ONNX model of ToKey outputs 1 based key, while 0 based expected

[ganik]

Repro
`from nimbusml.datasets import get_dataset
from nimbusml.preprocessing import OnnxRunner, ToKey

iris_df = get_dataset("iris").as_df()
iris_df = iris_df.drop(['Label'], axis=1)

transform = ToKey() << {'NewVals': 'Setosa'}
print(transform.fit_transform(iris_df))
transform.export_to_onnx("test.onnx", 'com.microsoft.ml')
onnx_runner = OnnxRunner(model_file="test.onnx")
print(onnx_runner.fit_transform(iris_df))`

Output:
Sepal_Length Sepal_Width Petal_Length Petal_Width Species Setosa NewVals
0 5.1 3.5 1.4 0.2 setosa 1.0 0
1 4.9 3.0 1.4 0.2 setosa 1.0 0
2 4.7 3.2 1.3 0.2 setosa 1.0 0
3 4.6 3.1 1.5 0.2 setosa 1.0 0
4 5.0 3.6 1.4 0.2 setosa 1.0 0
.. ... ... ... ... ... ... ...
145 6.7 3.0 5.2 2.3 virginica 0.0 1
146 6.3 2.5 5.0 1.9 virginica 0.0 1
147 6.5 3.0 5.2 2.0 virginica 0.0 1
148 6.2 3.4 5.4 2.3 virginica 0.0 1
149 5.9 3.0 5.1 1.8 virginica 0.0 1

[150 rows x 7 columns]
Sepal_Length Sepal_Width Petal_Length ... Species.onnx.0 Setosa.onnx.0 NewVals.onnx.0
0 5.1 3.5 1.4 ... setosa 1.0 1.0
1 4.9 3.0 1.4 ... setosa 1.0 1.0
2 4.7 3.2 1.3 ... setosa 1.0 1.0
3 4.6 3.1 1.5 ... setosa 1.0 1.0
4 5.0 3.6 1.4 ... setosa 1.0 1.0
.. ... ... ... ... ... ... ...
145 6.7 3.0 5.2 ... virginica 0.0 2.0
146 6.3 2.5 5.0 ... virginica 0.0 2.0
147 6.5 3.0 5.2 ... virginica 0.0 2.0
148 6.2 3.4 5.4 ... virginica 0.0 2.0
149 5.9 3.0 5.1 ... virginica 0.0 2.0

[150 rows x 13 columns]

[Lynx1820]

Update: It was decided that this issue would not be resolved, as Pandas expects 1 based keys.