Tensorboard :: Anaconda.org
anaconda.org › conda-forge › tensorboardlinux-64 v1.15.0. win-32 v1.6.0. noarch v2.7.0. win-64 v1.15.0. osx-64 v1.15.0. To install this package with conda run one of the following: conda install -c conda-forge tensorboard. conda install -c conda-forge/label/cf201901 tensorboard. conda install -c conda-forge/label/cf202003 tensorboard.
Loggers — PyTorch Lightning 1.5.8 documentation
pytorch-lightning.readthedocs.io › loggersconda install -c conda-forge neptune-client Then configure the logger and pass it to the Trainer : from pytorch_lightning.loggers import NeptuneLogger neptune_logger = NeptuneLogger ( api_key = "ANONYMOUS" , # replace with your own project = "common/pytorch-lightning-integration" , # format "<WORKSPACE/PROJECT>" tags = [ "training" , "resnet" ], # optional ) trainer = Trainer ( logger = neptune_logger )
tensorboard_logger · PyPI
pypi.org › project › tensorboard_loggerFeb 08, 2018 · Usage. You can either use default logger with tensorboard_logger.configure and tensorboard_logger.log_value functions, or use tensorboard_logger.Logger class.. This library can be used to log numerical values of some variables in TensorBoard format, so you can use TensorBoard to visualize how they changed, and compare same variables between different runs.