3.8 KiB
| title |
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| Version 0.13 |
:::important Trains is now ClearML. :::
Trains 0.13.3
Features and Bug Fixes
-
Add a binding for
tensorboard.summarywriter.addscalars -
Add the
tensorboard_single_series_per_graphmethod, which supports separate plots for each TensorBoard scalar. -
Add the
Task.set_base_dockerandTask.get_base_dockermethods 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, andAWS_DEFAULT_REGION. - Azure Storage:
AZURE_STORAGE_ACCOUNTandAZURE_STORAGE_KEY. - Google Cloud Storage:
GOOGLE_APPLICATION_CREDENTIALS.
- AWS:
-
Add the
Task.get_parameters_as_dictandTask.set_parameters_as_dictmethods supporting get / set of parameters from referenced Tasks (use theTask.get_taskto get a reference). -
Make sure
Task.connectalways returns the connected instance passed to it. -
tensorflow_gputakes precedence overtensorflowwhen Trains detects installed packages to record experiment dependencies. -
Remove title and series naming restrictions (allow
$and.) when reporting metrics. -
Fix incorrect printouts in initialization wizard and upgrade notifications.
-
Fix debug images URL for uploaded files with
%in their name.
Trains 0.13.2
Features and Bug Fixes
- Allow reporting a pre-uploaded image url in
Logger.report_image()using theLogger.report_image.params.urlparameter. - Add support for Git repositories without a
.gitsuffix, for example Azure Repos. - Improve conda support.
- Improve hyperparameters argparser integration.
- Fix savefig patching in matplotlib binding.
- Fix logs, events and Jupyter Notebook flushing on exit.
Trains 0.13.1
Features and Bug Fixes
- Add support for
pyplot.savefigandpylab.savefigin matplotlib binding. - Add support for SageMaker.
- Improve configuration wizard.
- Try to make sure TensorBoard is available when using torch.
- Do not store keras model network design if it cannot be serialized (GitHub Issue #72).
- Fix matplotlib binding support.
Trains 0.13.0
Features and Bug Fixes
- Add support for trains-server v0.13.0.
- Add support for nested (non-main) tasks.
- Add warning when automatic argument parser binding cannot be turned off.
- Add
Task.upload_artifactsupport for external URLs (pre-uploaded). - Add support for special characters in hyperparameter keys (white-spaces,
.and$) (GitHub Issue #69). - Add support for PyTorch
.ptmodel 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-initconfiguration 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
Aggbackend. - Fix
ProxyDictPreWriteandProxyDictPostWriteso 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 hyperparameters overridden during remote execution.