[API Compatibility] paddle.sigmoid sink into C++

paddle/phi/ops/yaml/ops.yaml

@@ -4933,6 +4933,10 @@
 
 - op : sigmoid
   args : (Tensor x)
+  python_api:
+    name : [paddle.sigmoid,paddle.Tensor.sigmoid,paddle.nn.functional.sigmoid]
+    args_alias:
+      use_default_mapping : True
   output : Tensor
   infer_meta :
     func : UnchangedInferMeta

python/paddle/_paddle_docs.py

@@ -590,6 +590,47 @@ def any(
 
 # shenwei
 
+add_doc_and_signature(
+    "sigmoid",
+    r"""
+    Sigmoid Activation.
+
+    .. math::
+       out = \\frac{1}{1 + e^{-x}}
+
+    Args:
+        x (Tensor): Input of Sigmoid operator, an N-D Tensor, with data type bfloat16, float16, float32, float64,
+            uint8, int8, int16, int32, int64, complex64 or complex128.
+        name (str|None, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
+    Keyword Args:
+        out (Tensor|optional): The output tensor.
+
+    Returns:
+        Tensor. Output of Sigmoid operator, a Tensor with shape same as input
+            (integer types are autocasted into float32).
+
+    Examples:
+        .. code-block:: python
+
+            >>> import paddle
+            >>> import paddle.nn.functional as F
+
+            >>> x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
+            >>> out = F.sigmoid(x)
+            >>> print(out)
+            Tensor(shape=[4], dtype=float32, place=Place(cpu), stop_gradient=True,
+            [0.40131235, 0.45016602, 0.52497917, 0.57444251])
+    """,
+    """
+    def sigmoid(
+        x: paddle.Tensor,
+        name: str | None = None,
+        *,
+        out: Tensor | None = None,
+    ) -> paddle.Tensor
+    """,
+)
+
 # zhouxin
 
 # hehongyu

test/legacy_test/test_sigmoid.py

@@ -0,0 +1,161 @@
+# Copyright (c) 2020 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
+from op_test import get_places
+
+import paddle
+from paddle import base
+
+
+class TestSigmoidAPI_Compatibility(unittest.TestCase):
+    def setUp(self):
+        np.random.seed(123)
+        paddle.enable_static()
+        self.places = get_places()
+        self.init_data()
+
+    def init_data(self):
+        self.shape = [10, 15]
+        self.dtype = "float32"
+        self.np_input = np.random.uniform(-1, 1, self.shape).astype(self.dtype)
+
+    def ref_forward(self, x):
+        return 1 / (1 + np.exp(-x))
+
+    def test_dygraph_Compatibility(self):
+        paddle.disable_static()
+        x = paddle.to_tensor(self.np_input)
+        paddle_dygraph_out = []
+        # Position args (args)
+        out1 = paddle.sigmoid(x)
+        paddle_dygraph_out.append(out1)
+        # Key words args (kwargs) for paddle
+        out2 = paddle.sigmoid(x=x)
+        paddle_dygraph_out.append(out2)
+        # Key words args for torch
+        out3 = paddle.sigmoid(input=x)
+        paddle_dygraph_out.append(out3)
+        # Tensor method args
+        out4 = x.sigmoid()
+        paddle_dygraph_out.append(out4)
+        # Test out
+        out5 = paddle.empty([])
+        paddle.sigmoid(x, out=out5)
+        paddle_dygraph_out.append(out5)
+        # Reference output
+        ref_out = self.ref_forward(self.np_input)
+        # Check
+        for i in range(len(paddle_dygraph_out)):
+            np.testing.assert_allclose(
+                ref_out, paddle_dygraph_out[i].numpy(), rtol=1e-05
+            )
+        paddle.enable_static()
+
+    def test_static_Compatibility(self):
+        main = paddle.static.Program()
+        startup = paddle.static.Program()
+        with base.program_guard(main, startup):
+            x = paddle.static.data(name="x", shape=self.shape, dtype=self.dtype)
+            # Position args (args)
+            out1 = paddle.sigmoid(x)
+            # Key words args (kwargs) for paddle
+            out2 = paddle.sigmoid(x=x)
+            # Key words args for torch
+            out3 = paddle.sigmoid(input=x)
+            # Tensor method args
+            out4 = x.sigmoid()
+            exe = base.Executor(paddle.CPUPlace())
+            fetches = exe.run(
+                main,
+                feed={"x": self.np_input},
+                fetch_list=[out1, out2, out3, out4],
+            )
+            ref_out = self.ref_forward(self.np_input)
+            for i in range(len(fetches)):
+                np.testing.assert_allclose(fetches[i], ref_out, rtol=1e-05)
+
+
+class TestTensorSigmoidAPI_Compatibility(unittest.TestCase):
+    def setUp(self):
+        np.random.seed(123)
+        paddle.enable_static()
+        self.places = get_places()
+        self.init_data()
+
+    def init_data(self):
+        self.shape = [10, 15]
+        self.dtype = "float32"
+        self.np_input = np.random.uniform(-1, 1, self.shape).astype(self.dtype)
+
+    def ref_forward(self, x):
+        return 1 / (1 + np.exp(-x))
+
+    def test_dygraph_Compatibility(self):
+        paddle.disable_static()
+        x = paddle.to_tensor(self.np_input)
+        paddle_dygraph_out = []
+        # Position args (args)
+        out1 = paddle.Tensor.sigmoid(x)
+        paddle_dygraph_out.append(out1)
+        # Key words args (kwargs) for paddle
+        out2 = paddle.Tensor.sigmoid(x=x)
+        paddle_dygraph_out.append(out2)
+        # Key words args for torch
+        out3 = paddle.Tensor.sigmoid(input=x)
+        paddle_dygraph_out.append(out3)
+        # Tensor method args
+        out4 = x.sigmoid()
+        paddle_dygraph_out.append(out4)
+        # Test out
+        out5 = paddle.empty([])
+        paddle.Tensor.sigmoid(x, out=out5)
+        paddle_dygraph_out.append(out5)
+        # Reference output
+        ref_out = self.ref_forward(self.np_input)
+        # Check
+        for i in range(len(paddle_dygraph_out)):
+            np.testing.assert_allclose(
+                ref_out, paddle_dygraph_out[i].numpy(), rtol=1e-05
+            )
+        paddle.enable_static()
+
+    def test_static_Compatibility(self):
+        main = paddle.static.Program()
+        startup = paddle.static.Program()
+        with base.program_guard(main, startup):
+            x = paddle.static.data(name="x", shape=self.shape, dtype=self.dtype)
+            # Position args (args)
+            out1 = paddle.Tensor.sigmoid(x)
+            # Key words args (kwargs) for paddle
+            out2 = paddle.Tensor.sigmoid(x=x)
+            # Key words args for torch
+            out3 = paddle.Tensor.sigmoid(input=x)
+            # Tensor method args
+            out4 = x.sigmoid()
+            exe = base.Executor(paddle.CPUPlace())
+            fetches = exe.run(
+                main,
+                feed={"x": self.np_input},
+                fetch_list=[out1, out2, out3, out4],
+            )
+            ref_out = self.ref_forward(self.np_input)
+            for i in range(len(fetches)):
+                np.testing.assert_allclose(fetches[i], ref_out, rtol=1e-05)
+
+
+if __name__ == '__main__':
+    unittest.main()