[API Compatibility No.359、378] param alias for deg2rad -part

python/paddle/tensor/math.py

@@ -51,6 +51,7 @@
     sign,
     sin,
     sum,
+    tan,
     tanh,
 )
 from paddle.base.libpaddle import DataType
@@ -125,7 +126,6 @@
     sqrt_,
     square,
     square_,
-    tan,
     tan_,
 )
 
@@ -5043,7 +5043,10 @@ def rad2deg(x: Tensor, name: str | None = None) -> Tensor:
         return out
 
 
-def deg2rad(x: Tensor, name: str | None = None) -> Tensor:
+@param_one_alias(['x', 'input'])
+def deg2rad(
+    x: Tensor, name: str | None = None, *, out: Tensor | None = None
+) -> Tensor:
     r"""
     Convert each of the elements of input x from degrees to angles in radians.
 
@@ -5054,6 +5057,7 @@ def deg2rad(x: Tensor, name: str | None = None) -> Tensor:
     Args:
         x (Tensor): An N-D Tensor, the data type is float32, float64, int32, int64.
         name (str|None, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
+        out (Tensor|None, optional): The output Tensor. If set, the result will be stored in this Tensor. Default is None.
 
     Returns:
         out (Tensor): An N-D Tensor, the shape and data type is the same with input (The output data type is float32 when the input data type is int).
@@ -5080,7 +5084,7 @@ def deg2rad(x: Tensor, name: str | None = None) -> Tensor:
     if in_dynamic_or_pir_mode():
         if convert_dtype(x.dtype) in ['int32', 'int64']:
             x = cast(x, dtype="float32")
-        return _C_ops.scale(x, deg2rad_scale, 0.0, True)
+        return _C_ops.scale(x, deg2rad_scale, 0.0, True, out=out)
     else:
         check_variable_and_dtype(
             x, 'x', ['int32', 'int64', 'float32', 'float64'], 'deg2rad'
@@ -5097,7 +5101,10 @@ def deg2rad(x: Tensor, name: str | None = None) -> Tensor:
                 outputs={'Out': out_cast},
                 attrs={'in_dtype': x.dtype, 'out_dtype': paddle.float32},
             )
-        out = helper.create_variable_for_type_inference(dtype=out_cast.dtype)
+        if out is None:
+            out = helper.create_variable_for_type_inference(
+                dtype=out_cast.dtype
+            )
         helper.append_op(
             type='scale',
             inputs={'X': out_cast},

test/legacy_test/test_activation_op.py

@@ -6377,6 +6377,7 @@ class TestActivationAPI_Compatibility(unittest.TestCase):
         ("paddle.tanh", np.tanh, {'min_val': -1.0, 'max_val': 1.0}),
         ("paddle.cosh", np.cosh, {'min_val': -1.0, 'max_val': 1.0}),
         ("paddle.sinh", np.sinh, {'min_val': -1.0, 'max_val': 1.0}),
+        ("paddle.tan", np.tan, {'min_val': -1.0, 'max_val': 1.0}),
     ]
     ACTIVATION_NOT_METHOD_CONFIGS = [
         (

test/legacy_test/test_deg2rad.py

@@ -12,8 +12,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
 import unittest
 
+os.environ['FLAGS_enable_pir_api'] = '0'
+
 import numpy as np
 from op_test import get_device_place
 
@@ -61,22 +64,143 @@ def test_dygraph(self):
 
 
 class TestDeg2radAPI2(TestDeg2radAPI):
-    # Test input data type is int
+    # Test input data type is int64
     def setUp(self):
-        self.x_np = [180]
+        self.x_np = np.array([180]).astype(np.int64)
         self.x_shape = [1]
         self.out_np = np.pi
         self.x_dtype = 'int64'
 
     def test_dygraph(self):
         paddle.disable_static()
 
-        x2 = paddle.to_tensor([180])
+        # Test int64 input
+        x2 = paddle.to_tensor([180], dtype="int64")
         result2 = paddle.deg2rad(x2)
         np.testing.assert_allclose(np.pi, result2.numpy(), rtol=1e-05)
 
         paddle.enable_static()
 
