Add remaining fixes

.pre-commit-config.yaml

@@ -55,7 +55,7 @@ repos:
     hooks:
     - id: doctest
       name: doctest
-      entry: python3 -m doctest
+      entry: python3 -m doctest -o NORMALIZE_WHITESPACE
       files: "^cyclops/evaluate/"
       language: system
 

cyclops/evaluate/metrics/experimental/confusion_matrix.py

@@ -20,7 +20,7 @@
 )
 from cyclops.evaluate.metrics.experimental.metric import Metric
 from cyclops.evaluate.metrics.experimental.utils.ops import dim_zero_cat
-from cyclops.evaluate.metrics.experimental.utils.typing import Array
+from cyclops.evaluate.metrics.experimental.utils.types import Array
 
 
 class _AbstractConfusionMatrix(Metric):

cyclops/evaluate/metrics/experimental/distributed_backends/base.py

@@ -3,7 +3,7 @@
 from abc import ABC, abstractmethod, abstractproperty
 from typing import Any, List, Optional
 
-from cyclops.evaluate.metrics.experimental.utils.typing import Array
+from cyclops.evaluate.metrics.experimental.utils.types import Array
 from cyclops.utils.log import setup_logging
 
 

cyclops/evaluate/metrics/experimental/distributed_backends/mpi4py.py

@@ -8,7 +8,7 @@
     DistributedBackend,
 )
 from cyclops.evaluate.metrics.experimental.utils.ops import flatten
-from cyclops.evaluate.metrics.experimental.utils.typing import Array
+from cyclops.evaluate.metrics.experimental.utils.types import Array
 from cyclops.utils.optional import import_optional_module
 
 

cyclops/evaluate/metrics/experimental/functional/confusion_matrix.py

@@ -13,7 +13,7 @@
     squeeze_all,
     to_int,
 )
-from cyclops.evaluate.metrics.experimental.utils.typing import Array
+from cyclops.evaluate.metrics.experimental.utils.types import Array
 from cyclops.evaluate.metrics.experimental.utils.validation import (
     _basic_input_array_checks,
     _check_same_shape,
@@ -252,7 +252,7 @@ class over the number of samples with the same true class.
     >>> preds = np.asarray([0.11, 0.22, 0.84, 0.73, 0.33, 0.92])
     >>> binary_confusion_matrix(target, preds)
     Array([[2, 1],
-           [1, 2]], dtype=int32)
+           [1, 2]], dtype=int64)
 
     """  # noqa: W505
     _binary_confusion_matrix_validate_args(
@@ -707,21 +707,21 @@ class over the number of true samples for each class.
     >>> multilabel_confusion_matrix(target, preds, num_labels=3)
     Array([[[1, 0],
             [0, 1]],
-
+    <BLANKLINE>
            [[1, 0],
             [1, 0]],
-
+    <BLANKLINE>
            [[0, 1],
             [0, 1]]], dtype=int64)
     >>> target = np.asarray([[0, 1, 0], [1, 0, 1]])
     >>> preds = np.asarray([[0.11, 0.22, 0.84], [0.73, 0.33, 0.92]])
     >>> multilabel_confusion_matrix(target, preds, num_labels=3)
     Array([[[1, 0],
             [0, 1]],
-
+    <BLANKLINE>
            [[1, 0],
             [1, 0]],
-
+    <BLANKLINE>
            [[0, 1],
             [0, 1]]], dtype=int64)
 

cyclops/evaluate/metrics/experimental/metric.py

@@ -28,7 +28,7 @@
     dim_zero_sum,
     flatten_seq,
 )
-from cyclops.evaluate.metrics.experimental.utils.typing import Array
+from cyclops.evaluate.metrics.experimental.utils.types import Array
 from cyclops.utils.log import setup_logging
 
 

cyclops/evaluate/metrics/experimental/utils/__init__.py

@@ -17,7 +17,7 @@
     squeeze_all,
     to_int,
 )
-from cyclops.evaluate.metrics.experimental.utils.typing import Array
+from cyclops.evaluate.metrics.experimental.utils.types import Array
 from cyclops.evaluate.metrics.experimental.utils.validation import (
     is_floating_point,
     is_numeric,

cyclops/evaluate/metrics/experimental/utils/ops.py

@@ -16,7 +16,7 @@
 from array_api_compat.common._helpers import _is_numpy_array, _is_torch_array
 from numpy.core.multiarray import normalize_axis_index  # type: ignore
 
