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Bump the nuget-dependencies group with 6 updates - #20

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Bump the nuget-dependencies group with 6 updates#20
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dependabot/nuget/nuget-dependencies-9b8c474e66

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Updated Microsoft.Bcl.Memory from 10.0.13 to 11.0.0.

Release notes

Sourced from Microsoft.Bcl.Memory's releases.

10.0.404

You can build .NET 10.0 from the repository by cloning the release tag v10.0.404 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

Important

Please use https://builds.dotnet.microsoft.com/dotnet/source-build/dotnet-source-10.0.404-servicing.26529.119.tar.gz instead of the GitHub-generated sources tarball. This is due to a discrepancy in the ownership metadata. The signatures were generated from build-produced source archives with ownership normalized to UID/GID 2001:2001, while GitHub’s automatically generated archives use 0:0. The source contents are identical, but the ownership metadata changes the archive bytes, causing signature verification to fail.

10.0.403

You can build .NET 10.0 from the repository by cloning the release tag v10.0.403 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.402

You can build .NET 10.0 from the repository by cloning the release tag v10.0.402 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.401

Release

What's Changed

... (truncated)

10.0.400

You can build .NET 10.0 from the repository by cloning the release tag v10.0.400 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.303

You can build .NET 10.0 from the repository by cloning the release tag v10.0.303 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.302

You can build .NET 10.0 from the repository by cloning the release tag v10.0.302 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.301

You can build .NET 10.0 from the repository by cloning the release tag v10.0.301 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.300

You can build .NET 10.0 from the repository by cloning the release tag v10.0.300 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.204

You can build .NET 10.0 from the repository by cloning the release tag v10.0.204 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.203

You can build .NET 10.0 from the repository by cloning the release tag v10.0.203 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.202

You can build .NET 10.0 from the repository by cloning the release tag v10.0.202 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.201

You can build .NET 10.0 from the repository by cloning the release tag v10.0.201 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.200

You can build .NET 10.0 from the repository by cloning the release tag v10.0.200 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.115

You can build .NET 10.0 from the repository by cloning the release tag v10.0.115 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

Important

Please use https://builds.dotnet.microsoft.com/dotnet/source-build/dotnet-source-10.0.115-servicing.26529.108.tar.gz instead of the GitHub-generated sources tarball. This is due to a discrepancy in the ownership metadata. The signature was generated from a build-produced source archive with ownership normalized to UID/GID 2001:2001, while GitHub’s automatically generated archive uses 0:0. The source contents are identical, but the ownership metadata changes the archive bytes, causing signature verification to fail.

10.0.114

You can build .NET 10.0 from the repository by cloning the release tag v10.0.114 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

Important

Please use https://builds.dotnet.microsoft.com/dotnet/source-build/dotnet-source-10.0.114-servicing.26522.126.tar.gz instead of the GitHub-generated sources tarball. This is due to a discrepancy in the ownership metadata. The signatures were generated from build-produced source archives with ownership normalized to UID/GID 2001:2001, while GitHub’s automatically generated archives use 0:0. The source contents are identical, but the ownership metadata changes the archive bytes, causing signature verification to fail.

10.0.113

You can build .NET 10.0 from the repository by cloning the release tag v10.0.113 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.112

You can build .NET 10.0 from the repository by cloning the release tag v10.0.112 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.111

You can build .NET 10.0 from the repository by cloning the release tag v10.0.111 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.110

You can build .NET 10.0 from the repository by cloning the release tag v10.0.110 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.109

You can build .NET 10.0 from the repository by cloning the release tag v10.0.109 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.108

You can build .NET 10.0 from the repository by cloning the release tag v10.0.108 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.107

You can build .NET 10.0 from the repository by cloning the release tag v10.0.107 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.106

You can build .NET 10.0 from the repository by cloning the release tag v10.0.106 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.105

You can build .NET 10.0 from the repository by cloning the release tag v10.0.105 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.104

You can build .NET 10.0 from the repository by cloning the release tag v10.0.104 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.103

You can build .NET 10.0 from the repository by cloning the release tag v10.0.103 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached is the PGP signature for the GitHub generated tarball. You can find the public key at https://dot.net/release-key-2023

10.0.102-sb1

You can build .NET 10.0 from the repository by cloning the release tag v10.0.102-sb1 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.101

You can build .NET 10.0 from the repository by cloning the release tag v10.0.101 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.100

You can build .NET 10.0 from the repository by cloning the release tag v10.0.100 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

To produce artifacts with the .NET 10 GA version strings, users must pass the branding argument to the build: --branding rtm.

