TensorBoardX lets you watch Tensors Flow without Tensorflow
Now you can tag Hparams trials with custom name instead of the default epoch time
Fixed a bug that add_hparams are rendered incorrectly with non-string values.
Supports logging to Amazon S3 or Google Cloud Storage
Bug fixes and error message for add_embedding function
Draw openvino format with add_openvino_graph
Use new JIT backend for pytorch. This works better with pytorch 1.2 and 1.3
Supports hparams plugin
add_embedding now supports numpy array input
Draw label text on image with bounding box provided.
crc32c speed up (optional by installing crc32c manually)
Rewrite add_graph. onnx backend is replaced by JIT to support more advanced structure.
Now you can add_mesh() to visualize colorful point cloud or meshes.
Able to write to S3
Fixed raw histogram issue that nothing is shown in TensorBoard
Users can use various image/video dimension permutation by passing ‘dataformats’ parameter.
You can bybass the writer by passing write_to_disk=True to SummaryWriter
Many graph related bug is fixed in this version.
New function: add_images(). This function accepts 4D iamge tensor. See documentation.
Make add_image_with_boxes() usable.
API change: add_video now accepts BxTxCxHxW instead of BxCxTxHxW tensor.
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)
Made add_text compatible with tensorboard>1.6
Fix the issue of strange histogram if default binning method is used
Supports passing matplotlib figures to add_image()
Resolve namespace confliction with TF tensorboard
Supports custom timestamp for event
Supports tensorshape information in graph visualization. Drop support for 0.3.1
Adds add_video function
Supports pytorch 0.3.1 (hacky)
Supports graph (the pretty one)
Supports markdown for add_text function
It’s ready to log precision recall curve (needs tensorboard>=0.4)
Adds context manager for the SummaryWriter class
Package name renamed to tensorboardX to fix namespace confliction with tensorflow’s tensorboard
Supports multi-scalars and JSON export
Multiple Embeddings in One Experiment
Supports Chainer and mxnet
remove tensorflow dependency for embedding function
fixed incorrect image<->label pairing in embedding function (#12)
unifies API call and adds docstring. Documentation is available at: http://tensorboard-pytorch.readthedocs.io/
add travis test (py2.7, py3.6)
add support for python2 (in PyPI)
supports graph summary
fixed np.histogram issue
supports text summary
supports audio summary
simplifies add_image API
speed up add_histogram API by 35x
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