Support Simple For Range Loop in Dygraph to Static (#22867)

1. Add basic support for `for in range` loop
2. Move `test_dygraph_to_static_*` to `dygraph_to_static` dir and rename them
3. Add test case for dict in while_loop

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

@@ -21,6 +21,8 @@ from collections import defaultdict
 from paddle.fluid import unique_name
 from paddle.fluid.dygraph.dygraph_to_static.utils import generate_name_node
 from paddle.fluid.dygraph.dygraph_to_static.static_analysis import AstNodeWrapper
+from paddle.fluid.dygraph.dygraph_to_static.utils import get_constant_variable_node
+from paddle.fluid.dygraph.dygraph_to_static.utils import get_attribute_full_name
 from paddle.fluid.dygraph.dygraph_to_static.variable_trans_func import create_static_variable_gast_node
 from paddle.fluid.dygraph.dygraph_to_static.variable_trans_func import to_static_variable_gast_node
 
@@ -29,6 +31,9 @@ __all__ = ['LoopTransformer', 'NameVisitor']
 WHILE_CONDITION_PREFIX = 'while_condition'
 WHILE_BODY_PREFIX = 'while_body'
 
+FOR_CONDITION_PREFIX = 'for_loop_condition'
+FOR_BODY_PREFIX = 'for_loop_body'
+
 
 def create_while_node(condition_name, body_name, loop_var_names):
     while_args = []
@@ -63,13 +68,16 @@ class NameVisitor(gast.NodeVisitor):
     '''
 
     def __init__(self, root_node):
-        # Set of gast.Name
+        # Set of gast.Name or gast.Attribute for variables
         self.current_seen_vars = set()
+        # list of nodes of current visit node
+        self.ancestor_nodes = []
+
         # List of gast.While/gast.For nodes
         self.current_loop = []
 
-        # Mapping from gast.While/gast.For to string name of vars
-        self.before_loop_vars = defaultdict(set)
+        # Mapping from gast.While/gast.For to variable nodes
+        self.before_loop_body_vars = defaultdict(set)
         self.in_loop_vars = defaultdict(set)
 
         self.visit(root_node)
@@ -86,13 +94,12 @@ class NameVisitor(gast.NodeVisitor):
         read_context = {type(gast.Load()), type(gast.AugLoad())}
 
         in_loop_vars = self.in_loop_vars[node]
-        in_loop_name_strs = set(name.id for name in in_loop_vars)
-        before_loop_vars = self.before_loop_vars[node]
-        before_loop_name_strs = set(name.id for name in before_loop_vars)
-        after_loop_vars = self.current_seen_vars - before_loop_vars - in_loop_vars
-        after_loop_name_strs = set(
-            name.id for name in after_loop_vars
-            if type(name.ctx) in read_context)
+        in_loop_name_strs = self._var_nodes_to_names(in_loop_vars)
+        before_loop_body_vars = self.before_loop_body_vars[node]
+        before_loop_name_strs = self._var_nodes_to_names(before_loop_body_vars)
+        after_loop_vars = self.current_seen_vars - before_loop_body_vars - in_loop_vars
+        after_loop_name_strs = self._var_nodes_to_names(after_loop_vars,
+                                                        read_context)
         for name in in_loop_name_strs:
             if name in before_loop_name_strs:
                 # If a variable is used in loop and created before loop, it
@@ -106,23 +113,65 @@ class NameVisitor(gast.NodeVisitor):
         return loop_var_names, create_var_names
 
     def visit_Name(self, node):
+        if self._is_call_func_name_node(node):
+            self.generic_visit(node)
+            return
+
         self.current_seen_vars.add(node)
         for loop_node in self.current_loop:
             self.in_loop_vars[loop_node].add(node)
         self.generic_visit(node)
 
