feat(mge/functional): add isnan and isinf oprs

GitOrigin-RevId: b4a347751c2022a2b0b2eca5a7e62c625b5e8c27

python_module/megengine/functional/__init__.py

@@ -21,6 +21,8 @@ from .elemwise import (
     floor,
     greater,
     greater_equal,
+    isinf,
+    isnan,
     less,
     less_equal,
     log,

python_module/megengine/functional/elemwise.py

@@ -27,6 +27,8 @@ __all__ = [
     "greater",
     "greater_equal",
     "floor",
+    "isinf",
+    "isnan",
     "less",
     "less_equal",
     "log",
@@ -244,3 +246,49 @@ def clamp(inp: Tensor, lower=None, upper=None) -> Tensor:
             return maximum(inp, lower)
     else:
         return minimum(inp, upper)
+
+
+def isnan(inp: Tensor) -> Tensor:
+    r"""Returns a new tensor representing if each element is NaN or not.
+
+    :param: inp
+    :return: a new tensor representing if each element in :attr:`inp` is NaN or not.
+
+    Examples:
+
+    .. testcode::
+        from megengine import tensor
+        import megengine.functional as F
+
+        x = tensor([1, float("nan"), 0])
+
+        print(F.isnan(x))
+
+    .. testoutput::
+        Tensor([0 1 0], dtype=uint8)
+
+    """
+    return (inp != inp).astype("uint8")
+
+
+def isinf(inp: Tensor) -> Tensor:
+    r"""Returns a new tensor representing if each element is Inf or not.
+
+    :param: inp
+    :return: a new tensor representing if each element in :attr:`inp` is Inf or not.
+
+    Examples:
+
+    .. testcode::
+        from megengine import tensor
+        import megengine.functional as F
+
+        x = tensor([1, float("inf"), 0])
+
+        print(F.isinf(x))
+
+    .. testoutput::
+        Tensor([0 1 0], dtype=uint8)
+
+    """
+    return (abs(inp) == float("inf")).astype("uint8")

python_module/test/unit/functional/test_elemwise.py

@@ -53,3 +53,13 @@ def test_clamp():
     x = np.linspace(-6, 6, dtype="float32")
     assertTensorClose(F.clamp(tensor(x) + 3, 0, 6).numpy(), np.clip(x + 3, 0, 6))
     assertTensorClose(F.clamp(tensor(x) - 3, -6, 0).numpy(), np.clip(x - 3, -6, 0))
+
+
+def test_isnan():
+    for case in [[1, float("nan"), 0]]:
+        assertTensorClose(F.isnan(tensor(case)), np.isnan(case).astype("uint8"))
+
+
+def test_isinf():
+    for case in [[1, float("inf"), 0]]:
+        assertTensorClose(F.isinf(tensor(case)), np.isinf(case).astype("uint8"))