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""" |
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@author: Jianjie Luo |
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@contact: jianjieluo.sysu@gmail.com |
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""" |
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import torch |
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from uniperceiver.config import configurable |
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from .build import SOLVER_REGISTRY |
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@SOLVER_REGISTRY.register() |
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class AdamW(torch.optim.AdamW): |
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@configurable |
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def __init__( |
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self, |
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*, |
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params, |
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lr=1e-3, |
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betas=(0.9, 0.999), |
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eps=1e-8, |
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weight_decay=0.01, |
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amsgrad=False |
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): |
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super(AdamW, self).__init__( |
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params, |
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lr, |
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betas, |
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eps, |
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weight_decay, |
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amsgrad |
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) |
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|
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@classmethod |
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def from_config(cls, cfg, params): |
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return { |
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"params": params, |
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"lr": cfg.SOLVER.BASE_LR, |
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"betas": cfg.SOLVER.BETAS, |
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"eps": cfg.SOLVER.EPS, |
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"weight_decay": cfg.SOLVER.WEIGHT_DECAY, |
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"amsgrad": cfg.SOLVER.AMSGRAD |
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} |
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