diff --git a/imperative/python/megengine/functional/elemwise.py b/imperative/python/megengine/functional/elemwise.py
index 85fc27276cbb8088d7f74c644bc24d056829d22a..08436ac547a7db6900c35c0dc02becf73c685366 100644
--- a/imperative/python/megengine/functional/elemwise.py
+++ b/imperative/python/megengine/functional/elemwise.py
@@ -26,7 +26,7 @@ __all__ = [
     "acosh",
     "atanh",
     "ceil",
-    "clamp",
+    "clip",
     "cos",
     "cosh",
     "div",
@@ -547,7 +547,7 @@ def sigmoid(x):
     return _elwise(x, mode="sigmoid")
 
 
-def clamp(x: Tensor, lower=None, upper=None) -> Tensor:
+def clip(x: Tensor, lower=None, upper=None) -> Tensor:
     r"""Clamps all elements in input tensor into the range `[` :attr:`lower`, :attr:`upper` `]` and returns
     a resulting tensor:
 
@@ -572,9 +572,9 @@ def clamp(x: Tensor, lower=None, upper=None) -> Tensor:
         import megengine.functional as F
 
         a = tensor(np.arange(5).astype(np.int32))
-        print(F.clamp(a, 2, 4).numpy())
-        print(F.clamp(a, lower=3).numpy())
-        print(F.clamp(a, upper=3).numpy())
+        print(F.clip(a, 2, 4).numpy())
+        print(F.clip(a, lower=3).numpy())
+        print(F.clip(a, upper=3).numpy())
 
     Outputs:
 
@@ -590,7 +590,7 @@ def clamp(x: Tensor, lower=None, upper=None) -> Tensor:
     ), "At least one of 'lower' or 'upper' must not be None"
     if lower is not None:
         if upper is not None:
-            assert lower <= upper, "clamp lower bound is bigger that upper bound"
+            assert lower <= upper, "clip lower bound is bigger that upper bound"
             return minimum(maximum(x, lower), upper)
         else:
             return maximum(x, lower)
diff --git a/imperative/python/megengine/functional/math.py b/imperative/python/megengine/functional/math.py
index 77f7f0a6ec9adb2a791b09bdcaf12581b1c553bb..a61ea8dd7e439505a2bf404f526d1d78c62d6109 100644
--- a/imperative/python/megengine/functional/math.py
+++ b/imperative/python/megengine/functional/math.py
@@ -18,7 +18,7 @@ from ..core.ops.special import Const
 from ..core.tensor import utils
 from ..core.tensor.core import TensorBase, TensorWrapperBase, apply
 from ..tensor import Tensor
-from .elemwise import clamp, exp, log, log1p
+from .elemwise import clip, exp, log, log1p
 from .tensor import add_axis, remove_axis, reshape
 
 __all__ = [
@@ -85,7 +85,7 @@ def isinf(inp: Tensor) -> Tensor:
         print(F.isinf(x).numpy())
 
     Outputs:
-    
+
     .. testoutput::
 
         [False  True False]
@@ -109,7 +109,7 @@ def sign(inp: Tensor):
 
         x = tensor([1, -1, 0])
         print(F.sign(x).numpy())
-    
+
     Outputs:
 
     .. testoutput::
@@ -557,9 +557,9 @@ def normalize(
     :return: normalized output tensor.
     """
     if axis is None:
-        return inp / clamp(norm(inp, p, axis), lower=eps)
+        return inp / clip(norm(inp, p, axis), lower=eps)
     else:
-        return inp / clamp(norm(inp, p, axis, keepdims=True), lower=eps)
+        return inp / clip(norm(inp, p, axis, keepdims=True), lower=eps)
 
 
 def argsort(inp: Tensor, descending: bool = False) -> Tensor:
diff --git a/imperative/python/test/unit/functional/test_elemwise.py b/imperative/python/test/unit/functional/test_elemwise.py
index 0b167942929c89f3b6e5080b16cb46e0fb7fd6f2..f0b51a56f221902a031f2f1939c7fdcb24628a8b 100644
--- a/imperative/python/test/unit/functional/test_elemwise.py
+++ b/imperative/python/test/unit/functional/test_elemwise.py
@@ -47,14 +47,14 @@ def test_multiply():
 
 def test_clamp():
     """Fix an issue when `lower` or `upper` is 0, it will be recognized as `False` and
-    `F.clamp` will fall into wrong conditions unexpectedly.
+    `F.clip` will fall into wrong conditions unexpectedly.
     """
     x = np.linspace(-6, 6, dtype="float32")
     np.testing.assert_allclose(
-        F.clamp(tensor(x) + 3, 0, 6).numpy(), np.clip(x + 3, 0, 6)
+        F.clip(tensor(x) + 3, 0, 6).numpy(), np.clip(x + 3, 0, 6)
     )
     np.testing.assert_allclose(
-        F.clamp(tensor(x) - 3, -6, 0).numpy(), np.clip(x - 3, -6, 0)
+        F.clip(tensor(x) - 3, -6, 0).numpy(), np.clip(x - 3, -6, 0)
     )