【Hackathon 5th No.13】【关联 PR】Added int support for sign

python/paddle/__init__.py

@@ -409,6 +409,7 @@
     polygamma_,
     hypot,
     hypot_,
+    signbit,
 )
 
 from .tensor.random import (
@@ -908,4 +909,5 @@
     'polygamma_',
     'hypot',
     'hypot_',
+    'signbit',
 ]

python/paddle/tensor/__init__.py

@@ -719,6 +719,7 @@
     'asinh_',
     'diag',
     'normal_',
+    'signbit',
 ]
 
 # this list used in math_op_patch.py for magic_method bind

python/paddle/tensor/math.py

@@ -6985,3 +6985,51 @@ def hypot_(x, y, name=None):
 
     out = x.pow_(2).add_(y.pow(2)).sqrt_()
     return out
+
+
+def signbit(x, name=None):
+    r"""
+    Tests if each element of input has its sign bit set or not.
+
+    Args:
+        x (Tensor): The input Tensor. Must be one of the following types: float16, float32, float64, bfloat16, uint8, int8, int16, int32, int64.
+        name (str, optional): Name for the operation (optional, default is None).For more information, please refer to :ref:`api_guide_Name`.
+
+    Returns:
+        out (Tensor): The output Tensor. The sign bit of the corresponding element of the input tensor, True means negative, False means positive.
+            >>> # example1
+            >>> x = paddle.to_tensor([1.1, -2.1, -0., 2.5], dtype='float32')
+            >>> res = paddle.signbit(x, y)
+            >>> print(res)
+            Tensor(shape=[4], dtype=bool, place=Place(cpu), stop_gradient=True,
+            [False , True, True, False])
+
+            >>> # example2
+            >>> x = paddle.to_tensor([-5, -2, 3], dtype='int32')
+            >>> res = paddle.signbit(x, y)
+            >>> print(res)
+            Tensor(shape=[3], dtype=bool, place=Place(cpu), stop_gradient=True,
+            [True. , True , False])
+    """
+    if not isinstance(x, (paddle.Tensor, Variable)):
+        raise TypeError(f"x must be tensor type, but got {type(x)}")
+
+    check_variable_and_dtype(
+        x,
+        "x",
+        [
+            'float16',
+            'float32',
+            'float64',
+            'bfloat16',
+            'int8',
+            'int16',
+            'int32',
+            'int64',
+        ],
+        "signbit",
+    )
+
+    out_mask = paddle.cast(x < 0, dtype='bool')
+    out_mask[x == -0] = True
+    return out_mask

test/legacy_test/test_signbit.py

@@ -0,0 +1,66 @@
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+
+import numpy as np
+
+import paddle
+
+
+def np_signbit(x: np.ndarray):
+    return np.signbit(x)
+
+
+class TestSignbitAPI(unittest.TestCase):
+    def setUp(self) -> None:
+        self.support_dtypes = [
+            'float16',
+            'float32',
+            'float64',
+            'bfloat16',
+            'int8',
+            'int16',
+            'int32',
+            'int64',
+        ]
+        if paddle.device.get_device() == 'cpu':
+            self.support_dtypes = [
+                'float32',
+                'float64',
+                'int8',
+                'int16',
+                'int32',
+                'int64',
+            ]
+
+    def test_dtype(self):
+        for dtype in self.support_dtypes:
+            x = paddle.to_tensor(
+                np.random.randint(-10, 10, size=[12, 20, 2]).astype(dtype)
+            )
+            paddle.signbit(x)
+
+    def test_float(self):
+        for dtype in self.support_dtypes:
+            np_x = np.random.randint(-10, 10, size=[12, 20, 2]).astype(dtype)
+            x = paddle.to_tensor(np_x)
+            out = paddle.signbit(x)
+            np_out = out.numpy()
+            out_expected = np_signbit(np_x)
+            np.testing.assert_allclose(np_out, out_expected, rtol=1e-05)
+
+
+if __name__ == "__main__":
+    unittest.main()