Sam Banerjee developed comprehensive support for XFE custom operations within the Xilinx/onnx-mlir repository, focusing on both the dialect and operational layers for neural network integration. Leveraging C++ and Python, Sam implemented shape inference, verification logic, and NHWC adaptation passes to ensure robust operation handling. The work included YAML-based schema and code generation utilities, along with updates to build systems and integration layers for seamless adoption. Extensive documentation and onboarding materials were created to guide users and maintainers. Test coverage was expanded with new utilities and shape inference tests, reflecting a thorough and maintainable approach to custom op integration.