set dtype for multilabel test inputs

VectorInstitute · Feb 7, 2024 · 2834deb · 2834deb
1 parent b6651f4
commit 2834deb
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Showing 3 changed files with 52 additions and 30 deletions.
diff --git a/tests/cyclops/evaluate/metrics/experimental/inputs.py b/tests/cyclops/evaluate/metrics/experimental/inputs.py
@@ -1,4 +1,5 @@
 """Input data for tests of metrics in cyclops/evaluate/metrics/experimental."""
+
 import random
 from collections import namedtuple
 from types import ModuleType
@@ -296,43 +297,46 @@ def _multilabel_cases(*, xp: Any):
     return (
         pytest.param(
             InputSpec(
-                target=xp.asarray(_multilabel_labels),
-                preds=xp.asarray(_multilabel_preds),
+                target=xp.asarray(_multilabel_labels, dtype=xp.int32),
+                preds=xp.asarray(_multilabel_preds, dtype=xp.int32),
             ),
             id="input[2d-labels]",
         ),
         pytest.param(
             InputSpec(
-                target=xp.asarray(_multilabel_labels_multidim),
-                preds=xp.asarray(_multilabel_preds_multidim),
+                target=xp.asarray(_multilabel_labels_multidim, dtype=xp.int32),
+                preds=xp.asarray(_multilabel_preds_multidim, dtype=xp.int32),
             ),
             id="input[multidim-labels]",
         ),
         pytest.param(
             InputSpec(
-                target=xp.asarray(_multilabel_labels),
-                preds=xp.asarray(_multilabel_probs),
+                target=xp.asarray(_multilabel_labels, dtype=xp.int32),
+                preds=xp.asarray(_multilabel_probs, dtype=xp.float32),
             ),
             id="input[2d-probs]",
         ),
         pytest.param(
             InputSpec(
-                target=xp.asarray(_multilabel_labels),
-                preds=xp.asarray(_inv_sigmoid(_multilabel_probs)),
+                target=xp.asarray(_multilabel_labels, dtype=xp.int32),
+                preds=xp.asarray(_inv_sigmoid(_multilabel_probs), dtype=xp.float32),
             ),
             id="input[2d-logits]",
         ),
         pytest.param(
             InputSpec(
-                target=xp.asarray(_multilabel_labels_multidim),
-                preds=xp.asarray(_multilabel_probs_multidim),
+                target=xp.asarray(_multilabel_labels_multidim, dtype=xp.int32),
+                preds=xp.asarray(_multilabel_probs_multidim, dtype=xp.float32),
             ),
             id="input[multidim-probs]",
         ),
         pytest.param(
             InputSpec(
-                target=xp.asarray(_multilabel_labels_multidim),
-                preds=xp.asarray(_inv_sigmoid(_multilabel_probs_multidim)),
+                target=xp.asarray(_multilabel_labels_multidim, dtype=xp.int32),
+                preds=xp.asarray(
+                    _inv_sigmoid(_multilabel_probs_multidim),
+                    dtype=xp.float32,
+                ),
             ),
             id="input[multidim-logits]",
         ),

diff --git a/tests/cyclops/evaluate/metrics/experimental/test_precision_recall_curve.py b/tests/cyclops/evaluate/metrics/experimental/test_precision_recall_curve.py
@@ -1,4 +1,5 @@
 """Test precision-recall curve metric."""
+
 from functools import partial
 from typing import List, Tuple, Union
 
@@ -45,9 +46,11 @@ def _binary_precision_recall_curve_reference(
     return tm_binary_precision_recall_curve(
         torch.utils.dlpack.from_dlpack(preds),
         torch.utils.dlpack.from_dlpack(target),
-        thresholds=torch.utils.dlpack.from_dlpack(thresholds)
-        if apc.is_array_api_obj(thresholds)
-        else thresholds,
+        thresholds=(
+            torch.utils.dlpack.from_dlpack(thresholds)
+            if apc.is_array_api_obj(thresholds)
+            else thresholds
+        ),
         ignore_index=ignore_index,
     )
 
