Backfill issue -421 — The AI Toolchain

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The daily firehose — everything the toolchain shipped today, already filtered.

// HOW THIS ISSUE IS MADE

We read every release from the 174 tools on our watchlist at the source — GitHub and GitLab release notes, vendor release pages and changelogs, project blogs and feeds, vendor press releases, and the source code behind the tag. Bug-fix-only releases and non-product newsroom noise are dropped; what's left is summarized down to the new capability, how to try it, and any screenshots or videos the release itself published. Every entry links to the sources it was built from.

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$ tct list   # 3 tools matched

AI & LLM Tooling

◆ AI Model & Data Infrastructure

Microsoft ONNX Runtime

v1.5.2 NOTES

ONNX Runtime v1.5.2 adds trilinear sampling in Resize, flatbuffers verification for ORT format, and config keys header for Linux/Mac.

└──▷ GET THIS VERSION

$ git clone --branch v1.5.2 https://github.com/microsoft/onnxruntime.git
# already have the repo? check out this version:
$ git checkout v1.5.2

›Adds flatbuffers verifier for ORT format buffers, enabling integrity validation of serialized models.
›Adds config keys header file to Linux and Mac packages, exposing session configuration constants for native consumers.
›Supports trilinear sampling mode in the Resize operator.
›Removes the cudnn64_7.dll dependency from the GPU C# NuGet package, simplifying deployment on Windows.

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NVIDIA Triton Inference Server

v2.4.0 2 RELEASES · 2020-10-02 → 2020-10-27 NOTES STABLE

Triton 2.4.0 adds Python and DALI backends, a new Model Analyzer tool, and moves backends to separate repositories.

└──▷ GET THIS VERSION

$ git clone --branch v2.4.0 https://github.com/triton-inference-server/server.git
# already have the repo? check out this version:
$ git checkout v2.4.0

└──▷ TRY IT

Run Triton on Jetson with an explicit backend directory and TensorFlow 2.x selected, since the device requires both flags.

$ tritonserver --model-repository=/path/to/model_repo --backend-directory=/path/to/tritonserver/backends --backend-config=tensorflow,version=2

›New --backend-directory flag lets you explicitly set the backend directory path when running Triton, required on Jetson deployments.
›New --backend-config=tensorflow,version=2 argument allows selecting TensorFlow 2.x when Triton defaults to TensorFlow 1.x.
›New Python backend enables running arbitrary Python code as a model within Triton (see github.com/triton-inference-server/python_backend).
›New DALI backend enables running pre-processing and data augmentation pipelines directly within Triton (see github.com/triton-inference-server/dali_backend).
›New Model Analyzer project provides analysis and guidance for optimizing single or multiple models within Triton; initial release analyzes GPU memory usage (see github.com/triton-inference-server/model_analyzer).

+1 moreshow less

›TensorFlow, ONNX Runtime, Python, and DALI backends are now hosted in separate repositories, enabling independent versioning and distribution.

└──▷ BREAKING ON UPGRADE

!The perf_client application is renamed to perf_analyzer; any scripts or automation invoking perf_client will break.

1 more release in this issue · 2020-10-02 → 2020-10-27

v2.3.0 NOTES STABLE

Triton v2.3.0 ships the Python client as a pip package and drops the legacy custom backend SDK in favor of the new Triton backend API.

└──▷ GET THIS VERSION

$ git clone --branch v2.3.0 https://github.com/triton-inference-server/server.git
# already have the repo? check out this version:
$ git checkout v2.3.0

›Python client library is now installable as a pip package from the NVIDIA PyPI index, replacing the previous tarball-only distribution.
›The legacy custom backend API (custom.h) and its SDK are no longer shipped with Triton releases; users are directed to migrate to the new Triton backend API.

└──▷ BREAKING ON UPGRADE

!The custom backend SDK (custom.h and associated tooling) is no longer included in the Triton release package; new custom backends must use the new Triton backend API, though existing compiled legacy backends continue to work.

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Other / Uncategorized

◆ VECTOR DB RAG

Weaviate

0.22.19 NOTES

Weaviate 0.22.19 adds _certainty underscore prop to Get {} queries with explore set.

└──▷ GET THIS VERSION

$ git clone --branch 0.22.19 https://github.com/weaviate/weaviate.git
# already have the repo? check out this version:
$ git checkout 0.22.19

›Adds _certainty underscore prop to Get {} queries when the explore parameter is set, enabling certainty scores (proximity to the search query) that were previously only available on Explore {}.

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// END OF TRANSMISSION

The AI Toolchain · curated daily · October 27, 2020
Releases & features from the open-source and commercial AI tools that practitioners actually run.

The AI Toolchain — issue -421, October 27, 2020

Microsoft ONNX Runtime

NVIDIA Triton Inference Server

Weaviate