10.0.100-rc.2.25502.107

You can build .NET 10.0 RC 2 from the repository by cloning the release tag v10.0.100-rc.2.25502.107 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

Note: GitHub automatically generates the "Source code (tar.gz/zip)" archives included in this release. Please download the official source code from:

10.0.100-rc.1.25451.107

You can build .NET 10.0 RC 1 from the repository by cloning the release tag v10.0.100-rc.1.25451.107 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

10.0.100-preview.7.25380.108

You can build .NET 10.0 Preview 7 from the repository by cloning the release tag v10.0.100-preview.7.25380.108 and following the build instructions in the main README.md.

Alternatively, you can build from the sources attached to this release directly.
More information on this process can be found in the dotnet/dotnet repository.

Attached are PGP signatures for the GitHub generated tarball and zipball. You can find the public key at https://dot.net/release-key-2023

Commits viewable in compare view.

Updated Microsoft.ML.OnnxRuntime from 1.31.0 to 1.31.1.

Release notes

Sourced from Microsoft.ML.OnnxRuntime's releases.

1.31.1

ONNX Runtime 1.31.1 is a patch release that fixes an OpenVINO-enabled Python build regression and corrects WASM Debug external-data tests. These notes cover changes since ONNX Runtime 1.31.0.

Highlights

  • Fixed a provider-info namespace mismatch that caused compilation failures when building with both OpenVINO and Python enabled (#​33327).
  • Fixed WASM Debug test failures by skipping file-backed external-data cases unsupported by the WASM test module, while retaining compile-output checks, buffer-destination coverage, and native test coverage. This is a test-only change and does not change runtime behavior (#​33226).

Contributors

Thanks to our 3 human contributors for this release!

@​eserscor, @​mustjab, @​tianleiwu

Full Changelog: rel-1.31.0...rel-1.31.1

Release highlights were prepared with AI assistance.

Commits viewable in compare view.

Updated Microsoft.ML.Tokenizers from 2.0.1 to 3.0.0.

Release notes

Sourced from Microsoft.ML.Tokenizers's releases.

3.0.0

ML.NET 3.0.0

New Features

  • Add the ability to use Object Detection using TorchSharp (#​6605) - We have added a new deep learning model back by TorchSharp that lets you fine tune your own Object Detection model!
  • Add SamplingKeyColumnName to AutoMLExperiment API (#​6649) - You can now set the SamplingKeyColumnName when you are using AutoML. Thanks @​torronen!
  • Add Object Detection to AutoML Sweeper (#​6633) - Added Object Detection to the AutoML Sweeper so now they can be used together.
  • Add String Vector support to DataFrame (#​6628) - Adds support for String Vectors in DataFrame. This also allows for Better IDataView <-> DataFrame conversions.
  • Add AutoZero tuner to BinaryClassification (#​6615) - Can now use AutoZero tuner in AutoML Binary Classification experiments.
  • Added in fairness assessment and mitigation (#​6539) - Support for fairness assessment and mitigation tool
  • Added in Support for some Intel OneDal Algorithms (#​6521) - You can now use Intel's OneDal for some algorithms. This gives you access to some accelerated versions of these algorithms. The models are fully interoperable between ML.NET's normal models and these, so you can train with OneDal and then still run on machines where OneDal is not supported. Thanks @​rgesteve!
  • Add in ability to have pre-defined weights for ngrams (#​6458) - If you know the weights of your NGrams already you can now directly provide that.
  • Add SentenceSimilarity sweepable estimator in AutoML (#​6445) - Can now use SentenceSimilarity with the sweepable estimator.
  • Add VBufferDataFrameCoumn to DataFrame (#​6409) - Now DataFrame can support the VBuffer from ML.NET so the IDataView <-> DataFrame conversion can work with those types.
  • Added ADO.NET importing/exporting functionality to DataFrame (#​5975) - Can now use ADO.NET import/export with DataFrames. Thanks @​andrei-faber!
  • Added native binaries for Windows Arm64 (#​6813) - This allows certain native transforms to be run on Widows Arm that were disabled before.
  • Switches some computational code to use the new Tensor Primitives package (#​6875)
  • Add QA sweepable estimator in AutoML (#​6781)
  • Add NameEntityRecognition and Q&A deep learning tasks. (#​6760)
  • Adds the ability to load a pre-trained LightGBM file and import it into ML.Net. (#​6569)

