January 2026 monthly work summary for ROCm/tensorflow-upstream focused on delivering robust legalization pipelines and improving build stability. Key features delivered and bugs fixed were coordinated with test coverage to ensure correctness and downstream reliability. Impact highlights include preserving 64-bit constants during TFLite to TOSA legalization, preventing truncation to i48 and ensuring correct tensor operations and legalization integrity. This was complemented by MLIR TOSA build stability improvements through corrected include paths for the Affine pass, eliminating related compilation failures across MLIR TOSA components. Tests were updated to reflect 64-bit constant handling and include-path changes, strengthening validation and regression coverage. Technologies/skills demonstrated include MLIR TOSA, TFLite-to-TOSA legalization flows, 64-bit constant handling, and build-system maintenance across ROCm/tensorflow-upstream. Business value is increased correctness, stability, and faster feedback in CI, enabling more reliable downstream usage and reduced risk in legalization paths.

Monthly summary for ROCm/tensorflow-upstream - December 2025: Delivered two key TOSA-related updates that improve production readiness, compatibility, and flexibility. 1) TOSA pass API cleanup and metadata macro enhancements: removed deprecated GEN_PASS_CLASSES API usage and added new macros to strip function/module metadata, improving compatibility and maintainability of TOSA transformations. 2) Dynamic batch size support for FullyConnected in TOSA: enables dynamic batch processing, updates legalization to accommodate dynamic shapes, and includes tests to validate dynamic batch handling, boosting robustness for varying input sizes. Overall impact: Reduced technical debt in pass infrastructure, expanded runtime flexibility for inference workloads, and enhanced test coverage for dynamic shapes. Skills demonstrated include MLIR/TOSA pass engineering, macro-driven metadata handling, dynamic shape legalization, and end-to-end test validation.