[question] Pad time-dimension to a multiple
For Conformer setups, does NeMo support / recommend padding batches after frontend to a certain multiple, e.g. so that after Conformer input batch time dimension is e.g. a multiple of 32 (which may suit best cudnn / gemm kernels for fp16/TensorCores)

Having batches of a few fixed shapes also benefits pytorch allocator performance and cudnn benchmarking / cache