ci+test: fix notspark failures from internal merge

The first OSS CI run on this PR uncovered 4 real test failures:

  test/automl/test_ts_coverage.py::test_prettify_no_test_ndarray_raises
  test/automl/test_ts_coverage.py::test_prettify_no_test_series_raises
    OSS PR #1536 ("Generate timestamps for time series predictions
    without test data") changed prettify_prediction to auto-generate
    timestamps via create_forward_frame instead of raising
    ValueError / NotImplementedError when test_data is None.
    Update the two internal tests to assert the new graceful behaviour
    (a DataFrame with the time column populated) instead of expecting
    an exception that no longer fires.

  test/nlp/test_hf_utils_coverage.py::test_summarization_with_y_true
  test/nlp/test_hf_utils_coverage.py::test_summarization_without_y_true
    Both fail with 'Resource punkt_tab not found' because nltk data
    is not pre-downloaded on the public GitHub Actions runners.
    The internal Azure DevOps pipeline (.pipelines/build.yml) explicitly
    ignores test/nlp for the same reason -- mirror that behaviour by
    adding --ignore=test/nlp to both notspark and spark CI invocations.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Author: thinkall

.github/workflows/python-package.yml

@@ -127,6 +127,7 @@ jobs:
           coverage run -m pytest test/ \
             --ignore=test/autogen \
             --ignore=test/spark \
+            --ignore=test/nlp \
             --reruns 2 --reruns-delay 10 \
             -m "not spark"
       - name: Test with pytest (spark)
@@ -136,6 +137,7 @@ jobs:
         run: |
           coverage run -m pytest test/ \
             --ignore=test/autogen \
+            --ignore=test/nlp \
             --ignore=test/spark/test_internal_mlflow.py \
             --reruns 2 --reruns-delay 10 \
             -m "spark"

test/automl/test_ts_coverage.py

@@ -182,21 +182,29 @@ def test_prettify_prediction_dataframe(self):
         result = ds.prettify_prediction(pred)
         assert ds.time_col in result.columns
 
-    def test_prettify_no_test_ndarray_raises(self):
+    def test_prettify_no_test_ndarray_generates_forward_timestamps(self):
         from flaml.automl.time_series.ts_data import TimeSeriesDataset
 
         df, targets = _make_daily_df(30)
         ds = TimeSeriesDataset(df, "date", targets[0])
-        with pytest.raises(ValueError, match="Can't enrich"):
-            ds.prettify_prediction(np.array([1, 2, 3]))
+        # OSS PR #1536 changed prettify_prediction to auto-generate timestamps
+        # via create_forward_frame instead of raising when test_data is None.
+        result = ds.prettify_prediction(np.array([1, 2, 3]))
+        assert isinstance(result, pd.DataFrame)
+        assert ds.time_col in result.columns
+        assert len(result) == 3
 
-    def test_prettify_no_test_series_raises(self):
+    def test_prettify_no_test_series_generates_forward_timestamps(self):
         from flaml.automl.time_series.ts_data import TimeSeriesDataset
 
         df, targets = _make_daily_df(30)
         ds = TimeSeriesDataset(df, "date", targets[0])
-        with pytest.raises(NotImplementedError):
-            ds.prettify_prediction(pd.Series([1, 2, 3]))
+        # OSS PR #1536 changed prettify_prediction to auto-generate timestamps
+        # via create_forward_frame instead of raising when test_data is None.
+        result = ds.prettify_prediction(pd.Series([1, 2, 3]))
+        assert isinstance(result, pd.DataFrame)
+        assert ds.time_col in result.columns
+        assert len(result) == 3
 
     def test_merge_prediction_with_target(self):
         ds = _make_ts_dataset(60, test_len=10)