctionInfo::OutputArgNames);
+
+  m->def("Load",
+         [](const std::string &path, const platform::CPUPlace &cpu_place) {
+           return paddle::jit::Load(path, cpu_place);
+         });
+
+  m->def("Load",
+         [](const std::string &path, const platform::CUDAPlace &cuda_place) {
+           return paddle::jit::Load(path, cuda_place);
+         });
+}
+
+}  // namespace pybind
+}  // namespace paddle

paddle/fluid/pybind/jit.h

@@ -0,0 +1,27 @@
+/* Copyright (c) 2022 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.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+#pragma once
+
+#include <Python.h>
+
+#include "pybind11/pybind11.h"
+#include "pybind11/stl.h"
+
+namespace paddle {
+namespace pybind {
+
+void BindJit(pybind11::module* m);
+
+}  // namespace pybind
+}  // namespace paddle

paddle/fluid/pybind/pybind.cc

@@ -90,6 +90,7 @@ limitations under the License. */
 #include "paddle/fluid/pybind/eager.h"
 #include "paddle/fluid/pybind/imperative.h"
 #include "paddle/fluid/pybind/io.h"
+#include "paddle/fluid/pybind/jit.h"
 #include "paddle/phi/core/compat/convert_utils.h"
 #include "paddle/phi/core/lod_utils.h"
 #include "paddle/utils/none.h"
@@ -566,6 +567,7 @@ PYBIND11_MODULE(core_noavx, m) {
   BindEager(&m);
   BindEagerStringTensor(&m);
   BindCudaStream(&m);
+  BindJit(&m);
 
   // Not used, just make sure cpu_info.cc is linked.
   paddle::platform::CpuTotalPhysicalMemory();
@@ -1746,48 +1748,6 @@ PYBIND11_MODULE(core_noavx, m) {
         return new_rows;
       });
 
-  py::class_<jit::ExecutorFunction, std::shared_ptr<jit::ExecutorFunction>>(
-      m, "ExectorFunction", R"DOC(ExectorFunction Class.)DOC")
-      .def("__call__",
-           [](jit::ExecutorFunction &self,
-              const std::vector<std::shared_ptr<imperative::VarBase>>
-                  &tensor_inputs) {
-             std::vector<Variable> var_inputs;
-             for (auto &tensor : tensor_inputs) {
-               var_inputs.emplace_back(tensor->Var());
-             }
-             auto var_outputs = self(var_inputs);
-
-             std::vector<std::shared_ptr<imperative::VarBase>> tensor_outputs;
-             auto output_names = self.Info()->OutputArgNames();
-             for (size_t i = 0; i < var_outputs.size(); ++i) {
-               auto var = var_outputs[i];
-               std::string name = output_names[i];
-               imperative::VariableWrapper var_wrapper(name, var);
-               auto shared_wrapper =
-                   std::make_shared<imperative::VariableWrapper>(var_wrapper);
-               auto shared_varbase =
-                   std::make_shared<imperative::VarBase>(shared_wrapper);
-               tensor_outputs.emplace_back(shared_varbase);
-             }
-             return tensor_outputs;
-           });
-
-  py::class_<jit::Layer>(m, "Layer", R"DOC(Layer Class.)DOC")
-      .def("function", &jit::Layer::Function)
-      .def("forward", &jit::Layer::forward)
-      .def("function_names", &jit::Layer::FunctionNames);
-
-  m.def("Load",
-        [](const std::string &path, const platform::CPUPlace &cpu_place) {
-          return paddle::jit::Load(path, cpu_place);
-        });
-
-  m.def("Load",
-        [](const std::string &path, const platform::CUDAPlace &cuda_place) {
-          return paddle::jit::Load(path, cuda_place);
-        });
-
   py::class_<Variable>(m, "Variable", R"DOC(Variable Class.
 
 All parameter, weight, gradient are variables in Paddle.

python/paddle/fluid/dygraph/jit.py

@@ -41,30 +41,13 @@
 from paddle.fluid.framework import _current_expected_place, _dygraph_guard, _dygraph_tracer
 from paddle.fluid.framework import dygraph_only, _non_static_mode
 from paddle.fluid.wrapped_decorator import wrap_decorator
-from paddle.fluid.core import Load
 
 __all__ = [
     'TracedLayer', 'declarative', 'dygraph_to_static_func', 'set_code_level',
     'set_verbosity', 'save', 'load', 'not_to_static'
 ]
 
 
-class JitLayer():
-
-    def __init__(self, load_path, place):
-        self.cpp_jit_layer = Load(load_path, place)
-        # bind method
-        for func_name in self.cpp_jit_layer.function_names():
-            setattr(self, func_name, self.bind_funciton(func_name))
-
-    def bind_funciton(self, name):
-
-        def inner_funciton(*args):
-            return self.cpp_jit_layer.function(name)(args)
-
-        return inner_funciton
-
-
 def create_program_from_desc(program_desc):
     program = Program()
     program.desc = program_desc

python/paddle/fluid/tests/unittests/test_jit_layer.py

@@ -19,7 +19,7 @@
 import numpy as np
 from paddle.static import InputSpec
 from paddle.fluid.framework import _enable_legacy_dygraph
-from paddle.fluid.dygraph.jit import JitLayer
+from paddle.jit.layer import Layer
 from paddle.fluid.dygraph.dygraph_to_static.program_translator import ProgramTranslator
 
 _enable_legacy_dygraph()
@@ -68,7 +68,8 @@ def test_multi_load(self):
         place = paddle.CPUPlace()
         if paddle.is_compiled_with_cuda():
             place = paddle.CUDAPlace(0)
-        jit_layer = JitLayer(model_path, place)
+        jit_layer = Layer()
+        jit_layer.load(model_path, place)
         forward_out2 = jit_layer.forward(x)
         infer_out2 = jit_layer.infer(x)
         self.assertEqual(np.allclose(forward_out1, forward_out2[0]), True)

python/paddle/jit/layer.py

@@ -0,0 +1,51 @@
+# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2021 NVIDIA Corporation. 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.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from paddle.fluid.core import Load
+
+
+class Layer():
+
+    def __init__(self):
+        self.cpp_layer = None
+        # {name: Function}
+        self.funciton_map = {}
+
+    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.funciton_map[name] = Function(function)
+            setattr(self, name, self.funciton_map[name].__call__)
+
+
+class Function():
+
+    def __init__(self, function):
+        self.function = function
+        self.info = FunctionInfo(function.info())
+
+    def __call__(self, *args):
+        return self.function(args)
+
+
+class FunctionInfo():
+
+    def __init__(self, info):
+        self.info = info
+
+    def name(self):
+        return self.info.name()