class VQVAE_PL(pl.LightningModule): def __init__(self,warmup_epochs=2,num_training_samples=20942, batch_size=256, learning_rate=2e-5): super().__init__( ) self.encoder = Encoder() self.decoder = Decoder() self.quantizer = QuantizeEMA() self.loss_layer = ReConsLoss() self.warmup...
update_ema, requires_grad, text_preprocessing, get_experiment_dir, clip_grad_norm_, cleanup, ) class LatteTrainingModule(LightningModule): def __init__(self, args, logger: logging.Logger): super(LatteTrainingModule, self).__init__() self.args = args self.logging = logger self.model = ...
The EMA callback is often used to track the exponential moving average of model parameters during training.Args: trainer ('lightning.pytorch.Trainer'): The trainer instance.Returns: EMA: The EMA callback instance if found, or None if not present....
I'm porting training scripts from torchvision and timm to pytorch-lightning, and I'm trying to implement ExponentialMovingAverage (EMA) as a callback. EMA averages the model weights across training steps, and is called after the optimizer update step. EMA is used in bothtorchvision training sc...
Lightning docs implies that they be always called when loading from a checkpoint. I believe that docs should mention that Callbacks.on_load_checkpoint is only called with trainer.fit. You can find a working EMA callback here (apply this changes for MultiGPU support). 👍 2 carmocca added...
13 + pytorch-lightning==2.1.4 14 + scipy==1.10.1 15 + sdeint==0.3.0 16 + setuptools==44.0.0 17 + seaborn==0.13.2 18 + torch==2.2.0 19 + torch-ema==0.3 20 + torchaudio==2.2.0 21 + torchvision==0.17.0 22 + torchinfo==1.8.0 23 + torchsde==0.2.6 24...
ema = ModelEMA(self.model) 244 243 self.resume_training(ckpt) 244 + self.scheduler.last_epoch = self.start_epoch - 1 # do not move 245 245 self.run_callbacks("on_pretrain_routine_end") 246 246 247 247 def _do_train(self, rank=-1, world_size=1): @@ -555,6 +555,...
self.ema_decay = self.config.train.ema_decay self.log_img_every_epoch = self.config.train.log_img_every_epoch assert self.config.train.num_train_steps is not None assert self.config.train.num_train_steps % self.config.train.substeps == 0 @@ -81,10 +83,11 @@ def __init__(self,...
6 5 pytorch-lightning==1.8.5 7 6 pytorch_metric_learning==1.7.1 8 7 pytorch-msssim 9 8 thop 10 9 timm>=0.9.6.dev0 11 10 torchmetrics==0.10.3 12 - open-clip-torch[training]==2.20.0 11 + open-clip-torch[training]==2.23.0 12 + sentencepiece==0.1.99 13 13 ftfy...
='localhost'os.environ['MASTER_PORT']='42819'os.environ['RANK']='0'os.environ['WORLD_SIZE']='1'module=torch.nn.Linear(10,10)fsdp_module=torch.distributed.fsdp.fully_shard(module)model_avg=torch.optim.swa_utils.AveragedModel(fsdp_module,multi_avg_fn=torch.optim.swa_utils.get_ema_multi...