mark slow tests as slow instead of as CI (#13736)

* mark slow tests as slow instead of as CI

* CI shouldn't have different behavior

* more skips / CI

* slow

test/unit/test_disk_tensor.py

@@ -3,7 +3,8 @@ import numpy as np
 from tinygrad import Tensor, Device, dtypes
 from tinygrad.dtype import DType
 from tinygrad.nn.state import safe_load, safe_save, get_state_dict, torch_load
-from tinygrad.helpers import Timing, fetch, temp, CI, OSX
+from tinygrad.helpers import Timing, fetch, temp, OSX
+from test.helpers import slow
 from tinygrad.device import is_dtype_supported
 
 def compare_weights_both(url):
@@ -340,8 +341,8 @@ class TestDiskTensor(unittest.TestCase):
       on_dev = t.to(Device.DEFAULT).realize()
       np.testing.assert_equal(on_dev.numpy(), t.numpy())
 
+  @slow
   def test_copy_from_disk_huge(self):
-    if CI and not hasattr(Device["DISK"], 'io_uring'): self.skipTest("slow on ci without iouring")
 
     fn = pathlib.Path(temp("dt_copy_from_disk_huge"))
     fn.unlink(missing_ok=True)

test/unit/test_dtype_spec.py

@@ -2,7 +2,8 @@ import unittest, math, operator, subprocess, struct
 from tinygrad.tensor import Tensor, dtypes, Device
 from tinygrad.dtype import DType, DTYPES_DICT, truncate, float_to_fp16, float_to_bf16, _to_np_dtype, least_upper_dtype, least_upper_float
 from tinygrad.device import is_dtype_supported
-from tinygrad.helpers import getenv, CI, DEBUG
+from tinygrad.helpers import getenv, DEBUG
+from test.helpers import slow
 from hypothesis import given, settings, strategies as strat
 import numpy as np
 import torch
@@ -594,7 +595,7 @@ class TestAutoCastType(unittest.TestCase):
     dtypes.default_float = old_default_float
 
   @unittest.skipIf(Device.DEFAULT == "PYTHON", "very slow")
-  @unittest.skipIf(CI and Device.DEFAULT == "AMD", "very slow")
+  @slow
   @unittest.skipIf(Device.DEFAULT == "WEBGPU", "Binding size is larger than the maximum storage buffer binding size")
   @unittest.skipUnless(is_dtype_supported(dtypes.half), "need half")
   def test_mean_half_precision_underflow(self):

test/unit/test_hashing.py

@@ -1,8 +1,8 @@
 from typing_extensions import Callable
 import hashlib, random, unittest
 from tinygrad import Tensor, Device, getenv, dtypes
+from test.helpers import slow
 from tinygrad.device import is_dtype_supported
-from tinygrad.helpers import CI
 from tinygrad.uop.ops import UOp
 from tinygrad.engine.jit import TinyJit
 
@@ -58,7 +58,7 @@ class TestKeccak(unittest.TestCase):
     self.assertEqual(bytes(Tensor(b"abc").keccak().tolist()),
                      bytearray.fromhex("3a985da74fe225b2 045c172d6bd390bd 855f086e3e9d525b 46bfe24511431532"))
 
-  @unittest.skipIf(CI, "times out in ci")
+  @slow
   def test_long(self):
     data = b"\x00" * 4
     self.assertEqual(bytes(Tensor(data).keccak("shake_128").tolist()), hashlib.shake_128(data).digest(16))
@@ -74,7 +74,7 @@ class TestKeccak(unittest.TestCase):
     self.assertEqual(bytes(out[1].tolist()), bytearray.fromhex("3a985da74fe225b2 045c172d6bd390bd 855f086e3e9d525b 46bfe24511431532"))
     self.assertEqual(bytes(out[2].tolist()), bytearray.fromhex("8e0d8f672252acb0 ffc5093db8653b18 1513bf9a2097e737 b4f73533dcaf46df"))
 
-  @unittest.skipIf(CI, "redundant with test_variable_bs")
+  @slow
   def test_variable_bs_jit(self):
     def f(data):
       return data.keccak()

test/unit/test_helpers.py

@@ -1,6 +1,6 @@
 import ctypes, gzip, unittest, timeit
 from tinygrad import Variable
-from tinygrad.helpers import Context, ContextVar, argfix, colored, word_wrap, is_numpy_ndarray, CI, mv_address, get_contraction
+from tinygrad.helpers import Context, ContextVar, argfix, colored, word_wrap, is_numpy_ndarray, mv_address, get_contraction
 from tinygrad.helpers import merge_dicts, strip_parens, prod, round_up, fetch, fully_flatten, from_mv, to_mv, polyN, time_to_str, cdiv, cmod, getbits
 from tinygrad.tensor import Tensor, get_shape
 import numpy as np
@@ -198,7 +198,7 @@ class TestMemoryview(unittest.TestCase):
     mv[0] = 2
     assert base[0] == 2
 
-  @unittest.skipIf(CI, "dangerous for CI, it allocates tons of memory")
+  @unittest.skip("allocates tons of memory")
   def test_to_mv(self):
     sizes = [
       (16, "16 B"),

test/unit/test_indexing.py

@@ -5,7 +5,8 @@ import numpy as np
 
 from tinygrad import Tensor, dtypes, Device, TinyJit
 from tinygrad.device import is_dtype_supported
-from tinygrad.helpers import CI, all_same, prod
+from tinygrad.helpers import all_same, prod
+from test.helpers import slow
 
 random.seed(42)
 
@@ -1140,7 +1141,7 @@ def get_set_tensor(indexed: Tensor, indexer):
   set_tensor = Tensor.randint(set_count, high=set_count).reshape(set_size) #.cast(dtypes.float64)
   return set_tensor
 
-@unittest.skipIf(CI and Device.DEFAULT in ["CPU", "CL", "METAL", "NV", "AMD"], "slow")
+@slow
 class TestAdvancedIndexing(unittest.TestCase):
   def test_integer_array_indexing(self):
     # pick a random valid indexer type

test/unit/test_shm_tensor.py

@@ -20,7 +20,7 @@ class TestRawShmBuffer(unittest.TestCase):
     assert np.allclose(t.numpy(), t2.numpy())
     s.unlink()
 
-  @unittest.skipIf(CI, "CI doesn't like big shared memory")
+  @unittest.skip("big shared memory")
   def test_e2e_big(self):
     # bigger than this doesn't work on Linux, maybe this is a limit somewhere?
     t = Tensor.randn(2048, 128, 8).realize()