Enhancements

  • Expose ExperimentSettings.MaxModel as public (#​6663) - Exposes ExperimentSettings.MaxModel as public so now you can set the number of Max Models you want for an AutoML experiment.
  • Update to latest version of TorchSharp (#​6636) - Updated to the latest version of TorchSharp and fixed any breaking changes so we can take advantage of their new features and bug fixes.
  • Update to latest version of Onnx Runtime (#​6624) - Updated to the latest version of Onnx Runtime and fixed any breaking changes so we can take advantage of their new features and bug fixes.
  • Update ML.NET to compile with .NET8 (#​6641) - Removed some deprecated code now throws errors on .NET8 as well as other minor fixes to allow working/building with .NET8.
  • Added more logging to Object Detection (#​6646) - Added more logging while Object Detection is training so even if epochs take a long time you can be sure things are still moving.
  • Update timeout error message in AutoMLExperiment (#​6613) - Updated the error message so it is more clear what happened.
  • Add batchsize and arch to imageClassification SweepableTrainer (#​6597) - Added batchsize and arch to the ImageClassification SweepableTrainer so those can now be trained on.
  • Update max_model when trial fails (#​6596)
  • Add default search space for standard trainers (#​6576) - Added a default search space for all standard trainers so users have reasonable default values.
  • Adding more metrics to BinaryClassification Experiment (#​6571)
  • Add checkAlive in NasBertTrainer (#​6546) - Now we check between batches if cancellation was requested and stop processing if so.
  • OneDAL - Fallback to default implementation (#​6538) - If you specify you want to use OneDal but something happens that prevents you from using it, like it can't find the binaries/etc, it will auto default back to the normal implementation instead of crashing.
  • Add addKeyValueAnnotationsAsText flag in AutoML (#​6535)
  • Add continuous resource monitoring to AutoML.IMonitor (#​6520) - Thanks @​andrasfuchs!
  • Update WebClient to HttpClient implementations (#​6476) - Update the usage of WebClient to HttpClient since WebClient is now deprecated. Thanks @​rgesteve!
  • Set AutoML trial to unsuccess if trial loss is nan/inf (#​6430) - Now trial will be marked as unsuccesssful if the loss is an invalid number.
  • Add diskConvert option in fast tree search space (#​6316)
  • Avoid Boxing/Unboxing on accessing elements of VBufferDataFrameColumn (#​6867) and (#​6865) - Thanks @​asmirnov82!
  • Update LightGBM to version 3.X.X from 2.X.X (#​6880)
  • Implement vectorized binary arithmetic operations for DataFrames (#​6854) - Thanks @​asmirnov82!
  • Upgrade .NET Interactive (#​6857) - Thanks @​colombod!
  • Improve performance of column cloning inside DataFrame arithmetics (#​6814) - Thanks @​asmirnov82!
  • Add performance benchmarks for dataframe arithmetic operations (#​6827) - Thanks @​asmirnov82!
  • Simplify tt files for PrimitiveDataFrameColumnAritmetics (#​6830) - Thanks @​asmirnov82!
  • Improve performance of DataFrame binary comparison operations (#​6869) - Thanks @​asmirnov82!
  • Allow a CultureInfo to be used for parsing CSV values into DataFrame (#​6782) - Thanks @​asmirnov82!
  • File-scoped namespaces in files under Prediction (Microsoft.ML.Core) (#​6792) - Thanks @​Lehonti!
  • File-scoped namespaces in files under ComponentModel (Microsoft.ML.Core) (#​6788) - Thanks @​Lehonti!
  • File-scoped namespaces in files under Data (Microsoft.ML.Core) (#​6789) - Thanks @​Lehonti!
    ... (truncated)

