Skip to content
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

Initialize aggregation metrics with default floating type #2366

Merged
merged 5 commits into from
Feb 12, 2024
Merged

Initialize aggregation metrics with default floating type #2366

Show file tree
Hide file tree
Changes from 3 commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
486cba8
implementation
SkafteNicki Feb 9, 2024
43abc5f
tests
SkafteNicki Feb 9, 2024
30d5531
Merge branch 'master' into bugfix/aggregation_with_default_type
SkafteNicki Feb 9, 2024
2f0714a
changelog
SkafteNicki Feb 9, 2024
59bb3c9
Merge branch 'master' into bugfix/aggregation_with_default_type
SkafteNicki Feb 12, 2024
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
10 changes: 5 additions & 5 deletions src/torchmetrics/aggregation.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -157,7 +157,7 @@ def __init__(
) -> None:
super().__init__(
"max",
-torch.tensor(float("inf")),
-torch.tensor(float("inf"), dtype=torch.get_default_dtype()),
nan_strategy,
state_name="max_value",
**kwargs,
Expand Down Expand Up @@ -262,7 +262,7 @@ def __init__(
) -> None:
super().__init__(
"min",
torch.tensor(float("inf")),
torch.tensor(float("inf"), dtype=torch.get_default_dtype()),
nan_strategy,
state_name="min_value",
**kwargs,
Expand Down Expand Up @@ -366,7 +366,7 @@ def __init__(
) -> None:
super().__init__(
"sum",
torch.tensor(0.0),
torch.tensor(0.0, dtype=torch.get_default_dtype()),
nan_strategy,
state_name="sum_value",
**kwargs,
Expand Down Expand Up @@ -536,12 +536,12 @@ def __init__(
) -> None:
super().__init__(
"sum",
torch.tensor(0.0),
torch.tensor(0.0, dtype=torch.get_default_dtype()),
nan_strategy,
state_name="mean_value",
**kwargs,
)
self.add_state("weight", default=torch.tensor(0.0), dist_reduce_fx="sum")
self.add_state("weight", default=torch.tensor(0.0, dtype=torch.get_default_dtype()), dist_reduce_fx="sum")

def update(self, value: Union[float, Tensor], weight: Union[float, Tensor] = 1.0) -> None:
"""Update state with data.
Expand Down
17 changes: 17 additions & 0 deletions tests/unittests/bases/test_aggregation.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -204,3 +204,20 @@ def test_mean_metric_broadcast(nan_strategy):
metric.update(x, w)
res = metric.compute()
assert round(res.item(), 4) == 3.2222 # (0*0 + 2*2 + 3*3 + 4*4) / (0 + 2 + 3 + 4)


@pytest.mark.parametrize(
("metric_class", "compare_function"),
[(MinMetric, torch.min), (MaxMetric, torch.max), (SumMetric, torch.sum), (MeanMetric, torch.mean)],
)
def test_with_default_dtype(metric_class, compare_function):
"""Test that the metric works with a default dtype of float64."""
torch.set_default_dtype(torch.float64)
metric = metric_class()
values = torch.randn(10000)
metric.update(values)
result = metric.compute()
assert result.dtype == torch.float64
assert result.dtype == values.dtype
assert torch.allclose(result, compare_function(values), atol=1e-12)
torch.set_default_dtype(torch.float32)
Loading