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docs: add release notes for 0.19.2 (#4877)
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Co-authored-by: Vishnu Mohan <[email protected]>
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mackrorysd and vishnu2kmohan authored Aug 29, 2022
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55 changes: 55 additions & 0 deletions docs/release-notes.rst
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Version 0.19
**************

Version 0.19.2
==============

**Release Date:** August 26, 2022

**Breaking Changes**

- API: Response format for metrics has been standardized to return aggregated and per-batch metrics
in a uniform way. ``GetTrialWorkloads``, ``GetTrials`` API response format has changed.
``ReportTrialTrainingMetrics``, ``ReportTrialValidationMetrics`` API request format has changed
as well.

- API: ``GetJobs`` request format for pagination object has changed. Instead of being contained in
a nested ``pagination`` object, these are now top level options, in line with the other
paginatable API requests.

- CLI: ``det trial describe --json`` output format has changed. Fixed a bug where ``det trial
describe --json --metrics`` would fail for trials with a very large number of steps.

- CLI: ``det job list`` will now return all jobs by default instead of a single API results page.
Use ``--pages=1`` option for the old behavior.

**Bug Fixes**

- Kubernetes: Fixed an issue where restoring a job in a Kubernetes set up could crash the resource
manager.

- CLI: Fixed a bug where ``det e set gc-policy`` would fail when deserializing an api response
because it wasn't adjusted for the new format.

- Distributed training: Previously, experiments launched with determined.launch.torch_distributed
were wrongly skipping torch.distributed.run for single-slot trials and invoking training scripts
directly. As a result, functions such as torch.distributed.init_process_group() would fail, but
only inside single-slot trials. Now, determined.launch.torch_distributed will conform to the
intended behavior as a wrapper around torch.distributed.run and will invoke torch.distributed.run
on all training scripts.

- Experiments with a single trial are now considered canceled when their trial is canceled or
killed.

**Improvements**

- API: `GetTrialWorkloads` can now optionally include per-batch metrics when
``includeBatchMetrics`` query parameter is set.

**New Features**

- Cluster: The enterprise edition of Determined ([HPE Machine Learning Development
Environment](https://www.hpe.com/us/en/solutions/artificial-intelligence/machine-learning-development-environment.html)),
can now be deployed on a Slurm cluster. When using Slurm, Determined delegates all job scheduling
and prioritization to the Slurm workload manager. This integration enables existing Slurm
workloads and Determined workloads to coexist and access all of the advanced capabilities of the
Slurm workload manager. The Determined Slurm integration can use either Singularity or Podman for
the container runtime.

Version 0.19.1
==============

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