add doc for is_complex and is_integer and expose them as public APIs (#38158)

python/paddle/__init__.py

@@ -66,6 +66,8 @@ import paddle.vision  # noqa: F401
 
 from .tensor.random import bernoulli  # noqa: F401
 
+from .tensor.attribute import is_complex  # noqa: F401
+from .tensor.attribute import is_integer  # noqa: F401
 from .tensor.attribute import rank  # noqa: F401
 from .tensor.attribute import shape  # noqa: F401
 from .tensor.attribute import real  # noqa: F401
@@ -379,6 +381,8 @@ __all__ = [  # noqa
            'equal',
            'equal_all',
            'is_tensor',
+           'is_complex',
+           'is_integer',
            'cross',
            'where',
            'log1p',

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

+# Copyright (c) 2021 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 paddle
+import numpy as np
+import unittest
+
+
+class TestIsComplex(unittest.TestCase):
+    def test_for_integer(self):
+        x = paddle.arange(10)
+        self.assertFalse(paddle.is_complex(x))
+
+    def test_for_floating_point(self):
+        x = paddle.randn([2, 3])
+        self.assertFalse(paddle.is_complex(x))
+
+    def test_for_complex(self):
+        x = paddle.randn([2, 3]) + 1j * paddle.randn([2, 3])
+        self.assertTrue(paddle.is_complex(x))
+
+    def test_for_exception(self):
+        with self.assertRaises(TypeError):
+            paddle.is_complex(np.array([1, 2]))
+
+
+if __name__ == '__main__':
+    unittest.main()

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

+# Copyright (c) 2021 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 paddle
+import numpy as np
+import unittest
+
+
+class TestIsInteger(unittest.TestCase):
+    def test_for_integer(self):
+        x = paddle.arange(10)
+        self.assertTrue(paddle.is_integer(x))
+
+    def test_for_floating_point(self):
+        x = paddle.randn([2, 3])
+        self.assertFalse(paddle.is_integer(x))
+
+    def test_for_complex(self):
+        x = paddle.randn([2, 3]) + 1j * paddle.randn([2, 3])
+        self.assertFalse(paddle.is_integer(x))
+
+    def test_for_exception(self):
+        with self.assertRaises(TypeError):
+            paddle.is_integer(np.array([1, 2]))
+
+
+if __name__ == '__main__':
+    unittest.main()

python/paddle/tensor/__init__.py

@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from .attribute import is_complex  # noqa: F401
+from .attribute import is_integer  # noqa: F401
 from .attribute import rank  # noqa: F401
 from .attribute import shape  # noqa: F401
 from .attribute import real  # noqa: F401
@@ -408,6 +410,8 @@ tensor_method_func  = [ #noqa
            'var',
            'numel',
            'median',
+           'is_complex',
+           'is_integer',
            'rank',
            'shape',
            'real',

python/paddle/tensor/attribute.py

@@ -21,6 +21,7 @@ from ..fluid.data_feeder import check_variable_and_dtype
 # TODO: define functions to get tensor attributes  
 from ..fluid.layers import rank  # noqa: F401
 from ..fluid.layers import shape  # noqa: F401
+import paddle
 from paddle import _C_ops
 
 __all__ = []
@@ -45,6 +46,34 @@ def _real_to_complex_dtype(dtype):
 
 
 def is_complex(x):
+    """Return whether x is a tensor of complex data type(complex64 or complex128).
+
+    Args:
+        x (Tensor): The input tensor.
+
+    Returns:
+        bool: True if the data type of the input is complex data type, otherwise false.
+
+    Examples:
+        .. code-block:: python
+
+            import paddle
+
+            x = paddle.to_tensor([1 + 2j, 3 + 4j])
+            print(paddle.is_complex(x))
+            # True
+
+            x = paddle.to_tensor([1.1, 1.2])
+            print(paddle.is_complex(x))
+            # False
+
+            x = paddle.to_tensor([1, 2, 3])
+            print(paddle.is_complex(x))
+            # False
+    """
+    if not isinstance(x, (paddle.Tensor, paddle.static.Variable)):
+        raise TypeError("Expected Tensor, but received type of x: {}".format(
+            type(x)))
     dtype = x.dtype
     is_complex_dtype = (dtype == core.VarDesc.VarType.COMPLEX64 or
                         dtype == core.VarDesc.VarType.COMPLEX128)
@@ -61,6 +90,34 @@ def is_floating_point(x):
 
 
 def is_integer(x):
+    """Return whether x is a tensor of integeral data type.
+
+    Args:
+        x (Tensor): The input tensor.
+
+    Returns:
+        bool: True if the data type of the input is integer data type, otherwise false.
+
+    Examples:
+        .. code-block:: python
+
+            import paddle
+
+            x = paddle.to_tensor([1 + 2j, 3 + 4j])
+            print(paddle.is_integer(x))
+            # False
+
+            x = paddle.to_tensor([1.1, 1.2])
+            print(paddle.is_integer(x))
+            # False
+
+            x = paddle.to_tensor([1, 2, 3])
+            print(paddle.is_integer(x))
+            # True
+    """
+    if not isinstance(x, (paddle.Tensor, paddle.static.Variable)):
+        raise TypeError("Expected Tensor, but received type of x: {}".format(
+            type(x)))
     dtype = x.dtype
     is_int_dtype = (dtype == core.VarDesc.VarType.UINT8 or
                     dtype == core.VarDesc.VarType.INT8 or