[[Dy2Static]]convert for stmt and support variable loaded and created in loop(#24901)

* Move function 'convert_len' to file convert_operators.py 

* Support that for statements are transformed to while statements.

* Fix bug: raise None -> return None. 

* Support variable loaded and created in loop.

* Use int64 in Py2 and Py3 in function to_static_variable.

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

@@ -1,47 +0,0 @@
-# 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
-
-from paddle.fluid import framework
-from paddle.fluid import core
-from paddle.fluid.layers import nn
-from paddle.fluid.layers import control_flow
-
-
-def convert_len(var):
-    """
-    return variable(length) from shape ops based on var.type
-
-    Note: In addition to some ast transformations, some block-related
-          operations are added in `len` transformation, such as appending
-          `shape_op` in var.block.
-    """
-    if isinstance(var, framework.Variable):
-        if var.type in [
-                core.VarDesc.VarType.LOD_TENSOR,
-                core.VarDesc.VarType.SELECTED_ROWS
-        ]:
-            # Note: Length of var may be known ahead of time in dygraph,
-            # but it probably represents batch size which can be variant.
-            # so we return a variable dynamically inferred from var.shape.
-            return nn.shape(var)[0]
-        elif var.type == core.VarDesc.VarType.LOD_TENSOR_ARRAY:
-            return control_flow.array_length(var)
-        else:
-            raise TypeError(
-                'len(var) only supports LoDTensor/LoDTensorArray/SelectedRows, but received %s.'
-                % type(var))
-    else:
-        return len(var)

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

@@ -29,7 +29,7 @@ import six
 
 from paddle.fluid.dygraph.dygraph_to_static import ProgramTranslator
 from paddle.fluid.dygraph.layers import Layer
-from paddle.fluid.dygraph.dygraph_to_static.convert_builtins_func import convert_len
+from paddle.fluid.dygraph.dygraph_to_static.convert_operators import convert_len
 
 DECORATOR_NAMES = ['declarative', 'dygraph_to_static_func']
 program_translator = ProgramTranslator()

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

@@ -12,10 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from paddle.fluid.framework import Variable
-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
+from paddle.fluid.dygraph.dygraph_to_static.variable_trans_func import to_static_variable
+from paddle.fluid.framework import Variable, core
+from paddle.fluid.layers import cast, control_flow, logical_and, logical_not, logical_or, nn
 
 
 def convert_while_loop(cond, body, loop_vars):
@@ -175,6 +175,33 @@ def _run_py_ifelse(pred, true_fn, false_fn):
     return true_fn() if pred else false_fn()
 
 
+def convert_len(var):
+    """
+    Returns variable(length) from shape ops based on var.type
+
+    Note: In addition to some ast transformations, some block-related
+          operations are added in `len` transformation, such as appending
+          `shape_op` in var.block.
+    """
+    if isinstance(var, Variable):
+        if var.type in [
+                core.VarDesc.VarType.LOD_TENSOR,
+                core.VarDesc.VarType.SELECTED_ROWS
+        ]:
+            # Note: Length of var may be known ahead of time in dygraph,
+            # but it probably represents batch size which can be variant.
+            # so we return a variable dynamically inferred from var.shape.
+            return nn.shape(var)[0]
+        elif var.type == core.VarDesc.VarType.LOD_TENSOR_ARRAY:
+            return control_flow.array_length(var)
+        else:
+            raise TypeError(
+                'len(var) only supports LoDTensor/LoDTensorArray/SelectedRows, but received %s.'
+                % type(var))
+    else:
+        return len(var)
+
+
 def cast_bool_if_necessary(var):
     assert isinstance(var, Variable)
     if convert_dtype(var.dtype) not in ['bool']:

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

@@ -22,14 +22,11 @@ from paddle.fluid import unique_name
 from paddle.fluid.dygraph.dygraph_to_static.static_analysis import AstNodeWrapper
 from paddle.fluid.dygraph.dygraph_to_static.static_analysis import NodeVarType
 from paddle.fluid.dygraph.dygraph_to_static.static_analysis import StaticAnalysisVisitor
-from paddle.fluid.dygraph.dygraph_to_static.utils import ast_to_source_code
 from paddle.fluid.dygraph.dygraph_to_static.utils import generate_name_node
 from paddle.fluid.dygraph.dygraph_to_static.utils import get_attribute_full_name
-from paddle.fluid.dygraph.dygraph_to_static.utils import is_control_flow_to_transform
 from paddle.fluid.dygraph.dygraph_to_static.utils import ForNodeVisitor
 from paddle.fluid.dygraph.dygraph_to_static.utils import RenameTransformer
 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
 
 __all__ = ['LoopTransformer', 'NameVisitor']
 
@@ -89,7 +86,8 @@ class NameVisitor(gast.NodeVisitor):
 
         # Mapping from gast.While/gast.For to variable nodes
         self.before_loop_body_vars = defaultdict(set)
-        self.in_loop_vars = defaultdict(set)
+        # NOTE: Use ordered list as dict value
+        self.in_loop_vars = defaultdict(list)
 
         # Mapping from gast.While/gast.For to variable nodes which is condition
         # of loop or being modified during the loop
@@ -103,11 +101,6 @@ class NameVisitor(gast.NodeVisitor):
 
         self.visit(root_node)
 
-    def is_control_flow_loop(self, node):
-        need_transform = is_control_flow_to_transform(
-            node, self.static_analysis_visitor)
-        return need_transform
-
     def get_loop_var_names(self, node):
         assert isinstance(
             node, (gast.While, gast.For)), "Input node is not gast loop node"
@@ -115,7 +108,15 @@ class NameVisitor(gast.NodeVisitor):
         create_var_names = set()
         read_context = {type(gast.Load()), type(gast.AugLoad())}
 
-        in_loop_vars = self.in_loop_vars[node]
+        in_loop_vars_list = self.in_loop_vars[node]
+
+        # get dict `var_name_to_ctxs`
+        var_name_to_ctxs = defaultdict(list)
+        for var_node in in_loop_vars_list:
+            var_name_to_ctxs[self._var_node_to_name(var_node)].append(
+                var_node.ctx)
+
+        in_loop_vars = set(in_loop_vars_list)
         in_loop_name_strs = self._var_nodes_to_names(in_loop_vars)
 
         before_loop_body_vars = self.before_loop_body_vars[node]
@@ -160,6 +161,22 @@ class NameVisitor(gast.NodeVisitor):
                 # vars out
                 loop_var_names.add(name)
                 create_var_names.add(name)
+            else:
+                # If a variable is used and created in loop, but used before created,
+                # it should be in loop_var and we should create it.
+
+                # For example, `var_a` should be in loop_var and we should create it.
+                #
+                #   res = 0
+                #   for i, x in enumerate(x_array):
+                #       if i > 2:
+                #           x = func1(var_a)
+                #       var_a = func2(x)
+                #
+
+                if isinstance(var_name_to_ctxs[name][0], gast.Load):
+                    loop_var_names.add(name)
+                    create_var_names.add(name)
 
         return loop_var_names, create_var_names
 
@@ -176,7 +193,7 @@ class NameVisitor(gast.NodeVisitor):
             type(gast.Store()), type(gast.AugStore()), type(gast.Del())
         }
         for loop_node in self.current_loop:
-            self.in_loop_vars[loop_node].add(node)
+            self.in_loop_vars[loop_node].append(node)
             if type(node.ctx) in write_context:
                 self.write_in_loop[loop_node].add(node)
         if self.in_condition:
@@ -219,7 +236,7 @@ class NameVisitor(gast.NodeVisitor):
         self.current_seen_vars.add(node)
 
         for loop_node in self.current_loop:
-            self.in_loop_vars[loop_node].add(node)
+            self.in_loop_vars[loop_node].append(node)
 
