Because TensorFlow tensors are immutable and gradients do not flow through variable assignments, the framework does not provide an explicit way to run individual operations in-place on standard tensors. Instead, TensorFlow provides the @tf.function decorator to wrap computations inside a compiled and optimized graph. This allows the framework to automatically prune unused values and reuse prior memory allocations that are no longer needed, thereby minimizing memory overhead.