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Fix some tests (especially compile with fullgraph=True on Python<3.11) (#38319)

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* fix tests

* better fix for python<3.11

* fixes

* style
This commit is contained in:
Cyril Vallez
2025-05-23 17:11:40 +02:00
committed by GitHub
parent a63bc17416
commit 896833c183
7 changed files with 48 additions and 83 deletions
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6
tests/models/cohere/test_modeling_cohere.py
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@@ -232,8 +232,8 @@ class CohereIntegrationTest(unittest.TestCase):
EXPECTED_LOGITS = torch.Tensor(
[
[[0.0000, 0.1866, -0.1997], [0.0000, -0.0736, 0.1785], [0.0000, -0.1965, -0.0569]],
[[0.0000, -0.0302, 0.1488], [0.0000, -0.0402, 0.1351], [0.0000, -0.0341, 0.1116]],
[[0.0000, 0.0285, 0.0322], [0.0000, 0.0011, 0.1105], [0.0000, -0.0018, -0.1019]],
[[0.0000, 0.1080, 0.0454], [0.0000, -0.1808, -0.1553], [0.0000, 0.0452, 0.0369]],
]
).to(device=torch_device, dtype=torch.float16)
@@ -251,4 +251,4 @@ class CohereIntegrationTest(unittest.TestCase):
output = model(**inputs)
logits = output.logits
torch.testing.assert_close(EXPECTED_LOGITS, logits[:, :3, :3], rtol=1e-3, atol=1e-3)
torch.testing.assert_close(EXPECTED_LOGITS, logits[:, -3:, :3], rtol=1e-3, atol=1e-3)

1
tests/models/csm/test_modeling_csm.py
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@@ -150,7 +150,6 @@ class CsmForConditionalGenerationTest(ModelTesterMixin, GenerationTesterMixin, u
test_headmasking = False
test_resize_embeddings = False
test_resize_embeddings_untied = False
test_torch_exportable = True
def setUp(self):
self.model_tester = CsmModelTester(self)

23
tests/models/mixtral/test_modeling_mixtral.py
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@@ -402,24 +402,12 @@ class MixtralIntegrationTest(unittest.TestCase):
#
# Note: Key 9 is currently set for MI300, but may need potential future adjustments for H100s,
# considering differences in hardware processing and potential deviations in generated text.
EXPECTED_LOGITS_LEFT = {
7: torch.Tensor(
[[0.1904, 0.0500, 0.7187], [0.1933, 0.0515, 0.7187], [0.2001, 0.0559, 0.7148]],
).to(torch_device),
8: torch.Tensor([[0.1914, 0.0508, 0.7188], [0.1953, 0.0510, 0.7227], [0.1973, 0.0562, 0.7148]]).to(
torch_device
),
9: torch.Tensor([[0.1904, 0.0513, 0.7227], [0.1943, 0.0518, 0.7227], [0.1982, 0.0557, 0.7148]]).to(
torch_device
),
}
EXPECTED_LOGITS_LEFT_UNPADDED = {
7: torch.Tensor(
[[0.2236, 0.5195, -0.3828], [0.8203, -0.2275, 0.6054], [0.2656, -0.7070, 0.2460]],
).to(torch_device),
8: torch.Tensor([[0.2217, 0.5195, -0.3828], [0.8203, -0.2295, 0.6055], [0.2676, -0.7109, 0.2461]]).to(
torch_device
8: torch.Tensor([[0.2207, 0.5234, -0.3828], [0.8203, -0.2285, 0.6055], [0.2656, -0.7109, 0.2451]]).to(
torch_device,
),
9: torch.Tensor([[0.2236, 0.5195, -0.3828], [0.8203, -0.2285, 0.6055], [0.2637, -0.7109, 0.2451]]).to(
torch_device
@@ -430,8 +418,8 @@ class MixtralIntegrationTest(unittest.TestCase):
7: torch.Tensor([[0.2167, 0.1269, -0.1640], [-0.3496, 0.2988, -1.0312], [0.0688, 0.7929, 0.8007]]).to(
torch_device
),
8: torch.Tensor([[0.2178, 0.1260, -0.1621], [-0.3496, 0.2988, -1.0312], [0.0693, 0.7930, 0.8008]]).to(
torch_device
8: torch.Tensor([[0.2178, 0.1270, -0.1621], [-0.3496, 0.3008, -1.0312], [0.0693, 0.7930, 0.7969]]).to(
torch_device,
),
9: torch.Tensor([[0.2197, 0.1250, -0.1611], [-0.3516, 0.3008, -1.0312], [0.0684, 0.7930, 0.8008]]).to(
torch_device
@@ -442,9 +430,6 @@ class MixtralIntegrationTest(unittest.TestCase):
logits = model(dummy_input, attention_mask=attention_mask).logits
logits = logits.float()
torch.testing.assert_close(
logits[0, :3, :3], EXPECTED_LOGITS_LEFT[self.cuda_compute_capability_major_version], atol=1e-3, rtol=1e-3
)
torch.testing.assert_close(
logits[0, -3:, -3:],
EXPECTED_LOGITS_LEFT_UNPADDED[self.cuda_compute_capability_major_version],

1
tests/test_modeling_common.py
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@@ -4461,6 +4461,7 @@ class ModelTesterMixin:
del loss
model = torch.compile(model, fullgraph=True, mode="reduce-overhead")
# forward compilation
set_seed(42)
loss = model(**inputs).loss