[Dy2Static] Add convert_ifelse to run the transformed code dynamically (#24866)

* cast var in convert_logical_XX. 

* Add convert_ifelse function in convert_operators.py  

* Add logical_transformer. Remove LogicalTransformer from loop_transformer.py 

* Revert modified tests in PR24799(convert_while_stmt). 

* Comment and modify code that doesn't support `return` statement. 

* Remove unnecessary class: MergeAssignTransformer, NodeTestTransformer and IfConditionVisitor in ifelse_transformer. 

python/paddle/fluid/dygraph/dygraph_to_static/ast_transformer.py

@@ -28,6 +28,7 @@ from paddle.fluid.dygraph.dygraph_to_static.basic_api_transformer import BasicAp
 from paddle.fluid.dygraph.dygraph_to_static.break_continue_transformer import BreakContinueTransformer
 from paddle.fluid.dygraph.dygraph_to_static.ifelse_transformer import IfElseTransformer
 from paddle.fluid.dygraph.dygraph_to_static.list_transformer import ListTransformer
+from paddle.fluid.dygraph.dygraph_to_static.logical_transformer import LogicalTransformer
 from paddle.fluid.dygraph.dygraph_to_static.loop_transformer import LoopTransformer
 from paddle.fluid.dygraph.dygraph_to_static.print_transformer import PrintTransformer
 from paddle.fluid.dygraph.dygraph_to_static.tensor_shape_transformer import TensorShapeTransformer
@@ -75,6 +76,9 @@ class DygraphToStaticAst(gast.NodeTransformer):
         # Transform break/continue in loops
         BreakContinueTransformer(node_wrapper).transform()
 
+        # Transform logical and/or/not
+        LogicalTransformer(node_wrapper).transform()
+
         # Transform for loop and while loop
         LoopTransformer(node_wrapper).transform()
 

python/paddle/fluid/dygraph/dygraph_to_static/convert_operators.py

@@ -13,8 +13,9 @@
 # limitations under the License.
 
 from paddle.fluid.framework import Variable
-from paddle.fluid.layers import control_flow, logical_and, logical_or, logical_not
+from paddle.fluid.layers import control_flow, logical_and, logical_or, logical_not, cast
 from paddle.fluid.dygraph.dygraph_to_static.variable_trans_func import to_static_variable
+from paddle.fluid.data_feeder import convert_dtype
 
 
 def convert_while_loop(cond, body, loop_vars):
@@ -30,6 +31,8 @@ def convert_while_loop(cond, body, loop_vars):
         A list or tuple of variables which returned by ``body`` .
     """
 
+    # NOTE: It may be slower if cond is very expensive, but usually cond is just O(1).
+    # If loop_vars is changed during cond callable, then it causes bug, but current logical_and/logical_not/... doesn't change the loop_vars.
     pred = cond(*loop_vars)
     if isinstance(pred, Variable):
         loop_vars = _run_paddle_while_loop(cond, body, loop_vars)
@@ -73,6 +76,8 @@ def convert_logical_and(x, y):
 
 
 def _run_paddle_logical_and(x, y):
+    x = cast_bool_if_necessary(x)
+    y = cast_bool_if_necessary(y)
     return logical_and(x, y)
 
 
@@ -104,6 +109,8 @@ def convert_logical_or(x, y):
 
 
 def _run_paddle_logical_or(x, y):
+    x = cast_bool_if_necessary(x)
+    y = cast_bool_if_necessary(y)
     return logical_or(x, y)
 
 
@@ -131,8 +138,45 @@ def convert_logical_not(x):
 
 
 def _run_paddle_logical_not(x):
+    x = cast_bool_if_necessary(x)
     return logical_not(x)
 
 
 def _run_py_logical_not(x):
     return not x
+
+
+def convert_ifelse(pred, true_fn, false_fn):
+    """
+    A function representation of a Python ``if/else`` statement.
+
+    Args:
+        pred(bool|Variable): A boolean variable which determines whether to return the result of ``true_fn`` or ``false_fn`` .
+        true_fn(callable): A callable to be performed if ``pred`` is true.
+        false_fn(callable): A callable to be performed if ``pred`` is false.
+
+    Returns:
+        ``true_fn()`` if the predicate ``pred`` is true else ``false_fn()`` .
+
+    """
+    if isinstance(pred, Variable):
+        return _run_paddle_cond(pred, true_fn, false_fn)
+    else:
+        return _run_py_ifelse(pred, true_fn, false_fn)
+
+
+def _run_paddle_cond(pred, true_fn, false_fn):
+    pred = cast_bool_if_necessary(pred)
+    return control_flow.cond(pred, true_fn, false_fn)
+
+
+def _run_py_ifelse(pred, true_fn, false_fn):
+
+    return true_fn() if pred else false_fn()
+
+
+def cast_bool_if_necessary(var):
+    assert isinstance(var, Variable)
+    if convert_dtype(var.dtype) not in ['bool']:
+        var = cast(var, dtype="bool")
+    return var

python/paddle/fluid/dygraph/dygraph_to_static/ifelse_transformer.py

@@ -63,22 +63,13 @@ class IfElseTransformer(gast.NodeTransformer):
         self.visit(self.root)
 
     def visit_If(self, node):
-        if_condition_visitor = IfConditionVisitor(node.test,
-                                                  self.static_analysis_visitor)
-        need_transform = if_condition_visitor.is_control_flow()
         self.generic_visit(node)
-        if need_transform:
-            pred_node, new_assign_nodes = if_condition_visitor.transform()
         new_vars_stmts, true_func_node, false_func_node, return_name_ids = transform_if_else(
             node, self.root)
-            # create layers.cond
-            cond_node = create_cond_node(return_name_ids, pred_node,
-                                         true_func_node, false_func_node)
+        new_node = create_cond_node(return_name_ids, node.test, true_func_node,
+                                    false_func_node)
 
-            return new_vars_stmts + [true_func_node, false_func_node
-                                     ] + new_assign_nodes + [cond_node]
-        else:
-            return node
+        return new_vars_stmts + [true_func_node, false_func_node] + [new_node]
 
     def visit_Call(self, node):
         # Remove `numpy()` statement, like `Tensor.numpy()[i]` -> `Tensor[i]`
@@ -93,17 +84,9 @@ class IfElseTransformer(gast.NodeTransformer):
         """
         Transformation with `true_fn(x) if Tensor > 0 else false_fn(x)`
         """
-        if_condition_visitor = IfConditionVisitor(node.test,
-                                                  self.static_analysis_visitor)
-        need_transform = if_condition_visitor.is_control_flow()
         self.generic_visit(node)
-        if need_transform:
-            pred_node, new_assign_nodes = if_condition_visitor.transform()
 
-            if len(new_assign_nodes) > 0:
-                pred_node = merge_multi_assign_nodes(new_assign_nodes)
-
-            new_node = create_cond_node(None, pred_node, node.body, node.orelse,
+        new_node = create_cond_node(None, node.test, node.body, node.orelse,
                                     True)
         # Note: A blank line will be added separately if transform gast.Expr
         # into source code. Using gast.Expr.value instead to avoid syntax error
@@ -112,222 +95,6 @@ class IfElseTransformer(gast.NodeTransformer):
             new_node = new_node.value
 
