diff --git a/imperative/python/megengine/functional/elemwise.py b/imperative/python/megengine/functional/elemwise.py
index 8757b77645a2c9c15ed9ee91a53bf83bfb766c2c..3b71291c83d77bec501797cbcb16e04a640a8b20 100644
--- a/imperative/python/megengine/functional/elemwise.py
+++ b/imperative/python/megengine/functional/elemwise.py
@@ -33,7 +33,6 @@ __all__ = [
     "equal",
     "exp",
     "expm1",
-    "fast_tanh",
     "floor",
     "floor_div",
     "greater",
@@ -369,15 +368,6 @@ def atanh(x):
     return log1p(2 * x / (1 - x)) / 2
 
 
-def fast_tanh(x):
-    r"""Element-wise `fast tanh`; this is an approximation:
-
-    .. math::
-        \text{fast_tanh}(x) = x * (27. + x * x) / (27. + 9. * x * x)
-    """
-    return _elwise(x, mode="fast_tanh")
-
-
 # bit-twiddling functions
 
 
diff --git a/imperative/python/megengine/module/elemwise.py b/imperative/python/megengine/module/elemwise.py
index 3542359d633da9cc82c6c135ce973367b40a9f5a..9bc05fbfc0c145cc0a3de3ffad898630ca85f324 100644
--- a/imperative/python/megengine/module/elemwise.py
+++ b/imperative/python/megengine/module/elemwise.py
@@ -34,7 +34,7 @@ class Elemwise(Module):
         * "EXP": exp(x)
         * "TANH": tanh(x)
         * "FUSE_MUL_ADD3": x * y + z
-        * "FAST_TANH": fast_tanh(x)
+        * "FAST_TANH": x * (27. + x * x) / (27. + 9. * x * x)
         * "NEGATE": -x
         * "ACOS": acos(x)
         * "ASIN": asin(x)
diff --git a/imperative/python/test/unit/functional/test_elemwise.py b/imperative/python/test/unit/functional/test_elemwise.py
index f0b51a56f221902a031f2f1939c7fdcb24628a8b..30421dd8ca9910ba09958bff6499758d9b3efc0f 100644
--- a/imperative/python/test/unit/functional/test_elemwise.py
+++ b/imperative/python/test/unit/functional/test_elemwise.py
@@ -113,14 +113,6 @@ def test_atanh():
     np.testing.assert_almost_equal(y_np, y_mge, decimal=5)
 
 
-def test_fast_tanh():
-    np.random.seed(42)
-    x = np.random.randn(100).astype("float32")
-    y_np = x * (27.0 + x * x) / (27.0 + 9.0 * x * x)
-    y_mge = F.fast_tanh(tensor(x)).numpy()
-    np.testing.assert_almost_equal(y_np, y_mge, decimal=6)
-
-
 def test_hswish():
     np.random.seed(42)
     x = np.random.randn(100).astype("float32")