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Hello, you may find help with 2.13/3 compatability using the new cross version features in sbt 1.5, you can read about them in this scala-lang.org blog: Scala 3 in sbt 1.5 | The Scala Programming Language

Historically, protobuf has not documented its cross-version runtimecompatibility guarantees and has been inconsistent about enforcing whatguarantees it provides. Moving forward, we intend to offer the followingguarantees across all languages except C++. These are the default guarantees;however, owners of protobuf code generators and runtimes may explicitly overridethem with more specific guarantees for that language.

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As we can see, different MLR environments provide different library versions. Additionally, users often want to upgrade libraries to try new features. This range of versions poses a significant compatibility challenge and requires a comprehensive testing strategy. Testing MLflow only against one specific version (for instance, only the latest version) is insufficient; we need to test MLflow against a range of ML library versions that users commonly leverage. Another challenge is that ML libraries are constantly evolving and releasing new versions which may contain breaking changes that are incompatible with the integrations MLflow provides (for instance, removal of an API that MLflow relies on for model serialization). We want to detect such breaking changes as early as possible, ideally even before they are shipped in a new version release. To address these challenges, we have implemented cross-version testing.

We implemented cross-version testing using GitHub Actions that trigger automatically each day, as well as when a relevant pull request is filed. A test workflow automatically identifies a matrix of versions to test for each of MLflow's library integrations, creating a separate job for each one. Each of these jobs runs a collection of tests that are relevant to the ML library.

One of the outcomes of cross-version testing is that MLflow can clearly document which ML library versions it supports and warn users when an installed library version is unsupported. For example, the documentation for the mlflow.sklearn.autolog API provides a range of compatible scikit-learn versions:

Now that we have a testing structure, let's run the tests. To start, we created a GitHub Actions workflow that constructs a testing matrix from the configuration file and runs each item in the matrix as a separate job in parallel. An example of the GitHub Actions workflow summary for scikit-learn cross-version testing is shown below. Based on the configuration, we have a minimum version "0.20.3", which is shown at the top. We populate all versions that exist between that minimum version and the maximum version "1.0.2". At the bottom, you can see the addition of one final test: the "dev" version, which represents a prerelease version of scikit-learn installed from the main development branch in scikit-learn/scikit-learn via the command specified in the install_dev field. We'll explain the aim of this prerelease version testing in the "Testing the future" section later.

In cross-version testing, we run daily tests against both publicly available versions and prerelease versions installed from on the main development branch for all dependent libraries that are used by MLflow. This allows us to predict what will happen to MLflow in the future.

Check out this README file for further reading on the implementation of cross-version testing. We hope this blog post will help other open-source projects that provide integrations for many ML libraries.

If your Identity Management (IdM) environment has IdM servers running on both RHEL 8 and RHEL 9, specifically RHEL 9.2 or earlier, an incompatibility due to the upstream implementation of the MS-PAC ticket signature support may cause certain operations to fail. However, in RHEL 9.2.z and RHEL 9.3, the implementation of the dynamic ticket signature enforcement mechanism feature fixes this cross-version incompatibility between RHEL 8 and RHEL 9 IdM servers.

In case of a gradual migration environment, that is a domain with IdM servers running on both RHEL 9 and RHEL 8, an incompatibility due to the upstream implementation of the PAC ticket signature support may cause certain operations to fail. This cross-versions incompatibility has been fixed with the introduction of the dynamic ticket signature enforcement mechanism in the following updates:

