fast-reid/fastreid/solver/build.py

76 lines
2.1 KiB
Python

# encoding: utf-8
"""
@author: liaoxingyu
@contact: sherlockliao01@gmail.com
"""
import math
from . import lr_scheduler
from . import optim
def build_optimizer(cfg, model):
params = []
for key, value in model.named_parameters():
if not value.requires_grad: continue
lr = cfg.SOLVER.BASE_LR
weight_decay = cfg.SOLVER.WEIGHT_DECAY
if "heads" in key:
lr *= cfg.SOLVER.HEADS_LR_FACTOR
if "bias" in key:
lr *= cfg.SOLVER.BIAS_LR_FACTOR
weight_decay = cfg.SOLVER.WEIGHT_DECAY_BIAS
params += [{"name": key, "params": [value], "lr": lr, "weight_decay": weight_decay}]
solver_opt = cfg.SOLVER.OPT
if solver_opt == "SGD":
opt_fns = getattr(optim, solver_opt)(
params,
momentum=cfg.SOLVER.MOMENTUM,
nesterov=True if cfg.SOLVER.MOMENTUM and cfg.SOLVER.NESTEROV else False
)
else:
opt_fns = getattr(optim, solver_opt)(params)
return opt_fns
def build_lr_scheduler(cfg, optimizer, iters_per_epoch):
max_epoch = cfg.SOLVER.MAX_EPOCH - max(
math.ceil(cfg.SOLVER.WARMUP_ITERS / iters_per_epoch), cfg.SOLVER.DELAY_EPOCHS)
scheduler_dict = {}
scheduler_args = {
"MultiStepLR": {
"optimizer": optimizer,
# multi-step lr scheduler options
"milestones": cfg.SOLVER.STEPS,
"gamma": cfg.SOLVER.GAMMA,
},
"CosineAnnealingLR": {
"optimizer": optimizer,
# cosine annealing lr scheduler options
"T_max": max_epoch,
"eta_min": cfg.SOLVER.ETA_MIN_LR,
},
}
scheduler_dict["lr_sched"] = getattr(lr_scheduler, cfg.SOLVER.SCHED)(
**scheduler_args[cfg.SOLVER.SCHED])
if cfg.SOLVER.WARMUP_ITERS > 0:
warmup_args = {
"optimizer": optimizer,
# warmup options
"warmup_factor": cfg.SOLVER.WARMUP_FACTOR,
"warmup_iters": cfg.SOLVER.WARMUP_ITERS,
"warmup_method": cfg.SOLVER.WARMUP_METHOD,
}
scheduler_dict["warmup_sched"] = lr_scheduler.WarmupLR(**warmup_args)
return scheduler_dict