3.0.0-Preview

ML.NET 3.0.0 Preview

New Features

  • Add the ability to use Object Detection using TorchSharp (#​6605) - We have added a new deep learning model back by TorchSharp that lets you fine tune your own Object Detection model!
  • Add SamplingKeyColumnName to AutoMLExperiment API (#​6649) - You can now set the SamplingKeyColumnName when you are using AutoML. Thanks @​torronen!
  • Add Object Detection to AutoML Sweeper (#​6633) - Added Object Detection to the AutoML Sweeper so now they can be used together.
  • Add String Vector support to DataFrame (#​6628) - Adds support for String Vectors in DataFrame. This also allows for Better IDataView <-> DataFrame conversions.
  • Add AutoZero tuner to BinaryClassification (#​6615) - Can now user AutoZero tuner in AutoML Binary Classification experiments.
  • Added in fairness assessment and mitigation (#​6539) - Support for fairness assessment and mitigation tool
  • Added in Support for some Intel OneDal Algorithms (#​6521) - You can now use Intel's OneDal for some algorithms. This gives you access to some accelerated versions of these algorithms. The models are fully interoperable between ML.NET's normal models and these, so you can train with OneDal and then still run on machines where OneDal is not supported. Thanks @​rgesteve!
  • Add in ability to have pre-defined weights for ngrams (#​6458) - If you know the weights of your NGrams already you can now directly provide that.
  • Add SentenceSimilarity sweepable estimator in AutoML (#​6445) - Can now use SentenceSimilarity with the sweepable estimator.
  • Add VBufferDataFrameCoumn to DataFrame (#​6445) - Now DataFrame can support the VBuffer from ML.NET so the IDataView <-> DataFrame conversion can work with those types.
  • Added ADO.NET importing/exporting functionality to DataFrame (#​5975) - Can now use ADO.NET import/export with DataFrames. Thanks @​andrei-faber!

Enhancements

  • Expose ExperimentSettings.MaxModel as public (#​6663) - Exposes ExperimentSettings.MaxModel as public so now you can set the number of Max Models you want for an AutoML experiment.
  • Update to latest version of TorchSharp (#​6636) - Updated to the latest version of TorchSharp and fixed any breaking changes so we can take advantage of their new features and bug fixes.
  • Update to latest version of Onnx Runtime (#​6624) - Updated to the latest version of Onnx Runtime and fixed any breaking changes so we can take advantage of their new features and bug fixes.
  • Update ML.NET to compile with .NET8 (#​6641) - Removed some deprecated code now throws errors on .NET8 as well as other minor fixes to allow working/building with .NET8.
  • Added more logging to Object Detection (#​6646) - Added more logging while Object Detection is training so even if epochs take a long time you can be sure things are still moving.
  • Update timeout error message in AutoMLExperiment (#​6613) - Updated the error message so it is more clear what happened.
  • Add batchsize and arch to imageClassification SweepableTrainer (#​6597) - Added batchsize and arch to the ImageClassification SweepableTrainer so those can now be trained on.
  • Update max_model when trial fails (#​6596)
  • Add default search space for standard trainers (#​6576) - Added a default search space for all standard trainers so users have reasonable default values.
  • Adding more metrics to BinaryClassification Experiment (#​6571)
  • Add checkAlive in NasBertTrainer (#​6546) - Now we check between batches if cancellation was requested and stop processing if so.
  • OneDAL - Fallback to default implementation (#​6538) - If you specify you want to use OneDal but something happens that prevents you from using it, like it can't find the binaries/etc, it will auto default back to the normal implementation instead of crashing.
  • Add addKeyValueAnnotationsAsText flag in AutoML (#​6535)
  • Add continuous resource monitoring to AutoML.IMonitor (#​6520) - Thanks @​andrasfuchs!
  • Update WebClient to HttpClient implementations (#​6476) - Update a usage of WebClient to HttpClient since WebClient is now deprecated. Thanks @​rgesteve!
  • Set AutoML trial to unsuccess if trial loss is nan/inf (#​6430) - Now trial will be marked as unsuccesssful if the loss is an invalid number.
  • Add diskConvert option in fast tree search space (#​6316)

