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Fix integration test in 24.10 #8480

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Merged
merged 4 commits into from
Jun 13, 2025
Merged

Fix integration test in 24.10 #8480

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9025295
fix #8479
KumoLiu Jun 12, 2025
15625a5
try fix coverage
KumoLiu Jun 12, 2025
8a0e60b
revert coverage config change
KumoLiu Jun 12, 2025
c542e57
Merge branch 'dev' into fix-integration
KumoLiu Jun 13, 2025
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2 changes: 1 addition & 1 deletion setup.cfg
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Original file line number Diff line number Diff line change
Expand Up @@ -278,7 +278,7 @@ disallow_incomplete_defs = True

[coverage:run]
concurrency = multiprocessing
source = .
source = monai
data_file = .coverage/.coverage
omit = setup.py

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4 changes: 2 additions & 2 deletions tests/integration/test_integration_classification_2d.py
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Expand Up @@ -256,7 +256,7 @@ def train_and_infer(self, idx=0):
# check training properties
self.assertTrue(test_integration_value(TASK, key="losses", data=losses, rtol=1e-2))
self.assertTrue(test_integration_value(TASK, key="best_metric", data=best_metric, rtol=1e-4))
np.testing.assert_allclose(best_metric_epoch, 4)
np.testing.assert_allclose(best_metric_epoch, 1)
model_file = os.path.join(self.data_dir, "best_metric_model.pth")
self.assertTrue(os.path.exists(model_file))
# check inference properties
Expand All @@ -268,7 +268,7 @@ def train_and_infer(self, idx=0):

def test_training(self):
repeated = []
for i in range(1):
for i in range(2):
results = self.train_and_infer(i)
repeated.append(results)
np.testing.assert_allclose(repeated[0], repeated[1])
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2 changes: 1 addition & 1 deletion tests/integration/test_integration_workflows_adversarial.py
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Expand Up @@ -158,7 +158,7 @@ def tearDown(self):
set_determinism(seed=None)
shutil.rmtree(self.data_dir)

@TimedCall(seconds=200, daemon=False)
@TimedCall(seconds=300, daemon=False)
def test_training(self):
torch.manual_seed(0)

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155 changes: 97 additions & 58 deletions tests/testing_data/integration_answers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -70,64 +70,6 @@
],
}
},
{ # test answers for PyTorch 1.13
"integration_workflows": {
"output_sums_2": [
0.14264830205979873,
0.15264129328718357,
0.1519652511118344,
0.14003114557361543,
0.18870416611118465,
0.1699260498246968,
0.14727475398203582,
0.16870874483246967,
0.15757932277023196,
0.1797779694564011,
0.16310501082450635,
0.16850569170136015,
0.14472958359864832,
0.11402527744419455,
0.16217657428257873,
0.20135486560244975,
0.17627557567092866,
0.09802074024435596,
0.19418729084978026,
0.20339278025379662,
0.1966174446916041,
0.20872528599049203,
0.16246183433492764,
0.1323750751202327,
0.14830347036335728,
0.14300732028781024,
0.23163101813922762,
0.1612925258625139,
0.1489573676973957,
0.10299491921717041,
0.11921404797064328,
0.1300212751422368,
0.11437829790254125,
0.1524755276727056,
0.16350584736767904,
0.19424317961257148,
0.2229762916892286,
0.18121074825540173,
0.19064286213535897,
0.0747544243069024,
]
},
"integration_segmentation_3d": { # for the mixed readers
"losses": [
0.5451162219047546,
0.4709601759910583,
0.45201429128646853,
0.4443251401185989,
0.4341257899999619,
0.4350819975137711,
],
"best_metric": 0.9316844940185547,
"infer_metric": 0.9316383600234985,
},
},
{ # test answers for cuda 12
"integration_segmentation_3d": {
"losses": [
Expand Down Expand Up @@ -296,6 +238,103 @@
],
}
},
{ # test answers for 24.10
"integration_classification_2d": {
"losses": 0.7806512035761669,
"best_metric": 0.9977695200407783,
"infer_prop": [805, 727, 955, 1033, 321, 993],
},
"integration_workflows": {
"best_metric": 0.9207136034965515,
"best_metric_2": 0.9216295480728149,
"infer_metric": 0.920440673828125,
"infer_metric_2": 0.9203161001205444,
"output_sums": [
0.1423349380493164,
0.15172767639160156,
0.1382155418395996,
0.13398218154907227,
0.18552064895629883,
0.16435527801513672,
0.14128494262695312,
0.16725540161132812,
0.15690851211547852,
0.17731285095214844,
0.16189050674438477,
0.16543960571289062,
0.14431238174438477,
0.11064529418945312,
0.16129302978515625,
0.1970067024230957,
0.17503118515014648,
0.053476810455322266,
0.1914362907409668,
0.2001795768737793,
0.19636154174804688,
0.2040243148803711,
0.1606454849243164,
0.13213014602661133,
0.15132904052734375,
0.1370987892150879,
0.22805070877075195,
0.16170072555541992,
0.1477980613708496,
0.10428047180175781,
0.1195521354675293,
0.13089942932128906,
0.11238527297973633,
0.15204906463623047,
0.1603565216064453,
0.19054937362670898,
0.21789216995239258,
0.17824840545654297,
0.18654584884643555,
0.03622245788574219,
],
"output_sums_2": [
0.1423349380493164,
0.15172767639160156,
0.1382155418395996,
0.13398218154907227,
0.18552064895629883,
0.16435527801513672,
0.14128494262695312,
0.16725540161132812,
0.15690851211547852,
0.17731285095214844,
0.16189050674438477,
0.16543960571289062,
0.14431238174438477,
0.11064529418945312,
0.16129302978515625,
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0.17503118515014648,
0.053476810455322266,
0.1914362907409668,
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0.19636154174804688,
0.2040243148803711,
0.1606454849243164,
0.13213014602661133,
0.15132904052734375,
0.1370987892150879,
0.22805070877075195,
0.16170072555541992,
0.1477980613708496,
0.10428047180175781,
0.1195521354675293,
0.13089942932128906,
0.11238527297973633,
0.15204906463623047,
0.1603565216064453,
0.19054937362670898,
0.21789216995239258,
0.17824840545654297,
0.18654584884643555,
0.03622245788574219,
],
},
},
]


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