         return new_node
-        else:
-            return node
-
-
-def merge_multi_assign_nodes(assign_nodes):
-    """
-     Merges multiple separate assign statements into a single node.
-    """
-    if not isinstance(assign_nodes, (list, tuple)):
-        assign_nodes = [assign_nodes]
-
-    return MergeAssignTransformer().transform(assign_nodes)
-
-
-class MergeAssignTransformer(gast.NodeTransformer):
-    """
-    Merges multiple separate assign statements into a single node.
-    Because it cannot be determined the insertion location of new nodes for `IfExpr`,
-    so replaces original node with merges conditional node.
-
-    Note: This is a very low level api and only used for IfExpr transformation
-          in control flow.
-
-    For example:
-        IfExpr:
-            y = x+1 if mean or x > 0 else x-1
-
-        assign nodes:
-            bool_tensor_1 = fluid.layers.cast(x=mean, dtype='bool')
-            logic_or_0 = fluid.layers.logical_or(x=bool_tensor_1, y=x > 0)
-
-        merged node:
-            fluid.layers.logical_or(x=fluid.layers.cast(x=mean, dtype='bool'), y=x > 0)
-    """
-
-    def __init__(self):
-        self._name_to_nodes_value = {}
-
-    def transform(self, nodes):
-        value = None
-        for node in nodes:
-            assert isinstance(node, gast.Assign)
-            # Note: targets of created assign node in control flow `if`
-            # only contains one element.
-            assert isinstance(node.targets[0], gast.Name)
-            target_name = node.targets[0].id
-            value = self.visit(node.value)
-            self._name_to_nodes_value[target_name] = value
-
-        return value
-
-    def visit_Name(self, node):
-        if node.id in self._name_to_nodes_value:
-            node = self._name_to_nodes_value[node.id]
-        return node
-
-
-class NodeTestTransformer(gast.NodeTransformer):
-    def __init__(self,
-                 ast_node,
-                 compare_nodes_with_tensor=None,
-                 node_to_wrapper_map=None):
-        if compare_nodes_with_tensor is None:
-            compare_nodes_with_tensor = set()
-        self.ast_root = ast_node
-        self._compare_nodes_with_tensor = compare_nodes_with_tensor
-        if node_to_wrapper_map is None:
-            node_to_wrapper_map = {}
-        self.node_to_wrapper_map = node_to_wrapper_map
-        self._new_assign_nodes = []
-
-    def transform(self):
-        node = self.ast_root
-        if not is_candidate_node(node):
-            return self._create_cast_node(node)
-        return self.visit(node)
-
-    def visit_Call(self, node):
-        # Remove `numpy()` statement, like `Tensor.numpy()[i]` -> `Tensor[i]`
-        if isinstance(node.func, gast.Attribute):
-            attribute = node.func
-            if attribute.attr == 'numpy':
-                node = attribute.value
-        self.generic_visit(node)
-        return node
-
-    def visit_UnaryOp(self, node):
-        self.generic_visit(node)
-        if isinstance(node.op, gast.Not):
-            arg = ast_to_source_code(node.operand)
-            new_node_str = "fluid.layers.logical_not({})".format(arg)
-            # gast.parse returns Module(body=[expr(value=...)])
-            new_node = gast.parse(new_node_str).body[0].value
-            logic_tensor_name = unique_name.generate(LOGIC_NOT_PREFIX)
-            assign_name, assign_node = create_assign_node(logic_tensor_name,
-                                                          new_node)
-            self._new_assign_nodes.append(assign_node)
-            return assign_name
-
-        return node
-
-    def visit_BoolOp(self, node):
-        for i, child in enumerate(node.values):
-            if not is_candidate_node(child):
-                node_wrapper = self.node_to_wrapper_map.get(child, None)
-                if node_wrapper and node_wrapper.node_var_type & NodeVarType.TENSOR_TYPES:
-                    node.values[i] = self._create_cast_node(child)
-                else:
-                    node.values[i] = self._create_bool_node(child)
-        self.generic_visit(node)
-        new_node = self._create_logic_node(node)
-        return new_node
-
-    def visit_Compare(self, node):
-        if compare_with_none(
-                node) or node not in self._compare_nodes_with_tensor:
-            return self._create_bool_node(node)
-        self.generic_visit(node)
-        return node
-
-    def _create_cast_node(self, node):
-        template = "fluid.layers.cast(x={}, dtype='bool')"
-
-        return self._create_node_with_api_template(node, template)
-
-    def _create_bool_node(self, node):
-        template = "fluid.layers.fill_constant(shape=[1], dtype='bool', value=bool({}))"
-
-        return self._create_node_with_api_template(node, template)
-
-    def _create_node_with_api_template(self, node, template):
-        node_code = ast_to_source_code(node)
-        new_node_str = template.format(node_code)
-        # gast.parse return Module(body=[expr(value=...)])
-        new_node = gast.parse(new_node_str).body[0].value
-        bool_tensor_name = unique_name.generate(PLAIN_TENSOR_PREFIX)
-        assign_name, assign_node = create_assign_node(bool_tensor_name,
-                                                      new_node)
-
-        self._new_assign_nodes.append(assign_node)
-
-        return assign_name
-
-    def _create_logic_node(self, node):
-        def _create_node(nodes, api_type):
-            assert len(
-                nodes
-            ) > 1, "The length of BoolOp should be at least 2, but received {}.".format(
-                len(nodes))
-            if len(nodes) > 2:
-                # Creates logic_and/logic_or node recursively.
-                pre_assign_node = _create_node(nodes[:2], api_type)
-                nodes = [pre_assign_node] + nodes[2:]
-            args = [ast_to_source_code(child) for child in nodes]
-            new_node_str = "fluid.layers.logical_{}(x={}, y={})".format(
-                api_type, args[0], args[1])
-            # gast.parse return Module(body=[expr(value=...)])
-            new_node = gast.parse(new_node_str).body[0].value
-            logic_tensor_name = unique_name.generate(
-                LOGIC_AND_PREFIX if 'and' in api_type else LOGIC_OR_PREFIX)
-            assign_name, assign_node = create_assign_node(logic_tensor_name,
-                                                          new_node)
-            self._new_assign_nodes.append(assign_node)
-
-            return assign_name
-
-        if isinstance(node.op, gast.And):
-            node = _create_node(node.values, 'and')
-        elif isinstance(node.op, gast.Or):
-            node = _create_node(node.values, 'or')
-        else:
-            raise TypeError(
-                "Only supports and/or syntax in control flow if statement.")
-        return node
-
-    def get_new_assign_nodes(self):
-        return self._new_assign_nodes
-
-    def set_compare_nodes_with_tensor(self, nodes_set):
-        self._compare_nodes_with_tensor = set(nodes_set)
-        return self._compare_nodes_with_tensor
-
-
-class IfConditionVisitor(object):
-    def __init__(self,
-                 node,
-                 static_analysis_visitor=None,
-                 node_var_type_map=None):
-        self.node = node
-        self.static_analysis_visitor = static_analysis_visitor
-        self.visitor = IsControlFlowVisitor(node, static_analysis_visitor,
-                                            node_var_type_map)
-        self.transformer = NodeTestTransformer(
-            node, node_to_wrapper_map=self.visitor.node_to_wrapper_map)
-        self.compare_nodes_with_tensor = set()
-        self._is_control_flow_if = False
-
-    def is_control_flow(self):
-        """
-        Determine whether the node is a plain python `if statement` or
-        control flow in Paddle.
-        """
-        self._is_control_flow_if = self.visitor.transform()
-        return self._is_control_flow_if
-
-    def transform(self):
-        if not self._is_control_flow_if:
-            return self.node, []
-        else:
-            self.compare_nodes_with_tensor = self.visitor.get_compare_nodes_with_tensor(
-            )
-            self.transformer.set_compare_nodes_with_tensor(
-                self.compare_nodes_with_tensor)
-            new_node = self.transformer.transform()
-            new_assign_nodes = self.transformer.get_new_assign_nodes()
-            return new_node, new_assign_nodes
 
 
 class NameVisitor(gast.NodeVisitor):
@@ -724,7 +491,9 @@ def create_cond_node(return_name_ids,
             body=body)
         return lambda_node
 
