April 2026 monthly summary for pytorch/pytorch: Delivered provenance-aware FxGraphCache key to improve tlparse accuracy by making provenance_tracking_level a first-class part of the FxGraphHashDetails. This prevents provenance-missing cache entries from serving provenance-required requests and eliminates 0-byte provenance files in tlparse reports. Implemented tests validating that provenance_tracking_level affects cache behavior and hash generation. Result: more reliable tlparse reporting, fewer cache-related regressions, and improved correctness of build-time provenance data. Technologies: Python, FxGraphCache, cache hashing, provenance tracking, and test automation. Collaboration: PR 179728, commit 018bf8672b85241e93af4d85c2f6f702fbfedc7a, reviewed by yushangdi.

February 2026 focused on improving metric accuracy and training stability for TorchRec under variable batch sizes. Delivered TowerQPSMetric enhancement to use batch_size_stages, fixed a bug where warmup used the final batch size, and ensured batch_size_stages propagate to all RecMetrics. Result: reduced runtime errors and more reliable throughput metrics. Changes implemented in bf0892c250c8e07ce91fe79eb49a63453bc6b896, merged via PR #3817 (D93789002).