Svyatoslav Pchelintsev

> With regards to https://github.com/soyeonm/FILM/issues/2#issue-1188383110 issue, I will reply again soon! But I do believe it does work.. does it not? The https://github.com/soyeonm/FILM/issues/9#issuecomment-1124906829 states that it's necessary to use `--data...

Hmm, it looks like the best solution for this is offered [here](https://github.com/soyeonm/FILM/issues/2#issue-1188383110). It's necessary to use `--data data/json_2.1.0`, not `--data data/json_feat_2.1.0`, then the preprocessed files are saved in `json_2.1.0` and...

I also want to note that `best_model_multi.pt` is extracted as `best_model_multi.pt` **and** `new_best_model.pt` in the instructions:  It looks like a typo, since `new_best_model.pt` is also present in the the...

@xadupre, yes, I tried. I've just tried one more time and got exactly the same error (I compared it to the output above using www.diffchecker.com and the only difference is...

@xadupre, thank you for the tests! I looked at the tests and they gave me an idea of what is wrong. I haven't noticed that `month, hour, holiday, weekday, workingday`...

Oh, I didn't know this... > You should convert them into int64 before calling the converter. Sorry, I don't understand. Should I convert the entire column before training? Or can...

Ah, I see. It's more coherent to convert the entire dataset before the training then. I did this and ``` model_onnx = to_onnx(model.model, X=X_train[:1], verbose=1) ``` has worked correctly: ```...

Oh, no, there is another error when I try to load the onnx model. ``` model_onnx = to_onnx(model.model, X=X_train[:1], verbose=1) sess = InferenceSession( model_onnx.SerializeToString(), providers=["CPUExecutionProvider"] ) ``` gives ``` File...

Sorry, I don't know onnx well, but at what point is something send to the LabelEncoder? I do not provide any data. If `X_train[:1]` is used, I'm sure there are...

I don't see any problems here, do you? (The LabelEncoder5 is under `Y = 5`)  Here is also `Concat`: