Swachhand worked on enhancing device memory management for TPU v4i across the Intel-tensorflow/tensorflow and Intel-tensorflow/xla repositories. Using C++ and backend development skills, Swachhand implemented a feature that treats TPU v4i as an alias of TPU v4 lite within the GetDeviceMemoryInBytes function, standardizing memory allocation and reporting. This approach ensures that memory size calculations for TPU v4i match those of TPU v4 lite, improving allocation accuracy and device observability for newer TPU configurations. Swachhand also addressed a related bug, further refining device management and reducing memory-related risks for deployments relying on these updated TensorFlow components.