mirror of
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70 lines
4.1 KiB
Markdown
70 lines
4.1 KiB
Markdown
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---
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title: Version 1.8
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---
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### ClearML 1.8.3
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**Bug Fixes**
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* Set GCS credentials to `None` if invalid service account credentials are provided ([ClearML GitHub issue #840](https://github.com/allegroai/clearml/issues/840))
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* Fix a sync issue when loading deferred configuration
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### ClearML 1.8.2
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**New Features and Improvements**
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* Added `VCS_ENTRY_POINT` environment variable that overrides ClearML's entrypoint auto-detection
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**Bug Fixes**
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* Fix all parameters returned from a pipeline are considered strings
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* Fix `Task.set_parameters()` does not add parameter type when parameter exists but does not have a type
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### ClearML 1.8.1
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**New Features and Improvements**
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* Raise error on failed uploads ([ClearML GitHub issue #810](https://github.com/allegroai/clearml/issues/819))
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* Add hyperdataset examples ([ClearML GitHub PR #823](https://github.com/allegroai/clearml/commit/f6b9efe54e1246adba4036c56bc6e8a0bdb99948))
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* Change `report_event_flush_threshold` default to 100
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* Add `ModelInfo.weights_object()` to store callback access to the actual model object being stored (valid for both
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pre/post save calls, otherwise `None`)
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* Support `num_workers` in dataset operation
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* Support max connections setting for Azure storage using the `sdk.azure.storage.max_connection` configuration option
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**Bug Fixes**
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* Fix clearml logger default level cannot be changed ([ClearML GitHub issue #741](https://github.com/allegroai/clearml/issues/741))
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* Fix Hydra doesn't get overridden information from ClearML ([ClearML GitHub issue #751](https://github.com/allegroai/clearml/issues/751))
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* Fix `StorageManager.list(“s3://..”, with_metadata=True)` doesn't work
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* Fix `ModelsList.keys()` is missing
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* Fix `CLEARML_DEFERRED_TASK_INIT=1` doesn't work
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* Fix default API method does not work when set in configuration
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### ClearML 1.8.0
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**New Features and Improvements**
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* Add tarfile member sanitization to `extractall()`([ClearML GitHub PR #803](https://github.com/allegroai/clearml/pull/803))
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* Add `Task.delete_artifacts()` with `raise_on_errors` argument ([ClearML GitHub issue #805](https://github.com/allegroai/clearml/issues/805))
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* Add CI/CD example ([ClearML GitHub PR #815](https://github.com/allegroai/clearml/pull/815))
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* Limit number of `_serialize` requests when adding list of links with `add_external_files()` ([ClearML GitHub issue #813](https://github.com/allegroai/clearml/issues/813))
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* Add support for connecting Enum values as parameters
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* Improve Colab integration (store entire colab, not history)
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* Add `clearml.browser_login` to authenticate browser online sessions such as Colab, Jupyter Notebooks etc.
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* Remove `import_bind` from stack trace of import errors
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* Add `sdk.development.worker.report_event_flush_threshold` configuration option to control the number of events to trigger a report
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* Return stub object from `Task.init()` if no `clearml.conf` file is found
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* Improve manual model uploading example
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* Remove deprecated demo server
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**Bug Fixes**
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* Fix passing `compression=ZIP_STORED` (or 0) to `Dataset.upload()` uses `ZIP_DEFLATED` and overrides the user-supplied
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argument ([ClearML GitHub PR #812](https://github.com/allegroai/clearml/pull/812))
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* Fix `unique_selector` is not applied properly on batches after the first batch. Remove default selector value since
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it does not work for all event types (and we always specify it anyway)
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* Fix `clearml-init` colab detection
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* Fix cloning pipelines run with `start_locally()` doesn't work
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* Fix if project has a default output uri there is no way to disable it in development mode (manual), allow passing
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`output_uri=False` to disable it
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* Fix git remote repository detection when remote is not "origin"
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* Fix reported images might not all be reported when waiting to complete the task
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* Fix `Dataset.get_local_copy()` deletes the source archive if it is stored locally
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* Fix too many parts will cause preview to inflate Task object beyond its 16MB limit - set a total limit of 320kbs
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* Fix media preview is created instead of a table preview
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* Fix `task.update_output_model()` should always upload local models to a remote server
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* Fix broken pip package might mess up requirements detection
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