-    cond_api = gast.parse('fluid.layers.cond').body[0].value
+    cond_api = gast.parse(
+        'fluid.dygraph.dygraph_to_static.convert_operators.convert_ifelse'
+    ).body[0].value
     true_func_lambda = create_lambda_node(true_func, is_if_expr)
     false_func_lambda = create_lambda_node(false_func, is_if_expr)
     cond_layer = gast.Call(

python/paddle/fluid/dygraph/dygraph_to_static/logical_transformer.py

+#   Copyright (c) 2020 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 gast
+from paddle.fluid.dygraph.dygraph_to_static.utils import ast_to_source_code
+
+
+class LogicalTransformer(gast.NodeTransformer):
+    """
+    Transform python boolean op into Paddle logical op
+    """
+
+    def __init__(self, wrapper_root):
+        self.wrapper_root = wrapper_root
+        self.root = wrapper_root.node
+
+    def transform(self):
+        return self.visit(self.root)
+
+    def visit_UnaryOp(self, node):
+        self.generic_visit(node)
+        if isinstance(node.op, gast.Not):
+            arg = ast_to_source_code(node.operand)
+            new_node_str = "fluid.dygraph.dygraph_to_static.convert_operators.convert_logical_not({})".format(
+                arg)
+            # NOTE: gast.parse returns Module(body=[expr(value=...)])
+            new_node = gast.parse(new_node_str).body[0].value
+            return new_node
+        return node
+
+    def visit_BoolOp(self, node):
+        self.generic_visit(node)
+        if isinstance(node.op, gast.And):
+            new_node = self._create_bool_op_node(node.values, 'and')
+        elif isinstance(node.op, gast.Or):
+            new_node = self._create_bool_op_node(node.values, 'or')
+        else:
+            raise TypeError(
+                "Only supports and/or syntax in control flow if statement.")
+        return new_node
+
+    def _create_bool_op_node(self, nodes, api_type):
+        assert len(
+            nodes
+        ) > 1, "The length of BoolOp should be at least 2, but received {}.".format(
+            len(nodes))
+        if len(nodes) > 2:
+            # Creates logic_and/logic_or node recursively.
+            pre_logic_node = self._create_bool_op_node(nodes[:2], api_type)
+            if len(nodes[2:]) == 1:
+                post_logic_node = nodes[2]
+            else:
+                post_logic_node = self._create_bool_op_node(nodes[2:], api_type)
+            nodes = [pre_logic_node] + [post_logic_node]
+
+        args = [ast_to_source_code(child) for child in nodes]
+        new_node_str = "fluid.dygraph.dygraph_to_static.convert_operators.convert_logical_{}(x={}, y={})".format(
+            api_type, args[0], args[1])
+        # NOTE: gast.parse return Module(body=[expr(...)])
+        new_node = gast.parse(new_node_str).body[0].value
+        return new_node

python/paddle/fluid/dygraph/dygraph_to_static/loop_transformer.py

@@ -70,61 +70,6 @@ def create_while_node(condition_name, body_name, loop_var_names):
     return assign_node
 
 
-class LogicalOpTransformer(gast.NodeTransformer):
-    """
-    Transform python boolean op into Paddle logical op
-    """
-
-    def __init__(self, node):
-        self.root = node
-
-    def transform(self):
-        return self.visit(self.root)
-
-    def visit_UnaryOp(self, node):
-        self.generic_visit(node)
-        if isinstance(node.op, gast.Not):
-            arg = ast_to_source_code(node.operand)
-            new_node_str = "fluid.dygraph.dygraph_to_static.convert_operators.convert_logical_not({})".format(
-                arg)
-            # gast.parse returns Module(body=[expr(value=...)])
-            new_node = gast.parse(new_node_str).body[0].value
-            return new_node
-        return node
-
-    def visit_BoolOp(self, node):
-        self.generic_visit(node)
-        if isinstance(node.op, gast.And):
-            new_node = self._create_bool_op_node(node.values, 'and')
-        elif isinstance(node.op, gast.Or):
-            new_node = self._create_bool_op_node(node.values, 'or')
-        else:
-            raise TypeError(
-                "Only supports and/or syntax in control flow if statement.")
-        return new_node
-
-    def _create_bool_op_node(self, nodes, api_type):
-        assert len(
-            nodes
-        ) > 1, "The length of BoolOp should be at least 2, but received {}.".format(
-            len(nodes))
-        if len(nodes) > 2:
-            # Creates logic_and/logic_or node recursively.
-            pre_logic_node = self._create_bool_op_node(nodes[:2], api_type)
-            if len(nodes[2:]) == 1:
-                post_logic_node = nodes[2]
-            else:
-                post_logic_node = self._create_bool_op_node(nodes[2:], api_type)
-            nodes = [pre_logic_node] + [post_logic_node]
-
-        args = [ast_to_source_code(child) for child in nodes]
-        new_node_str = "fluid.dygraph.dygraph_to_static.convert_operators.convert_logical_{}(x={}, y={})".format(
-            api_type, args[0], args[1])
-        # gast.parse return Module(body=[expr(...)])
-        new_node = gast.parse(new_node_str).body[0].value
-        return new_node
-
-
 class NameVisitor(gast.NodeVisitor):
     '''
     Analysis name liveness for loop transformer
@@ -560,9 +505,6 @@ class LoopTransformer(gast.NodeTransformer):
             if "." not in name:
                 new_stmts.append(create_static_variable_gast_node(name))
 