CellMiner Cross-Database (CellMinerCDB, discover.nci.nih.gov/cellminercdb) allows integration and analysis of molecular and pharmacological data within and across cancer cell line datasets from the National Cancer Institute (NCI), Broad Institute, Sanger/MGH and MD Anderson Cancer Center (MDACC). We present CellMinerCDB 1.2 with updates to datasets from NCI-60, Broad Cancer Cell Line Encyclopedia and Sanger/MGH, and the addition of new datasets, including NCI-ALMANAC drug combination, MDACC Cell Line Project proteomic, NCI-SCLC DNA copy number and methylation data, and Broad methylation, genetic dependency and metabolomic datasets. CellMinerCDB (v1.2) includes several improvements over the previously published version: (i) new and updated datasets; (ii) support for pattern comparisons and multivariate analyses across data sources; (iii) updated annotations with drug mechanism of action information and biologically relevant multigene signatures; (iv) analysis speedups via caching; (v) a new dataset download feature; (vi) improved visualization of subsets of multiple tissue types; (vii) breakdown of univariate associations by tissue type; and (viii) enhanced help information. The curation and common annotations (e.g. tissues of origin and identifiers) provided here across pharmacogenomic datasets increase the utility of the individual datasets to address multiple researcher question types, including data reproducibility, biomarker discovery and multivariate analysis of drug activity.

From time to time, AWS Lake Formation updates the cross-account data sharing settings to distinguish the changes made to the AWS RAM usage and to support updates made to the cross-account data sharing feature. When Lake Formation does this, it creates a new version of the Cross account version settings.

Named resource method: Optimizes the number of AWS RAM resource shares by mapping multiple cross-account permission grants with one AWS RAM resource share. User does not require additional permissions.

Considerations when updating versions: Users who want to grant cross-account Lake Formation permissions must have the permissions in the AWSLakeFormationCrossAccountManager AWS managed policy. Otherwise, you need to have ram:AssociateResourceShare and ram:DisassociateResourceShare permissions to successfully share resources with another account.

LF-TBAC method: Lake Formation uses AWS RAM for cross-account grants. User must add glue:ShareResource statement to the glue:PutResourcePolicy permission. The recipient must accept resource share invitations from AWS RAM.

Considerations when updating versions: If the grantor uses a version lower than version 3, and the recipient is using version 3 or higher, the grantor receives the following error message: "Invalid cross account grant request. Consumer account has opt-in to cross account version: v3. Please update CrossAccountVersion in DataLakeSetting to minimal version v3 (Service: AmazonDataCatalog; Status Code: 400; Error Code: InvalidInputException)". However, if the grantor uses version 3 and the recipient is using version 1 or version 2, the cross-account grants go through successfully.

Cross-account grants made using LF-TBAC method require users to have an AWS Glue Data Catalog resource policy in the account. When you update to version 3, LF-TBAC grants uses AWS RAM. To allow AWS RAM based cross-account grants to succeed, you must add the glue:ShareResource statement to your existing Data Catalog resource policies as shown in the Managing cross-account permissions using both AWS Glue and Lake Formation section.

New versions (version 2 and above) of cross-account grants optimally utilize AWS RAM capacity to maximize cross account usage. When you share a resource with an external AWS account or an IAM principal, Lake Formation may create a new resource share or associate the resource with an existing share. By associating with existing shares, Lake Formation reduces the number of resource share invitations a consumer needs to accept.

To share resources directly with IAM principals in another account or to enable TBAC cross-account shares to Organizations or organizational units, you need to update the Cross account version settings to version 3. For more information about AWS RAM resource limits, see Cross-account data sharing best practices and considerations.

If a cross-account permission grantor has AWSLakeFormationCrossAccountManager managed IAM policy permissions, then there is no extra permission setup required for the cross-account permission grantor role or principal. However, if the cross-account grantor is not using the managed policy, then the grantor role or principal should have following IAM permissions granted for the new version of the cross-account grant to be successful.

Once you choose Version 2 or Version 3, all new named resource grants will go through the new cross-account grant mode. To optimally use AWS RAM capacity for your existing cross-account shares, we recommend you to revoke the grants that were made with the older version, and re-grant in the new mode.

We cannot guarantee binary compatibility across versions, especially if using C++. Given that MSFT didn't even attempt to have cross-version compatibility across Visual C++ version until VS2017 (with a special pragma to refuse to even try to link against different versions), there isn't much we can do about it. We do make every effort to maintain that compatibility. 006ab0faaa