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rename lazydata to uop (#10698)

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This commit is contained in:
George Hotz
2025-06-08 08:42:22 -07:00
committed by GitHub
parent 8e3f337075
commit 32e9949052
57 changed files with 485 additions and 486 deletions
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36
test/test_tensor.py
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@@ -565,17 +565,17 @@ class TestZeroShapeTensor(unittest.TestCase):
t = Tensor.empty(3, 2, 0)
assert t.shape == (3, 2, 0)
# numpy has stride 0, 0, 0; torch has stride 2, 1, 1
assert t.lazydata.st.real_strides() == (0, 0, 0)
assert t.uop.st.real_strides() == (0, 0, 0)
t = Tensor.empty(3, 0, 2)
assert t.shape == (3, 0, 2)
# numpy has stride 0, 0, 0; torch has stride 2, 2, 1
assert t.lazydata.st.real_strides() == (0, 0, 0)
assert t.uop.st.real_strides() == (0, 0, 0)
t = Tensor.empty(0, 0, 0)
assert t.shape == (0, 0, 0)
# numpy has stride 0, 0, 0; torch has stride 1, 1, 1
assert t.lazydata.st.real_strides() == (0, 0, 0)
assert t.uop.st.real_strides() == (0, 0, 0)
def test_rand(self):
t = Tensor.rand(3, 2, 0)
@@ -690,24 +690,24 @@ class TestZeroShapeTensor(unittest.TestCase):
a = Tensor.rand(16, 16).realize()
b = a.clone()
np.testing.assert_allclose(a.numpy(), b.numpy())
self.assertIsNot(a.lazydata.base.buffer, b.lazydata.base.buffer)
self.assertIsNot(a.uop.base.buffer, b.uop.base.buffer)
a = Tensor.rand(16, 16).mul(5.0).add(5.0).realize()
b = a.clone()
np.testing.assert_allclose(a.numpy(), b.numpy())
self.assertIsNot(a.lazydata.base.buffer, b.lazydata.base.buffer)
self.assertIsNot(a.uop.base.buffer, b.uop.base.buffer)
def test_clone_with_shrink(self):
a = Tensor.rand(16, 16)
b = a.shrink(((2, 10), None)).clone()
b.realize()
self.assertIsNot(a.lazydata.base.buffer, b.lazydata.base.buffer)
self.assertIsNot(a.uop.base.buffer, b.uop.base.buffer)
def test_clone_with_shrink_realized(self):
a = Tensor.rand(16, 16).realize()
b = a.shrink(((2, 10), None)).clone()
b.realize()
self.assertIsNot(a.lazydata.base.buffer, b.lazydata.base.buffer)
self.assertIsNot(a.uop.base.buffer, b.uop.base.buffer)
def test_clone_with_grad(self):
a = Tensor.rand(16, 16, requires_grad=True)
@@ -780,7 +780,7 @@ class TestTensorMetadata(unittest.TestCase):
@unittest.skip("why would this be true?")
def test_exclude_noop_metadata(self):
a = Tensor.rand(4, 4)*1
self.assertEqual(a.lazydata.metadata[0].name, "__mul__")
self.assertEqual(a.uop.metadata[0].name, "__mul__")
k = a.schedule()[-1]
self.assertEqual([m.name for m in k.metadata], ["rand"])
@@ -797,7 +797,7 @@ class TestTensorMetadata(unittest.TestCase):
x = Tensor.rand(3, requires_grad=True)
W = Tensor.rand(3, 3, requires_grad=True)
out = x.matmul(W)
self.assertEqual(out.lazydata.metadata[0].name, "matmul")
self.assertEqual(out.uop.metadata[0].name, "matmul")
si = out.schedule()[-1]
self.assertEqual(len(si.metadata), 1)
self.assertEqual(si.metadata[0].name, "matmul")
@@ -805,7 +805,7 @@ class TestTensorMetadata(unittest.TestCase):
def test_relu(self):
x = Tensor.rand(3, requires_grad=True)
out = x.relu()
self.assertEqual(out.lazydata.metadata[0].name, "relu")
self.assertEqual(out.uop.metadata[0].name, "relu")
si = out.schedule()[-1]
self.assertEqual(len(si.metadata), 1)
self.assertEqual(si.metadata[0].name, "relu")
@@ -814,9 +814,9 @@ class TestTensorMetadata(unittest.TestCase):
x = Tensor.rand(3, requires_grad=True)
y = Tensor.rand(3, requires_grad=True)
out = x.relu() * y.sigmoid()
self.assertEqual(out.lazydata.metadata[0].name, "__mul__")
self.assertEqual(out.lazydata.src[0].metadata[0].name, "relu")
self.assertEqual(out.lazydata.src[1].metadata[0].name, "sigmoid")
self.assertEqual(out.uop.metadata[0].name, "__mul__")
self.assertEqual(out.uop.src[0].metadata[0].name, "relu")
self.assertEqual(out.uop.src[1].metadata[0].name, "sigmoid")
si = out.schedule()[-1]
self.assertEqual(len(si.metadata), 3)
self.assertEqual(set(m.name for m in si.metadata), {"relu", "sigmoid", "__mul__"})
@@ -825,12 +825,12 @@ class TestTensorMetadata(unittest.TestCase):
x = Tensor.rand(3, requires_grad=True).realize()
y = Tensor.rand(3, requires_grad=True).realize()
out = (x.relu() * y.sigmoid()).sum()
self.assertEqual(out.lazydata.metadata[0].name, "sum")
self.assertEqual(out.uop.metadata[0].name, "sum")
out.backward()
self.assertEqual(x.grad.lazydata.metadata[0].name, "relu")
self.assertTrue(x.grad.lazydata.metadata[0].backward)
self.assertEqual(y.grad.lazydata.metadata[0].name, "sigmoid")
self.assertTrue(y.grad.lazydata.metadata[0].backward)
self.assertEqual(x.grad.uop.metadata[0].name, "relu")
self.assertTrue(x.grad.uop.metadata[0].backward)
self.assertEqual(y.grad.uop.metadata[0].name, "sigmoid")
self.assertTrue(y.grad.uop.metadata[0].backward)
si = Tensor.schedule(out, x.grad, y.grad)[-1]
self.assertEqual(len(si.metadata), 4, f"failed with {si.metadata}")
self.assertSetEqual(set(m.name for m in si.metadata), {"sigmoid", "__mul__", "relu"})