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Releases: microsoft/SynapseML

v1.0.4-spark3.5

10 Apr 19:16
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chore: Adding Spark35 support

v1.0.4-spark3.3

10 Apr 19:15
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chore: downgrade to spark3.3

SynapseML v1.0.4

10 Apr 19:14
2cba4c4
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v1.0.4

Bug Fixes 🐞

  • companionModelClassName no longer returns generic type variable (#2195)
  • Fix tag for pyCodeGenImpl (#2194)

Build 🏭

  • bump azure/login from 1 to 2 (#2176)
  • bump azure/CLI from 1 to 2 (#2178)

Maintenance 🔧

  • Bump version to 1.0.4 (#2200)
  • fix flaky HyperOpt NB (#2198)
  • Bump python version to 3.11 (#2193)
  • exclude non-executable docs from automated tests (#2197)
  • add retry logic to build steps (#2192)
  • update openai api version to 2024 (#2190)
  • fix 1.0.1 version tags (#2189)

Acknowledgements

We would like to acknowledge the developers and contributors, both internal and external who helped create this version of SynapseML.

SynapseML v1.0.3

22 Mar 21:27
964ebfc
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[v1.0.3]

Bug Fixes 🐞

  • repair failing speech tests (#2179)
  • update openai completion (#2142)

Build 🏭

  • bump github/codeql-action from 2 to 3 (#2148)
  • bump actions/setup-python from 4 to 5 (#2146)
  • bump peter-evans/create-or-update-comment from 3 to 4 (#2162)
  • bump actions/upload-artifact from 3.1.3 to 4.3.1 (#2165)

Features 🌈

  • OpenAI embeddings with GPU based KNN (#2157)
  • Synthetic difference in differences (#2095)

Maintenance 🔧

  • Update to version 1.0.3 (#2183)
  • update build system service principals (#2181)
  • raise error with documentation link - find_secret (#2180)
  • check Fabric Tenant (#2175)
  • rotate outdates SAS url in speech tests (#2173)
  • Support Token Provider Mode (#2160)
  • Bump isolation forest to 3.0.4 (#2168)
  • Add script to generate pypi mfa qr (#2150)
  • Add Unified Logging Base Class for Python (#2159)
  • fix failing tests (#2153)

v1.0.3-spark3.5

22 Mar 21:37
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v1.0.3-spark3.5 Pre-release
Pre-release
chore: Adding Spark35 support

v1.0.3-spark3.3

22 Mar 21:40
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v1.0.3-spark3.3 Pre-release
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chore: downgrade to spark3.3

SynapseML v0.10.2-spark3.3

05 Dec 16:49
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v1.0.2-spark3.3

chore: downgrade to spark3.3

SynapseML v1.0.2

27 Nov 21:27
522661a
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[SynapseML v1.0.2]

Bug Fixes 🐞

  • Add the error handling for Langchain transformer (#2137)
  • use java class loader (#2135)
  • Support to Bool input for Onnx models (#2130)

Build 🏭

  • bump amannn/action-semantic-pull-request from 5.3.0 to 5.4.0 (#2125)

Doc

  • update find_secret on Fabric and doc (#2132)

Documentation 📘

  • update CONTRIBUTING.md (#2138)
  • fix install instructions (#2136)
  • fix readme install
  • add audiobook paper to README
  • add analyze text document (#2127)
  • use the new AnalyzeText API in docs(#2126)
  • removing spark 3.2 instructions

Maintenance 🔧

  • bump to v1.0.2 (#2140)
  • change udf vec2array to pyspark.ml.functions.vector_to_array (#2131)
  • fix failing notebooks (#2134)

Acknowledgements

We would like to acknowledge the developers and contributors, both internal and external who helped create this version of SynapseML.\n

Changes:

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SynapseML v1.0.1

02 Nov 01:41
cb4fd82
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v1.0.1

Documentation 📘

  • pointing cognitive apis to azure ai (#2119)
  • bump readme to spark 3.4

Maintenance 🔧

  • bump to v1.0.1 (#2123)
  • add back in exclusions (#2122)

Acknowledgements

We would like to acknowledge the developers and contributors, both internal and external who helped create this version of SynapseML.\n

Changes:

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SynapseML v1.0.0

01 Nov 17:35
ef435a2
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SynapseML: Simple and distributed machine learning

We are excited to announce the release and general availability of SynapseML v1.0 following seven years of continuous development. SynapseML is an open-source library that aims to streamline the development of massively scalable machine learning pipelines. It unifies several existing ML Frameworks and new Microsoft algorithms in a single, scalable API that is usable across Python, R, Scala, and Java. SynapseML is usable from any Apache Spark platform and is now generally available with enterprise support on Microsoft Fabric.

Highlights

Distributed Langchain Vector Search Indices Semantic Link
Deploy your LLM apps on millions of documents Quickly create semantic and multi-modal search engines Work with PowerBI datasets natively from Microsoft Fabric
View Notebook Try an Example Learn More
Keyless AI Services Orthogonal Forests
Use built-in AI services without keys in Microsoft Fabric Discover and measure heterogeneous causal effects
Learn More Try an Example

New Features

General ✨

  • Add support for spark 3.4.1 (#2052) (#2116)
  • Enterprise support on Microsoft Fabric

Open AI and Langchain 🦜

  • Add the LangchainTransformer for orchestrating LLMs at scale (#1925, #2036)
  • Add ChatGPT through the OpenAIChatCompletion transformer (#1887)
  • Add Langchain notebook (#2002, #2013)
  • Add OpenAI document Q+A notebook (#2029, #2033)
  • Add custom chatbot creation to form recognition demo (#1888)

Azure AI Services 🧠

  • Add Support for Azure Cognitive Search Vector Indices (#2041)
  • Add keyless Azure AI services on Microsoft Fabric (#2070, #1859)
  • Support new form recognizer APIs (#1882)
  • Support streaming multivariate anomaly detection (#1893)
  • Add prerequisites page for setting up OpenAI and Azure AI services (#2008)

Deep Learning 🕸

Causal Learning 📈

  • Add OrthogonalForestDML for causal learning with heterogeneous effects (#1873)
  • Add Heterogeneous Effect Quickstart
  • Support custom reference distribution in DistributionBalanceMeasures to detect data drift (#1885)
  • Add statistical significance reporting for causal learners using getPValue (#1863)

LightGBM 🌳

Additional Updates

Bug Fixes 🐞

  • Improve LGBM exception and logging (#2037)
  • AI Services and other HTTP Clients no longer retry 4XX codes other than 429 (#2005)
  • Make geospatial services robust to 404s thrown by the service (#2007)
  • Fix bug #1869, where DoubleML .setFitIntercept should default to true (#1876)
  • Fix Multivariate Anomaly error handling (#1991)
  • Fix import error when using AI services on Azure Machine Learning clusters (#1951)
  • Fix default values of aadToken & url on Fabric (#1918)
  • Fix ONNX model shape inference on batches with shape [-1] (#1906)
  • Add getPValue to python API of DoubleML (#1909)
  • Add diagnosticsInfo in Multivariate Anomaly detection response (#1892)
  • Fix Double ML timeout on large datasets (#1903)
  • Retry OnnxHub calls to improve test reliability (#1889)
  • Remove case matching for erased generic types (#1880)
  • Remove extraneous Foo type from Python codegen (#1867)
  • Update OpenAIEmbedding Schema to account for internalServiceType
  • Update Maven package to include correct GitHub path (#2073)

Documentation 📘

Read more