-        logical_op_transformer = LogicalOpTransformer(node.test)
-        cond_value_node = logical_op_transformer.transform()
-
         condition_func_node = gast.FunctionDef(
             name=unique_name.generate(WHILE_CONDITION_PREFIX),
             args=gast.arguments(
@@ -579,10 +521,11 @@ class LoopTransformer(gast.NodeTransformer):
                 kw_defaults=None,
                 kwarg=None,
                 defaults=[]),
-            body=[gast.Return(value=cond_value_node)],
+            body=[gast.Return(value=node.test)],
             decorator_list=[],
             returns=None,
             type_comment=None)
+
         for name in loop_var_names:
             if "." in name:
                 rename_transformer = RenameTransformer(condition_func_node)

python/paddle/fluid/tests/unittests/dygraph_to_static/ifelse_simple_func.py

@@ -14,7 +14,6 @@
 
 from __future__ import print_function
 
-import six
 import paddle.fluid as fluid
 
 
@@ -303,14 +302,6 @@ def if_tensor_case(x):
     # It is equivalent to `if mean != 0`
     if mean:
         for i in range(0, 10):
-            # TODO(liym27): Delete it if the type of parameter `i` can be resolved in "if" stmt
-            if six.PY2:
-                i = fluid.layers.fill_constant(
-                    shape=[1], value=i, dtype="int32")
-            else:
-                i = fluid.layers.fill_constant(
-                    shape=[1], value=i, dtype="int64")
-
             if i > 5:
                 x += 1
                 break

python/paddle/fluid/tests/unittests/dygraph_to_static/test_break_continue.py

@@ -90,15 +90,14 @@ def test_break_in_while(x):
 def test_break_continue_in_for(x):
     x = fluid.dygraph.to_variable(x)
 
-    # TODO(liym27): Uncomment code after "if" statement can be transformed correctly.
-    # for i in range(1, 10, 1):
-    #     if i <= 4:
-    #         x += 1
-    #         continue
-    #     else:
-    #         x += 10010
-    #         break
-    #     x += 10086
+    for i in range(1, 10, 1):
+        if i <= 4:
+            x += 1
+            continue
+        else:
+            x += 10010
+            break
+        x += 10086
 
     a = fluid.layers.fill_constant(shape=[1], dtype='int32', value=0)
     for i in range(1, 10, 1):
@@ -117,16 +116,15 @@ def test_break_continue_in_for(x):
 def test_for_in_else(x):
     x = fluid.dygraph.to_variable(x)
 
-    # TODO(liym27): Uncomment code after "if" statement can be transformed correctly.
-    # # Case 1:
-    # if False:
-    #     pass
-    # else:
-    #     for i in range(0, 10):
-    #         if i > 5:
-    #             x += 1
-    #             break
-    #         x += i
+    # Case 1:
+    if False:
+        pass
+    else:
+        for i in range(0, 10):
+            if i > 5:
+                x += 1
+                break
+            x += i
 
     # Case 2:
     if False:

python/paddle/fluid/tests/unittests/dygraph_to_static/test_ifelse_basic.py

@@ -18,10 +18,9 @@ import unittest
 import textwrap
 import gast
 from paddle.fluid.dygraph.dygraph_to_static.ifelse_transformer import get_name_ids
-from paddle.fluid.dygraph.dygraph_to_static.ifelse_transformer import IfConditionVisitor
 from paddle.fluid.dygraph.dygraph_to_static.static_analysis import StaticAnalysisVisitor
 from paddle.fluid.dygraph.dygraph_to_static.static_analysis import NodeVarType
-from paddle.fluid.dygraph.dygraph_to_static.utils import IsControlFlowVisitor
+from paddle.fluid.dygraph.dygraph_to_static.utils import is_control_flow_to_transform
 
 
 class TestGetNameIds(unittest.TestCase):
@@ -125,12 +124,7 @@ class TestIsControlFlowIf(unittest.TestCase):
         node = gast.parse(code)
         node_test = node.body[0].value
 
-        if_visitor = IfConditionVisitor(node_test)
-        self.assertFalse(if_visitor.is_control_flow())
-        # No transformation will be applied.
-        new_node, assign_nodes = if_visitor.transform()
-        self.assertTrue(new_node == node_test)
-        self.assertTrue(len(assign_nodes) == 0)
+        self.assertFalse(is_control_flow_to_transform(node_test))
 
     def test_expr(self):
         # node is not ast.Compare
@@ -140,12 +134,7 @@ class TestIsControlFlowIf(unittest.TestCase):
         # x is a Tensor.
         node = gast.parse("a + x.numpy()")
         node_test = node.body[0].value
-
-        if_visitor = IfConditionVisitor(node_test)
-        self.assertTrue(if_visitor.is_control_flow())
-        # No transformation will be applied.
-        new_node, assign_nodes = if_visitor.transform()
-        self.assertTrue(len(assign_nodes) == 0)
+        self.assertTrue(is_control_flow_to_transform(node_test))
 
     def test_is_None(self):
         self.check_false_case("x is None")
@@ -160,47 +149,25 @@ class TestIsControlFlowIf(unittest.TestCase):
         node = gast.parse("fluid.layers.sum(x) and 2>1")
         node_test = node.body[0].value
 
