add python interface of sub_graph

paddle/fluid/pybind/ir.cc

@@ -125,7 +125,15 @@ void BindGraph(py::module *m) {
            return_value_policy::reference)
       .def("resolve_hazard", &Graph::ResolveHazard)
       .def("origin_program_desc", &Graph::OriginProgram,
-           return_value_policy::reference);
+           return_value_policy::reference)
+      .def("sub_graph_size", &Graph::SubGraphsSize)
+      .def("get_sub_graph", [](Graph &self, int i) {
+        /* Here we use a lambda function as an empty deleter to avoid the double
+        free of smart pointer.
+        Otherwise, this shared pointer will be free both in python and
+        cpp scope, which will lead a core dumped. */
+        return std::shared_ptr<Graph>(self.GetSubGraph(i), [](Graph *) {});
+      });
 }
 
 void BindNode(py::module *m) {

python/paddle/fluid/framework.py

@@ -3956,6 +3956,23 @@ def all_op_nodes(self):
         """
         return {IrOpNode(node) for node in self.graph.nodes() if node.is_op()}
 
+    def all_sub_graphs(self, for_test=False):
+        """
+        Return all sub_graphs included in the main graph as a set.
+        """
+
+        return [
+            IrGraph(
+                self.graph.get_sub_graph(i), for_test=for_test)
+            for i in range(self.graph.sub_graph_size())
+        ]
+
+    def get_sub_graph(self, i, for_test=False):
+        """
+        Return i-th sub_graph in the main graph.
+        """
+        return IrGraph(self.graph.get_sub_graph(i), for_test=for_test)
+
     def create_persistable_node(self, name, var_type, shape, var_dtype):
         """
         Create a persistable variable node in the graph. In IrGraph,
@@ -4102,8 +4119,10 @@ def link_to(self, node_in, node_out):
             node_in(IrNode): the input node.
             node_out(IrNode): the output node.
         """
-        assert node_in.node in self.graph.nodes() and node_out.node in self.graph.nodes(), \
-            'The two arguments(node_in&node_out) must be in the graph nodes.'
+        assert node_in.node in self.graph.nodes(), (
+            'node_in(%s) must be in the graph nodes.' % node_in.node.name())
+        assert node_out.node in self.graph.nodes(), (
+            'node_out(%s) must be in the graph nodes.' % node_out.node.name())
         node_in.append_output(node_out)
         node_out.append_input(node_in)
 
@@ -4265,7 +4284,8 @@ def _find_node_by_name(self, nodes, node_name):
         for n in nodes:
             if n.name() == node_name:
                 target_node = n
-        assert target_node is not None, "Cannot find the target node in the giving set."
+        assert target_node is not None, (
+            "Cannot find the target node (%s)in the giving set." % node_name)
         return target_node
 
     def _update_desc_attr(self, desc, name, val):

python/paddle/fluid/tests/unittests/ir/test_ir_subgraph_python_interface.py

@@ -0,0 +1,96 @@
+# Copyright (c) 2021 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.
+
+import unittest
+import paddle
+import paddle.fluid as fluid
+import six
+
+from paddle.fluid.framework import IrGraph
+from paddle.fluid.framework import IrNode
+from paddle.fluid.tests.unittests.op_test import OpTestTool
+from paddle.fluid import core
+import paddle.fluid.layers as layers
+from paddle.fluid.framework import Program, program_guard, default_startup_program
+from paddle.fluid.contrib.slim.quantization import QuantizationTransformPass
+
+paddle.enable_static()
+
+
+class TestQuantizationSubGraph(unittest.TestCase):
+    def build_graph_with_sub_graph(self):
+        def linear_fc(num):
+            data = fluid.layers.data(
+                name='image', shape=[1, 32, 32], dtype='float32')
+            label = fluid.layers.data(name='label', shape=[1], dtype='int64')
+            hidden = data
+            for _ in six.moves.xrange(num):
+                hidden = fluid.layers.fc(hidden, size=128, act='relu')
+            loss = fluid.layers.cross_entropy(input=hidden, label=label)
+            loss = fluid.layers.mean(loss)
+            return loss
+
+        main_program = Program()
+        startup_program = Program()
+
+        def true_func():
+            return linear_fc(3)
+
+        def false_func():
+            return linear_fc(5)
+
+        with program_guard(main_program, startup_program):
+            x = layers.fill_constant(shape=[1], dtype='float32', value=0.1)
+            y = layers.fill_constant(shape=[1], dtype='float32', value=0.23)
+            pred = layers.less_than(y, x)
+            out = layers.cond(pred, true_func, false_func)
+
+        core_graph = core.Graph(main_program.desc)
+        # We should create graph for test, otherwise it will throw a 
+        # error that it cannot find the node of "STEP_COUNTER"
+        graph = IrGraph(core_graph, for_test=True)
+        sub_graph = graph.get_sub_graph(0)
+        all_sub_graphs = graph.all_sub_graphs(
+            for_test=True)  # same reason for subgraph
+        # Should return graph and sub_graphs at the same time. If only return sub_graph, the graph will
+        # be destructed and the sub_graphs will be empty.
+        return graph, all_sub_graphs
+
+    def test_quant_sub_graphs(self, use_cuda=False):
+        graph, sub_graphs = self.build_graph_with_sub_graph()
+        place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
+        transform_pass = QuantizationTransformPass(
+            scope=fluid.global_scope(),
+            place=place,
+            activation_quantize_type='abs_max',
+            weight_quantize_type='range_abs_max')
+        Find_inserted_quant_op = False
+        for sub_graph in sub_graphs:
+            transform_pass.apply(sub_graph)
+            for op in sub_graph.all_op_nodes():
+                if 'quantize' in op.name():
+                    Find_inserted_quant_op = True
+        self.assertTrue(Find_inserted_quant_op)
+
+    def test_quant_sub_graphs_cpu(self):
+        self.test_quant_sub_graphs(use_cuda=False)
+
+    @OpTestTool.skip_if(not paddle.is_compiled_with_cuda(),
+                        "Not GPU version paddle")
+    def test_quant_sub_graphs_gpu(self):
+        self.test_quant_sub_graphs(use_cuda=True)
+
+
+if __name__ == '__main__':
+    unittest.main()