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- Integration with NeptuneML feature set in AWS Neptune - Add helper library to perform Sigv4 signing for `%neptune_ml export ...`, we will move our other signing at a later date. - Swap how credentials are obtained for `ROLE` iam credentials provider such that it uses a botocore session now instead of calling the ec2 metadata service. This should make the module more usable outside of Sagemaker. New Line magics: - `%neptune_ml export status` - `%neptune_ml dataprocessing start` - `%neptune_ml dataprocessing status` - `%neptune_ml training start` - `%neptune_ml training status` - `%neptune_ml endpoint create` - `%neptune_ml endpoint status` New Cell magics: - `%%neptune_ml export start` - `%%neptune_ml dataprocessing start` - `%%neptune_ml training start` - `%%neptune_ml endpoint create` NOTE: If a cell magic is used, its line inputs for specifying parts of the command will be ignore such as `--job-id` as a line-param. Inject variable as cell input: Currently this will only work for our new cell magic commands details above. You can now specify a variable to use as the cell input received by our `neptune_ml` magics using the syntax ${var_name}. For example... ``` # in one notebook cell: foo = {'foo', 'bar'} # in another notebook cell: %%neptune_ml export start ${foo} ``` NOTE: The above will only work if it is the sole content of the cell body. You cannot inline multiple variables at this time.
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__version__ = '2.0.2' | ||
__version__ = '2.0.3' |
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