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Merged
vfdev-5 merged 6 commits into from
Aug 19, 2022
Merged

Update test_cohen_kappa.py #2656

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b777d2d
Update test_cohen_kappa.py
puhuk Aug 19, 2022
c500240
Update test_cohen_kappa.py
puhuk Aug 19, 2022
11f66bf
Update test_cohen_kappa.py
puhuk Aug 19, 2022
5788cd6
Update test_cohen_kappa.py
puhuk Aug 19, 2022
9fd7408
Merge branch 'master' into test_cohen_kappa
vfdev-5 Aug 19, 2022
535f480
Merge branch 'master' into test_cohen_kappa
vfdev-5 Aug 19, 2022
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23 changes: 12 additions & 11 deletions tests/ignite/contrib/metrics/test_cohen_kappa.py
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Original file line number Diff line number Diff line change
Expand Up @@ -173,15 +173,12 @@ def get_test_cases():
def _test_distrib_binary_input(device):

rank = idist.get_rank()
torch.manual_seed(12)

def _test(y_pred, y, batch_size, metric_device):

metric_device = torch.device(metric_device)
ck = CohenKappa(device=metric_device)

torch.manual_seed(10 + rank)

ck.reset()
if batch_size > 1:
n_iters = y.shape[0] // batch_size + 1
Expand Down Expand Up @@ -213,7 +210,8 @@ def get_test_cases():
]
return test_cases

for _ in range(3):
for i in range(3):
torch.manual_seed(10 + rank + i)
test_cases = get_test_cases()
for y_pred, y, batch_size in test_cases:
_test(y_pred, y, batch_size, "cpu")
Expand All @@ -224,23 +222,23 @@ def get_test_cases():
def _test_distrib_integration_binary_input(device):

rank = idist.get_rank()
torch.manual_seed(12)

def _test(n_epochs, metric_device):
metric_device = torch.device(metric_device)
n_iters = 80
s = 16
batch_size = 16
n_classes = 2
offset = n_iters * s

torch.manual_seed(12 + rank)

# Binary input data of shape (N,) or (N, 1)
y_true = torch.randint(0, n_classes, size=(offset * idist.get_world_size(),)).to(device)
y_preds = torch.randint(0, n_classes, size=(offset * idist.get_world_size(),)).to(device)
y_true = torch.randint(0, n_classes, size=(n_iters * batch_size,)).to(device)
y_preds = torch.randint(0, n_classes, size=(n_iters * batch_size,)).to(device)

def update(engine, i):
return (
y_preds[i * s + rank * offset : (i + 1) * s + rank * offset],
y_true[i * s + rank * offset : (i + 1) * s + rank * offset],
y_preds[i * batch_size : (i + 1) * batch_size],
y_true[i * batch_size : (i + 1) * batch_size],
)

engine = Engine(update)
Expand All @@ -251,6 +249,9 @@ def update(engine, i):
data = list(range(n_iters))
engine.run(data=data, max_epochs=n_epochs)

y_true = idist.all_gather(y_true)
y_preds = idist.all_gather(y_preds)

assert "ck" in engine.state.metrics

res = engine.state.metrics["ck"]
Expand Down