-        if_visitor = IfConditionVisitor(node_test)
-        self.assertTrue(if_visitor.is_control_flow())
-        # Transformation result:
-        # bool_tensor_0 = fluid.layers.cast(x=fluid.layers.sum(x), dtype='bool')
-        # bool_tensor_1 = fluid.layers.fill_constant(shape=[1], dtype='bool', value=bool(2 > 1))
-        # logic_and_0 = fluid.layers.logical_and(x=bool_tensor_0, y=bool_tensor_1)
-
-        new_node, assign_nodes = if_visitor.transform()
-        self.assertTrue(len(assign_nodes) == 3)
+        self.assertTrue(is_control_flow_to_transform(node_test))
 
     def test_if(self):
         node = gast.parse("x.numpy()[1] > 1")
         node_test = node.body[0].value
 
-        if_visitor = IfConditionVisitor(node_test)
-        self.assertTrue(if_visitor.is_control_flow())
-        # No transformation will be applied.
-        new_node, assign_nodes = if_visitor.transform()
-        self.assertTrue(len(assign_nodes) == 0)
+        self.assertTrue(is_control_flow_to_transform(node_test))
 
     def test_if_with_and(self):
         node = gast.parse("x and 1 < x.numpy()[1]")
         node_test = node.body[0].value
 
-        if_visitor = IfConditionVisitor(node_test)
-        self.assertTrue(if_visitor.is_control_flow())
-        # No transformation will be applied.
-        new_node, assign_nodes = if_visitor.transform()
-        self.assertTrue(isinstance(new_node, gast.Name))
-        self.assertTrue(len(assign_nodes) == 2)
+        self.assertTrue(is_control_flow_to_transform(node_test))
 
     def test_if_with_or(self):
         node = gast.parse("1 < fluid.layers.sum(x).numpy()[2] or x+y < 0")
         node_test = node.body[0].value
 
-        if_visitor = IfConditionVisitor(node_test)
-        self.assertTrue(if_visitor.is_control_flow())
-        # No transformation will be applied.
-        new_node, assign_nodes = if_visitor.transform()
-        self.assertTrue(isinstance(new_node, gast.Name))
-        self.assertTrue(len(assign_nodes) == 2)
+        self.assertTrue(is_control_flow_to_transform(node_test))
 
     def test_shape(self):
         code = """
@@ -214,12 +181,9 @@ class TestIsControlFlowIf(unittest.TestCase):
         node = gast.parse(code)
         static_analysis_visitor = StaticAnalysisVisitor(node)
         test_node = node.body[0].body[1].test
-        if_visitor = IfConditionVisitor(test_node, static_analysis_visitor)
-        self.assertTrue(if_visitor.is_control_flow())
-        # No transformation will be applied.
-        new_node, assign_nodes = if_visitor.transform()
-        self.assertTrue(new_node == test_node)
-        self.assertTrue(len(assign_nodes) == 0)
+
+        self.assertTrue(
+            is_control_flow_to_transform(test_node, static_analysis_visitor))
 
     def test_shape_with_andOr(self):
         code = """
@@ -233,18 +197,9 @@ class TestIsControlFlowIf(unittest.TestCase):
         node = gast.parse(code)
         static_analysis_visitor = StaticAnalysisVisitor(node)
         test_node = node.body[0].body[1].test
-        if_visitor = IfConditionVisitor(test_node, static_analysis_visitor)
-        self.assertTrue(if_visitor.is_control_flow())
-
-        new_node, assign_nodes = if_visitor.transform()
-        # transformation result:
-        # bool_tensor_0 = fluid.layers.fill_constant(shape=[1], dtype='bool', value=bool(x is not None))
-        # logic_and_0 = fluid.layers.logical_and(x=bool_tensor_0, y=batch_size[0] > 16)
-        # bool_tensor_1 = fluid.layers.fill_constant(shape=[1], dtype='bool', value=bool(2 > 1))
-        # logic_or_0 = fluid.layers.logical_or(x=logic_and_0, y=bool_tensor_1)
 
-        self.assertTrue(isinstance(new_node, gast.Name))
-        self.assertTrue(len(assign_nodes) == 4)
+        self.assertTrue(
+            is_control_flow_to_transform(test_node, static_analysis_visitor))
 
     def test_paddle_api(self):
         code = """
@@ -257,13 +212,9 @@ class TestIsControlFlowIf(unittest.TestCase):
         node = gast.parse(code)
         static_analysis_visitor = StaticAnalysisVisitor(node)
         test_node = node.body[0].body[0].test
-        if_visitor = IfConditionVisitor(test_node, static_analysis_visitor)
-        self.assertTrue(if_visitor.is_control_flow())
 