Bug Fixes

  • Fix DataFrame ToString (#​6673) - Use correct alignment for columns to produce readable output when columns have longer names. Thanks @​asmirnov82!
  • Fix DataFrame null math (#​6661) - Fixes max in DataFrame columns when there are null values to match what Pandas does.
  • Clean up PrimitiveColumnContainer (#​6656) - Cleaned up the code in PrimitiveColumnContainer so its more correct and easier to use.
  • Fix Apply in PrimitiveColumnContainer (#​6642) - Fixes the Apply method so it no longer changes the source column. Thanks @​janholo!
  • Fix datetime null error (#​6627) - Fixes loading a null datetime from a database so it now returns correctly instead of throwing an error.
  • Fix AggregateTrainingStopManager is trying to cancel disposed tokens (#​6612) - Will no longer try and cancel already disposed tokens.
  • Fix tostring bug for sweepable pipeline (#​6610)
  • Change Test to Validate in Dataset manager (#​6599)
  • Fixed System.OperationCanceledException when calling experimentResult.BestRun.Estimator.Fit (#​6572)
  • Fixed cancellation bug in SweepablePipelineRunner && Fixed object null exception in AutoML v1.0 regression API (#​6560)
  • Fixed one dal dispatching issues (#​6547) - OneDal now dispatches correctly.
  • Fixed Multi-threaded access issue (#​6537) - Fixed a multi-threaded access issue for variable length string arrays in ONNX models.
  • Fixed AutoML experiments in non declarative style not working (#​6447)

Build / Test updates

... (truncated)

Commits viewable in compare view.

Updated Microsoft.ML.Tokenizers.Data.O200kBase from 2.0.1 to 3.0.0.

Release notes

Sourced from Microsoft.ML.Tokenizers.Data.O200kBase's releases.

3.0.0

ML.NET 3.0.0

New Features

  • Add the ability to use Object Detection using TorchSharp (#​6605) - We have added a new deep learning model back by TorchSharp that lets you fine tune your own Object Detection model!
  • Add SamplingKeyColumnName to AutoMLExperiment API (#​6649) - You can now set the SamplingKeyColumnName when you are using AutoML. Thanks @​torronen!
  • Add Object Detection to AutoML Sweeper (#​6633) - Added Object Detection to the AutoML Sweeper so now they can be used together.
  • Add String Vector support to DataFrame (#​6628) - Adds support for String Vectors in DataFrame. This also allows for Better IDataView <-> DataFrame conversions.
  • Add AutoZero tuner to BinaryClassification (#​6615) - Can now use AutoZero tuner in AutoML Binary Classification experiments.
  • Added in fairness assessment and mitigation (#​6539) - Support for fairness assessment and mitigation tool
  • Added in Support for some Intel OneDal Algorithms (#​6521) - You can now use Intel's OneDal for some algorithms. This gives you access to some accelerated versions of these algorithms. The models are fully interoperable between ML.NET's normal models and these, so you can train with OneDal and then still run on machines where OneDal is not supported. Thanks @​rgesteve!
  • Add in ability to have pre-defined weights for ngrams (#​6458) - If you know the weights of your NGrams already you can now directly provide that.
  • Add SentenceSimilarity sweepable estimator in AutoML (#​6445) - Can now use SentenceSimilarity with the sweepable estimator.
  • Add VBufferDataFrameCoumn to DataFrame (#​6409) - Now DataFrame can support the VBuffer from ML.NET so the IDataView <-> DataFrame conversion can work with those types.
  • Added ADO.NET importing/exporting functionality to DataFrame (#​5975) - Can now use ADO.NET import/export with DataFrames. Thanks @​andrei-faber!
  • Added native binaries for Windows Arm64 (#​6813) - This allows certain native transforms to be run on Widows Arm that were disabled before.
  • Switches some computational code to use the new Tensor Primitives package (#​6875)
  • Add QA sweepable estimator in AutoML (#​6781)
  • Add NameEntityRecognition and Q&A deep learning tasks. (#​6760)
  • Adds the ability to load a pre-trained LightGBM file and import it into ML.Net. (#​6569)