 
+class TestDeg2radAPI3(TestDeg2radAPI):
+    # Test input data type is int32
+    def setUp(self):
+        self.x_np = np.array([180]).astype(np.int32)
+        self.x_shape = [1]
+        self.out_np = np.pi
+        self.x_dtype = 'int32'
+
+    def test_dygraph(self):
+        paddle.disable_static()
+
+        # Test int32 input
+        x3 = paddle.to_tensor([180], dtype="int32")
+        result3 = paddle.deg2rad(x3)
+        np.testing.assert_allclose(np.pi, result3.numpy(), rtol=1e-05)
+
+        paddle.enable_static()
+
+
+class TestDeg2radAPI4(TestDeg2radAPI):
+    # Test input data type is float32
+    def setUp(self):
+        self.x_np = np.array(
+            [180.0, -180.0, 360.0, -360.0, 90.0, -90.0]
+        ).astype(np.float32)
+        self.x_shape = [6]
+        self.out_np = np.deg2rad(self.x_np)
+        self.x_dtype = 'float32'
+
+
+class TestDeg2radAliasAndOut(unittest.TestCase):
+    def test_alias(self):
+        paddle.disable_static()
+        x = paddle.to_tensor([180.0])
+        expected = np.deg2rad(180.0)
+
+        # Test alias
+        res = paddle.deg2rad(input=x)
+        np.testing.assert_allclose(res.numpy(), expected, rtol=1e-05)
+
+        paddle.enable_static()
+
+    def test_out(self):
+        paddle.disable_static()
+        x = paddle.to_tensor([180.0])
+        expected = np.deg2rad(180.0)
+
+        # Test without out parameter (default None)
+        res_no_out = paddle.deg2rad(x)
+        np.testing.assert_allclose(res_no_out.numpy(), expected, rtol=1e-05)
+
+        # Test out parameter with float input
+        out = paddle.zeros([1], dtype="float32")
+        res = paddle.deg2rad(x, out=out)
+        np.testing.assert_allclose(out.numpy(), expected, rtol=1e-05)
+        self.assertTrue(res is out)
+
+        # Test out parameter with int64 input
+        x_int = paddle.to_tensor([180], dtype="int64")
+        out_float = paddle.zeros([1], dtype="float32")
+        res = paddle.deg2rad(x_int, out=out_float)
+        np.testing.assert_allclose(out_float.numpy(), expected, rtol=1e-05)
+        self.assertTrue(res is out_float)
+
+        # Test out parameter with int32 input
+        x_int32 = paddle.to_tensor([180], dtype="int32")
+        out_float32 = paddle.zeros([1], dtype="float32")
+        res = paddle.deg2rad(x_int32, out=out_float32)
+        np.testing.assert_allclose(out_float32.numpy(), expected, rtol=1e-05)
+        self.assertTrue(res is out_float32)
+
+        paddle.enable_static()
+
+
+class TestDeg2radStaticOut(unittest.TestCase):
+    def test_static_out_float(self):
+        """Test out parameter in static graph with float input"""
+        paddle.enable_static()
+        startup_program = paddle.static.Program()
+        train_program = paddle.static.Program()
+        with paddle.static.program_guard(startup_program, train_program):
+            x = paddle.static.data(name='input', dtype='float32', shape=[1])
+            out = paddle.static.data(name='out', dtype='float32', shape=[1])
+            result = paddle.deg2rad(x, out=out)
+
+            place = get_device_place()
+            exe = base.Executor(place)
+            x_np = np.array([180.0]).astype(np.float32)
+            out_np = np.zeros([1]).astype(np.float32)
+            expected = np.deg2rad(180.0)
+
+            res, out_res = exe.run(
+                feed={'input': x_np, 'out': out_np},
+                fetch_list=[result, out],
+            )
+            np.testing.assert_allclose(out_res, expected, rtol=1e-05)
+
+    def test_static_out_int(self):
+        """Test out parameter in static graph with int input"""
+        paddle.enable_static()
+        startup_program = paddle.static.Program()
+        train_program = paddle.static.Program()
+        with paddle.static.program_guard(startup_program, train_program):
+            x = paddle.static.data(name='input', dtype='int64', shape=[1])
+            out = paddle.static.data(name='out', dtype='float32', shape=[1])
+            result = paddle.deg2rad(x, out=out)
+
+            place = get_device_place()
+            exe = base.Executor(place)
+            x_np = np.array([180]).astype(np.int64)
+            out_np = np.zeros([1]).astype(np.float32)
+            expected = np.deg2rad(180.0)
+
+            res, out_res = exe.run(
+                feed={'input': x_np, 'out': out_np},
+                fetch_list=[result, out],
+            )
+            np.testing.assert_allclose(out_res, expected, rtol=1e-05)
+
+
 if __name__ == '__main__':
     unittest.main()