add `no_need_buffer_slots` interface to pybind (#21575)

* add no_need_buffer_slots interface to pybind

paddle/fluid/pybind/pybind.cc

@@ -1103,7 +1103,20 @@ All parameter, weight, gradient are variables in Paddle.
   m.def("has_infer_inplace", [](const std::string op_type) {
     return framework::OpInfoMap::Instance().Get(op_type).HasInferInplace();
   });
-
+  m.def("infer_no_need_buffer_slots",
+        [](const std::string op_type, const framework::VariableNameMap &inputs,
+           const framework::VariableNameMap &outputs,
+           const framework::AttributeMap &attrs) {
+          auto infer_func = framework::OpInfoMap::Instance()
+                                .Get(op_type)
+                                .NoNeedBufferVarsInferer();
+          if (infer_func) {
+            return infer_func(inputs, outputs, attrs);
+          } else {
+            std::unordered_set<std::string> empty = {};
+            return empty;
+          }
+        });
   m.def("prune", [](const ProgramDesc &origin,
                     const std::set<std::string> &feeded_var_names,
                     const std::vector<std::array<size_t, 2>> &targets) {

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

@@ -0,0 +1,72 @@
+#   Copyright (c) 2019 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.
+
+from __future__ import print_function
+
+import unittest
+
+import paddle.fluid as fluid
+import paddle.fluid.framework as framework
+import paddle.compat as cpt
+import paddle.fluid.core as core
+
+
+class TestInferNoNeedBufferSlots(unittest.TestCase):
+    def net(self):
+        x1 = fluid.default_main_program().global_block().create_var(
+            dtype="float32", shape=[1], lod_level=0, name="x1")
+        x2 = fluid.default_main_program().global_block().create_var(
+            dtype="float32", shape=[1], lod_level=0, name="x2")
+        x = fluid.layers.elementwise_add(x1, x2)
+        return x
+
+    def test_infer_no_need_buffer_slots(self):
+        program = framework.Program()
+        startup_program = framework.Program()
+        with fluid.program_guard(program, startup_program):
+            loss = self.net()
+            sgd = fluid.optimizer.SGD(learning_rate=0.01)
+            sgd.minimize(loss)
+
+        block = program.global_block()
+        for idx, op in enumerate(block.ops):
+            op_desc = op.desc
+            inputs = {}
+            for input_name in op_desc.input_names():
+                inputs[input_name] = op_desc.input(input_name)
+            outputs = {}
+            for output_name in op_desc.output_names():
+                outputs[output_name] = op_desc.output(output_name)
+            attrs = {}
+            for attr_name in op_desc.attr_names():
+                attrs[attr_name] = op_desc.attr(attr_name)
+            if idx == 0:
+                # elementwise_add op
+                self.assertEqual(
+                    core.infer_no_need_buffer_slots(op.type, inputs, outputs,
+                                                    attrs), set([]))
+            elif idx == 1:
+                # fill constant op
+                self.assertEqual(
+                    core.infer_no_need_buffer_slots(op.type, inputs, outputs,
+                                                    attrs), set([]))
+            else:
+                # elementwise_add_grad op
+                self.assertEqual(
+                    core.infer_no_need_buffer_slots(op.type, inputs, outputs,
+                                                    attrs), set(['Y', 'X']))
+
+
+if __name__ == '__main__':
+    unittest.main()