diff --git a/test/test_ops.py b/test/test_ops.py
index bbc33147ee..6e413d3dff 100644
--- a/test/test_ops.py
+++ b/test/test_ops.py
@@ -2,7 +2,7 @@ import time, math, unittest, functools, platform, warnings
 import numpy as np
 from typing import List, Callable
 import torch
-from tinygrad.helpers import getenv, IMAGE, DEBUG, CI, Context, TRANSCENDENTAL, CPU_LLVM, AMD_LLVM
+from tinygrad.helpers import getenv, IMAGE, DEBUG, CI, Context, CPU_LLVM, AMD_LLVM
 from tinygrad import Tensor, Device, dtypes
 from tinygrad.tensor import _to_np_dtype
 from tinygrad.device import is_dtype_supported
@@ -901,7 +901,6 @@ class TestOps(unittest.TestCase):
   def test_abs_exact(self):
     helper_test_op(None, torch.abs, Tensor.abs, vals=[[-1.,0,1]])
 
-  @unittest.skipIf(TRANSCENDENTAL and Device.DEFAULT=="AMD", "TODO: remu crashes")
   def test_log(self):
     helper_test_op([(45,65)], torch.log, Tensor.log)
     helper_test_op(None, torch.log, Tensor.log, vals=[[math.inf, -math.inf, math.nan]])
@@ -911,7 +910,6 @@ class TestOps(unittest.TestCase):
     helper_test_op(None, torch.log2, Tensor.log2, vals=[[math.inf, -math.inf, math.nan]])
     helper_test_op([()], torch.log2, Tensor.log2)
 
-  @unittest.skipIf(TRANSCENDENTAL and Device.DEFAULT=="AMD", "TODO: remu crashes")
   def test_exp(self):
     helper_test_op([(45,65)], torch.exp, Tensor.exp)
     helper_test_op(None, torch.exp, Tensor.exp, vals=[[math.inf, -math.inf, math.nan]])
@@ -1549,7 +1547,6 @@ class TestOps(unittest.TestCase):
     helper_test_op([(3,4,5,6)], lambda x: torch.stack(torch.std_mean(x, axis=(1,2))),
                                 lambda x: Tensor.stack(*x.std_mean(axis=(1,2))))
 
-  @unittest.skip("TODO: this fails because of loaded nan in mul folding")
   def test_std_mean_loaded_nan(self):
     helper_test_op([(1,0,3,0,5)], lambda x: torch.stack(torch.std_mean(x, axis=(1,3))),
                                   lambda x: Tensor.stack(*x.std_mean(axis=(1,3))))