Changelogs » Trains

Trains

0.11.2

Features and Bug Fixes

* Fix Python 2.7 support
* Improve sample code Windows support

0.11.1

Features and Bug Fixes

* GPU Monitoring is now embedded into trains (*removed gpustat dependency*)
* Add initial support for Tensorflow v2.0 (tested with v2.0.0rc1)
* Add artifact upload retry on network errors (default: 3)
* Suppress urllib3 retry warnings
* Fix Matplotlib support with Agg backend (multiple plot windows caused repeated graphs to be sent)
* Fix support for tuples in hyper-parameters
* Fix multi processing issues with different task types

0.11.0

Features and Bug Fixes

* Full artifacts support (supported by trains-server >= 0.11.0)
* Artifacts include, Pandas.DataFrame, Numpy, PIL Image, local files, and local folder/wildcard ([example](https://github.com/allegroai/trains/blob/master/examples/artifacts_toy.py))
* Artifacts support for folder/wildcard, selected files will be zipped and uploaded
* Resource monitoring, remove sensor reading failure warnings

Breaking Changes

* Logger `info`/`error`/`warning`/`console` functions were removed, use `Logger.report_text` (or python logging or print instead)
* Tensorboard scalars are not grouped into one graph, but are stored on individual graphs (to match Tensorboard behavior). To restore previous behavior call `Logger.tensorboard_auto_group_scalars(group_scalars=True)`

0.10.7

Features and Bug Fixes
* Artifacts support
* Removed apache-libcloud from requirements
* `trains-init` now verifies credentials against the trains-server installation

0.10.6

Features and Bug Fixes
* Fix broken (v0.10.5) Keras Binding support

0.10.5

Features and Bug Fixes
* **Add GPU monitoring support** (add gpustat package to extras_require)
- Install with GPU monitoring support: `pip install trains[gpu]`
* Move all cloud storage package requirements to `extras_require`
Install with specific cloud provider support:
-  **Microsoft Azure support**: `pip install trains[azure]`
-  Google Storage support: `pip install trains[gs]`
-  Amazon S3 support: `pip install trains[s3]`
* Combine Cloud support with GPU monitoring:
For example S3 and GPU: `pip install trains[s3,gpu]`
* Improve stability with intermittent network connection
* Support upgrading *trains-server* while running training jobs without losing log data

0.10.4

Features and Bug Fixes

* Replace opencv-python with the more standard Pillow package
* Improve matplotlib support (custom axis ticks)
* Improve python package detection

0.10.3

Full feature overview [here](https://medium.com/allegroai/trains-the-maiden-voyage-e099dd003cf)

Features and Bug Fixes

* Add **scikit-learn support** (load/store using joblib) 20
* Add **xgboost support** 10
* Add loguru support  29
* Add sub-domain support [trains.conf](https://github.com/allegroai/trains/blob/master/docs/trains.confL3) 27
* Fix sub-process support
* Fix multiple Tensorboard writers 26

0.10.2

Features and Bug Fixes

* Add Matplotlib SVG support
* Add Seaborn support
* Add TRAINS_LOG_ENVIRONMENT environment logging [feature](https://github.com/allegroai/trains/issues/17issuecomment-507398767)
* Add Microsoft Azure notebook support
* Add Google Colab support
* Fix Tensorboard RGB channel order

0.10.1

Features and Bug Fixes
* Fix Jenkins CI/CD support

0.10.0

* Experiment code execution detection
- Automatically create package requirements section (including used versions)
- Automatically detect and store source code uncommitted changes
- Jupyter notebook support, automatically convert notebook to python script (stored under uncommitted changes)
- Jupyter notebook support, automatically update used packages in notebook (including used versions)
* Add resource monitoring to experiment metrics
- Sampled every 500ms, averaged over 30 seconds
- CPU / Network / IO / Memory etc.
- For GPU support please install gpustat
(currently not part of the requirements due to gpustat compatibility issues with Windows)
$ pip install gpustat

* Automatically stop inactive experiments (default: 2 hours)
* Improved visibility
- Finer status definitions: Identify successful completion vs. user aborted
- Experiment plot comparison: Ensure different colors for different experiments
- Parse newline character in experiment description
- Show experiment start time in table display
- Add vertical guide in scalar plots
- Move Hyper-parameters to designated tab
- "Admin" section now named "Profile"

0.9.3

Features and Bug Fixes
* Improved Jupyter and inline Matplotlib support
* Allow for insecure SSL connection to trains-server (use with care!)
* Automatically announce new *trains* version available (at least until we hit version 1.0)
* Fix support for local git branches (i.e. no matching remote branch)
* Verified support for Official TensorFlow 1.14 release and PyTorch with TensorBoard

0.9.2

Features and Bug Fixes

* Better support for Windows

0.9.1

Features and Bug Fixes
* Better support for python 2.7

0.9.0

Initial beta release

0.1.5


      

0.1.4


      

0.1.3


      

0.1.2


      

0.1.1