I noticed that when I use the fix for the pre-trained checkpoint issue, the model will output different attentions every time i run it on the same SMILES. now I took it out (bc this fix wasn't needed when i am working on our server where I pre-trained everything with the same setup myself) and now it seems to be consistent for each run. But that behaviour is quite weird no? After training a model the output should be consistent, anyone any idea what's going on there? running
kind='test'
model = model_class.load_from_checkpoint(ckpt_opt, input_dim = data_module.feature_vector_size, pretrained_checkpoint=None)
vs
model = model_class.load_from_checkpoint(ckpt_opt, input_dim = data_module.feature_vector_size)
I noticed that when I use the fix for the pre-trained checkpoint issue, the model will output different attentions every time i run it on the same SMILES. now I took it out (bc this fix wasn't needed when i am working on our server where I pre-trained everything with the same setup myself) and now it seems to be consistent for each run. But that behaviour is quite weird no? After training a model the output should be consistent, anyone any idea what's going on there? running
kind='test'model = model_class.load_from_checkpoint(ckpt_opt, input_dim = data_module.feature_vector_size, pretrained_checkpoint=None)vs
model = model_class.load_from_checkpoint(ckpt_opt, input_dim = data_module.feature_vector_size)