+    def visit(self, node):
+        self.ancestor_nodes.append(node)
+        method = 'visit_' + node.__class__.__name__
+        visitor = getattr(self, method, self.generic_visit)
+        ret = visitor(node)
+        self.ancestor_nodes.pop()
+        return ret
+
+    def visit_Attribute(self, node):
+        if self._is_call_func_name_node(node):
+            return
+
+        attr_full_name = get_attribute_full_name(node)
+        self.current_seen_vars.add(node)
+        for loop_node in self.current_loop:
+            self.in_loop_vars[loop_node].add(node)
+        # sub-nodes are visited during get_attribute_full_name and we shouldn't
+        # visit again
+
     def visit_For(self, node):
         self.current_loop.append(node)
-        self.before_loop_vars[node] = copy.copy(self.current_seen_vars)
+        self.visit(node.target)
+        self.before_loop_body_vars[node] = copy.copy(self.current_seen_vars)
         self.generic_visit(node)
         self.current_loop.pop()
 
     def visit_While(self, node):
         self.current_loop.append(node)
-        self.before_loop_vars[node] = copy.copy(self.current_seen_vars)
+        self.visit(node.test)
+        self.before_loop_body_vars[node] = copy.copy(self.current_seen_vars)
         self.generic_visit(node)
         self.current_loop.pop()
 
+    def _var_nodes_to_names(self, node_set, ctx_filter_set=None):
+        ret = set()
+        for node in node_set:
+            if ctx_filter_set is None or type(node.ctx) in ctx_filter_set:
+                if isinstance(node, gast.Name):
+                    ret.add(node.id)
+                elif isinstance(node, gast.Attribute):
+                    ret.add(get_attribute_full_name(node))
+        return ret
+
+    def _is_call_func_name_node(self, node):
+        if self.ancestor_nodes:
+            parent_node = self.ancestor_nodes[-1]
+            if isinstance(parent_node, gast.Call) and parent_node.func == node:
+                return True
+        return False
+
 
 class LoopTransformer(gast.NodeTransformer):
     """
@@ -140,11 +189,6 @@ class LoopTransformer(gast.NodeTransformer):
     def transform(self):
         self.visit(self.root)
 
-    def get_for_stmt_nodes(self, node):
-        self.generic_visit(node)
-        # TODO
-        return node
-
     def visit(self, node):
         self.generic_visit(node)
         # All parent nodes that may contain gast.While/gast.For
@@ -165,15 +209,166 @@ class LoopTransformer(gast.NodeTransformer):
                 body_list[i:i + 1] = new_stmts
                 i += len(new_stmts)
             elif isinstance(body_list[i], gast.For):
-                # TODO
-                i += 1
+                new_stmts = self.get_for_stmt_nodes(body_list[i])
+                body_list[i:i + 1] = new_stmts
+                i += len(new_stmts)
             else:
                 i += 1
 
