Version 0.13

Important

Trains is now ClearML.

Version 0.13.3

Trains

Features and Bug Fixes

  • Add a binding for tensorboard.summarywriter.addscalars

  • Add the tensorboard_single_series_per_graph method which supports separate plots for each TensorBoard scalar.

  • Add the Task.set_base_docker and Task.get_base_docker methods for the base Docker image used by Trains Agent.

  • Add support for the standard OS environment variables to obtain default credentials for:

    * AWS: `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, and `AWS_DEFAULT_REGION`.
    * Azure Storage: `AZURE_STORAGE_ACCOUNT` and `AZURE_STORAGE_KEY`.
    * Google Cloud Storage: `GOOGLE_APPLICATION_CREDENTIALS`.
    
  • Add the Task.get_parameters_as_dict and Task.set_parameters_as_dict methods supporting get / set of parameters from referenced Tasks (use the Task.get_task to get a reference).

  • Make sure Task.connect always returns the connected instance passed to it.

  • tensorflow_gpu takes precedence over tensorflow when Trains detects installed packages to record experiment dependencies.

  • Remove title and series naming restrictions (allow $ and .) when reporting metrics.

  • Fix incorrect printouts in initialization wizard and upgrade notifications

  • Fix debug images URL for uploaded files with % in their name

Trains Agent

Features and Bug Fixes

  • Allow providing queue names instead of queue IDs in daemon mode.

  • Docker mode improvements:

    • Support running as a specific user inside a docker using the TRAINS_AGENT_EXEC_USER environment flag.

    • Pass the correct GPU limit when skipping gpus flag.

    • Add the --force-current-version daemon command-line flag.

  • Add K8s/trains glue service example

  • Add K8s support in daemon mode

    • Running inside a K8s pod

    • Mounting dockerized experiment folders to host

    • Allow a specific network for the docker

  • Add default storage environment vars (for AWS, GS and Azure) to generated agent configuration

  • Improve Unicode/UTF stdout handling

Version 0.13.2

Trains

Features and Bug Fixes

  • Allow reporting a pre-uploaded image url in (Logger.report_image() using the (url parameter.

  • Add support for Git repositories without a .git suffix, for example Azure Repos.

  • Improve conda support.

  • Improve hyper-parameters (argparser integration.

  • Fix (savefig() patching in matplotlib binding.

  • Fix logs, events and Jupyter Notebook flushing on exit.

Version 0.13.1

Trains

Features and Bug Fixes

  • Add support for pyplot.savefig and pylab.savefig in matplotlib binding.

  • Add support for SageMaker.

  • Improve configuration wizard.

  • Try to make sure TensorBoard is available when using torch.

  • Do not store keras model network design if it cannot be serialized (GitHub Issue #72).

  • Fix matplotlib binding support.

Version 0.13.0

Trains

Features and Bug Fixes

  • Add support for (trains-server v0.13.0.

  • Add support for nested (non-main) tasks.

  • Add warning when automatic argument parser binding cannot be turned off.

  • Add Task.upload_artifact support for external URLs (pre-uploaded).

  • Add support for special characters in hyper-parameter keys (white-spaces, . and $) (GitHub Issue #69).

  • Add support for PyTorch .pt model files.

  • Calculate data-audit artifact uniqueness by user-criteria (GitHub Issue #45).

  • Use an environment variable for setting a default docker image (GitHub Issue #58).

  • Improve trains-init configuration wizard.

  • Update examples for new joblib versions.

  • Update jupyter example to TensorFlow 2.

  • Fix task clone to copy only input artifacts.

  • Fix matplotlib import binding when using Agg backend.

  • Fix ProxyDictPreWrite and ProxyDictPostWrite so they can be pickled correctly (GitHub Issue #72).

  • Fix requests issue in Python 2.7 that can cause a deadlock when importing netrc.

  • Fix argparser binding sub-parser and type casting support (GitHub Issue #74).

  • Fix argparser binding Python 2.7 unicode handling.

  • Fix unsynced connected hyper parameters overridden during remote execution.

Trains Server

Features and Bug Fixes

  • Add parallel coordinates hyper-parameter comparison, available under Compare Experiments -> HYPER PARAMETERS -> Parallel Coordinates (in the drop-down) (GitHub Issue #53).

  • Add encoding of experiment table view settings in URL to allow sharing using browser URL copy/paste.

  • Add loguru (ANSI color) support (GitHub Issue #29).

  • Add support for special characters in hyper-parameter keys (white-spaces, . and $) (GitHub Issue #69).

  • Add optional anonymous daily usage statistics (help us improve Trains Server):

  • Disabled by default.

  • Requires user opt-in.

  • Single averages report per day.

  • Reports average load metrics per day (CPU/memory).

  • Reports average workload per day (amount and average duration of queues, agents and experiments).

  • Improve experiment table filtering indication.

  • Improve model view to allow navigating to its generating experiment.

  • Fix experiment comparison to distinguish between experiments with the same name (GitHub Issue #52).

  • Fix Web UI compare plots bug (GitHub Issue #55), (GitHub Issue #73).

Trains Agent

Features

  • Add support for Docker pre-installed pytorch versions that do not exist on PyPI/PyTorch.org.

  • Add AWS dynamic cluster management service.

  • Add support for various event query endpoints in APIClient.

  • Improve the configuration wizard.