Enhancements

  • Expose ExperimentSettings.MaxModel as public (#​6663) - Exposes ExperimentSettings.MaxModel as public so now you can set the number of Max Models you want for an AutoML experiment.
  • Update to latest version of TorchSharp (#​6636) - Updated to the latest version of TorchSharp and fixed any breaking changes so we can take advantage of their new features and bug fixes.
  • Update to latest version of Onnx Runtime (#​6624) - Updated to the latest version of Onnx Runtime and fixed any breaking changes so we can take advantage of their new features and bug fixes.
  • Update ML.NET to compile with .NET8 (#​6641) - Removed some deprecated code now throws errors on .NET8 as well as other minor fixes to allow working/building with .NET8.
  • Added more logging to Object Detection (#​6646) - Added more logging while Object Detection is training so even if epochs take a long time you can be sure things are still moving.
  • Update timeout error message in AutoMLExperiment (#​6613) - Updated the error message so it is more clear what happened.
  • Add batchsize and arch to imageClassification SweepableTrainer (#​6597) - Added batchsize and arch to the ImageClassification SweepableTrainer so those can now be trained on.
  • Update max_model when trial fails (#​6596)
  • Add default search space for standard trainers (#​6576) - Added a default search space for all standard trainers so users have reasonable default values.
  • Adding more metrics to BinaryClassification Experiment (#​6571)
  • Add checkAlive in NasBertTrainer (#​6546) - Now we check between batches if cancellation was requested and stop processing if so.
  • OneDAL - Fallback to default implementation (#​6538) - If you specify you want to use OneDal but something happens that prevents you from using it, like it can't find the binaries/etc, it will auto default back to the normal implementation instead of crashing.
  • Add addKeyValueAnnotationsAsText flag in AutoML (#​6535)
  • Add continuous resource monitoring to AutoML.IMonitor (#​6520) - Thanks @​andrasfuchs!
  • Update WebClient to HttpClient implementations (#​6476) - Update the usage of WebClient to HttpClient since WebClient is now deprecated. Thanks @​rgesteve!
  • Set AutoML trial to unsuccess if trial loss is nan/inf (#​6430) - Now trial will be marked as unsuccesssful if the loss is an invalid number.
  • Add diskConvert option in fast tree search space (#​6316)
  • Avoid Boxing/Unboxing on accessing elements of VBufferDataFrameColumn (#​6867) and (#​6865) - Thanks @​asmirnov82!
  • Update LightGBM to version 3.X.X from 2.X.X (#​6880)
  • Implement vectorized binary arithmetic operations for DataFrames (#​6854) - Thanks @​asmirnov82!
  • Upgrade .NET Interactive (#​6857) - Thanks @​colombod!
  • Improve performance of column cloning inside DataFrame arithmetics (#​6814) - Thanks @​asmirnov82!
  • Add performance benchmarks for dataframe arithmetic operations (#​6827) - Thanks @​asmirnov82!
  • Simplify tt files for PrimitiveDataFrameColumnAritmetics (#​6830) - Thanks @​asmirnov82!
  • Improve performance of DataFrame binary comparison operations (#​6869) - Thanks @​asmirnov82!
  • Allow a CultureInfo to be used for parsing CSV values into DataFrame (#​6782) - Thanks @​asmirnov82!
  • File-scoped namespaces in files under Prediction (Microsoft.ML.Core) (#​6792) - Thanks @​Lehonti!
  • File-scoped namespaces in files under ComponentModel (Microsoft.ML.Core) (#​6788) - Thanks @​Lehonti!
  • File-scoped namespaces in files under Data (Microsoft.ML.Core) (#​6789) - Thanks @​Lehonti!
    ... (truncated)

