（fluid API clear）remove fluid.layers.brelu in nn.py under fluid (#47898)

* remove brelu in nn.py under fluid

* add brelu op test case

python/paddle/fluid/layers/nn.py

@@ -115,7 +115,6 @@ __all__ = [
     'log',
     'crop_tensor',
     'prelu',
-    'brelu',
     'flatten',
     'pad2d',
     'unique',
@@ -7831,52 +7830,6 @@ def prelu(x, mode, param_attr=None, data_format="NCHW", name=None):
     return out
 
 
-@templatedoc()
-def brelu(x, t_min=0.0, t_max=24.0, name=None):
-    """
-    ${comment}
-    Args:
-        x(${x_type}): ${x_comment}
-        t_min(${t_min_type}|0.0): ${t_min_comment}
-        t_max(${t_max_type}|24.0): ${t_max_comment}
-        name(str|None): The default value is None. Normally there is no need for user to set this property.
-                        For more information, please refer to :ref:`api_guide_Name`.
-    Returns:
-        ${out_type}: ${out_comment}
-
-    Examples:
-
-    .. code-block:: python
-
-            import paddle.fluid as fluid
-            import paddle
-            import numpy as np
-            paddle.enable_static()
-
-            input_brelu = np.array([[-1,6],[1,15.6]])
-            with fluid.dygraph.guard():
-                x = fluid.dygraph.to_variable(input_brelu)
-                y = fluid.layers.brelu(x, t_min=1.0, t_max=10.0)
-                print(y.numpy())
-                #[[ 1.  6.]
-                #[ 1. 10.]]
-    """
-    if _non_static_mode():
-        return _legacy_C_ops.brelu(x, 't_min', t_min, 't_max', t_max)
-
-    check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], 'brelu')
-
-    helper = LayerHelper('brelu', **locals())
-    out = helper.create_variable_for_type_inference(dtype=x.dtype)
-    helper.append_op(
-        type='brelu',
-        inputs={'X': x},
-        outputs={'Out': out},
-        attrs={'t_min': t_min, 't_max': t_max},
-    )
-    return out
-
-
 def flatten(x, axis=1, name=None):
     r"""
     **Flatten op**

python/paddle/fluid/tests/unittests/ipu/test_activation_ops_ipu.py

@@ -63,7 +63,7 @@ class TestBase(IPUOpTest):
         self.check()
 
 
-class TestBReluCase0(TestBase):
+class TestHardTanhCase0(TestBase):
     def set_data_feed(self):
         data = np.random.uniform(size=[1, 3, 10, 10]) * 30
         self.feed_fp32 = {'in_0': data.astype(np.float32)}
@@ -71,14 +71,14 @@ class TestBReluCase0(TestBase):
         self.feed_list = list(self.feed_fp32.keys())
 
     def set_test_op(self):
-        self.op = paddle.fluid.layers.brelu
+        self.op = paddle.nn.functional.hardtanh
         self.op_attrs = {}
 
 
-class TestBReluCase1(TestBReluCase0):
+class TestHardTanhCase1(TestHardTanhCase0):
     def set_test_op(self):
-        self.op = paddle.fluid.layers.brelu
-        self.op_attrs = {"t_min": 0.1, 't_max': 10.0}
+        self.op = paddle.nn.functional.hardtanh
+        self.op_attrs = {"min": 0.1, 'max': 10.0}
 
 
 class TestEluCase1(TestBase):

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

@@ -1891,51 +1891,6 @@ class TestBRelu(TestActivation):
         self.check_grad(['X'], 'Out')
 
 
-class TestBreluAPI(unittest.TestCase):
-    # test paddle.fluid.layers.brelu
-    def setUp(self):
-        np.random.seed(1024)
-        self.t_min = 0.0
-        self.t_max = 24.0
-        self.x_np = np.random.uniform(-1, 30, [10, 12]).astype('float32')
-        self.out_ref = np.copy(self.x_np)
-        self.out_ref[self.out_ref < self.t_min] = self.t_min
-        self.out_ref[self.out_ref > self.t_max] = self.t_max
-        self.out_ref = self.out_ref.astype('float32')
-        self.place = (
-            paddle.CUDAPlace(0)
-            if paddle.is_compiled_with_cuda()
-            else paddle.CPUPlace()
-        )
-
-    def test_fluid_api(self):
-        with paddle.static.program_guard(paddle.static.Program()):
-            x = paddle.static.data('X', [10, 12])
-            out = paddle.fluid.layers.brelu(x)
-            exe = paddle.static.Executor(self.place)
-            res = exe.run(feed={'X': self.x_np}, fetch_list=[out])
-            np.testing.assert_allclose(self.out_ref, res[0], rtol=1e-05)
-
-            paddle.disable_static(self.place)
-            x = paddle.to_tensor(self.x_np)
-            out = paddle.fluid.layers.brelu(x)
-            np.testing.assert_allclose(self.out_ref, out.numpy(), rtol=1e-05)
-            paddle.enable_static()
-
-    def test_errors(self):
-        with program_guard(Program()):
-            # The input type must be Variable.
-            self.assertRaises(TypeError, fluid.layers.brelu, 1)
-            # The input dtype must be float16, float32, float64.
-            x_int32 = fluid.data(name='x_int32', shape=[12, 10], dtype='int32')
-            self.assertRaises(TypeError, fluid.layers.brelu, x_int32)
-            # support the input dtype is float16
-            x_fp16 = fluid.layers.data(
-                name='x_fp16', shape=[12, 10], dtype='float16'
-            )
-            fluid.layers.brelu(x_fp16)
-
-
 def ref_relu6(x, threshold=6.0):
     out = np.copy(x)
     out[np.abs(x - threshold) < 0.005] = threshold + 0.02