fix doc linting

ignite/metrics/maximum_mean_discrepancy.py

@@ -29,7 +29,7 @@ class MaximumMeanDiscrepancy(Metric):
 
     More details can be found in `Gretton et al. 2012`__.
 
-    __ https://jmlr.csail.mit.edu/papers/v13/gretton12a.html
+    __ https://www.jmlr.org/papers/volume13/gretton12a/gretton12a.pdf
 
     - ``update`` must receive output of the form ``(x, y)``.
     - ``x`` and ``y`` are expected to be in the same shape :math:`(B, \ldots)`.

ignite/utils.py

@@ -94,31 +94,36 @@ def _tree_map(
 
 def flatten_format_and_include_keys(data: Any) -> List[str]:
     """
-        Recursively formats and flattens complex data structures, including keys for dictionaries.
-
-        This function processes nested dictionaries, lists, tuples, numbers, and PyTorch tensors,
-        formatting numbers to four decimal places and handling tensors with special formatting rules.
-        It's particularly useful for logging, debugging, or any scenario where a human-readable
-        representation of complex, nested data structures is required.
-
-        The function handles the following types:
-        - Numbers: Formatted to four decimal places.
-        - PyTorch tensors:
-            - Scalars are formatted to four decimal places.
-            - 1D tensors with more than 10 elements show the first 10 elements followed by an ellips
-    is.
-            - 1D tensors with 10 or fewer elements are fully listed.
-            - Multi-dimensional tensors display their shape.
-        - Dictionaries: Each key-value pair is included in the output with the key as a prefix.
-        - Lists and tuples: Flattened and included in the output. Empty lists/tuples are represented by an empty string.
-        - None values: Represented by an empty string.
-
-        Args:
-            data: The input data to be flattened and formatted. It can be a nested combination of
-                  dictionaries, lists, tuples, numbers, and PyTorch tensors.
-
-        Returns:
-            A list of formatted strings, each representing a part of the input data structure.
+    Recursively formats and flattens complex data structures, including keys for
+    dictionaries.
+
+    This function processes nested dictionaries, lists, tuples, numbers, and
+    PyTorch tensors, formatting numbers to four decimal places and handling
+    tensors with special formatting rules. It's particularly useful for logging,
+    debugging, or any scenario where a human-readable representation of complex,
+    nested data structures is required.
+
+    The function handles the following types: - Numbers: Formatted to four
+    decimal places. - PyTorch tensors:
+        - Scalars are formatted to four decimal places.
+        - 1D tensors with more than 10 elements show the first 10 elements
+          followed by an ellipsis.
+        - 1D tensors with 10 or fewer elements are fully listed.
+        - Multi-dimensional tensors display their shape.
+    - Dictionaries: Each key-value pair is included in the output with the key
+      as a prefix.
+    - Lists and tuples: Flattened and included in the output. Empty lists/tuples
+      are represented by an empty string.
+    - None values: Represented by an empty string.
+
+    Args:
+        data: The input data to be flattened and formatted. It can be a nested
+        combination of dictionaries, lists, tuples, numbers, and PyTorch
+        tensors.
+
+    Returns:
+        A list of formatted strings, each representing a part of the input data
+        structure.
     """
     formatted_items: List[str] = []