+    def get_for_range_node(self, node):
+        if not isinstance(node.iter, gast.Call):
+            return None
+        if not isinstance(node.iter.func, gast.Name):
+            return None
+        if node.iter.func.id != "range":
+            return None
+        return node.iter
+
+    def get_for_args_stmts(self, iter_name, args_list):
+        '''
+        Returns 3 gast stmt nodes for argument.
+        1. Initailize of iterate variable
+        2. Condition for the loop
+        3. Statement for changing of iterate variable during the loop
+        NOTE(TODO): Python allows to access iteration variable after loop, such
+           as "for i in range(10)" will create i = 9 after the loop. But using
+           current conversion will make i = 10. We should find a way to change it
+        '''
+        len_range_args = len(args_list)
+        assert len_range_args >= 1 and len_range_args <= 3, "range() function takes 1 to 3 arguments"
+        if len_range_args == 1:
+            init_stmt = get_constant_variable_node(iter_name, 0)
+        else:
+            init_stmt = gast.Assign(
+                targets=[
+                    gast.Name(
+                        id=iter_name,
+                        ctx=gast.Store(),
+                        annotation=None,
+                        type_comment=None)
+                ],
+                value=args_list[0])
+
+        range_max_node = args_list[0] if len_range_args == 1 else args_list[1]
+        step_node = args_list[2] if len_range_args == 3 else gast.Constant(
+            value=1, kind=None)
+
+        cond_stmt = gast.Compare(
+            left=gast.BinOp(
+                left=gast.Name(
+                    id=iter_name,
+                    ctx=gast.Load(),
+                    annotation=None,
+                    type_comment=None),
+                op=gast.Add(),
+                right=step_node),
+            ops=[gast.LtE()],
+            comparators=[range_max_node])
+
+        change_stmt = gast.AugAssign(
+            target=gast.Name(
+                id=iter_name,
+                ctx=gast.Store(),
+                annotation=None,
+                type_comment=None),
+            op=gast.Add(),
+            value=step_node)
+
+        return init_stmt, cond_stmt, change_stmt
+
+    def get_for_stmt_nodes(self, node):
+        # TODO: consider for - else in python
+        if not self.name_visitor.is_control_flow_loop(node):
+            return [node]
+
+        # TODO: support non-range case
+        range_call_node = self.get_for_range_node(node)
+        if range_call_node is None:
+            return [node]
+
+        if not isinstance(node.target, gast.Name):
+            return [node]
+        iter_var_name = node.target.id
+
+        init_stmt, cond_stmt, change_stmt = self.get_for_args_stmts(
+            iter_var_name, range_call_node.args)
+
+        loop_var_names, create_var_names = self.name_visitor.get_loop_var_names(
+            node)
+        new_stmts = []
+        # Python can create variable in loop and use it out of loop, E.g.
+        #
+        # for x in range(10):
+        #     y += x
+        # print(x) # x = 10
+        #
+        # We need to create static variable for those variables
+        for name in create_var_names:
+            new_stmts.append(create_static_variable_gast_node(name))
+
+        new_stmts.append(init_stmt)
+
+        # for x in range(10) in dygraph should be convert into static tensor + 1 <= 10
+        for name in loop_var_names:
+            new_stmts.append(to_static_variable_gast_node(name))
+
+        condition_func_node = gast.FunctionDef(
+            name=unique_name.generate(FOR_CONDITION_PREFIX),
+            args=gast.arguments(
+                args=[
+                    gast.Name(
+                        id=name,
+                        ctx=gast.Param(),
+                        annotation=None,
+                        type_comment=None) for name in loop_var_names
+                ],
+                posonlyargs=[],
+                vararg=None,
+                kwonlyargs=[],
+                kw_defaults=None,
+                kwarg=None,
+                defaults=[]),
+            body=[gast.Return(value=cond_stmt)],
+            decorator_list=[],
+            returns=None,
+            type_comment=None)
+        new_stmts.append(condition_func_node)
+
+        new_body = node.body
+        new_body.append(change_stmt)
+        new_body.append(
+            gast.Return(value=generate_name_node(
+                loop_var_names, ctx=gast.Load())))
+        body_func_node = gast.FunctionDef(
+            name=unique_name.generate(FOR_BODY_PREFIX),
+            args=gast.arguments(
+                args=[
+                    gast.Name(
+                        id=name,
+                        ctx=gast.Param(),
+                        annotation=None,
+                        type_comment=None) for name in loop_var_names
+                ],
+                posonlyargs=[],
+                vararg=None,
+                kwonlyargs=[],
+                kw_defaults=None,
+                kwarg=None,
+                defaults=[]),
+            body=new_body,
+            decorator_list=[],
+            returns=None,
+            type_comment=None)
+        new_stmts.append(body_func_node)
+
+        while_loop_node = create_while_node(condition_func_node.name,
+                                            body_func_node.name, loop_var_names)
+        new_stmts.append(while_loop_node)
+
+        return new_stmts
+
     def get_while_stmt_nodes(self, node):
         # TODO: consider while - else in python
-        # self.generic_visit(node)
-
         if not self.name_visitor.is_control_flow_loop(node):
             return [node]
 

