mmclassification/configs/mvit/mvitv2-tiny_8xb256_in1k.py

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746 B
Python

_base_ = [
'../_base_/models/mvit/mvitv2-tiny.py',
'../_base_/datasets/imagenet_bs64_swin_224.py',
'../_base_/schedules/imagenet_bs2048_AdamW.py',
'../_base_/default_runtime.py'
]
# dataset settings
data = dict(samples_per_gpu=256)
# schedule settings
paramwise_cfg = dict(
norm_decay_mult=0.0,
bias_decay_mult=0.0,
custom_keys={
'.pos_embed': dict(decay_mult=0.0),
'.rel_pos_h': dict(decay_mult=0.0),
'.rel_pos_w': dict(decay_mult=0.0)
})
optimizer = dict(lr=0.00025, paramwise_cfg=paramwise_cfg)
optimizer_config = dict(grad_clip=dict(max_norm=1.0))
# learning policy
lr_config = dict(
policy='CosineAnnealing',
warmup='linear',
warmup_iters=70,
warmup_by_epoch=True)