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Convolutional layers in ResNet152 are freezed in stage 1 #25
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I am also facing the same issue during stage_1 training: RuntimeError:
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@jchhuang @RamyaRaghuraman Actually, as written in the paper, we used frozen resnet 152 feature extractor for the places experiments. The first reason is that finetuning resnet 152 requires large gpu resource, which we don't have. Second, as I explained in #22 (comment) self attention module and meta embedding module require initialization. Since the feature extractor is already imagenet pretrained, so self attention module won't be affected too much. However, in stage 1, we are still training classifier module with an additional fc layer. The memory is initialized using the feature after the fc, and the meta embedding was initialized using the stage 1 pretrained classifier. So the training of stage 1 is not meaningless. |
@zhmiao Thank you for your reply. I understand that the stage 1 training is required, but I am still not able to overcome the stated "freeze_support()" error. Is there a work around for this? |
@RamyaRaghuraman Could you be a little bit more specific on the error? |
@zhmiao I have attached the entire output for stage_1 training. I am using only 1 GPU but I do not know where the multiprocessing error comes from. `C:\Users\RAR7ABT\AppData\Local\conda\conda\envs\pjval\python.exe C:/Users/RAR7ABT/pj-val-ml/pjval_ml/OSR/OLTR/main.py
Process finished with exit code 1 |
@RamyaRaghuraman Thanks for posting the error message. It seems to be a problem of running pytorch on windows instead of frozen weights. Here is an issue from pytorch official repo: pytorch/pytorch#5858 (comment) . I will close this issue and open a new one about this (#29 (comment)). We do not have a windows machine to test it for now. I think we will try to get one and see if it is possible to reproduce. Thanks. |
Hi, I don't agree this explain. In my understanding, the dimension of centroid is num_classnum_feature, however, the output of fc is a 1num_class vector, their size are not matched, how can a vector initialize a matrix? |
@zhmiao After carefully reading the code, I find that the convolutional layers in ResNet152 are freezed during the stage #1’ training which resulting the training no meaning, So pls help to check. thanks
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