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CI: AMD MI300 tests fix (#30797)

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* add fix

* update import

* updated dicts and comments

* remove prints

* Update testing_utils.py
This commit is contained in:
Mohit Sharma
2024-05-21 17:16:07 +05:30
committed by GitHub
parent a755745546
commit 7a4792e6b3
10 changed files with 126 additions and 10 deletions
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21
tests/models/mixtral/test_modeling_mixtral.py
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@@ -553,6 +553,10 @@ class MixtralIntegrationTest(unittest.TestCase):
)
# TODO: might need to tweak it in case the logits do not match on our daily runners
# these logits have been obtained with the original megablocks impelmentation.
# Key 9 for MI300, Key 8 for A100/A10, and Key 7 for T4.
#
# 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 output.
EXPECTED_LOGITS = {
7: torch.Tensor([[0.1670, 0.1620, 0.6094], [-0.8906, -0.1588, -0.6060], [0.1572, 0.1290, 0.7246]]).to(
torch_device
@@ -560,6 +564,9 @@ class MixtralIntegrationTest(unittest.TestCase):
8: torch.Tensor([[0.1631, 0.1621, 0.6094], [-0.8906, -0.1621, -0.6094], [0.1572, 0.1270, 0.7227]]).to(
torch_device
),
9: torch.Tensor([[0.1641, 0.1621, 0.6094], [-0.8906, -0.1631, -0.6094], [0.1572, 0.1260, 0.7227]]).to(
torch_device
),
}
with torch.no_grad():
logits = model(dummy_input).logits
@@ -583,6 +590,11 @@ class MixtralIntegrationTest(unittest.TestCase):
)
# TODO: might need to tweak it in case the logits do not match on our daily runners
#
# Key 9 for MI300, Key 8 for A100/A10, and Key 7 for T4.
#
# 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(
[[0.1750, 0.0537, 0.7007], [0.1750, 0.0537, 0.7007], [0.1750, 0.0537, 0.7007]],
@@ -590,6 +602,9 @@ class MixtralIntegrationTest(unittest.TestCase):
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 = {
@@ -599,6 +614,9 @@ class MixtralIntegrationTest(unittest.TestCase):
8: torch.Tensor([[0.2217, 0.5195, -0.3828], [0.8203, -0.2295, 0.6055], [0.2676, -0.7109, 0.2461]]).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
),
}
EXPECTED_LOGITS_RIGHT_UNPADDED = {
@@ -608,6 +626,9 @@ class MixtralIntegrationTest(unittest.TestCase):
8: torch.Tensor([[0.2178, 0.1260, -0.1621], [-0.3496, 0.2988, -1.0312], [0.0693, 0.7930, 0.8008]]).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
),
}
with torch.no_grad():