understanding the dataloader procedure

[seyeeet]

Thanks so much for providing the code of your paper.
I am new to FSL and trying to understand the training and data loader process. I understand the concept of support and query as well as shot and way. But I'm still confused about how you make the data loader and appreciate if you can explain it. I also read the paper several times but it didn't work to understand these details. I really appreciate your help in advance.

1. In the case of 1-shot 5-way, what does query=15 mean? how should we choose the number for query? does it need to be some specific number in agreement with previous works or it is arbitrary and kinda like hyperparameter?

in the cub dataset, we have 5892 images. and I see the data loader generate batch of 80x3x84x84 for input and the output is in forms of 80x640x5x5:

2. I don't understand where the 80 comes from at the first point, and then in the output where the 640 comes from?

3. later I see we have data_shot and logits, the size of logit is 75x5, can you please explain what 75 represent? I understand that it is 15*5=75 but I could not understand what it represents.

Thanks in advance for your help.

[icoz69]

hello
1.query=15 means the number of test images each class in this mini-task (an episode). it can be changed. since the evaluation is by repeatedly sampling tasks, larger query number and sampling times can make the average result more stable and convincing. for example, if you have large gpu memory, you can set a larger query size for training and eval.
2. 80 is the number of query images plus the number of support images, i.e. 5 way * (1 support image + 15 query image). 640 is the dim of the feature embedding.
3.75 is the predicted scores of 75 query images. since each class has 15 query images, and you have 5 class, you have 75 testing images totally.