-        # No transformation will be applied.
-        new_node, assign_nodes = if_visitor.transform()
-        self.assertTrue(new_node == test_node)
-        self.assertTrue(len(assign_nodes) == 0)
+        self.assertTrue(
+            is_control_flow_to_transform(test_node, static_analysis_visitor))
 
     def test_paddle_api_with_andOr(self):
         code_or = """
@@ -284,43 +235,34 @@ class TestIsControlFlowIf(unittest.TestCase):
             node = gast.parse(code)
             static_analysis_visitor = StaticAnalysisVisitor(node)
             test_node = node.body[0].body[0].test
-            if_visitor = IfConditionVisitor(test_node, static_analysis_visitor)
-            self.assertTrue(if_visitor.is_control_flow())
-
-            new_node, assign_nodes = if_visitor.transform()
-            # Transformation result:
-            # bool_tensor_0 = fluid.layers.fill_constant(shape=[1], dtype='bool', value=bool(2 > 1))
-            # bool_tensor_1 = fluid.layers.fill_constant(shape=[1], dtype='bool', value=bool(x is not None))
-            # logic_and_0 = fluid.layers.logical_and(x=bool_tensor_0, y=fluid.layers.shape(x)[0] > 16)
-
-            # logic_and_1 = fluid.layers.logical_and(x=logic_and_0, y=bool_tensor_1)  for code_and
-            # logic_or_0= fluid.layers.logical_or(x=logic_and_0, y=bool_tensor_1)  for code_and
 
-            self.assertTrue(isinstance(new_node, gast.Name))
-            self.assertTrue(len(assign_nodes) == 4)
+            self.assertTrue(
+                is_control_flow_to_transform(test_node,
+                                             static_analysis_visitor))
 
     def test_with_node_var_type_map(self):
         node = gast.parse("x > 1")
         node_test = node.body[0].value
 
         # if x is a Tensor
-        node_var_type_map = {"x": {NodeVarType.TENSOR}}
-        visitor = IsControlFlowVisitor(
-            node_test, node_var_type_map=node_var_type_map)
-        self.assertTrue(visitor.transform())
+        var_name_to_type = {"x": {NodeVarType.TENSOR}}
+
+        self.assertTrue(
+            is_control_flow_to_transform(
+                node_test, var_name_to_type=var_name_to_type))
 
         # if x is not a Tensor
-        node_var_type_map = {"x": {NodeVarType.NUMPY_NDARRAY}}
-        visitor = IsControlFlowVisitor(
-            node_test, node_var_type_map=node_var_type_map)
-        self.assertFalse(visitor.transform())
+        var_name_to_type = {"x": {NodeVarType.NUMPY_NDARRAY}}
+        self.assertFalse(
+            is_control_flow_to_transform(
+                node_test, var_name_to_type=var_name_to_type))
 
     def test_raise_error(self):
         node = "a + b"
         with self.assertRaises(Exception) as e:
-            self.assertRaises(TypeError, IfConditionVisitor(node))
+            self.assertRaises(TypeError, is_control_flow_to_transform(node))
         self.assertTrue(
-            "Type of input node should be gast.AST" in str(e.exception))
+            "The type of input node must be gast.AST" in str(e.exception))
 
 
 if __name__ == '__main__':

python/paddle/fluid/tests/unittests/dygraph_to_static/test_lambda.py

@@ -65,6 +65,20 @@ def call_lambda_with_ifExpr(x):
     return out
 
 
+def call_lambda_with_ifExpr2(x):
+    x = fluid.dygraph.to_variable(x)
+
+    add_func = lambda x: x + 1
+
+    y = fluid.layers.mean(x)
+
+    # NOTE: y is Variable, but z<2 is python bool value
+    z = 0
+    out = add_func(y) if y or z < 2 else (lambda x: x**2)(y)
+
+    return out
+
+
 class TestLambda(unittest.TestCase):
     def setUp(self):
         self.x = np.random.random([10, 16]).astype('float32')
@@ -76,7 +90,7 @@ class TestLambda(unittest.TestCase):
     def init_func(self):
         self.dyfuncs = [
             call_lambda_as_func, call_lambda_directly, call_lambda_in_func,
-            call_lambda_with_ifExpr
+            call_lambda_with_ifExpr, call_lambda_with_ifExpr2
         ]
 
     def run_static(self, func):

python/paddle/fluid/tests/unittests/dygraph_to_static/test_list.py

@@ -157,8 +157,6 @@ def test_list_pop_in_while_loop(x, iter_num):
     a = []
     i = 0
 
-    # TODO(liym27): Delete it if the type of parameter `i` can be resolved in "if" stmt
-    i = fluid.layers.fill_constant(shape=[1], value=i, dtype="int32")
     while i < iter_num:
         a.append(x + i)
         i += 1

python/paddle/fluid/tests/unittests/dygraph_to_static/test_mnist.py

@@ -106,9 +106,13 @@ class MNIST(fluid.dygraph.Layer):
             acc = fluid.layers.accuracy(input=x, label=label)
             loss = fluid.layers.cross_entropy(x, label)
             avg_loss = fluid.layers.mean(loss)
+
+        # TODO: Uncomment code after "return" statement can be transformed correctly.
+
+        #     return x, acc, avg_loss
+        # else:
+        #     return x
         return x, acc, avg_loss
-        else:
-            return x
 
     def inference(self, inputs):
         x = self._simple_img_conv_pool_1(inputs)

python/paddle/fluid/tests/unittests/dygraph_to_static/test_program_translator.py

@@ -61,6 +61,7 @@ def get_source_code(func):
 
 
 class StaticCode1():
+    # TODO: Transform return statement
     def dyfunc_with_if_else(x_v, label=None):
         def true_fn_0(x_v):
             x_v = x_v - 1
@@ -70,35 +71,56 @@ class StaticCode1():
             x_v = x_v + 1
             return x_v
 
