docs(datasets) Fix formatting of the DistributionPartitioner docs (#4582

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adap · Nov 26, 2024 · a21782f · a21782f
1 parent 62a301b
commit a21782f
Showing 1 changed file with 16 additions and 15 deletions.
diff --git a/datasets/flwr_datasets/partitioner/distribution_partitioner.py b/datasets/flwr_datasets/partitioner/distribution_partitioner.py
@@ -36,21 +36,22 @@ class DistributionPartitioner(Partitioner):  # pylint: disable=R0902
     in a deterministic pathological manner. The 1st dimension is the number of unique
     labels and the 2nd-dimension is the number of buckets into which the samples
     associated with each label will be divided. That is, given a distribution array of
-    shape,
-                           `num_unique_labels_per_partition` x `num_partitions`
-    ( `num_unique_labels`, ---------------------------------------------------- ),
-                                          `num_unique_labels`
-    the label_id at the i'th row is assigned to the partition_id based on the following
-    approach.
-
-    First, for an i'th row, generate a list of `id`s according to the formula:
-        id = alpha + beta
-    where,
-        alpha = (i - num_unique_labels_per_partition + 1) \
-                 + (j % num_unique_labels_per_partition),
-        alpha = alpha + (alpha >= 0 ? 0 : num_unique_labels),
-        beta = num_unique_labels * (j // num_unique_labels_per_partition)
-    and j in {0, 1, 2, ..., `num_columns`}. Then, sort the list of `id`s in ascending
+    shape,::
+
+                            `num_unique_labels_per_partition` x `num_partitions`
+        ( `num_unique_labels`, ---------------------------------------------------- ),
+                                            `num_unique_labels`
+        the label_id at the i'th row is assigned to the partition_id based on the
+        following approach.
+
+        First, for an i'th row, generate a list of `id`s according to the formula:
+            id = alpha + beta
+        where,
+            alpha = (i - num_unique_labels_per_partition + 1) +
+                    + (j % num_unique_labels_per_partition),
+            alpha = alpha + (alpha >= 0 ? 0 : num_unique_labels),
+            beta = num_unique_labels * (j // num_unique_labels_per_partition)
+    and j in {0, 1, 2, ..., `num_columns`}. Then, sort the list of `id` s in ascending
     order. The j'th index in this sorted list corresponds to the partition_id that the
     i'th unique label (and the underlying distribution array value) will be assigned to.
     So, for a dataset with 10 unique labels and a configuration with 20 partitions and