NarrowEmbedding.Config(
                channels_in=2,
                channels_out=4,
                dtype=torch.bfloat16,
                inner=Embedding.Config(
                        channels_in=2,
                        channels_out=4,
                        padding_idx=None,
                        device=None,
                        dtype=None,
                        shard=None,
                        depth_index=(),
                        init_weight=functools.partial(<function priml.model.init.truncated_normal at 0xdefacedeface>, std=0.02)
                )
        )
