[FLAML Crash] [Classification] 0 feature is supplied. Are you using raw Booster interface?

Hey, thanks for the great system.

I am experiencing a crash with the following multi-class classification dataset from Kaggle: spooky-author-identification. I get the following error when I try to fit FLAML:

  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/flaml/automl.py", line 1524, in fit
    self._search()
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/flaml/automl.py", line 2009, in _search
    self._search_sequential()
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/flaml/automl.py", line 1825, in _search_sequential
    use_ray=False,
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/flaml/tune/tune.py", line 382, in run
    result = training_function(trial_to_run.config)
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/flaml/automl.py", line 240, in _compute_with_config_base
    self.fit_kwargs,
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/flaml/ml.py", line 328, in compute_estimator
    fit_kwargs=fit_kwargs)
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/flaml/ml.py", line 267, in evaluate_model_CV
    log_training_metric=log_training_metric, fit_kwargs=fit_kwargs)
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/flaml/ml.py", line 196, in get_test_loss
    estimator.fit(X_train, y_train, budget, **fit_kwargs)
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/flaml/model.py", line 515, in fit
    return super().fit(X_train, y_train, budget, **kwargs)
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/flaml/model.py", line 318, in fit
    self._t1 = self._fit(X_train, y_train, **kwargs)
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/flaml/model.py", line 99, in _fit
    model.fit(X_train, y_train, **kwargs)
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/xgboost/core.py", line 422, in inner_f
    return f(**kwargs)
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/xgboost/sklearn.py", line 915, in fit
    callbacks=callbacks)
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/xgboost/training.py", line 235, in train
    early_stopping_rounds=early_stopping_rounds)
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/xgboost/training.py", line 102, in _train_internal
    bst.update(dtrain, i, obj)
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/xgboost/core.py", line 1282, in update
    dtrain.handle))
  File "/home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/xgboost/core.py", line 189, in _check_call
    raise XGBoostError(py_str(_LIB.XGBGetLastError()))
xgboost.core.XGBoostError: [04:04:16] ../src/learner.cc:567: Check failed: mparam_.num_feature != 0 (0 vs. 0) : 0 feature is supplied.  Are you using raw Booster interface?
Stack trace:
  [bt] (0) /home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/xgboost/lib/libxgboost.so(+0x8d264) [0x7fadf8272264]
  [bt] (1) /home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/xgboost/lib/libxgboost.so(+0x1ae8d2) [0x7fadf83938d2]
  [bt] (2) /home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/xgboost/lib/libxgboost.so(+0x1bc0ac) [0x7fadf83a10ac]
  [bt] (3) /home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/xgboost/lib/libxgboost.so(+0x1a29cb) [0x7fadf83879cb]
  [bt] (4) /home/mossad/anaconda3/envs/kgpip/lib/python3.7/site-packages/xgboost/lib/libxgboost.so(XGBoosterUpdateOneIter+0x58) [0x7fadf82650c8]
  [bt] (5) /home/mossad/anaconda3/envs/kgpip/lib/python3.7/lib-dynload/../../libffi.so.7(+0x69dd) [0x7fae5a76a9dd]
  [bt] (6) /home/mossad/anaconda3/envs/kgpip/lib/python3.7/lib-dynload/../../libffi.so.7(+0x6067) [0x7fae5a76a067]
  [bt] (7) /home/mossad/anaconda3/envs/kgpip/lib/python3.7/lib-dynload/_ctypes.cpython-37m-x86_64-linux-gnu.so(_ctypes_callproc+0x2e7) [0x7fae5a7823a7]
  [bt] (8) /home/mossad/anaconda3/envs/kgpip/lib/python3.7/lib-dynload/_ctypes.cpython-37m-x86_64-linux-gnu.so(+0x12e14) [0x7fae5a782e14]

Here is my script:

df = pd.read_csv('spooky.csv')
X, y = df.drop('author', axis=1), df['author']
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=123)
automl_model = AutoML()
automl_model.fit(X_train, y_train, task='classification',
                           time_budget=300,
                           retrain_full='budget',
                           verbose=0, metric='macro_f1')

Your feedback is appreciated.