LightGBM multiclass convert error

[little-eyes]

I try to add a test for lightgbm, but i found multiclass classification seems to have error:

=================================== FAILURES ===================================
_______ TestLGBMClassifierConverter.test_model_multiclass_classification _______

self = <test_LightGBMClassifier.TestLGBMClassifierConverter testMethod=test_model_multiclass_classification>

    def test_model_multiclass_classification(self):
        model = self._fit_model_binary_classification(LGBMClassifier(
            objective="ova",
            learning_rate=0.05,
            boosting_type="gbdt",
            num_class=10))
>       model_onnx = convert_sklearn(model, 'scikit-learn LGBM multiclass classifier', [('input', FloatTensorType([1, 10]))])

tests/sklearn/test_LightGBMClassifier.py:47: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
onnxmltools/convert/main.py:18: in convert_sklearn
    doc_string, targeted_onnx, custom_conversion_functions, custom_shape_calculators)
onnxmltools/convert/sklearn/convert.py:97: in convert
    onnx_model = convert_topology(topology, name, doc_string, targeted_onnx)
onnxmltools/convert/common/_topology.py:704: in convert_topology
    _registration.get_converter(operator.type)(scope, operator, container)
onnxmltools/convert/sklearn/operator_converters/LightGbm.py:140: in convert_lightgbm
    _parse_tree_structure(tree_id, class_id, learning_rate, tree['tree_structure'], attrs)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

tree_id = 2, class_id = 2, learning_rate = 1
tree_structure = {'leaf_value': -34.53877639770508}
attrs = {'class_ids': [0, 0, 0, 1, 1, 1], 'class_nodeids': [3, 4, 2, 3, 4, 2], 'class_treeids': [0, 0, 0, 1, 1, 1], 'class_weights': [0.004500000000000001, 0.005, -0.005000000000000001, -0.004500000000000001, -0.005, 0.005000000000000001], ...}

    def _parse_tree_structure(tree_id, class_id, learning_rate, tree_structure, attrs):
        # The pool of all nodes' indexes created when parsing a single tree. Different trees may use different pools.
        node_id_pool = set()
    
        node_id = _create_node_id(node_id_pool)
        left_id = _create_node_id(node_id_pool)
        right_id = _create_node_id(node_id_pool)
    
        attrs['nodes_treeids'].append(tree_id)
        attrs['nodes_nodeids'].append(node_id)
    
>       attrs['nodes_featureids'].append(tree_structure['split_feature'])
E       KeyError: 'split_feature'

onnxmltools/convert/sklearn/operator_converters/LightGbm.py:49: KeyError

The relevant code is here #152

[little-eyes]

Actually, given the dataset is small but I produced too many trees which cause the problem. I reduced it, then it works fine now.