Skip to content

Update test_accuracy.py #2647

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
vfdev-5 merged 1 commit into from
Aug 16, 2022
Merged

Update test_accuracy.py #2647

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
18 changes: 10 additions & 8 deletions tests/ignite/metrics/test_accuracy.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -488,22 +488,22 @@ def _test_distrib_accumulator_device(device):
def _test_distrib_integration_list_of_tensors_or_numbers(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 = 10

offset = n_iters * s
y_true = torch.randint(0, n_classes, size=(offset * idist.get_world_size(),)).to(device)
y_preds = torch.rand(offset * idist.get_world_size(), n_classes).to(device)
torch.manual_seed(12 + rank)

y_true = torch.randint(0, n_classes, size=(n_iters * batch_size,)).to(device)
y_preds = torch.rand(n_iters * batch_size, n_classes).to(device)

def update(_, i):
return (
[v for v in y_preds[i * s + rank * offset : (i + 1) * s + rank * offset, :]],
[v.item() for v in y_true[i * s + rank * offset : (i + 1) * s + rank * offset]],
[v for v in y_preds[i * batch_size : (i + 1) * batch_size, ...]],
[v.item() for v in y_true[i * batch_size : (i + 1) * batch_size]],
)

engine = Engine(update)
Expand All @@ -514,6 +514,9 @@ def update(_, 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 (
acc._num_correct.device == metric_device
), f"{type(acc._num_correct.device)}:{acc._num_correct.device} vs {type(metric_device)}:{metric_device}"
Expand All @@ -524,7 +527,6 @@ def update(_, i):
res = res.cpu().numpy()

true_res = accuracy_score(y_true.cpu().numpy(), torch.argmax(y_preds, dim=1).cpu().numpy())

assert pytest.approx(res) == true_res

metric_devices = ["cpu"]
Expand Down