Package: azure-mgmt-batchai
Microsoft Azure SDK for PythonThis is the Microsoft Azure Batch AI Management Client Library.Azure Resource Manager (ARM) is the next generation of management APIs that
replace the old Azure Service Management (ASM).This package has been tested with Python 2.7, 3.4, 3.5 and 3.6.For the older Azure Service Management (ASM) libraries, seeazure-servicemanagement-legacylibrary.For a more complete set of Azure libraries, see theazurebundle package.CompatibilityIMPORTANT: If you have an earlier version of the azure package
(version < 1.0), you should uninstall it before installing this package.You can check the version using pip:pipfreezeIf you see azure==0.11.0 (or any version below 1.0), uninstall it first:pipuninstallazureUsageFor code examples, seeBatch AI Managementon docs.microsoft.com.Provide FeedbackIf you encounter any bugs or have suggestions, please file an issue in theIssuessection of the project.Release History2.0.0 (2018-06-07)Breaking changesThis version uses 2018-05-01 BatchAI API specification which introduced the following braking changes:Clusters, FileServers must be created under a workspace;Jobs must be created under an experiment;Clusters, FileServers and Jobs do not accept location during creation and belong to the same location as the parent
workspace;Clusters, FileServers and Jobs do not support tags;BatchAIManagementClient.usage renamed to BatchAIManagementClient.usages;Job priority changed a type from int to an enum;File.is_directory is replaced with File.file_type;Job.priority and JobCreateParameters.priority is replaced with scheduling_priority;Removed unsupported MountSettings.file_server_type attribute;OutputDirectory.type unsupported attribute removed;OutputDirectory.create_new attributes removed, BatchAI will always create output directories if they not exist;SetupTask.run_elevated attribute removed, the setup task is always executed under root.FeaturesAdded support to workspaces to group Clusters, FileServers and Experiments and remove limit on number of allocated
resources;Added support for experiment to group jobs and remove limit on number of jobs;Added support for configuring /dev/shm for jobs which use docker containers;Added first class support for generic MPI jobs;Added first class support for Horovod jobs.1.0.1 (2018-04-16)BugfixesFix some invalid models in Python 3Compatibility of the sdist with wheel 0.31.01.0.0 (2018-03-19)General Breaking changesThis version uses a next-generation code generator thatmightintroduce breaking changes.Model signatures now use only keyword-argument syntax. All positional arguments must be re-written as keyword-arguments.
To keep auto-completion in most cases, models are now generated for Python 2 and Python 3. Python 3 uses the “*” syntax for keyword-only arguments.Enum types now use the “str” mixin (class AzureEnum(str, Enum)) to improve the behavior when unrecognized enum values are encountered.
While this is not a breaking change, the distinctions are important, and are documented here:https://docs.python.org/3/library/enum.html#othersAt a glance:“is” should not be used at all.“format” will return the string value, where “%s” string formatting will returnNameOfEnum.stringvalue. Format syntax should be prefered.New Long Running Operation:Return type changes frommsrestazure.azure_operation.AzureOperationPollertomsrest.polling.LROPoller. External API is the same.Return type is nowalwaysamsrest.polling.LROPoller, regardless of the optional parameters used.The behavior has changed when usingraw=True. Instead of returning the initial call result asClientRawResponse,
without polling, now this returns an LROPoller. After polling, the final resource will be returned as aClientRawResponse.Newpollingparameter. The default behavior isPolling=Truewhich will poll using ARM algorithm. WhenPolling=False,
the response of the initial call will be returned without polling.pollingparameter accepts instances of subclasses ofmsrest.polling.PollingMethod.add_done_callbackwill no longer raise if called after polling is finished, but will instead execute the callback right away.Featuresadded support for job level mountingadded support for environment variables with secret valuesadded support for performance counters reporting in Azure Application Insightsadded support for custom imagesadded support for pyTorch deep learning frameworkadded API for usage and limits reportingadded API for listing job files in subdirectoriesnow user can choose caching type during NFS creationget cluster now reports a path segment generated for storing start task output logsget job now reports a path segment generated for job’s output directoriesrenamed EnvironmentSetting to EnvironmentVariable0.2.0 (2017-10-05)credentials_info property got renamed to credentials.removed unused class FileServerStatus and Code enumrenamed enums for CachingType and VmPriorityremoved ‘statuses’ attribute on FileServer0.1.0 (2017-10-03)Initial Release