-from cyclops.evaluate.metrics.experimental.utils.typing import Array
+from cyclops.evaluate.metrics.experimental.utils.types import Array
 from cyclops.evaluate.metrics.experimental.utils.validation import (
     _get_int_dtypes,
     is_floating_point,

cyclops/evaluate/metrics/experimental/utils/validation.py

@@ -3,7 +3,7 @@
 
 import array_api_compat as apc
 
-from cyclops.evaluate.metrics.experimental.utils.typing import Array
+from cyclops.evaluate.metrics.experimental.utils.types import Array
 
 
 def is_floating_point(array: Array) -> bool:

cyclops/evaluate/metrics/functional/precision_recall_curve.py

@@ -956,7 +956,6 @@ def multilabel_precision_recall_curve(
     )
 
 
-# ruff: noqa: W505
 def precision_recall_curve(
     target: npt.ArrayLike,
     preds: npt.ArrayLike,
@@ -1060,7 +1059,7 @@ def precision_recall_curve(
     >>> thresholds
     [array([0.05, 0.1 ]), array([0.9 , 0.95]), array([0.35, 0.8 ])]
 
-    """
+    """  # noqa: W505
     if task == "binary":
         return binary_precision_recall_curve(
             target,

cyclops/evaluate/metrics/functional/roc.py

@@ -502,7 +502,6 @@ def multilabel_roc_curve(
     return _multilabel_roc_compute(state, num_labels, thresholds)
 
 
-# ruff: noqa: W505
 def roc_curve(
     target: npt.ArrayLike,
     preds: npt.ArrayLike,
@@ -623,7 +622,7 @@ def roc_curve(
     >>> thresholds
     [array([1. , 0.9, 0.8, 0.2]), array([1. , 0.8, 0.7, 0.3])]
 
-    """
+    """  # noqa: W505
     _check_thresholds(thresholds)
     if task == "binary":
         return binary_roc_curve(target, preds, thresholds, pos_label=pos_label)

cyclops/evaluate/metrics/roc.py

@@ -39,20 +39,16 @@ class BinaryROCCurve(BinaryPrecisionRecallCurve, registry_key="binary_roc_curve"
     >>> preds = [0.1, 0.4, 0.35, 0.8]
     >>> metric = BinaryROCCurve()
     >>> metric(target, preds)
-    (array([0. , 0. , 0.5, 0.5, 1. ]),
-    array([0. , 0.5, 0.5, 1. , 1. ]),
-    array([1.  , 0.8 , 0.4 , 0.35, 0.1 ]))
+    (array([0. , 0. , 0.5, 0.5, 1. ]), array([0. , 0.5, 0.5, 1. , 1. ]), array([1.  , 0.8 , 0.4 , 0.35, 0.1 ]))
     >>> metric.reset_state()
     >>> target = [[1, 1, 0, 0], [0, 0, 1, 1]]
     >>> preds = [[0.1, 0.2, 0.3, 0.4], [0.6, 0.5, 0.4, 0.3]]
     >>> for t, p in zip(target, preds):
     ...     metric.update_state(t, p)
     >>> metric.compute()
-    (array([0.  , 0.25, 0.5 , 0.75, 1.  , 1.  , 1.  ]),
-    array([0.  , 0.  , 0.  , 0.25, 0.5 , 0.75, 1.  ]),
-    array([1. , 0.6, 0.5, 0.4, 0.3, 0.2, 0.1]))
+    (array([0.  , 0.25, 0.5 , 0.75, 1.  , 1.  , 1.  ]), array([0.  , 0.  , 0.  , 0.25, 0.5 , 0.75, 1.  ]), array([1. , 0.6, 0.5, 0.4, 0.3, 0.2, 0.1]))
 
-    """
+    """  # noqa: W505
 
     name: str = "ROC Curve"
 
