Version 0.11¶
Important
Trains is now ClearML.
Version 0.11.3¶
Trains¶
Features and Bug Fixes
Resource-Monitor will only monitor active GPU devices based on environment variables:
NVIDIA_VISIBLE_DEVICESorCUDA_VISIBLE_DEVICES.Fix issue (GitHub Issue #48).
Version 0.11.2¶
Version 0.11.1¶
Trains¶
Features and Bug Fixes
GPU Monitoring 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.
Version 0.11.0¶
Trains¶
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).
Artifacts support for folder/wildcard, selected files will be zipped and uploaded.
Resource monitoring, remove sensor reading failure warnings.
Breaking Changes
Logger
info/error/warnin/consolefunctions were removed, useLogger.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).
Trains Server¶
Add scalar graphs smoothing (matched TensorBoard behavior).
Add scalar graphs X-axis selection: Iteration / Relative / Wall Time.
Add min/max/last value for all scalars (available in experiment table column selection / sorting).
Add hyper-parameter to experiment table custom columns.
Add artifacts support (Models tab moved into artifacts as specific artifact type).
Add full Azure storage support.
Fix column sorting N/A values.