3.0.0-Preview

ML.NET 3.0.0 Preview

New Features

  • Add the ability to use Object Detection using TorchSharp (#​6605) - We have added a new deep learning model back by TorchSharp that lets you fine tune your own Object Detection model!
  • Add SamplingKeyColumnName to AutoMLExperiment API (#​6649) - You can now set the SamplingKeyColumnName when you are using AutoML. Thanks @​torronen!
  • Add Object Detection to AutoML Sweeper (#​6633) - Added Object Detection to the AutoML Sweeper so now they can be used together.
  • Add String Vector support to DataFrame (#​6628) - Adds support for String Vectors in DataFrame. This also allows for Better IDataView <-> DataFrame conversions.
  • Add AutoZero tuner to BinaryClassification (#​6615) - Can now user AutoZero tuner in AutoML Binary Classification experiments.
  • Added in fairness assessment and mitigation (#​6539) - Support for fairness assessment and mitigation tool
  • Added in Support for some Intel OneDal Algorithms (#​6521) - You can now use Intel's OneDal for some algorithms. This gives you access to some accelerated versions of these algorithms. The models are fully interoperable between ML.NET's normal models and these, so you can train with OneDal and then still run on machines where OneDal is not supported. Thanks @​rgesteve!
  • Add in ability to have pre-defined weights for ngrams (#​6458) - If you know the weights of your NGrams already you can now directly provide that.
  • Add SentenceSimilarity sweepable estimator in AutoML (#​6445) - Can now use SentenceSimilarity with the sweepable estimator.
  • Add VBufferDataFrameCoumn to DataFrame (#​6445) - Now DataFrame can support the VBuffer from ML.NET so the IDataView <-> DataFrame conversion can work with those types.
  • Added ADO.NET importing/exporting functionality to DataFrame (#​5975) - Can now use ADO.NET import/export with DataFrames. Thanks @​andrei-faber!

Enhancements

  • Expose ExperimentSettings.MaxModel as public (#​6663) - Exposes ExperimentSettings.MaxModel as public so now you can set the number of Max Models you want for an AutoML experiment.
  • Update to latest version of TorchSharp (#​6636) - Updated to the latest version of TorchSharp and fixed any breaking changes so we can take advantage of their new features and bug fixes.
  • Update to latest version of Onnx Runtime (#​6624) - Updated to the latest version of Onnx Runtime and fixed any breaking changes so we can take advantage of their new features and bug fixes.
  • Update ML.NET to compile with .NET8 (#​6641) - Removed some deprecated code now throws errors on .NET8 as well as other minor fixes to allow working/building with .NET8.
  • Added more logging to Object Detection (#​6646) - Added more logging while Object Detection is training so even if epochs take a long time you can be sure things are still moving.
  • Update timeout error message in AutoMLExperiment (#​6613) - Updated the error message so it is more clear what happened.
  • Add batchsize and arch to imageClassification SweepableTrainer (#​6597) - Added batchsize and arch to the ImageClassification SweepableTrainer so those can now be trained on.
  • Update max_model when trial fails (#​6596)
  • Add default search space for standard trainers (#​6576) - Added a default search space for all standard trainers so users have reasonable default values.
  • Adding more metrics to BinaryClassification Experiment (#​6571)
  • Add checkAlive in NasBertTrainer (#​6546) - Now we check between batches if cancellation was requested and stop processing if so.
  • OneDAL - Fallback to default implementation (#​6538) - If you specify you want to use OneDal but something happens that prevents you from using it, like it can't find the binaries/etc, it will auto default back to the normal implementation instead of crashing.
  • Add addKeyValueAnnotationsAsText flag in AutoML (#​6535)
  • Add continuous resource monitoring to AutoML.IMonitor (#​6520) - Thanks @​andrasfuchs!
  • Update WebClient to HttpClient implementations (#​6476) - Update a usage of WebClient to HttpClient since WebClient is now deprecated. Thanks @​rgesteve!
  • Set AutoML trial to unsuccess if trial loss is nan/inf (#​6430) - Now trial will be marked as unsuccesssful if the loss is an invalid number.
  • Add diskConvert option in fast tree search space (#​6316)

