diff --git a/tinygrad/mixin/movement.py b/tinygrad/mixin/movement.py
index 68b64c7b9b..47ca3640e8 100644
--- a/tinygrad/mixin/movement.py
+++ b/tinygrad/mixin/movement.py
@@ -107,6 +107,12 @@ class MovementMixin:
     ret = self._mop(Ops.RESHAPE, arg=new_shape)
     return self if ret.shape == self.shape else ret
 
+  def pad(self, arg:tuple[tuple[sint, sint] | None, ...]) -> Self:
+    if self.ndim != len(arg):
+      raise ValueError(f"{self.ndim=} != {len(arg)=}")
+    ret = self._mop(Ops.PAD, tuple(x if x is not None else (0, 0) for x in arg))
+    return self if ret.shape == self.shape else ret
+
   def shrink(self, arg: tuple[tuple[sint, sint] | None, ...]) -> Self:
     """
     Returns a tensor that shrinks the each axis based on input arg.
diff --git a/tinygrad/uop/ops.py b/tinygrad/uop/ops.py
index c55847a08d..705c78082a 100644
--- a/tinygrad/uop/ops.py
+++ b/tinygrad/uop/ops.py
@@ -650,16 +650,6 @@ class UOp(OpMixin, metaclass=UOpMetaClass):
     if ret.shape == self.shape and same_shape_noop: return self
     return ret
 
-  # in these four, if the shape doesn't change we can return self
-  #def reshape(self, arg:tuple[sint, ...]): return self._mop(Ops.RESHAPE, arg, same_shape_noop=True)
-  #def expand(self, arg:tuple[sint, ...]): return self._mop(Ops.EXPAND, arg, same_shape_noop=True)
-  #def shrink(self, arg:tuple[tuple[sint, sint], ...]): return self._mop(Ops.SHRINK, arg, same_shape_noop=True)
-  def pad(self, arg:tuple[tuple[sint, sint], ...]): return self._mop(Ops.PAD, arg, same_shape_noop=True)
-
-  # in these two, we have custom logic to check if they are a no-op
-  #def permute(self, arg:tuple[int, ...]): return self._mop(Ops.PERMUTE, arg, same_shape_noop=False) if arg != tuple(range(len(self.shape))) else self
-  #def flip(self, arg:tuple[bool, ...]): return self._mop(Ops.FLIP, arg, same_shape_noop=False) if any(arg) and len(arg) == len(self.shape) else self
-
   # *** uop UNIQUE ***
 
   # TODO: use this in Buffer