fix(holdout): setting test size to 0 for holdout (#275)

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# Summary
Added an early return in naive_train_test_split when test_size == 0,
bypassing sklearn's train_test_split which rejects 0 as an invalid
value.

Also added test for `naive_train_test_split`

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- [ ] New or updated tests for any fix or new behavior
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## Other Notes

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- Closes #172

Signed-off-by: Sean Yang <seayang@nvidia.com>

Author: seayang-nv

src/nemo_safe_synthesizer/holdout/holdout.py

@@ -44,6 +44,9 @@ def naive_train_test_split(df, test_size, random_state=None) -> DataFrameOptiona
         Tuple of ``(train_df, test_df)``, or ``(train_df, None)`` if the
         split produces no test set.
     """
+    if test_size == 0:
+        return df.reset_index(drop=True), None
+
     train, test = train_test_split(df, test_size=test_size, random_state=random_state)
     if test is None:
         return train, None

tests/holdout/test_holdout.py

@@ -10,6 +10,7 @@
     HOLDOUT_TOO_SMALL_ERROR,
     INPUT_DATA_TOO_SMALL_ERROR,
     Holdout,
+    naive_train_test_split,
 )
 
 
@@ -88,6 +89,12 @@ def test_zero_max_holdout(df):
     assert test is None
 
 
+def test_naive_train_test_split_zero_int_test_size(df):
+    train, test = naive_train_test_split(df, test_size=0)
+    assert len(train) == 200
+    assert test is None
+
+
 def test_does_group_by_holdout(df):
     holdout = Holdout(SafeSynthesizerParameters.from_params(group_training_examples_by="big_cat"))
     train, test = holdout.train_test_split(df)