@@ -107,12 +103,10 @@ class MulticlassROCCurve(
     >>> metric = MulticlassROCCurve(num_classes=3, thresholds=4)
     >>> metric(target, preds)
     (array([[0.        , 0.        , 0.        , 1.        ],
-            [0.        , 0.33333333, 0.33333333, 1.        ],
-            [0.        , 0.        , 0.        , 1.        ]]),
-    array([[0. , 0.5, 0.5, 1. ],
-            [0. , 1. , 1. , 1. ],
-            [0. , 0. , 1. , 1. ]]),
-    array([1.        , 0.66666667, 0.33333333, 0.        ]))
+           [0.        , 0.33333333, 0.33333333, 1.        ],
+           [0.        , 0.        , 0.        , 1.        ]]), array([[0. , 0.5, 0.5, 1. ],
+           [0. , 1. , 1. , 1. ],
+           [0. , 0. , 1. , 1. ]]), array([1.        , 0.66666667, 0.33333333, 0.        ]))
     >>> metric.reset_state()
     >>> target = [[1, 1, 0, 0], [0, 0, 1, 1]]
     >>> preds = [[[0.1, 0.2, 0.7], [0.5, 0.4, 0.1],
@@ -123,14 +117,12 @@ class MulticlassROCCurve(
     ...     metric.update_state(t, p)
     >>> metric.compute()
     (array([[0.  , 0.25, 0.5 , 1.  ],
-            [0.  , 0.  , 0.25, 1.  ],
-            [0.  , 0.25, 0.5 , 1.  ]]),
-    array([[0.  , 0.25, 0.5 , 1.  ],
-            [0.  , 0.  , 0.25, 1.  ],
-            [0.  , 0.  , 0.  , 0.  ]]),
-    array([1.        , 0.66666667, 0.33333333, 0.        ]))
+           [0.  , 0.  , 0.25, 1.  ],
+           [0.  , 0.25, 0.5 , 1.  ]]), array([[0.  , 0.25, 0.5 , 1.  ],
+           [0.  , 0.  , 0.25, 1.  ],
+           [0.  , 0.  , 0.  , 0.  ]]), array([1.        , 0.66666667, 0.33333333, 0.        ]))
 
-    """
+    """  # noqa: W505
 
     name: str = "ROC Curve"
 
@@ -185,12 +177,10 @@ class MultilabelROCCurve(
     >>> metric = MultilabelROCCurve(num_labels=3, thresholds=4)
     >>> metric(target, preds)
     (array([[0. , 0. , 0. , 1. ],
-            [0. , 0. , 0. , 0. ],
-            [0. , 0.5, 0.5, 1. ]]),
-    array([[0., 0., 0., 1.],
-            [0., 1., 1., 1.],
-            [0., 0., 0., 0.]]),
-    array([1.        , 0.66666667, 0.33333333, 0.        ]))
+           [0. , 0. , 0. , 0. ],
+           [0. , 0.5, 0.5, 1. ]]), array([[0., 0., 0., 1.],
+           [0., 1., 1., 1.],
+           [0., 0., 0., 0.]]), array([1.        , 0.66666667, 0.33333333, 0.        ]))
     >>> metric.reset_state()
     >>> target = [[[1, 1, 0], [0, 1, 0]], [[1, 1, 0], [0, 1, 0]]]
     >>> preds = [[[0.1, 0.9, 0.8], [0.05, 0.95, 0]],
@@ -199,12 +189,10 @@ class MultilabelROCCurve(
     ...     metric.update_state(t, p)
     >>> metric.compute()
     (array([[0. , 0. , 0. , 1. ],
-            [0. , 0. , 0. , 0. ],
-            [0. , 0.5, 0.5, 1. ]]),
-    array([[0., 0., 0., 1.],
-            [0., 1., 1., 1.],
-            [0., 0., 0., 0.]]),
-    array([1.        , 0.66666667, 0.33333333, 0.        ]))
+           [0. , 0. , 0. , 0. ],
+           [0. , 0.5, 0.5, 1. ]]), array([[0., 0., 0., 1.],
+           [0., 1., 1., 1.],
+           [0., 0., 0., 0.]]), array([1.        , 0.66666667, 0.33333333, 0.        ]))
 
     """
 
@@ -272,44 +260,37 @@ class ROCCurve(Metric, registry_key="roc_curve", force_register=True):
     >>> preds = [0.1, 0.4, 0.35, 0.8]
     >>> metric = ROCCurve(task="binary", thresholds=None)
     >>> metric(target, preds)
-    (array([0. , 0. , 0.5, 0.5, 1. ]),
-    array([0. , 0.5, 0.5, 1. , 1. ]),
-    array([1.  , 0.8 , 0.4 , 0.35, 0.1 ]))
+    (array([0. , 0. , 0.5, 0.5, 1. ]), array([0. , 0.5, 0.5, 1. , 1. ]), array([1.  , 0.8 , 0.4 , 0.35, 0.1 ]))
     >>> metric.reset_state()
     >>> target = [[1, 1, 0, 0], [0, 0, 1, 1]]
     >>> preds = [[0.1, 0.2, 0.3, 0.4], [0.6, 0.5, 0.4, 0.3]]
     >>> for t, p in zip(target, preds):
     ...     metric.update_state(t, p)
     >>> metric.compute()
-    (array([0.  , 0.25, 0.5 , 0.75, 1.  , 1.  , 1.  ]),
-    array([0.  , 0.  , 0.  , 0.25, 0.5 , 0.75, 1.  ]),
-    array([1. , 0.6, 0.5, 0.4, 0.3, 0.2, 0.1]))
+    (array([0.  , 0.25, 0.5 , 0.75, 1.  , 1.  , 1.  ]), array([0.  , 0.  , 0.  , 0.25, 0.5 , 0.75, 1.  ]), array([1. , 0.6, 0.5, 0.4, 0.3, 0.2, 0.1]))
 