         # sub-nodes are visited during get_attribute_full_name and we shouldn't
         # visit again
@@ -367,27 +384,25 @@ class LoopTransformer(gast.NodeTransformer):
     def get_for_stmt_nodes(self, node):
         # TODO: consider for - else in python
 
-        # 1. check whether need to transform
-        # NOTE: Current need transform cases:
-        #   1). for x in range(VarBase[0]|VarBase.numpy()[0])
-        #   2). for x in VarBase|VarBase.numpy()
-        #   3). for i, x in enumerate(VarBase|VarBase.numpy())
-        if not self.name_visitor.is_control_flow_loop(node):
-            return [node]
-
-        # 2. get key statements for different cases
-        # NOTE: three key statements:
+        # 1. get key statements for different cases
+        # NOTE 1: three key statements:
         #   1). init_stmts: list[node], prepare nodes of for loop, may not only one
         #   2). cond_stmt: node, condition node to judge whether continue loop
         #   3). body_stmts: list[node], updated loop body, sometimes we should change
         #       the original statement in body, not just append new statement
+        #
+        # NOTE 2: The following `for` statements will be transformed to `while` statements:
+        #   1). for x in range(*)
+        #   2). for x in iter_var
+        #   3). for i, x in enumerate(*)
+
         current_for_node_parser = ForNodeVisitor(node)
         stmts_tuple = current_for_node_parser.parse()
         if stmts_tuple is None:
             return [node]
         init_stmts, cond_stmt, body_stmts = stmts_tuple
 
-        # 3. get original loop vars
+        # 2. get original loop vars
         loop_var_names, create_var_names = self.name_visitor.get_loop_var_names(
             node)
         # NOTE: in 'for x in var' or 'for i, x in enumerate(var)' cases,
@@ -402,7 +417,7 @@ class LoopTransformer(gast.NodeTransformer):
             if iter_var_name not in create_var_names:
                 loop_var_names.remove(iter_var_name)
 
-        # 4. prepare result statement list
+        # 3. prepare result statement list
         new_stmts = []
         # Python can create variable in loop and use it out of loop, E.g.
         #
@@ -415,13 +430,10 @@ class LoopTransformer(gast.NodeTransformer):
             if "." not in name:
                 new_stmts.append(create_static_variable_gast_node(name))
 
-        # 5. append init statements
+        # 4. append init statements
         new_stmts.extend(init_stmts)
-        # 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))
 
-        # 6. create & append condition function node
+        # 5. create & append condition function node
         condition_func_node = gast.FunctionDef(
             name=unique_name.generate(FOR_CONDITION_PREFIX),
             args=gast.arguments(
@@ -449,7 +461,7 @@ class LoopTransformer(gast.NodeTransformer):
                     name, unique_name.generate(GENERATE_VARIABLE_PREFIX))
         new_stmts.append(condition_func_node)
 
-        # 7. create & append loop body function node
+        # 6. create & append loop body function node
         # append return values for loop body
         body_stmts.append(
             gast.Return(value=generate_name_node(
@@ -481,7 +493,7 @@ class LoopTransformer(gast.NodeTransformer):
                     name, unique_name.generate(GENERATE_VARIABLE_PREFIX))
         new_stmts.append(body_func_node)
 
-        # 8. create & append while loop node 
+        # 7. create & append while loop node
         while_loop_node = create_while_node(condition_func_node.name,
                                             body_func_node.name, loop_var_names)
         new_stmts.append(while_loop_node)

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

@@ -38,7 +38,7 @@ dygraph_class_to_static_api = {
 }
 
 FOR_ITER_INDEX_PREFIX = '__for_loop_var_index'
-FOR_ITER_VAR_SHAPE_PREFIX = '__for_loop_var_shape'
+FOR_ITER_VAR_LEN_PREFIX = '__for_loop_var_len'
 
 
 def _is_api_in_module_helper(obj, module_prefix):
@@ -668,7 +668,7 @@ class ForNodeVisitor(object):
 
     In this process, the semantics of for does not change.
 
