tensorboard: command not found
You could call tensorboard as a python module like this: python3 -m tensorboard.main –logdir=~/my/training/dir or add this to your .profile alias tensorboard=’python3 -m tensorboard.main’
tensorboard
ValueError: Duplicate plugins for name projector
If you have two versions of tensorboard installed in your system,you need to uninstall one of them. I was stuck this for hours but I finally fixed it using: Worked like a charm: https://github.com/pytorch/pytorch/issues/22676 pip uninstall tb-nightly tensorboardX tensorboard pip install tensorboard
Tensorboard Error: No dashboards are active for current data set
Your issue may be related to the drive you are attempting to start tensorboard from and the drive your logdir is on. Tensorboard uses a colon to separate the optional run name and the path in the logdir flag, so your path is being interpreted as \path\to\output\folder with name C. This can be worked around … Read more
How to run Tensorboard from python scipt in virtualenv?
Using Tensorboard 2 API (2019): from tensorboard import program tracking_address = log_path # the path of your log file. if __name__ == “__main__”: tb = program.TensorBoard() tb.configure(argv=[None, ‘–logdir’, tracking_address]) url = tb.launch() print(f”Tensorflow listening on {url}”) Note: tb.launch() create a daemon thread that will die automatically when your process is finished
TensorBoard doesn’t show all data points
You don’t have to change the source code for this, there is a flag called –samples_per_plugin. Quoting from the help command –samples_per_plugin: An optional comma separated list of plugin_name=num_samples pairs to explicitly specify how many samples to keep per tag for that plugin. For unspecified plugins, TensorBoard randomly downsamples logged summaries to reasonable values to … Read more
Plot multiple graphs in one plot using Tensorboard
If you are using the SummaryWriter from tensorboardX or pytorch 1.2, you have a method called add_scalars: Call it like this: my_summary_writer.add_scalars(f’loss/check_info’, { ‘score’: score[iteration], ‘score_nf’: score_nf[iteration], }, iteration) And it will show up like this: Be careful that add_scalars will mess with the organisation of your runs: it will add mutliple entries to this … Read more
Change images slider step in TensorBoard
I answered this question over there “TensorBoard doesn’t show all data points”, but this seems to be more popular so I will quote it here. You don’t have to change the source code for this, there is a flag called –samples_per_plugin. Quoting from the help command –samples_per_plugin: An optional comma separated list of plugin_name=num_samples pairs … Read more
keras tensorboard: plot train and validation scalars in a same figure
To handle the validation logs with a separate writer, you can write a custom callback that wraps around the original TensorBoard methods. import os import tensorflow as tf from keras.callbacks import TensorBoard class TrainValTensorBoard(TensorBoard): def __init__(self, log_dir=”./logs”, **kwargs): # Make the original `TensorBoard` log to a subdirectory ‘training’ training_log_dir = os.path.join(log_dir, ‘training’) super(TrainValTensorBoard, self).__init__(training_log_dir, **kwargs) … Read more
How to create only one copy of graph in tensorboard events file with custom tf.Estimator?
You need to use the TensorBoard tool for visualizing the contents of your summary logs. The event file log can be read and use it. You can see the example from this link provides information about how to read events written to an event file. # This example supposes that the events file contains summaries … Read more