A small logger that lets you write logs readable by Tensorboard but
doesn’t require Tensorflow.
Usage
=====
You can use the logger as a context manager:
.. code:: python
from tensorboard_easy import Logger
import numpy as np
with Logger('/path/to/logs/folder/') as log:
log.log_scalar('my_scalar', 100, step=1)
log.log_image('my_images', np.random.rand(3, 20, 20), step=1)
or you can close the logger explicitly:
.. code:: python
log = Logger('/some/other/logs')
log.log_text('my_text', "Let's throw in some text", 0)
log.log_text('my_text', [['Some', 'tensor'], ['with', 'text!']], 1)
log.log_histogram('my_histogram', np.random.rand(500), step=0)
log.close()
It supports scalars, images, text and histograms.
You can also create functions, that write to a specific tag and automatically
increase the step:
.. code:: python
with Logger('/path/to/logs/folder/') as log:
write_loss = log.make_log_scalar('loss')
for i in range(1, 100):
write_loss(1 / i)
Installation
============
It can be installed via pip:
``pip install tensorboard-easy``
The ``tensorflow`` or ``tensorflow-tensorboard`` packages are not
required, however you will need one of them to visualize your logs.
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