Requirements

RedisAI v1.0.2 requires:

  • Minimum Redis compatibility version (database): 5.0.7
  • Minimum Redis Enterprise Software version (cluster): 5.4.11

v1.0.2 (October 2020)

This is a maintenance release for version 1.0.

Headlines:

This release improves overall stability and provides fixes for issues found after the previous release.

Details:

  • Minor updates:

    • #383 Enable AI.SCRIPTRUN inside AI.DAGRUN
    • #395 Add support for variadic arguments to AI.SCRIPTRUN
    • #400 Low level API additions for use in other modules (e.g. RedisGears)
    • #396 Add relevant RedisAI config entries to the Redis INFO output. Helpful for standard monitoring systems

  • Bug Fixes:

    • #403 Atomic ref count
    • #406 Avoid splitting outputs in batches when nbatches == 1
    • #438 Fixed flagged as “getkeys-api” during the registration (AI.DAGRUN, AI.DAGRUN_RO, AI.MODELRUN, AI.SCRIPTRUN)
    • #449 Safely add to arrays
    • #443 Segfault for AI.DAGRUN + AI.TENSORSET

v1.0.1 (July 2020)

This is a maintenance release for version 1.0.

Headlines:

  • This release improves overall stability and provides fixes for issues found after the previous release.

Details:

  • Bug Fixes:

    • 7f87f85 Allow inconsistent zero batch outputs.
    • #385,#382 AI.SCRIPTRUN results were being replicated twice.
    • #384 AI.MODELGET to return inputs, outputs, batchsize, and minbatchsize.
    • #412 Several memory leaks.

v1.0.0 (May 2020)

Supported Backends:

  • TensorFlow Lite 2.0
  • TensorFlow 1.15.0
  • PyTorch 1.5
  • ONXXRuntime 1.2.0

New features:

  • #241, #270 auto-batching support. Requests from multiple clients can be automatically and transparently batched in a single request for increased CPU/GPU efficiency during serving.
  • #322 Add AI.DAGRUN. With the new AI.DAGRUN (DAG as in direct acycilc graph) command we support the prescription of combinations of other AI.* commands in a single execution pass, where intermediate keys are never materialised to Redis.
  • #334 Add AI.DAGRUN_RO command, a read-only variant of AI.DAGRUN
  • #338 AI.MODELSET Added the possibility to provide a model in chunks.
  • #332 Standardized GET methods (TENSORGET,MODELGET,SCRIPTGET) replies (breaking change for clients)
  • #331 Cache model blobs for faster serialization and thread-safety.

Minor Enhancements:

  • #289 Memory access and leak fixes.
  • #319 Documentation improvements.

Build Enhancements:

  • #299 Coverage info.
  • #273 Enable running valgrind/callgrind on test platform
  • #277, #296 tests extension and refactoring per backend.