From 08c9d980dc70cb4c24327857f7ff5191fbf07d7e Mon Sep 17 00:00:00 2001
From: qazal <77887910+Qazalin@users.noreply.github.com>
Date: Thu, 2 Jan 2025 19:05:09 +0200
Subject: [PATCH] use const_like in uop zero folding [pr] (#8470)

---
 test/test_schedule.py | 2 --
 tinygrad/ops.py       | 4 ++--
 2 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/test/test_schedule.py b/test/test_schedule.py
index a900995a5d..ff8d0c7258 100644
--- a/test/test_schedule.py
+++ b/test/test_schedule.py
@@ -2054,14 +2054,12 @@ class TestBigGraph(unittest.TestCase):
     assert UPat(Ops.CONST, arg=0).match(sink, {}), f"expected {sink} to collapse to a const 0"
     assert sink.shape == a.shape
 
-  @unittest.expectedFailure
   def test_const_folding_ne(self):
     a = Tensor([1])
     sink = tensor_rewrite(a != a)
     assert UPat(Ops.CONST, arg=False).match(sink, {}), f"expected {sink} to collapse to a const False"
     assert sink.shape == a.shape
 
-  @unittest.expectedFailure
   def test_const_folding_lt(self):
     a = Tensor([1])
     sink = tensor_rewrite(a < a)
diff --git a/tinygrad/ops.py b/tinygrad/ops.py
index 14aa41f8e7..0dff5d3fce 100644
--- a/tinygrad/ops.py
+++ b/tinygrad/ops.py
@@ -1192,9 +1192,9 @@ symbolic_simple = PatternMatcher([
   (UPat.var("x", dtype=dtypes.bool).logical_not().logical_not(), lambda x: x),
   (UPat.var("x", dtype=dtypes.bool).where(UPat.const(dtypes.bool, True), UPat.const(dtypes.bool, False)), lambda x: x),
   # ** zero folding **
-  (UPat.var("x") < UPat.var("x"), lambda x: UOp.const(dtypes.bool.vec(x.dtype.count), False)), # x < x -> False
+  (UPat.var("x") < UPat.var("x"), lambda x: x.const_like(False).cast(dtypes.bool.vec(x.dtype.count))), # x < x -> False
   (UPat.var("x", dtype=dtypes.ints) != UPat.var("x", dtype=dtypes.ints),
-   lambda x: UOp.const(dtypes.bool.vec(x.dtype.count), False)), # x != x -> False (only ints)
+   lambda x: x.const_like(False).cast(dtypes.bool.vec(x.dtype.count))), # x != x -> False (only ints)
   # x*0 -> 0 or 0*x -> 0
   # if x is nan or inf it should render the nan value.
   # NOTE: this can be wrong for loaded NaN