diff --git a/tinygrad/mlops.py b/tinygrad/mlops.py
index bbfac292a4..00ad2a8531 100644
--- a/tinygrad/mlops.py
+++ b/tinygrad/mlops.py
@@ -24,7 +24,7 @@ class Log(Function):
 class Exp(Function):
   def forward(self, x):
     ret = x.unary_op(UnaryOps.EXP)
-    self.save_for_backward(ret)   # we save the output here, not the input
+    self.save_for_backward(ret)
     return ret
 
   def backward(self, grad_output):
diff --git a/tinygrad/ops.py b/tinygrad/ops.py
index aeacccfb37..8551159ea4 100644
--- a/tinygrad/ops.py
+++ b/tinygrad/ops.py
@@ -30,7 +30,7 @@ def get_lazyops(op:LazyOp) -> List[LazyOp]: return functools.reduce(operator.add
 
 # a placeholder class to extend by the exec classes
 class DeviceBuffer:
-  shape: Any   # should be Tuple[int, ...] but ndarray and torch.tensor have imcompatible types
+  shape: Any   # should be Tuple[int, ...] but ndarray and torch.tensor have incompatible types
 
 # extend this if you don't have an exec_ast function
 # used in CPUBuffer and TorchBuffer
diff --git a/tinygrad/shapetracker.py b/tinygrad/shapetracker.py
index d71d0d837b..47fe5c9175 100644
--- a/tinygrad/shapetracker.py
+++ b/tinygrad/shapetracker.py
@@ -156,4 +156,3 @@ class ShapeTracker:
     new_shape = [(s+(abs(m)-1))//abs(m) for s,m in zip(self.shape, mul)]
     offset = sum([(s-1)*z for s,z,m in zip(self.shape, self.strides, mul) if m < 0])
     self.views[-1] = View(new_shape, strides, self.offset + offset)
-