diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec
index 1bd4376f9157722a9a33c52ae4e644d7d42a5c5a..3378d210cdf6a625e11b1dd5fe348aa04cdb9361 100644
--- a/paddle/fluid/API.spec
+++ b/paddle/fluid/API.spec
@@ -103,7 +103,7 @@ paddle.fluid.layers.beam_search ArgSpec(args=['pre_ids', 'pre_scores', 'ids', 's
 paddle.fluid.layers.row_conv ArgSpec(args=['input', 'future_context_size', 'param_attr', 'act'], varargs=None, keywords=None, defaults=(None, None))
 paddle.fluid.layers.multiplex ArgSpec(args=['inputs', 'index'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.layers.layer_norm ArgSpec(args=['input', 'scale', 'shift', 'begin_norm_axis', 'epsilon', 'param_attr', 'bias_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(True, True, 1, 1e-05, None, None, None, None))
-paddle.fluid.layers.softmax_with_cross_entropy ArgSpec(args=['logits', 'label', 'soft_label', 'ignore_index', 'numeric_stable_mode'], varargs=None, keywords=None, defaults=(False, -100, False))
+paddle.fluid.layers.softmax_with_cross_entropy ArgSpec(args=['logits', 'label', 'soft_label', 'ignore_index', 'numeric_stable_mode', 'return_softmax'], varargs=None, keywords=None, defaults=(False, -100, False, False))
 paddle.fluid.layers.smooth_l1 ArgSpec(args=['x', 'y', 'inside_weight', 'outside_weight', 'sigma'], varargs=None, keywords=None, defaults=(None, None, None))
 paddle.fluid.layers.one_hot ArgSpec(args=['input', 'depth'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.layers.autoincreased_step_counter ArgSpec(args=['counter_name', 'begin', 'step'], varargs=None, keywords=None, defaults=(None, 1, 1))
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index d3623464e9974246708206d2204ed52ae74e2d0f..43d5ec1b52527cb4376aa796427717550545a546 100644
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -4742,7 +4742,8 @@ def softmax_with_cross_entropy(logits,
                                label,
                                soft_label=False,
                                ignore_index=-100,
-                               numeric_stable_mode=False):
+                               numeric_stable_mode=False,
+                               return_softmax=False):
     """
     **Softmax With Cross Entropy Operator.**
 
@@ -4806,9 +4807,15 @@ def softmax_with_cross_entropy(logits,
                                     the algorithm is always numerically stable. 
                                     Note that the speed may be slower when use 
                                     stable algorithm. Default: False
+        return_softmax (bool): A flag indicating whether to return the softmax 
+                               along with the cross entropy loss. Default: False
 
     Returns:
-        Variable: The cross entropy loss is a 2-D tensor with shape [N x 1].
+        Variable or Tuple of two Variables: Return the cross entropy loss if 
+                              `return_softmax` is False, otherwise the tuple 
+                              (loss, softmax), where the cross entropy loss is 
+                              a 2-D tensor with shape [N x 1], and softmax is a 
+                              2-D tensor with shape [N x K].
 
     Examples:
         .. code-block:: python
@@ -4833,6 +4840,10 @@ def softmax_with_cross_entropy(logits,
             'ignore_index': ignore_index,
             'numeric_stable_mode': numeric_stable_mode
         })
+
+    if return_softmax:
+        return loss, softmax
+
     return loss
 
 
diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py
index f48d9c84f9c10b0eff8e41a510d168543c9795fa..a8fa5436c43d2f05f632b920f67d43d837d28da9 100644
--- a/python/paddle/fluid/tests/unittests/test_layers.py
+++ b/python/paddle/fluid/tests/unittests/test_layers.py
@@ -369,6 +369,10 @@ class TestBook(unittest.TestCase):
         with program_guard(program):
             x = layers.data(name='x', shape=[16], dtype='float32')
             y = layers.data(name='label', shape=[1], dtype='int64')
+            loss, softmax = layers.softmax_with_cross_entropy(
+                x, y, return_softmax=True)
+            self.assertIsNotNone(loss)
+            self.assertIsNotNone(softmax)
             loss = layers.softmax_with_cross_entropy(x, y)
             self.assertIsNotNone(loss)
         print(str(program))