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please set 'STRIDE_IN_1X1' to be 'False' when backbone uses GN #465

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merged 27 commits into from
Feb 19, 2019

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zimenglan-sysu-512
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to fix the performance gap compared to Detectron.

…d use 'BaseStem'&'Bottleneck' to simply codes
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@zimenglan-sysu-512 zimenglan-sysu-512 changed the title please set 'STRIDE_IN_1X1' to be 'False' when backbone use GN please set 'STRIDE_IN_1X1' to be 'False' when backbone uses GN Feb 19, 2019
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Thanks!

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fmassa commented Feb 19, 2019

Can I merge this now or do you want me to wait (maybe for some results to finish computing)?

@zimenglan-sysu-512
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hi @fmassa
maybe wait for the trainings, because it will need 2 days to finish.

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fmassa commented Feb 19, 2019

Let's do it like the following: once the trainings are over, you can send another PR updating maybe the MODEL_ZOO description of the GN model that you trained?

@fmassa fmassa merged commit 192261d into facebookresearch:master Feb 19, 2019
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ok.
agree with u

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clw5180 commented Aug 14, 2019

Let's do it like the following: once the trainings are over, you can send another PR updating maybe the MODEL_ZOO description of the GN model that you trained?

Hi fmassa, I have a question here: What does the STRIDE_IN_1X1 mean? If I use ResNeXt101-FPN, should I set this option to True? Thank you for taking the time ! @fmassa

Lyears pushed a commit to Lyears/maskrcnn-benchmark that referenced this pull request Jun 28, 2020
…ookresearch#465)

* make pixel indexes 0-based for bounding box in pascal voc dataset

* replacing all instances of torch.distributed.deprecated with torch.distributed

* replacing all instances of torch.distributed.deprecated with torch.distributed

* add GroupNorm

* add GroupNorm -- sort out yaml files

* use torch.nn.GroupNorm instead, replace 'use_gn' with 'conv_block' and use 'BaseStem'&'Bottleneck' to simply codes

* modification on 'group_norm' and 'conv_with_kaiming_uniform' function

* modification on yaml files in configs/gn_baselines/ and reduce the amount of indentation and code duplication

* use 'kaiming_uniform' to initialize resnet, disable gn after fc layer, and add dilation into ResNetHead

* agnostic-regression for bbox

* please set 'STRIDE_IN_1X1' to be 'False' when backbone use GN
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4 participants