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[Refactor] rename config files, change fp16 to amp (#423)

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Yixiao Fang 2022-08-19 13:38:37 +08:00 committed by GitHub
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14 changed files with 8 additions and 8 deletions
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2
configs/selfsup/byol/byol_resnet50_8xb256-fp16-accum2-coslr-100e_in1k.py → configs/selfsup/byol/byol_resnet50_8xb256-amp-accum2-coslr-100e_in1k.py
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_base_ = 'byol_resnet50_8xb256-fp16-accum2-coslr-200e_in1k.py'
_base_ = 'byol_resnet50_8xb256-amp-accum2-coslr-200e_in1k.py'
# optimizer
optimizer = dict(lr=7.2)

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configs/selfsup/byol/byol_resnet50_8xb256-fp16-accum2-coslr-200e_in1k.py → configs/selfsup/byol/byol_resnet50_8xb256-amp-accum2-coslr-200e_in1k.py
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configs/selfsup/byol/byol_resnet50_8xb256-fp16-accum2-coslr-300e_in1k.py → configs/selfsup/byol/byol_resnet50_8xb256-amp-accum2-coslr-300e_in1k.py
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_base_ = 'byol_resnet50_8xb256-fp16-accum2-coslr-200e_in1k.py'
_base_ = 'byol_resnet50_8xb256-amp-accum2-coslr-200e_in1k.py'
# learning rate scheduler
param_scheduler = [

2
configs/selfsup/cae/cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k.py → configs/selfsup/cae/cae_vit-base-p16_16xb128-amp-coslr-300e_in1k.py
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_base_ = 'cae_vit-base-p16_32xb64-fp16-coslr-300e_in1k.py'
_base_ = 'cae_vit-base-p16_32xb64-amp-coslr-300e_in1k.py'
# dataset 128 x 16
train_dataloader = dict(batch_size=128, num_workers=16)

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configs/selfsup/cae/cae_vit-base-p16_32xb64-fp16-coslr-300e_in1k.py → configs/selfsup/cae/cae_vit-base-p16_32xb64-amp-coslr-300e_in1k.py
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configs/selfsup/cae/cae_vit-base-p16_8xb256-fp16-coslr-300e_in1k.py → configs/selfsup/cae/cae_vit-base-p16_8xb256-amp-coslr-300e_in1k.py
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_base_ = 'cae_vit-base-p16_16xb128-fp16-coslr-300e_in1k.py'
_base_ = 'cae_vit-base-p16_16xb128-amp-coslr-300e_in1k.py'
# dataset 8GPUs x 256
train_dataloader = dict(batch_size=256, num_workers=16)

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configs/selfsup/mae/mae_vit-base-p16_8xb512-fp16-coslr-1600e_in1k.py → configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-1600e_in1k.py
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_base_ = 'mae_vit-base-p16_8xb512-coslr-400e-fp16_in1k.py'
_base_ = 'mae_vit-base-p16_8xb512-amp-coslr-400e_in1k.py'
# pre-train for 800 epochs
train_cfg = dict(max_epochs=1600)

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configs/selfsup/mae/mae_vit-base-p16_8xb512-fp16-coslr-300e_in1k.py → configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-300e_in1k.py
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_base_ = 'mae_vit-base-p16_8xb512-coslr-400e-fp16_in1k.py'
_base_ = 'mae_vit-base-p16_8xb512-amp-coslr-400e_in1k.py'
# pre-train for 800 epochs
train_cfg = dict(max_epochs=300)

0
configs/selfsup/mae/mae_vit-base-p16_8xb512-fp16-coslr-400e_in1k.py → configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-400e_in1k.py
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configs/selfsup/mae/mae_vit-base-p16_8xb512-fp16-coslr-800e_in1k.py → configs/selfsup/mae/mae_vit-base-p16_8xb512-amp-coslr-800e_in1k.py
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_base_ = 'mae_vit-base-p16_8xb512-coslr-400e-fp16_in1k.py'
_base_ = 'mae_vit-base-p16_8xb512-amp-coslr-400e_in1k.py'
# pre-train for 800 epochs
train_cfg = dict(max_epochs=800)

0
configs/selfsup/mocov3/mocov3_vit-small-p16_16xb256-fp16-coslr-300e_in1k-224.py → configs/selfsup/mocov3/mocov3_vit-small-p16_16xb256-amp-coslr-300e_in1k.py
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configs/selfsup/rotation_pred/rotation-pred_resnet50_8xb16-fp16-steplr-70e_in1k.py → configs/selfsup/rotation_pred/rotation-pred_resnet50_8xb16-amp-steplr-70e_in1k.py
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configs/selfsup/simmim/simmim_swin-base_16xb128-coslr-100e_in1k-192.py → configs/selfsup/simmim/simmim_swin-base_16xb128-amp-coslr-100e_in1k-192.py
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configs/selfsup/simmim/simmim_swin-base_8xb256-coslr-100e_in1k-192.py → configs/selfsup/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192.py
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_base_ = 'simmim_swin-base_16xb128-coslr-100e_in1k-192.py'
_base_ = 'simmim_swin-base_16xb128-amp-coslr-100e_in1k-192.py'
# dataset 8 GPUs x 256
train_dataloader = dict(batch_size=256, num_workers=16)