diff --git a/tinygrad/tensor.py b/tinygrad/tensor.py
index d90b931b47..529554f18a 100644
--- a/tinygrad/tensor.py
+++ b/tinygrad/tensor.py
@@ -3315,14 +3315,10 @@ class Tensor(SimpleMathTrait):
     if not base.is_floating_point(): raise RuntimeError("base needs to be float")
     # start with b ** e = exp(e * log(b))
     ret = base.abs().log().mul(exponent).exp()
-    # correct sign of negative base with odd exponent
-    negative_base = (base < 0).detach().where(1, 0)
-    # 1 for non-negative base or negative even exponent, -1 for negative odd exponent, don't care about non-integer exponent
-    correct_sign = (exponent.int()%2==0).where(1, 1-2*negative_base)
-    # inject nan for negative base and non-integer exponent
-    inject_nan = (negative_base * (exponent != exponent.trunc())).detach().where(math.nan, 1)
-    # apply correct_sign inject_nan, and fix 0 ** 0 = 1
-    ret = ((base == 0) * (exponent == 0)).detach().where(1, ret * correct_sign * inject_nan)
+    # negative base adjustment: nan for non-integer exponent and -1 for odd exponent
+    adj = (base < 0).detach().where((exponent != exponent.int()).detach().where(math.nan, (exponent.int()%2==1).where(-1, 1)), 1)
+    # fix 0 ** 0 = 1
+    ret = ((base == 0) * (exponent == 0)).detach().where(1, ret * adj)
     return ret.round().cast(self.dtype) if not dtypes.is_float(self.dtype) else ret
 
   def maximum(self, x:Union[Tensor, ConstType]) -> Tensor: