def run(args):
# set random seed
seed = set_seed(args.seed)
if seed is not None:
print(f"Set random seed as {seed}")
conf, vocab = load_lm_conf(args.conf, args.dict)
print(f"Arguments in args:\n{pprint.pformat(vars(args))}", flush=True)
print(f"Arguments in yaml:\n{pprint.pformat(conf)}", flush=True)
nnet = aps_asr_nnet(conf["nnet"])(**conf["nnet_conf"])
task = aps_task(conf["task"], nnet, **conf["task_conf"])
train_worker(task, conf, vocab, args)
def run(args):
# set random seed
seed = set_seed(args.seed)
if seed is not None:
print(f"Set random seed as {seed}")
conf, vocab = load_lm_conf(args.conf, args.dict)
print(f"Arguments in args:\n{pprint.pformat(vars(args))}", flush=True)
print(f"Arguments in yaml:\n{pprint.pformat(conf)}", flush=True)
data_conf = conf["data_conf"]
load_conf = {
"vocab_dict": vocab,
"num_workers": args.num_workers,
"sos": vocab["<sos>"],
"eos": vocab["<eos>"],
"fmt": data_conf["fmt"],
"max_batch_size": args.batch_size
}
load_conf.update(data_conf["loader"])
trn_loader = aps_dataloader(train=True, **data_conf["train"], **load_conf)
dev_loader = aps_dataloader(train=False, **data_conf["valid"], **load_conf)
nnet = aps_asr_nnet(conf["nnet"])(**conf["nnet_conf"])
task = aps_task(conf["task"], nnet, **conf["task_conf"])
Trainer = aps_trainer(args.trainer, distributed=False)
trainer = Trainer(task,
device_ids=args.device_id,
checkpoint=args.checkpoint,
resume=args.resume,
save_interval=args.save_interval,
prog_interval=args.prog_interval,
tensorboard=args.tensorboard,
reduction_tag="#tok",
**conf["trainer_conf"])
# dump configurations
conf["cmd_args"] = vars(args)
with open(f"{args.checkpoint}/train.yaml", "w") as f:
yaml.dump(conf, f)
dump_dict(f"{args.checkpoint}/dict", vocab, reverse=False)
trainer.run(trn_loader,
dev_loader,
num_epochs=args.epochs,
eval_interval=args.eval_interval)
def run(args):
_ = set_seed(args.seed)
conf, vocab = load_lm_conf(args.conf, args.dict)
print(f"Arguments in args:\n{pprint.pformat(vars(args))}", flush=True)
print(f"Arguments in yaml:\n{pprint.pformat(conf)}", flush=True)
nnet = aps_asr_nnet(conf["nnet"])(**conf["nnet_conf"])
other_loader_conf = {
"vocab_dict": vocab,
"sos": vocab["<sos>"],
"eos": vocab["<eos>"],
}
start_trainer(args.trainer,
conf,
nnet,
args,
reduction_tag="#tok",
other_loader_conf=other_loader_conf)
dump_dict(f"{args.checkpoint}/dict", vocab, reverse=False)