Releases: lanpa/tensorboardX
release v1.5
- Add API for Custom scalar
- Add support for logging directly to S3
- Add support for Caffe2 graph
- Pytorch 1.0.0 JIT graph support (alpha-release)
release v1.2
- Supports tensorshape information and show node name in graph visualization. This requires pytorch==0.4
- Adds add_video function. You can play video clip now
- You can use tensorboard-dumper to dump images.
- Better embedding function
People who use pytorch==0.3.1
should use tensorboardX==1.1
People who use pytorch==0.4
should use tensorboardX==1.2
release v1.0
Major Tensorboard features are ready:
audio, scalar, distribution, graph, histogram, image, pr curve, projector, text (markdown).
TensorboardX
Some important change since v0.6:
-
The package name is changed from tensorboard to tensorboardX to prevent from name collision with official tensorboard. (which leads to import error, ...etc) The name tensorboardX means tensorboard for X. I hope this package can be used by other DL frameworks such as mxnet, chainer as well. This is achieved by wrapping an
make_np()
call to function arguments. In fact, you can log experiment if you use tensorflow's eager mode. -
Removes dependency for tensorflow and torchvision to make this package much neutral.
-
For other changes, see the commit log or HISTORY.rst
All tensorboard functions are implemented.
All tensorboard functions are implemented.
more details on:
https://medium.com/@dexterhuang/tensorboard-for-pytorch-201a228533c5