Bug Fixes

  • Fix DataFrame ToString (#​6673) - Use correct alignment for columns to produce readable output when columns have longer names. Thanks @​asmirnov82!
  • Fix DataFrame null math (#​6661) - Fixes max in DataFrame columns when there are null values to match what Pandas does.
  • Clean up PrimitiveColumnContainer (#​6656) - Cleaned up the code in PrimitiveColumnContainer so its more correct and easier to use.
  • Fix Apply in PrimitiveColumnContainer (#​6642) - Fixes the Apply method so it no longer changes the source column. Thanks @​janholo!
  • Fix datetime null error (#​6627) - Fixes loading a null datetime from a database so it now returns correctly instead of throwing an error.
  • Fix AggregateTrainingStopManager is trying to cancel disposed tokens (#​6612) - Will no longer try and cancel already disposed tokens.
  • Fix tostring bug for sweepable pipeline (#​6610)
  • Change Test to Validate in Dataset manager (#​6599)
  • Fixed System.OperationCanceledException when calling experimentResult.BestRun.Estimator.Fit (#​6572)
  • Fixed cancellation bug in SweepablePipelineRunner && Fixed object null exception in AutoML v1.0 regression API (#​6560)
  • Fixed one dal dispatching issues (#​6547) - OneDal now dispatches correctly.
  • Fixed Multi-threaded access issue (#​6537) - Fixed a multi-threaded access issue for variable length string arrays in ONNX models.
  • Fixed AutoML experiments in non declarative style not working (#​6447)

Build / Test updates

... (truncated)

Commits viewable in compare view.

Updated Microsoft.NET.Test.Sdk from 18.11.0 to 18.12.0.

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Sourced from Microsoft.NET.Test.Sdk's releases.

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Updated System.Numerics.Tensors from 10.0.13 to 11.0.0...

Description has been truncated

@dependabot
Bump the nuget-dependencies group with 6 updates
03e0c37 
Bumps Microsoft.Bcl.Memory from 10.0.13 to 11.0.0
Bumps Microsoft.ML.OnnxRuntime from 1.31.0 to 1.31.1
Bumps Microsoft.ML.Tokenizers from 2.0.1 to 3.0.0
Bumps Microsoft.ML.Tokenizers.Data.O200kBase from 2.0.1 to 3.0.0
Bumps Microsoft.NET.Test.Sdk from 18.11.0 to 18.12.0
Bumps System.Numerics.Tensors from 10.0.13 to 11.0.0

---
updated-dependencies:
- dependency-name: Microsoft.Bcl.Memory
  dependency-version: 11.0.0
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: nuget-dependencies
- dependency-name: Microsoft.ML.OnnxRuntime
  dependency-version: 1.31.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: nuget-dependencies
- dependency-name: Microsoft.ML.Tokenizers
  dependency-version: 3.0.0
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: nuget-dependencies
- dependency-name: Microsoft.ML.Tokenizers.Data.O200kBase
  dependency-version: 3.0.0
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: nuget-dependencies
- dependency-name: Microsoft.NET.Test.Sdk
  dependency-version: 18.12.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: nuget-dependencies
- dependency-name: System.Numerics.Tensors
  dependency-version: 11.0.0
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: nuget-dependencies
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot Bot added .NET Pull requests that update .NET code dependencies Pull requests that update a dependency file labels Nov 11, 2026
@dependabot dependabot Bot mentioned this pull request Nov 11, 2026
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