code: def __init__(self, config, name=None, init_scale=1.0):
      super().__init__(name=name)
      self.dim = config["d_model"]
      self.n_head = config["n_heads"]
      self.d_head = config["d_head"]
      self.d_rotary = config["pe_rotary_dims"]
      self.mp_num = thread_resources.env.shape["mp"]
  
      self.norm = hk.LayerNorm(-1, True, True)
      self.input_proj = hk.Linear(
          self.d_head * self.n_head * 3 + self.dim * 8
      )
      self.output_proj = hk.Linear(
          self.dim,
          w_init=hk.initializers.TruncatedNormal(
              stddev=init_scale / jnp.sqrt(self.dim)
          ),
      )
  
imports: import haiku
  import jax
  import jax.numpy
  import numpy
  from einops import rearrange, repeat
  from mesh_transformer.util import f_psum, g_psum, maybe_shard, head_print
  from jax.experimental import PartitionSpec
  from jax.experimental.maps import thread_resources
label_desc: Use image node_id 1 to create a new TransformerLayerShardV2 object from inherited base classes: hk with example: obj = TransformerLayerShardV2(config, name, init_scale)