Webclass MetricLogger (object): def __init__ (self, delimiter = " \t "): self. meters = defaultdict (SmoothedValue) self. delimiter = delimiter: def update (self, ** kwargs): for k, v in … Web[NeurIPS 2024 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training - VideoMAE/utils.py at main · MCG-NJU/VideoMAE

Twins/utils.py at main · Meituan-AutoML/Twins · GitHub

WebThis class is useful for collecting loss and metric values in one place for storage with checkpoint savers (`state_dict` and `load_state_dict` methods provided as expected by Pytorch and Ignite) and for graphing during training. WebLeViT a Vision Transformer in ConvNet's Clothing for Faster Inference - LeViT/utils.py at main · facebookresearch/LeViT i stalk my ex on social media

deep-learning-for-image-processing/distributed_utils.py at master ...

Webclass SmoothedValue (object): """Track a series of values and provide access to smoothed values over a window or the global series average. """ def __init__ (self, window_size=20, fmt=None): if fmt is None: fmt = " {value:.4f} ( {global_avg:.4f})" self.deque = deque (maxlen=window_size) self.total = 0.0 self.count = 0 self.fmt = fmt WebSmoothedValue Class __init__ Function update Function synchronize_between_processes Function median Function avg Function global_avg Function max Function value Function __str__ Function MetricLogger Class __init__ Function update Function __getattr__ Function __str__ Function synchronize_between_processes Function add_meter … Webclass MetricLogger ( object ): def __init__ ( self, delimiter="\t" ): self. meters = defaultdict ( SmoothedValue) self. delimiter = delimiter def update ( self, **kwargs ): for k, v in kwargs. items (): if isinstance ( v, torch. Tensor ): v = v. item () assert isinstance ( v, ( float, int )) self. meters [ k ]. update ( v) ifttt to make alexa show camera ring doorbell