-    Now only can parse 3 type statements (Here var is VarBase(Tensor)):
+    Now only can parse 3 type statements (Here var is VarBase(Tensor) or python variable):
         1). for x in range(var[*]|var.numpy()[*])
         2). for x in var|var.numpy()
         3). for i, x enumerate(var|var.numpy())
@@ -700,12 +700,11 @@ class ForNodeVisitor(object):
         #   - for i, x enumerate(var|var.numpy())
         self.iter_idx_name = unique_name.generate(FOR_ITER_INDEX_PREFIX)
 
-        # - created shape var to build loop condition: __for_loop_var_shape_0
+        # - created shape var to build loop condition: __for_loop_var_len_0
         #   - for x in var|var.numpy()
         #   - for i, x enumerate(var|var.numpy())
         #   - for x in var
-        self.iter_var_shape_name = unique_name.generate(
-            FOR_ITER_VAR_SHAPE_PREFIX)
+        self.iter_var_len_name = unique_name.generate(FOR_ITER_VAR_LEN_PREFIX)
 
         # - var.numpy()/var
         #   - for x in var|var.numpy()
@@ -728,7 +727,7 @@ class ForNodeVisitor(object):
         elif self.is_for_enumerate_iter():
             return self._parse_for_enumerate_stmts()
         else:
-            raise None
+            return None
 
     def is_for_range_iter(self):
         return isinstance(self.node.iter, gast.Call) and isinstance(
@@ -736,7 +735,7 @@ class ForNodeVisitor(object):
             gast.Name) and self.node.iter.func.id == "range"
 
     def is_for_iter(self):
-        if isinstance(self.node.iter, gast.Name):
+        if isinstance(self.node.iter, (gast.Name, gast.Attribute)):
             return True
         elif isinstance(self.node.iter, gast.Call) and isinstance(
                 self.node.iter.func,
@@ -776,7 +775,7 @@ class ForNodeVisitor(object):
     def _parse_for_stmts(self):
         init_stmts = []
         init_stmts.append(self._build_index_init_node())
-        init_stmts.append(self._build_var_shape_assign_node())
+        init_stmts.append(self._build_var_len_assign_node())
 
         compare_node = self._build_compare_node()
         step_node = self._build_step_node()
@@ -794,7 +793,7 @@ class ForNodeVisitor(object):
     def _parse_for_enumerate_stmts(self):
         init_stmts = []
         init_stmts.append(self._build_index_init_node())
-        init_stmts.append(self._build_var_shape_assign_node())
+        init_stmts.append(self._build_var_len_assign_node())
         init_stmts.append(self._build_enum_init_node())
 
         compare_node = self._build_compare_node()
@@ -814,51 +813,49 @@ class ForNodeVisitor(object):
     def _build_index_init_node(self):
         if self.is_for_range_iter():
             if self.args_length == 1:
-                index_init_node = get_constant_variable_node(self.iter_var_name,
-                                                             0)
+                index_init_value_str = '0'
             else:
-                index_init_node = gast.Assign(
-                    targets=[
-                        gast.Name(
-                            id=self.iter_var_name,
-                            ctx=gast.Store(),
-                            annotation=None,
-                            type_comment=None)
-                    ],
-                    value=self.iter_args[0])
+                index_init_value_str = ast_to_source_code(self.iter_args[
+                    0]).strip()
+
+            index_init_var_name = self.iter_var_name
         else:
-            index_init_node = get_constant_variable_node(self.iter_idx_name, 0)
+            index_init_value_str = '0'
+            index_init_var_name = self.iter_idx_name
+
+        index_init_node_source_str = "{target} = {value}".format(
+            target=index_init_var_name, value=index_init_value_str)
+
+        index_init_node = gast.parse(index_init_node_source_str).body[0]
+
         return index_init_node
 
