fp16_cfg = cfg.get('fp16',None)iffp16_cfgisnotNone:# 如果我们设置了,则会生成一个Fp16OptimizerHook的实例optimizer_config = Fp16OptimizerHook( **cfg.optimizer_config, **fp16_cfg, distributed=False)else:# 如果我们没有设置,则正常从config里面读取optimizer_config# 如设置grad_clip: optimizer_c...
#从config里读取fp16字段,如果没有为None;fp16_cfg=cfg.get('fp16',None)iffp16_cfgisnotNone:# 如果我们设置了,则会生成一个Fp16OptimizerHook的实例optimizer_config=Fp16OptimizerHook(**cfg.optimizer_config,**fp16_cfg,distributed=False)else:# 如果我们没有设置,则正常从config里面读取optimizer_config#...
fp16_cfg = cfg.get('fp16', None)if fp16_cfg is not None:# 如果我们设置了，则会⽣成⼀个Fp16OptimizerHook的实例 optimizer_config = Fp16OptimizerHook(**cfg.optimizer_config, **fp16_cfg, distributed=False)else:# 如果我们没有设置，则正常从config⾥⾯读取optimizer_config # 如设置grad...
# fp16 setting fp16_cfg = cfg.get('fp16', None) if fp16_cfg is not None: optimizer_config = Fp16OptimizerHook( **cfg.optimizer_config, **fp16_cfg, distributed=distributed) elif distributed and 'type' not in cfg.optimizer_config: optimizer_config = OptimizerHook(**cfg.optimizer_config...
See the following example code. from torch.optim.lr_scheduler import StepLR scheduler = StepLR( optimizer.optimizer if smp.state.cfg.fp16 else optimizer, step_size=1, gamma=args.gamma ) Document Conventions Activation Offloading Support for FlashAttention...
for name in int4_cfg: print('insert INT4 FakeQuantize::', name) qconfig['module_name'][name] = int4_qconfig # Find INT8 op and set the config: int8_cfg = extra_qparams.get('int8_op', None) if int8_cfg: if "module_name" not in qconfig: qconfig["module_name"] = {} w_...
Please check that this issue hasn't been reported before. I searched previous Bug Reports didn't find any similar reports. Expected Behavior Should run correctly. Current behaviour running crash wandb: WARNING Saving files without folder...
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Nehmen Sie für das FP16 Training mit Modellparallelität Änderungen an Ihrem Trainingsskript und Ihrem Schätzer vor.
self.__setup_decoder(input_ids, scfg, host_context_lengths) 1.对以下参数进行torch.full填充初始值,然后setup fastertransformer.setup self.top_k,self.top_p,self.temperature,self.repetition_penalty, self.length_penalty , self.presence_penalty,self.min_length, self.beam_search_diversity_rate ...