Month: 2025-10 — Focused on stabilizing performance, fixing benchmarking/configuration regressions, and tightening CI feedback loops across tt-xla and tt-forge. Delivered targeted fixes and configuration improvements that restore expected performance, improve benchmarking fidelity, and accelerate validation cycles.

May 2025 summary for tenstorrent/tt-forge-fe focused on delivering automated validation capabilities for PaddleOCR and strengthening the forge test framework. Key deliverable: PaddleOCR Nightly Validation Tests added to the forge suite, covering detection, recognition, and end-to-end scenarios. Implemented necessary dependencies, image and character-set fetching utilities, and new test files to enable robust nightly validation. The work is traceable to commit 20747da70ce9058906c043c4f47c2056ab5617b9 (PR #1823). No major bugs fixed this month; emphasis was on feature delivery and test automation. This enhances validation reliability, reduces manual QA effort, and speeds feedback for PaddleOCR models.

Month: 2025-04 — This month focused on expanding testing coverage for Paddle-based models and stabilizing dependencies to enable broader ML capabilities. Key features delivered include nightly testing infrastructure for Paddle Vision and PaddleNLP models, and dependency upgrades to streamline datasets, packaging, and Paddle libraries. No major bug fixes were needed this month as the work prioritized test infrastructure and maintainability.

March 2025 highlights: Delivered cross-framework PaddlePaddle support by adapting the PyTorch compilation flow, enabling Paddle module wrapping, Paddle-specific parameter parsing and verification, and targeted testing. Also refactored PyTorch-Paddle tensor conversion utilities, improved type hints and naming, and extended tests to ensure correctness. Resolved a critical PaddlePaddle frontend bug in the tt-tvm converter related to padding index handling in lookup_table by ensuring proper weight conversion through NumPy array materialization and back to TVM NDArrays. These efforts enhanced interoperability, correctness, and reliability across two major repos with measurable business value.