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fix symbolic_ops tests with Tensor.training=True (#1686)

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chenyu
2023-08-26 20:19:56 -07:00
committed by GitHub
parent 6c5dc9c153
commit 66fbf4800b
3 changed files with 10 additions and 5 deletions
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12
test/test_symbolic_ops.py
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@@ -44,9 +44,8 @@ class TestSymbolicOps(unittest.TestCase):
with self.assertRaises(AssertionError):
f(a.reshape(3, vi), b.reshape(vi, 5)).numpy()
@unittest.skipIf(Device.DEFAULT == "CLANG" and CI, "broken on CLANG CI")
def test_attention(self):
def f(q, k, v): return Tensor.scaled_dot_product_attention(q.transpose(1, 2), k.transpose(1, 2), v.transpose(1, 2)).realize()
def test_attention(self, dropout_p=0.0):
def f(q, k, v): return Tensor.scaled_dot_product_attention(q.transpose(1, 2), k.transpose(1, 2), v.transpose(1, 2), dropout_p=dropout_p).realize()
vi = Variable("i", 1, 10)
for i in range(1, 5):
q = Tensor.rand(2, 1, 4, 8)
@@ -56,6 +55,13 @@ class TestSymbolicOps(unittest.TestCase):
expected = f(q, k, v).numpy()
np.testing.assert_allclose(symbolic, expected, atol=1e-6, rtol=1e-6)
def test_attention_training(self):
Tensor.training = True
self.test_attention(dropout_p=0.0)
with self.assertRaises(TypeError):
# symbolic shape dropout is not supported
self.test_attention(dropout_p=0.5)
def test_cat_dim0(self):
def f(a, b): return a.cat(b, dim=0).realize()
vi = Variable("i", 1, 10)