     >>> # (multiclass)
     >>> from cyclops.evaluate.metrics import ROCCurve
-    >>> target = [[1, 1, 0], [0, 1, 0]]
-    >>> preds = [[0.1, 0.9, 0.8], [0.05, 0.95, 0]]
+    >>> target = [1, 2, 0]
+    >>> preds = [[0.05, 0.95, 0], [0.1, 0.8, 0.1], [0.2, 0.2, 0.6]]
     >>> metric = ROCCurve(task="multiclass", num_classes=3, thresholds=4)
     >>> metric(target, preds)
     (array([[0. , 0. , 0. , 1. ],
-            [0. , 0. , 0. , 0. ],
-            [0. , 0.5, 0.5, 1. ]]),
-    array([[0., 0., 0., 1.],
-            [0., 1., 1., 1.],
-            [0., 0., 0., 0.]]),
-    array([1.        , 0.66666667, 0.33333333, 0.        ]))
+           [0. , 0.5, 0.5, 1. ],
+           [0. , 0. , 0.5, 1. ]]), array([[0., 0., 0., 1.],
+           [0., 1., 1., 1.],
+           [0., 0., 0., 1.]]), array([1.        , 0.66666667, 0.33333333, 0.        ]))
     >>> metric.reset_state()
-    >>> target = [[[1, 1, 0], [0, 1, 0]], [[1, 1, 0], [0, 1, 0]]]
-    >>> preds = [[[0.1, 0.9, 0.8], [0.05, 0.95, 0]],
-    ...         [[0.1, 0.9, 0.8], [0.05, 0.95, 0]]]
+    >>> target = [1, 2]
+    >>> preds = [[[0.05, 0.75, 0.2]], [[0.1, 0.8, 0.1]]]
     >>> for t, p in zip(target, preds):
     ...     metric.update_state(t, p)
     >>> metric.compute()
-    (array([[0., 0., 0., 0.],
-           [0., 0., 0., 0.],
-           [0., 0., 0., 0.]]), array([[0., 0., 0., 0.],
-           [0., 0., 0., 0.],
-           [0., 0., 0., 0.]]), array([1.        , 0.66666667, 0.33333333, 0.        ]))
+    (array([[0., 0., 0., 1.],
+           [0., 1., 1., 1.],
+           [0., 0., 0., 1.]]), array([[0., 0., 0., 0.],
+           [0., 1., 1., 1.],
+           [0., 0., 0., 1.]]), array([1.        , 0.66666667, 0.33333333, 0.        ]))
 
     >>> # (multilabel)
     >>> from cyclops.evaluate.metrics import ROCCurve
@@ -335,7 +316,7 @@ class ROCCurve(Metric, registry_key="roc_curve", force_register=True):
            [0., 1., 1., 1.],
            [0., 0., 0., 0.]]), array([1.        , 0.66666667, 0.33333333, 0.        ]))
 
-    """
+    """  # noqa: W505
 
     name: str = "ROC Curve"
 

tests/cyclops/evaluate/metrics/experimental/inputs.py

@@ -9,7 +9,7 @@
 import torch
 from scipy.special import log_softmax
 
-from cyclops.evaluate.metrics.experimental.utils.typing import Array
+from cyclops.evaluate.metrics.experimental.utils.types import Array
 
 from ..conftest import BATCH_SIZE, EXTRA_DIM, NUM_BATCHES, NUM_CLASSES, NUM_LABELS
 

tests/cyclops/evaluate/metrics/experimental/test_operator_metric.py

@@ -4,7 +4,7 @@
 import pytest
 
 from cyclops.evaluate.metrics.experimental.metric import Metric, OperatorMetric
-from cyclops.evaluate.metrics.experimental.utils.typing import Array
+from cyclops.evaluate.metrics.experimental.utils.types import Array
 
 
 class DummyMetric(Metric):

tests/cyclops/evaluate/metrics/experimental/testers.py

@@ -7,7 +7,7 @@
 
 from cyclops.evaluate.metrics.experimental.metric import Metric
 from cyclops.evaluate.metrics.experimental.utils.ops import clone, flatten
-from cyclops.evaluate.metrics.experimental.utils.typing import Array
+from cyclops.evaluate.metrics.experimental.utils.types import Array
 
 
 def _assert_allclose(