* JitError

* test_symbolic_jit
This commit is contained in:
chenyu
2026-01-06 12:19:50 -05:00
committed by GitHub
parent 6ddddc68af
commit 4491ec0c9e
4 changed files with 20 additions and 17 deletions

View File

@@ -5,7 +5,7 @@ import numpy as np
from hypothesis import given, settings, strategies as strat
from test.helpers import assert_jit_cache_len, not_support_multi_device, REAL_DEV, needs_second_gpu
from tinygrad.tensor import Tensor
from tinygrad.engine.jit import TinyJit, GraphRunner, MultiGraphRunner, graph_class
from tinygrad.engine.jit import TinyJit, JitError, GraphRunner, MultiGraphRunner, graph_class
from tinygrad.engine.realize import CompiledRunner, BufferCopy, BufferXfer
from tinygrad.device import Device
from tinygrad.helpers import Context, JIT, GlobalCounters, getenv
@@ -76,7 +76,7 @@ class TestJit(unittest.TestCase):
def test_nothing_jitted(self):
@TinyJit
def add(a, b): return None
with self.assertRaises(AssertionError):
with self.assertRaises(JitError):
for _ in range(5):
a = Tensor.randn(10, 10)
b = Tensor.randn(10, 10)
@@ -125,13 +125,13 @@ class TestJit(unittest.TestCase):
b = Tensor.randn(10, 10)
add(a, b)
bad = Tensor.randn(20, 20)
with self.assertRaises(AssertionError):
with self.assertRaises(JitError):
add(a, bad)
def test_jit_shape_views_mismatch(self):
@TinyJit
def add(a): return (a+1).realize()
with self.assertRaises(AssertionError):
with self.assertRaises(JitError):
for i in range(1,5):
# a has an offset that the kernel doesn't know about
a = Tensor.randn(10, 10).realize()[:, i:i+2]
@@ -142,7 +142,7 @@ class TestJit(unittest.TestCase):
@TinyJit
def add(a, b): return (a+b).realize()
a = Tensor.randn(10, 10)
with self.assertRaises(AssertionError):
with self.assertRaises(JitError):
add(a, a)
def test_jit_assign(self, dtype=dtypes.float32):
@@ -510,7 +510,7 @@ class TestJit(unittest.TestCase):
# TODO: this should fail since input has a different size
f(Tensor(2.0)).item()
# TODO: this should not fail, and should return 3
with self.assertRaises(AssertionError):
with self.assertRaises(JitError):
f(Tensor([2.0])).item()
@unittest.skip("Pending multioutput implementation #3607")

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@@ -21,6 +21,7 @@ ERRORS RAISED (lower priority - at least users know):
import unittest
import numpy as np
from tinygrad import Tensor, TinyJit
from tinygrad.engine.jit import JitError
class TestJitFootguns(unittest.TestCase):
@@ -70,7 +71,7 @@ class TestJitFootguns(unittest.TestCase):
def f(a, b): return (a + b).realize()
x = Tensor([1, 2, 3])
with self.assertRaises(AssertionError):
with self.assertRaises(JitError):
f(x, x)
def test_tensors_in_containers_ignored(self):
@@ -116,7 +117,7 @@ class TestJitFootguns(unittest.TestCase):
def f(a): return (a + 1).realize()
base = Tensor.randn(10, 10).realize()
with self.assertRaises(AssertionError):
with self.assertRaises(JitError):
for i in range(1, 5):
f(base[:, i:i+2]) # different offset each time
@@ -128,7 +129,7 @@ class TestJitFootguns(unittest.TestCase):
f(Tensor.randn(10, 10), Tensor.randn(10, 10)) # warmup
f(Tensor.randn(10, 10), Tensor.randn(10, 10)) # capture
with self.assertRaises(AssertionError):
with self.assertRaises(JitError):
f(Tensor.randn(20, 20), Tensor.randn(20, 20))
def test_python_constants_frozen(self):
@@ -170,7 +171,7 @@ class TestJitFootguns(unittest.TestCase):
f(Tensor([1]), Tensor([2])) # warmup with positional
f(Tensor([1]), Tensor([2])) # capture with positional
with self.assertRaises(AssertionError):
with self.assertRaises(JitError):
f(a=Tensor([3]), b=Tensor([4])) # kwargs fail
def test_class_method_shared_across_instances(self):
@@ -213,7 +214,7 @@ class TestJitFootguns(unittest.TestCase):
@TinyJit
def f(a, b): return None
with self.assertRaises(AssertionError):
with self.assertRaises(JitError):
for _ in range(3):
f(Tensor([1]), Tensor([2]))

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@@ -2,6 +2,7 @@ import unittest
from test.helpers import assert_jit_cache_len
from tinygrad import Variable, Tensor, TinyJit
from tinygrad.engine.jit import JitError
import numpy as np
class TestSymbolicJit(unittest.TestCase):
@@ -172,7 +173,7 @@ class TestSymbolicJit(unittest.TestCase):
vi2 = Variable("i", 1, 10).bind(7)
a = Tensor.rand(3, 7)[:, :vi2]
bad = Tensor.rand(4, 7)[:, :vi2]
with self.assertRaises(AssertionError):
with self.assertRaises(JitError):
add(a, bad)
def test_shrink(self):