fix alpha dropout bug when p=1, test=develop

Author: huangjun12

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

@@ -43,7 +43,7 @@ def test_check_grad_normal(self):
 class TestDropoutOpInput1d(OpTest):
     def setUp(self):
         self.op_type = "dropout"
-        self.inputs = {'X': np.random.random((2000)).astype("float32")}
+        self.inputs = {'X': np.random.random((2000, )).astype("float32")}
         self.attrs = {'dropout_prob': 0.0, 'fix_seed': True, 'is_test': False}
         self.outputs = {
             'Out': self.inputs['X'],
@@ -672,9 +672,11 @@ def check_static_result(self, place):
             res1 = paddle.nn.functional.alpha_dropout(x=input, p=0.)
             res2 = paddle.nn.functional.alpha_dropout(
                 x=input, p=0., training=False)
+            res3 = paddle.nn.functional.alpha_dropout(x=input, p=1.)
 
             in_np = np.random.random([40, 40]).astype("float32")
             res_np = in_np
+            res_np3 = np.zeros_like(in_np)
 
             exe = fluid.Executor(place)
             res_list = [res1, res2]
@@ -683,6 +685,10 @@ def check_static_result(self, place):
                                   feed={"input": in_np},
                                   fetch_list=[res])
                 self.assertTrue(np.allclose(fetches[0], res_np))
+            fetches = exe.run(fluid.default_main_program(),
+                              feed={"input": in_np},
+                              fetch_list=[res3])
+            self.assertTrue(np.allclose(fetches[0], res_np3))
 
     def test_static(self):
         for place in self.places:
@@ -693,15 +699,18 @@ def test_dygraph(self):
             with fluid.dygraph.guard(place):
                 in_np = np.random.random([40, 40]).astype("float32")
                 res_np = in_np
+                res_np3 = np.zeros_like(in_np)
                 input = fluid.dygraph.to_variable(in_np)
 
                 res1 = paddle.nn.functional.alpha_dropout(x=input, p=0.)
                 res2 = paddle.nn.functional.alpha_dropout(
                     x=input, p=0., training=False)
+                res3 = paddle.nn.functional.alpha_dropout(x=input, p=1.)
 
             res_list = [res1, res2]
             for res in res_list:
                 self.assertTrue(np.allclose(res.numpy(), res_np))
+            self.assertTrue(np.allclose(res3.numpy(), res_np3))
 
 
 class TestAlphaDropoutFAPIError(unittest.TestCase):

python/paddle/nn/functional/common.py

@@ -1091,6 +1091,8 @@ def alpha_dropout(x, p=0.5, training=True, name=None):
                                  'alpha_dropout')
 
     if training:
+        if p == 1:
+            return layers.scale(x, scale=0.)
         #get transformation params
         alpha = 1.6732632423543772848170429916717
         scale = 1.0507009873554804934193349852946