Understanding multiclass on Chemprop

I have a CSV file that looks like the example below:

CAN_SMILES	class1	class2	class 3
SMILES1	0	0	1
SMILES2	0	0	1
SMILES3	0	0	1

I then trained the NN with:

chemprop_train --data_path data.csv --dataset_type multiclass \ 
--save_dir 00_all_datapoints_dedup_random_split.train.accuracy \
--metric accuracy --split_type random --split_sizes 0.8 0.2 0.0  \
--gpu 1 --dropout 0 --ensemble_size 1 --num_folds 1 --hidden_size 300 \
--ffn_hidden_size 300 --smiles_column CAN_SMILES  \
--target_columns class1 class2 class3  \
--multiclass_num_classes 3

What I was expecting from the predictions was something like [P(class1), P(class2), P(class3], and summing up those three probabilities equals 1. However, I am getting the following:

CAN_SMILES	class1	class2	class 3	class1_class_0	class1_class_1	class1_class_2
SMILES1	0	0	1	[0.4089986979961395, 0.3245898485183716, 0.2664114236831665]	[0.4382680356502533, 0.18726319074630737, 0.3744688332080841]	[0.37828463315963745, 0.417496919631958, 0.20421843230724335]
SMILES2	0	0	1	[0.4023689031600952, 0.3176715075969696, 0.27995961904525757]	[0.42649418115615845, 0.20301619172096252, 0.3704896569252014]	[0.365766704082489, 0.4299478232860565, 0.20428545773029327]
SMILES3	0	0	1	[0.4001476764678955, 0.3139444887638092, 0.28590789437294006]	[0.4191807508468628, 0.2087540626525879, 0.3720651865005493]	[0.3638008236885071, 0.41967928409576416, 0.21651984751224518]

I am completely lost with these results. As I mentioned above, I was expecting a single output vector with the probabilities for each class. Also, I don’t understand the labeling class1_class_0 – what is it referring to? I inspected the code and found;

https://github.com/chemprop/chemprop/blob/2ae05928f386fcf3306ce2491a8fc6a1f03655ec/chemprop/train/make_predictions.py#L129-L133

But it is not clear to me yet. I hope someone could help me to understand this. As you see, I have 3 columns with three different classes, and I want Chemprop to predict the probability of each one in a vector [P(class1), P(class2), P(class3)].

Note: I also tried saving to the CSV file the SMILES, [class1, class2, class3] but that seems to not being parsed by Chemprop.

[hesther]

Dear @muammar, this looks great. Happy I could help!

[hesther]

Hey @muammar, if the classes are mutually exclusive (what they seem to be), you need to reformat your CSV into something like:

CAN_SMILES	class
SMILES1	2
SMILES2	2
SMILES3	2

so, class1 = 0, class2 = 1 and class3 = 2