Merge pull request #13339 from chengduoZH/debug_while_op

Enable nested WhileOp

Author: reyoung

paddle/fluid/operators/while_op.cc

@@ -63,7 +63,7 @@ class WhileOp : public framework::OperatorBase {
     while (cond.data<bool>()[0]) {
       auto &current_scope = scope.NewScope();
       step_scopes->push_back(&current_scope);
-      executor.RunPreparedContext(ctx.get(), &current_scope, false);
+      executor.RunPreparedContext(ctx.get(), &current_scope, false, true, true);
       if (is_test) {
         scope.DeleteScope(&current_scope);
       }
@@ -169,7 +169,8 @@ class WhileGradOp : public framework::OperatorBase {
           }
         }
       }
-      executor.RunPreparedContext(ctx.get(), *cur_scope_iter, false);
+      executor.RunPreparedContext(ctx.get(), *cur_scope_iter, false, true,
+                                  true);
 
       auto &pg_names = Outputs(kXGRAD);
       auto &p_names = Inputs(kX);

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

@@ -1,4 +1,4 @@
-#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2018 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.
@@ -30,8 +30,10 @@ def test_simple_forward(self):
             "d1", shape=[10], append_batch_size=False, dtype='float32')
         d2 = layers.data(
             "d2", shape=[10], append_batch_size=False, dtype='float32')
+
         i = layers.zeros(shape=[1], dtype='int64')
         i.stop_gradient = True
+
         init = layers.zeros(shape=[10], dtype='float32')
         mem_array = layers.array_write(x=init, i=i)
         data_array = layers.array_write(x=d0, i=i)
@@ -45,11 +47,19 @@ def test_simple_forward(self):
         i = layers.zeros(shape=[1], dtype='int64')
         i.stop_gradient = True
 
-        array_len = layers.fill_constant(shape=[1], dtype='int64', value=3)
+        array_len = layers.fill_constant(shape=[1], dtype='int64', value=1)
         array_len.stop_gradient = True
         cond = layers.less_than(x=i, y=array_len)
 
+        j = layers.fill_constant(shape=[1], dtype='int64', value=1)
+        j.stop_gradient = True
+
+        array_len2 = layers.fill_constant(shape=[1], dtype='int64', value=3)
+        array_len2.stop_gradient = True
+        cond2 = layers.less_than(x=j, y=array_len2)
+
         while_op = layers.While(cond=cond)
+        while_op2 = layers.While(cond=cond2)
         with while_op.block():
             d = layers.array_read(array=data_array, i=i)
             prev = layers.array_read(array=mem_array, i=i)
@@ -59,7 +69,16 @@ def test_simple_forward(self):
             layers.array_write(result, i=i, array=mem_array)
             layers.less_than(x=i, y=array_len, cond=cond)
 
-        sum_result = layers.array_read(array=mem_array, i=i)
+            with while_op2.block():
+                d2 = layers.array_read(array=data_array, i=j)
+                prev2 = layers.array_read(array=mem_array, i=j)
+                result2 = layers.sums(input=[d2, prev2])
+
+                j = layers.increment(x=j, in_place=True)
+                layers.array_write(result2, i=j, array=mem_array)
+                layers.less_than(x=j, y=array_len2, cond=cond2)
+
+        sum_result = layers.array_read(array=mem_array, i=j)
         loss = layers.mean(sum_result)
 
         append_backward(loss)