-    def _build_var_shape_assign_node(self):
-        # get variable shape as iter length
-        if isinstance(self.iter_node, gast.Call):
-            iter_var = self.iter_node.func
+    def _build_var_len_assign_node(self):
+        # get the length of iterable variable
+        if isinstance(self.iter_node, gast.Call) and isinstance(
+                self.iter_node.func,
+                gast.Attribute) and self.iter_node.func.attr == 'numpy':
+            iter_var_name = ast_to_source_code(self.iter_node.func.value).strip(
+            )
         else:
-            iter_var = self.iter_node
-        return gast.Assign(
-            targets=[
-                gast.Name(
-                    id=self.iter_var_shape_name,
-                    ctx=gast.Load(),
-                    annotation=None,
-                    type_comment=None)
-            ],
-            value=create_api_shape_node(iter_var))
+            iter_var_name = ast_to_source_code(self.iter_node).strip()
+
+        convert_len_node_source_str = '{} = fluid.dygraph.dygraph_to_static.convert_operators.convert_len({})'.format(
+            self.iter_var_len_name, iter_var_name)
+
+        convert_len_node = gast.parse(convert_len_node_source_str).body[0]
+
+        return convert_len_node
 
     def _build_enum_init_node(self):
-        enum_init_node = get_constant_variable_node(
-            name=self.enum_idx_name, value=0)
         if self.is_for_enumerate_iter() and self.args_length != 1:
-            enum_init_node = gast.Assign(
-                targets=[
-                    gast.Name(
-                        id=self.enum_idx_name,
-                        ctx=gast.Store(),
-                        annotation=None,
-                        type_comment=None)
-                ],
-                value=self.iter_args[1])
+            init_value_str = ast_to_source_code(self.iter_args[1]).strip()
+        else:
+            init_value_str = '0'
+
+        enum_init_node_source_str = "{} = {}".format(self.enum_idx_name,
+                                                     init_value_str)
+        enum_init_node = gast.parse(enum_init_node_source_str).body[0]
         return enum_init_node
 
     def _build_compare_node(self):
@@ -866,15 +863,11 @@ class ForNodeVisitor(object):
             compare_node = self.iter_args[
                 0] if self.args_length == 1 else self.iter_args[1]
         else:
-            compare_node = gast.Subscript(
-                value=gast.Name(
-                    id=self.iter_var_shape_name,
-                    ctx=gast.Load(),
-                    annotation=None,
-                    type_comment=None),
-                slice=gast.Index(value=gast.Constant(
-                    value=0, kind=None)),
-                ctx=gast.Load())
+            compare_node = gast.Name(
+                id=self.iter_var_len_name,
+                ctx=gast.Load(),
+                annotation=None,
+                type_comment=None)
         return compare_node
 
     def _build_step_node(self):

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

@@ -118,11 +118,10 @@ def to_static_variable(x):
         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):
+        if isinstance(x, (int, 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_loop.py

@@ -84,6 +84,16 @@ def for_loop_dyfunc(max_len):
     return ret
 
 
+def for_loop_dyfunc2(max_len):
+    # Test case: a variable is used and created in loop, but used before created
+    for i in range(max_len):
+        if i > 1:
+            s = a
+        a = 1
+    ret = fluid.layers.fill_constant(shape=[1], dtype="int32", value=s)
+    return ret
+
+
 def while_loop_bool_op(x):
     i = fluid.dygraph.to_variable(x)
 
@@ -131,7 +141,6 @@ def for_loop_class_var(max_len):
     foo = Foo()
 
     # Use `to_variable` so that static analysis can analyze the type of X is Tensor
-    # TODO(liym27): Delete it if the type of parameter x can be resolved
     max_len = fluid.layers.fill_constant(
         shape=[1], value=max_len, dtype="int32")
 
@@ -298,6 +307,11 @@ class TestTransformForLoop(unittest.TestCase):
         self.assertTrue(np.allclose(self._run_dygraph(), self._run_static()))
 
 
+class TestTransformForLoop2(TestTransformForLoop):
+    def _init_dyfunc(self):
+        self.dyfunc = for_loop_dyfunc2
+
+
 class TestClassVarInForLoop(TestTransformForLoop):
     def _init_dyfunc(self):
         self.dyfunc = for_loop_class_var