Request for the complete arguments for the eval part.

[songquanpeng]

Hello, first of all thanks for your excellent work!
But when I try to reproduce the results that you provided, what I got is pretty low.

Here is the complete log for MiniImageNet DeepEMD-FCN 1-Shot 5-Way:

C:\Users\admin\Anaconda3\envs\tensorflow\python.exe D:/Projects/DeepEMD/eval.py
{'data_dir': 'your/default/dataset/dir',  # it's fine because I make some changes to the fcn\mini_imagenet.py and already hardcode the real path.
 'dataset': 'miniimagenet',
 'deepemd': 'fcn',
 'feature_pyramid': None,
 'gpu': '0', 
 'metric': 'cosine',
 'model_dir': 'D:\\Projects\\DeepEMD\\trained\\deepemd_trained_model\\miniimagenet\\fcn\\max_acc.pth',
 'norm': 'center',
 'num_patch': 9,
 'patch_list': [2, 3],
 'patch_ratio': 2,
 'query': 15,
 'seed': 1,
 'set': 'test',
 'sfc_bs': 4,
 'sfc_lr': 100,
 'sfc_update_step': 100,
 'sfc_wd': 0,
 'shot': 1,
 'solver': 'opencv',
 'temperature': 12.5,
 'test_episode': 5000,
 'way': 5}
manual seed: 1
use gpu: [0]
loading model from : D:\Projects\DeepEMD\trained\deepemd_trained_model\miniimagenet\fcn\max_acc.pth
batch 5000: This episode:49.33  average: 57.1491+0.2795: 100%|██████████| 5000/5000 [38:01<00:00,  2.19it/s]
test Acc 57.1491
Test Acc 57.1491 + 0.2795

Process finished with exit code 0

I think if you could publish the complete arguments it will help to resolve this problem.

Thx in advance!

[icoz69]

hi. did you change any parts of the code? i have checked the model the running scripts before uploading them, and there are no problems here. Using the default arguments should be OK.

[songquanpeng]

Thanks for your reply! I will check my changes again later.

[Jiawen-huang]

I noticed that your arguments have not been updated.
'sfc_lr': 100
I think this argument is unreasonable

[icoz69]

@Jiawen-huang ,
hi, as cosine is used to compute the EMD distance between SFC and data embedding, the magnitude of fc weights will not influence the distance. so the lr can be very large for quicker optimization.