add @deprecated for reduce_mean

PaddlePaddle · Aug 12, 2020 · 2d14150 · 2d14150
1 parent 80b2cb7
commit 2d14150
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Showing 2 changed files with 1 addition and 64 deletions.
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
@@ -4397,6 +4397,7 @@ def reduce_sum(input, dim=None, keep_dim=False, name=None):
     return out
 
 
+@deprecated(since="2.0.0", update_to="paddle.mean")
 def reduce_mean(input, dim=None, keep_dim=False, name=None):
     """
     Computes the mean of the input tensor's elements along the given dimension.

diff --git a/python/paddle/fluid/tests/unittests/test_reduce_op.py b/python/paddle/fluid/tests/unittests/test_reduce_op.py
@@ -628,70 +628,6 @@ def test_1(self):
         self.assertEqual((np_z == z_expected).all(), True)
 
 
-class API_TestMaxOp(unittest.TestCase):
-    def test_1(self):
-        # type: float
-        with fluid.program_guard(fluid.Program(), fluid.Program()):
-            data = fluid.data("data", shape=[10, 10], dtype="float32")
-            result_max = paddle.max(input=data, dim=1)
-            place = fluid.CPUPlace()
-            exe = fluid.Executor(place)
-            input_data = np.random.rand(10, 10).astype(np.float32)
-            res, = exe.run(feed={"data": input_data}, fetch_list=[result_max])
-        self.assertEqual((res == np.max(input_data, axis=1)).all(), True)
-
-        # type: int
-        with fluid.program_guard(fluid.Program(), fluid.Program()):
-            data = fluid.data("data", shape=[10, 10], dtype="int64")
-            result_max = paddle.max(input=data, dim=1)
-            place = fluid.CPUPlace()
-            exe = fluid.Executor(place)
-            input_data = np.random.randint(10, size=(10, 10)).astype(np.int64)
-            res, = exe.run(feed={"data": input_data}, fetch_list=[result_max])
-        self.assertEqual((res == np.max(input_data, axis=1)).all(), True)
-
-        # dygraph
-        with fluid.dygraph.guard():
-            np_x = np.array([10, 10]).astype('float64')
-            x = fluid.dygraph.to_variable(np_x)
-            z = paddle.max(x, dim=0)
-            np_z = z.numpy()
-            z_expected = np.array(np.max(np_x, axis=0))
-        self.assertEqual((np_z == z_expected).all(), True)
-
-
-class API_TestMinOp(unittest.TestCase):
-    def test_1(self):
-        # type: float
-        with fluid.program_guard(fluid.Program(), fluid.Program()):
-            data = fluid.data("data", shape=[10, 10], dtype="float32")
-            result_min = paddle.min(input=data, dim=1)
-            place = fluid.CPUPlace()
-            exe = fluid.Executor(place)
-            input_data = np.random.rand(10, 10).astype(np.float32)
-            res, = exe.run(feed={"data": input_data}, fetch_list=[result_min])
-        self.assertEqual((res == np.min(input_data, axis=1)).all(), True)
-
-        # type: int
-        with fluid.program_guard(fluid.Program(), fluid.Program()):
-            data = fluid.data("data", shape=[10, 10], dtype="int64")
-            result_min = paddle.min(input=data, dim=1)
-            place = fluid.CPUPlace()
-            exe = fluid.Executor(place)
-            input_data = np.random.randint(10, size=(10, 10)).astype(np.int64)
-            res, = exe.run(feed={"data": input_data}, fetch_list=[result_min])
-        self.assertEqual((res == np.min(input_data, axis=1)).all(), True)
-
-        # dygraph
-        with fluid.dygraph.guard():
-            np_x = np.array([10, 10]).astype('float64')
-            x = fluid.dygraph.to_variable(np_x)
-            z = paddle.min(x, dim=0)
-            np_z = z.numpy()
-            z_expected = np.array(np.min(np_x, axis=0))
-        self.assertEqual((np_z == z_expected).all(), True)
-
-
 class API_TestReduceMeanOp(unittest.TestCase):
     def test_static(self):
         with fluid.program_guard(fluid.Program(), fluid.Program()):