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

@@ -215,6 +215,18 @@ def create_api_shape_node(tensor_shape_node):
     return api_shape_node
 
 
+def get_constant_variable_node(name, value, shape=[1], dtype='int64'):
+    return gast.parse('%s = fluid.layers.fill_constant(%s, "%s", %s)' %
+                      (name, str(shape), dtype, str(value)))
+
+
+def get_attribute_full_name(node):
+    assert isinstance(
+        node,
+        gast.Attribute), "Input non-Attribute node to get attribute full name"
+    return astor.to_source(gast.gast_to_ast(node)).strip()
+
+
 def generate_name_node(name_ids, ctx=gast.Load()):
     """
     Generate list or gast.Tuple of ast.Name for Return statement.

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

@@ -14,6 +14,7 @@
 
 from __future__ import print_function
 
+import six
 import gast
 
 from paddle.fluid.layers import fill_constant
@@ -39,8 +40,15 @@ def to_static_variable(x):
     '''
     if isinstance(x, bool):
         return fill_constant(shape=[1], dtype='bool', value=x)
-    if isinstance(x, int):
-        return fill_constant(shape=[1], dtype='int64', value=x)
     if isinstance(x, float):
         return fill_constant(shape=[1], dtype='float64', value=x)
+
+    if six.PY2:
+        if isinstance(x, int):
+            return fill_constant(shape=[1], dtype='int32', value=x)
+        if isinstance(x, long):
+            return fill_constant(shape=[1], dtype='int64', value=x)
+    else:
+        if isinstance(x, int):
+            return fill_constant(shape=[1], dtype='int64', value=x)
     return x

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

@@ -59,7 +59,17 @@ class SubNetWithDict(fluid.dygraph.Layer):
             cache_k, cache_v = cache["k"], cache["v"]
             k = 0.1 * cache_k + k
             v = 0.2 * cache_v + v
-            cache["k"], cache["v"] = k, v
+            # TODO: currently while_loop can have a dict as loop_vars, but
+            # to change the value in a dict, you have to use layers.assign
+            # because cache["k"] = k is putting k in dict without building
+            # network. So we cannot write:
+            #
+            # cache["k"], cache["v"] = k, v
+            #
+            # we have to support this kind of dict in loop in the future.
+            # For example, automatically change = to assign in AutoTracer
+            fluid.layers.assign(k, cache["k"])
+            fluid.layers.assign(v, cache["v"])
 
         weight = fluid.layers.matmul(x=q, y=k, transpose_y=True)
         weight = fluid.layers.softmax(weight)
@@ -94,12 +104,20 @@ class MainNetWithDict(fluid.dygraph.Layer):
         for i in range(max_len):
             out = self.sub_net(out, cache)
             cache = self.update_cache(cache)
-
         return out
 
     def update_cache(self, cache):
         for k, val in six.iteritems(cache):
-            cache[k] = fluid.layers.softmax(val)
+            # TODO: currently while_loop can have a dict as loop_vars, but
+            # to change the value in a dict, you have to use layers.assign
+            # because cache["k"] = k is putting k in dict without building
+            # network. So we cannot write:
+            #
+            # cache[k] = fluid.layers.softmax(val)
+            #
+            # we have to support this kind of dict in loop in the future.
+            # For example, automatically change = to assign in AutoTracer
+            fluid.layers.assign(fluid.layers.softmax(val), cache[k])
 
