diff --git a/torch_xla/experimental/fori_loop.py b/torch_xla/experimental/fori_loop.py
index 3db18f4bc0f..f80da7156bd 100644
--- a/torch_xla/experimental/fori_loop.py
+++ b/torch_xla/experimental/fori_loop.py
@@ -20,9 +20,9 @@ def fori_loop(lower, upper, body_fun, *init_vals): # *init_val):
   # iterator = lower
 
   # one_value_original = torch.tensor([1], dtype=torch.int32, device=device)
-  (a, b) = init_vals
+  # (a, b) = init_vals
 
-  def cond_fn(upper, lower, *init_vals):
+  def cond_fn(upper, lowers): # lower, *init_vals):
     # init_val_compy = init_val.clone()
     # one_value1 = torch.tensor([0], dtype=torch.int32, device=device)
     # one_value2 = torch.tensor([0], dtype=torch.int32, device=device)
@@ -30,27 +30,30 @@ def cond_fn(upper, lower, *init_vals):
     # lower = torch.sub(lower, one_value2[0])
     # assert isinstance(init_vals[0], torch.Tensor)
     # assert isinstance(init_vals[1], torch.Tensor)
-    bool_value = isinstance(init_vals[0], torch.Tensor) and isinstance(init_vals[1], torch.Tensor)
+    # bool_value = isinstance(init_vals[0], torch.Tensor) and isinstance(init_vals[1], torch.Tensor)
     # body_fun(*init_vals)
     # result = True
     # if (lower[0] <= upper[0]) and bool_value:
     #   return True
     # return False
-    bool_result = ((lower[0] <= upper[0]) and bool_value)
-    bool_tensor = torch.tensor(bool_result, dtype=torch.bool)
-    return False # bool_tensor # (lower[0] <= upper[0]) and bool_tensor
+    # bool_result = ((lower[0] <= upper[0]) and bool_value)
+    # bool_tensor = torch.tensor(bool_result, dtype=torch.bool)
+    # return bool_tensor # (lower[0] <= upper[0]) and bool_tensor
+    # return lower[0] <= upper[0]
+    return lowers[0] <= upper[0]
 
-  def body_fn(upper, lower, *init_vals):
+  def body_fn(upper, lowers): # , *init_vals):
     # one_value_original = torch.tensor(1, dtype=torch.int32, device=device)
-    (a, b) = init_vals
+    # (a, b) = init_vals
     # return (upper, torch.add(lower, 1), body_fun(a, b), b.clone())
     # return (upper.clone(), (torch.add(lower.clone(), init_vals[1].clone())).clone(), (body_fun(*init_vals)).clone(), init_vals[1].clone()) # init_vals[1:])
-    return (upper, torch.add(lower, b), body_fun(a, b), b) # init_vals[1:])
+    return (upper, (torch.add(lowers[0], lowers[2]), body_fun(lowers[1], lowers[2]), lowers[2])) # init_vals[1:])
     # (body_fun(*init_vals)).clone(), init_vals[1].clone())
     # body_fun(one_value_original, init_val)) # body_fun(lower, init_val))
 
   # res = while_loop(cond_fn, body_fn, (upper, lower, *init_vals))
-  res = _xla_while_loop(cond_fn, body_fn, (upper, lower, *init_vals))
+  lowers = (lower, *init_vals)
+  res = _xla_while_loop(cond_fn, body_fn, (upper, lowers)) # , *init_vals))
   # print("upper: ", upper)
   # print("lower: ", lower)
   return res