chore: import upstream snapshot with attribution

python/paddle/jit/layer.py

@@ -0,0 +1,50 @@
+# 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.base import core
+from paddle.base.core import Load
+
+
+class Layer:
+    def __init__(self):
+        self.cpp_layer = None
+        # {name: Function}
+        self.functions = {}
+
+    def load(self, load_path, place):
+        self.cpp_layer = Load(load_path, place)
+
+        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, info):
+        self.function = function
+        self.info = FunctionInfo(info)
+
+    def __call__(self, *args):
+        return core.eager.jit_function_call(self.function, args)
+
+
+class FunctionInfo:
+    def __init__(self, info):
+        self.info = info
+
+    def name(self):
+        return self.info.name()