update docstring

ignite/metrics/clustering/calinski_harabasz_score.py

@@ -35,7 +35,7 @@ class CalinskiHarabaszScore(_ClusteringMetricBase):
     <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.calinski_harabasz_score.html>`_.
 
     - ``update`` must receive output of the form ``(features, labels)``
-       or ``{'features': features, 'labels': labels}``.
+      or ``{'features': features, 'labels': labels}``.
     - `features` and `labels` must be of same shape `(B, D)` and `(B,)`.
 
     Parameters are inherited from ``EpochMetric.__init__``.
@@ -47,6 +47,9 @@ class CalinskiHarabaszScore(_ClusteringMetricBase):
             you want to compute the metric with respect to one of the outputs.
             By default, metrics require the output as ``(features, labels)``
             or ``{'features': features, 'labels': labels}``.
+        check_compute_fn: if True, ``compute_fn`` is run on the first batch of data to ensure there are no
+            issues. If issues exist, user is warned that there might be an issue with the ``compute_fn``.
+            Default, True.
         device: specifies which device updates are accumulated on. Setting the
             metric's device to be the same as your ``update`` arguments ensures the ``update`` method is
             non-blocking. By default, CPU.

ignite/metrics/clustering/davies_bouldin_score.py

@@ -35,7 +35,7 @@ class DaviesBouldinScore(_ClusteringMetricBase):
     <https://scikit-learn.org/1.5/modules/generated/sklearn.metrics.davies_bouldin_score.html>`_.
 
     - ``update`` must receive output of the form ``(features, labels)``
-       or ``{'features': features, 'labels': labels}``.
+      or ``{'features': features, 'labels': labels}``.
     - `features` and `labels` must be of same shape `(B, D)` and `(B,)`.
 
     Parameters are inherited from ``EpochMetric.__init__``.
@@ -47,6 +47,9 @@ class DaviesBouldinScore(_ClusteringMetricBase):
             you want to compute the metric with respect to one of the outputs.
             By default, metrics require the output as ``(features, labels)``
             or ``{'features': features, 'labels': labels}``.
+        check_compute_fn: if True, ``compute_fn`` is run on the first batch of data to ensure there are no
+            issues. If issues exist, user is warned that there might be an issue with the ``compute_fn``.
+            Default, True.
         device: specifies which device updates are accumulated on. Setting the
             metric's device to be the same as your ``update`` arguments ensures the ``update`` method is
             non-blocking. By default, CPU.

ignite/metrics/clustering/silhouette_score.py

@@ -43,7 +43,7 @@ class SilhouetteScore(_ClusteringMetricBase):
     <https://scikit-learn.org/1.5/modules/generated/sklearn.metrics.silhouette_score.html>`_.
 
     - ``update`` must receive output of the form ``(features, labels)``
-       or ``{'features': features, 'labels': labels}``.
+      or ``{'features': features, 'labels': labels}``.
     - `features` and `labels` must be of same shape `(B, D)` and `(B,)`.
 
     Parameters are inherited from ``EpochMetric.__init__``.
@@ -55,6 +55,9 @@ class SilhouetteScore(_ClusteringMetricBase):
             you want to compute the metric with respect to one of the outputs.
             By default, metrics require the output as ``(features, labels)``
             or ``{'features': features, 'labels': labels}``.
+        check_compute_fn: if True, ``compute_fn`` is run on the first batch of data to ensure there are no
+            issues. If issues exist, user is warned that there might be an issue with the ``compute_fn``.
+            Default, True.
         device: specifies which device updates are accumulated on. Setting the
             metric's device to be the same as your ``update`` arguments ensures the ``update`` method is
             non-blocking. By default, CPU.