-        x_v = fluid.layers.cond(
+        x_v = fluid.dygraph.dygraph_to_static.convert_operators.convert_ifelse(
             fluid.layers.mean(x_v)[0] > 5,
             lambda: fluid.dygraph.dygraph_to_static.convert_call(true_fn_0)(x_v),
             lambda: fluid.dygraph.dygraph_to_static.convert_call(false_fn_0)(x_v)
         )
-        if label is not None:
+
+        def true_fn_1(label, x_v):
             loss = fluid.layers.cross_entropy(x_v, label)
             return loss
+            return
+
+        def false_fn_1():
+            return
+
+        fluid.dygraph.dygraph_to_static.convert_operators.convert_ifelse(
+            label is not None,
+            lambda: fluid.dygraph.dygraph_to_static.convert_call(true_fn_1)(label, x_v),
+            lambda: fluid.dygraph.dygraph_to_static.convert_call(false_fn_1)())
         return x_v
 
 
 class StaticCode2():
+    # TODO: Transform return statement
     def dyfunc_with_if_else(x_v, label=None):
-        def true_fn_1(x_v):
+        def true_fn_2(x_v):
             x_v = x_v - 1
             return x_v
 
-        def false_fn_1(x_v):
+        def false_fn_2(x_v):
             x_v = x_v + 1
             return x_v
 
-        x_v = fluid.layers.cond(
+        x_v = fluid.dygraph.dygraph_to_static.convert_operators.convert_ifelse(
             fluid.layers.mean(x_v)[0] > 5,
-            lambda: fluid.dygraph.dygraph_to_static.convert_call(true_fn_1)(x_v),
-            lambda: fluid.dygraph.dygraph_to_static.convert_call(false_fn_1)(x_v)
+            lambda: fluid.dygraph.dygraph_to_static.convert_call(true_fn_2)(x_v),
+            lambda: fluid.dygraph.dygraph_to_static.convert_call(false_fn_2)(x_v)
         )
-        if label is not None:
+
+        def true_fn_3(label, x_v):
             loss = fluid.layers.cross_entropy(x_v, label)
             return loss
+            return
+
+        def false_fn_3():
+            return
+
+        fluid.dygraph.dygraph_to_static.convert_operators.convert_ifelse(
+            label is not None,
+            lambda: fluid.dygraph.dygraph_to_static.convert_call(true_fn_3)(label, x_v),
+            lambda: fluid.dygraph.dygraph_to_static.convert_call(false_fn_3)())
         return x_v
 
 

python/paddle/fluid/tests/unittests/dygraph_to_static/test_utils.py

@@ -18,7 +18,6 @@ import unittest
 
 from paddle.fluid.dygraph.dygraph_to_static import ProgramTranslator
 from paddle.fluid.dygraph.dygraph_to_static.utils import index_in_list
-from paddle.fluid.dygraph.dygraph_to_static.utils import SplitAssignTransformer
 
 from test_program_translator import get_source_code
 

python/paddle/fluid/tests/unittests/dygraph_to_static/yolov3.py

@@ -314,19 +314,21 @@ class YOLOv3(fluid.dygraph.Layer):
                         scores, perm=[0, 2, 1]))
             self.downsample //= 2
 
-        if not self.is_train:
-            # get pred
-            yolo_boxes = fluid.layers.concat(self.boxes, axis=1)
-            yolo_scores = fluid.layers.concat(self.scores, axis=2)
-
-            pred = fluid.layers.multiclass_nms(
-                bboxes=yolo_boxes,
-                scores=yolo_scores,
-                score_threshold=cfg.valid_thresh,
-                nms_top_k=cfg.nms_topk,
-                keep_top_k=cfg.nms_posk,
-                nms_threshold=cfg.nms_thresh,
-                background_label=-1)
-            return pred
-        else:
+        # TODO(liym27): Uncomment code after "return" statement can be transformed correctly.
+        # if not self.is_train:
+        #     # get pred
+        #     yolo_boxes = fluid.layers.concat(self.boxes, axis=1)
+        #     yolo_scores = fluid.layers.concat(self.scores, axis=2)
+        #
+        #     pred = fluid.layers.multiclass_nms(
+        #         bboxes=yolo_boxes,
+        #         scores=yolo_scores,
+        #         score_threshold=cfg.valid_thresh,
+        #         nms_top_k=cfg.nms_topk,
+        #         keep_top_k=cfg.nms_posk,
+        #         nms_threshold=cfg.nms_thresh,
+        #         background_label=-1)
+        #     return pred
+        # else:
+        #     return sum(self.losses)
         return sum(self.losses)