@@ -215,9 +218,11 @@ def _multiclass_precision_recall_curve_reference(
         torch.utils.dlpack.from_dlpack(preds),
         torch.utils.dlpack.from_dlpack(target),
         num_classes,
-        thresholds=torch.utils.dlpack.from_dlpack(thresholds)
-        if apc.is_array_api_obj(thresholds)
-        else thresholds,
+        thresholds=(
+            torch.utils.dlpack.from_dlpack(thresholds)
+            if apc.is_array_api_obj(thresholds)
+            else thresholds
+        ),
         ignore_index=ignore_index,
     )
 
@@ -371,16 +376,20 @@ def _multilabel_precision_recall_curve_reference(
         torch.utils.dlpack.from_dlpack(preds),
         torch.utils.dlpack.from_dlpack(target),
         num_labels,
-        thresholds=torch.utils.dlpack.from_dlpack(thresholds)
-        if apc.is_array_api_obj(thresholds)
-        else thresholds,
+        thresholds=(
+            torch.utils.dlpack.from_dlpack(thresholds)
+            if apc.is_array_api_obj(thresholds)
+            else thresholds
+        ),
         ignore_index=ignore_index,
     )
 
 
 class TestMultilabelPrecisionRecallCurve(MetricTester):
     """Test multilabel precision-recall curve function and class."""
 
+    atol: float = 2e-7
+
     @pytest.mark.parametrize("inputs", _multilabel_cases(xp=anp)[2:])
     @pytest.mark.parametrize("thresholds", _thresholds(xp=anp))
     @pytest.mark.parametrize("ignore_index", [None, 0, -1])

diff --git a/tests/cyclops/evaluate/metrics/experimental/test_roc.py b/tests/cyclops/evaluate/metrics/experimental/test_roc.py
@@ -1,4 +1,5 @@
 """Test roc curve metric."""
+
 from functools import partial
 from typing import List, Tuple, Union
 
@@ -45,9 +46,11 @@ def _binary_roc_reference(
     return tm_binary_roc(
         torch.utils.dlpack.from_dlpack(preds),
         torch.utils.dlpack.from_dlpack(target),
-        thresholds=torch.utils.dlpack.from_dlpack(thresholds)
-        if apc.is_array_api_obj(thresholds)
-        else thresholds,
+        thresholds=(
+            torch.utils.dlpack.from_dlpack(thresholds)
+            if apc.is_array_api_obj(thresholds)
+            else thresholds
+        ),
         ignore_index=ignore_index,
     )
 
@@ -215,9 +218,11 @@ def _multiclass_roc_reference(
         torch.utils.dlpack.from_dlpack(preds),
         torch.utils.dlpack.from_dlpack(target),
         num_classes,
-        thresholds=torch.utils.dlpack.from_dlpack(thresholds)
-        if apc.is_array_api_obj(thresholds)
-        else thresholds,
+        thresholds=(
+            torch.utils.dlpack.from_dlpack(thresholds)
+            if apc.is_array_api_obj(thresholds)
+            else thresholds
+        ),
         ignore_index=ignore_index,
     )
 
@@ -371,16 +376,20 @@ def _multilabel_roc_reference(
         torch.utils.dlpack.from_dlpack(preds),
         torch.utils.dlpack.from_dlpack(target),
         num_labels,
-        thresholds=torch.utils.dlpack.from_dlpack(thresholds)
-        if apc.is_array_api_obj(thresholds)
-        else thresholds,
+        thresholds=(
+            torch.utils.dlpack.from_dlpack(thresholds)
+            if apc.is_array_api_obj(thresholds)
+            else thresholds
+        ),
         ignore_index=ignore_index,
     )
 
 
 class TestMultilabelROC(MetricTester):
     """Test multilabel roc curve function and class."""
 
+    atol: float = 9e-8
+
     @pytest.mark.parametrize("inputs", _multilabel_cases(xp=anp)[2:])
     @pytest.mark.parametrize("thresholds", _thresholds(xp=anp))
     @pytest.mark.parametrize("ignore_index", [None, 0, -1])