XLA Serving v0.0.13

Highlights

• 78 Elementwise Math & Bitwise Data Ops: Added C++ kernels and Python bindings (data.ops.math and data.ops.bitwise) for 78 elementwise math, bitwise, special-function, Bessel, floating-point predicate, and matmul transforms with broadcasting (#610, #611, #612, #634).
• Priority-Aware Batch Scheduling: Added priority-aware request queuing (PriorityAwareQueue, SchedulerConfig, and QueueSelectionPolicy) to the serving runtime's batch scheduler (#599, #602, #615, #619).
• Zero-Copy & Pre-Allocated Buffers: Added support for TPU premapped buffers, pinned host buffers, partial/mixed pre-allocated outputs, input buffer aliasing, and zero-copy tensorflow::Tensor host conversion (#594, #628, #639, #655, #662, #686).
• CLI History & Rollback: Added xsm-cli history and xsm-cli rollback for inspecting and reverting model configuration updates, plus full BatchOptions support in xsm-cli update (#597, #660).

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What's Changed

Serving Runtime & Performance

• Priority-aware batching: Integrate PriorityAwareQueue, SchedulerScope, QueueSelectionPolicy, and SchedulerConfig into SharedBatchScheduler and BatchRunnerOp (#599, #602, #615, #619).
• Pre-allocated & zero-copy buffers:
  • Support TPU premapped buffers in the serving runtime (#639).
  • Support pinned host buffers and partial/mixed pre-allocated outputs with load-time output name resolution (#628, #655, #662).
  • Honor exported input buffer aliasing in the AOT serving runtime (#594).
  • Add zero-copy tensorflow::Tensor to HostBuffer conversion via a type-keyed converter registry (#686).
• Model warmup improvements: Bypass the batch queue for warmup requests and record model warmup latency metrics (#673, #699, #701).
• Runtime overhead reductions: Cache transform factory lookups in TransformBase (#605), execute RunWithMapReturnOnWorker as a single worker-pool task (#683), and drop unused MLIR dialects from StableHloLoader (#663).
• Self-contained TPU serving image: Bundle libtpu.so directly into the TPU serving container (#640).
• TensorFlow SavedModel interop: Add bundle detection and HostBuffer conversion in TfSavedModelFunctionRunnerOp (#547, #629).

Data Processing (xla_serving_data)

• Math & bitwise transforms: Add 78 elementwise math, bitwise, special-function, Bessel, predicate, and matmul C++ transforms and Python bindings (#610, #611, #612).
• Dynamic shapes: Add PartialShape to represent shapes with unknown dimensions in data/processor and HostBufferSpec (#681, #688).
• CPU embeddings: Unify CPU embedding method signatures with structured input configs (#595, #633).
• Transform registry: Simplify transform deserializer registration with SetDeserializerWithDetail and fall back to std::type_info::name() matching across shared libraries (#635, #649, #664, #665).

CLI (xsm-cli)

• Configuration history & rollback: Add xsm-cli history and xsm-cli rollback commands to inspect and revert model configuration updates (#597).
• Batching configuration: Support full BatchOptions flags in xsm-cli update (#660).
• Model inspection: Improve xsm-cli show and xsm-cli show --details output for CompositeProcessor functions (#607).

Examples & Benchmarks

• DLRM benchmark: Add reproducible DLRM serving benchmark and Cloud TPU v6e results (#606).
• Gemma 3 example: Add Gemma 3 (keras_hub) export example and prediction client by @gaurides (#601).
• Math preprocessor example: Add examples/math_preprocessor demonstrating data.ops.math and data.ops.bitwise (#634).

New Contributors

• @gaurides made their first contribution in #601

Full Changelog: v0.0.12...v0.0.13