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mmpretrain/configs/vision_transformer/vit-large-p16_pt-64xb64_in1...

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[Refactor] Refator ViT (Continue #295) (#395) * [Squash] Refator ViT (from #295) * Use base variable to simplify auto_aug setting * Use common PatchEmbed, remove HybridEmbed and refactor ViT init structure. * Add `output_cls_token` option and change the output format of ViT and input format of ViT head. * Update unit tests and add test for `output_cls_token`. * Support out_indices. * Standardize config files * Support resize position embedding. * Add readme file of vit * Rename config file * Improve docs about ViT. * Update docstring * Use local version `MultiheadAttention` instead of mmcv version. * Fix MultiheadAttention * Support `qk_scale` argument in `MultiheadAttention` * Improve docs and change `layer_cfg` to `layer_cfgs` and support sequence. * Use init_cfg to init Linear layer in VisionTransformerHead * update metafile * Update checkpoints and configs * Imporve docstring. * Update README * Revert GAP modification.
2021-10-18 16:07:00 +08:00
_base_ = [
'../_base_/models/vit-large-p16.py',
'../_base_/datasets/imagenet_bs64_pil_resize_autoaug.py',
'../_base_/schedules/imagenet_bs4096_AdamW.py',
'../_base_/default_runtime.py'
]
[Refactor] Add `ResizeEdge` and refactor all dataset configs.
2022-06-01 14:11:53 +08:00
# model setting
[Refactor] Refator ViT (Continue #295) (#395) * [Squash] Refator ViT (from #295) * Use base variable to simplify auto_aug setting * Use common PatchEmbed, remove HybridEmbed and refactor ViT init structure. * Add `output_cls_token` option and change the output format of ViT and input format of ViT head. * Update unit tests and add test for `output_cls_token`. * Support out_indices. * Standardize config files * Support resize position embedding. * Add readme file of vit * Rename config file * Improve docs about ViT. * Update docstring * Use local version `MultiheadAttention` instead of mmcv version. * Fix MultiheadAttention * Support `qk_scale` argument in `MultiheadAttention` * Improve docs and change `layer_cfg` to `layer_cfgs` and support sequence. * Use init_cfg to init Linear layer in VisionTransformerHead * update metafile * Update checkpoints and configs * Imporve docstring. * Update README * Revert GAP modification.
2021-10-18 16:07:00 +08:00
model = dict(
head=dict(hidden_dim=3072),
train_cfg=dict(
[Refactor] Add `ResizeEdge` and refactor all dataset configs.
2022-06-01 14:11:53 +08:00
augments=dict(
type='BatchMixup',
alpha=0.2,
num_classes=1000,
prob=1.,
)))
# runtime setting
default_hooks = dict(optimizer=dict(grad_clip=dict(max_norm=1.0)))