         return cache
 

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

@@ -35,20 +35,34 @@ def while_loop_dyfunc(x):
     return i
 
 
+def for_loop_dyfunc(max_len):
+    for i in range(max_len):
+        ret = fluid.layers.zeros(shape=[1], dtype='float32')
+        fluid.layers.increment(ret, value=2.0, in_place=True)
+    return ret
+
+
 class TestNameVisitor(unittest.TestCase):
+    def setUp(self):
+        self.loop_funcs = [while_loop_dyfunc, for_loop_dyfunc]
+        self.loop_var_names = [set(["i", "x"]), set(["i", "ret", "max_len"])]
+        self.create_var_names = [set(), set(["ret"])]
+
     def test_loop_vars(self):
-        test_func = inspect.getsource(while_loop_dyfunc)
+        for i in range(len(self.loop_funcs)):
+            func = self.loop_funcs[i]
+            test_func = inspect.getsource(func)
             gast_root = gast.parse(test_func)
             name_visitor = NameVisitor(gast_root)
             for node in gast.walk(gast_root):
-            if isinstance(node, gast.While):
+                if isinstance(node, (gast.While, gast.For)):
                     loop_var_names, create_var_names = name_visitor.get_loop_var_names(
                         node)
-                self.assertEqual(loop_var_names, set(["i", "x"]))
-                self.assertEqual(create_var_names, set())
+                    self.assertEqual(loop_var_names, self.loop_var_names[i])
+                    self.assertEqual(create_var_names, self.create_var_names[i])
 
 
-class TestTransformWhile(unittest.TestCase):
+class TestTransformWhileLoop(unittest.TestCase):
     def setUp(self):
         self.place = fluid.CUDAPlace(0) if fluid.is_compiled_with_cuda(
         ) else fluid.CPUPlace()
@@ -83,5 +97,35 @@ class TestTransformWhile(unittest.TestCase):
         # self.assertTrue(np.allclose(self._run_dygraph(), self._run_static()))
 
 
+class TestTransformForLoop(unittest.TestCase):
+    def setUp(self):
+        self.place = fluid.CUDAPlace(0) if fluid.is_compiled_with_cuda(
+        ) else fluid.CPUPlace()
+        self.len = 100
+
+    def _run_static(self):
+        main_program = fluid.Program()
+        with fluid.program_guard(main_program):
+            static_func = dygraph_to_static_graph(for_loop_dyfunc)
+            out = static_func(self.len)
+            exe = fluid.Executor(self.place)
+            ret = exe.run(main_program, fetch_list=out)
+        return ret
+
+    def _run_dygraph(self):
+        with fluid.dygraph.guard(self.place):
+            ret = for_loop_dyfunc(self.len)
+            return ret.numpy()
+
+    def test_ast_to_func(self):
+        static_numpy = self._run_static()
+        self.assertTrue(
+            np.allclose(
+                np.full(
+                    shape=(1), fill_value=2, dtype=np.int32), static_numpy))
+        self._run_dygraph()
+        self.assertTrue(np.allclose(self._run_dygraph(), self._run_static()))
+
+
 if __name__ == '__main__':
     unittest.main()

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

@@ -77,6 +77,34 @@ class TestApiWhileLoop(unittest.TestCase):
             data = np.add(data, data_one)
         self.assertTrue(np.allclose(np.asarray(res[1]), data))
 
+    def test_var_dict(self):
+        def cond(i, ten, test_dict):
+            return layers.less_than(i, ten)
+
+        def body(i, ten, test_dict):
+            layers.assign(i, test_dict["test_key"])
+            i = layers.increment(i)
+            return [i, ten, test_dict]
+
+        main_program = Program()
+        startup_program = Program()
+        with program_guard(main_program, startup_program):
+            i = layers.zeros(shape=[1], dtype='int64')
+            ten = layers.fill_constant(shape=[1], dtype='int64', value=10)
+            test_data = layers.fill_constant(shape=[1], dtype='int64', value=0)
+            test_dict = {"test_key": test_data}
+            i, ten, test_dict = layers.while_loop(cond, body,
+                                                  [i, ten, test_dict])
+        place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
+        ) else fluid.CPUPlace()
+        exe = fluid.Executor(place)
+        res = exe.run(main_program, fetch_list=[test_dict["test_key"]])
+        self.assertTrue(
+            np.allclose(
+                np.asarray(res[0]),
+                np.full(
+                    shape=(1), fill_value=9, dtype=np.int64)))
+
 
 class TestApiWhileLoop_Nested(unittest.TestCase):
     def test_nested_net(self):