Getting predictions for all observations in train (or test) in order?

I am trying to get feature vectors of images from models pre-trained on imagenet. I am using learn.get_preds() since it does the scoring in batches which is much quicker than scoring individually.

The problem I am having is I can’t seem to confirm that rows in my predictions tensor (number of images x 1000 (output size of pre-trained models)). I am trying to compare the model output of the first input in my dataset with the output of the get_preds, but the predictions are different. I tried to check if it was because of fastai automatically normalizing on get_preds, but may have not checked that correctly. Any help would be appreciated.

Below is code I am using and a screen shot of different vector outputs.

# fastai 1.0.52 (SageMaker notebook)

data = (

data_test = (

learn = Learner(data, m)

preds = learn.get_preds('train')