code: def __call__(self, cfg: Config, x, *, rngs: nnx.Rngs):
      # TODO: handle right-shifting for training: here or in train loop.
      # TODO: handle general mask routing.
      x = self.embed.astype(cfg.dtype)[x]
  
      if cfg.scanned:
          assert isinstance(self.layers, DecoderBlock)
  
          state, static = self.layers.split()
          rngs, rngsdef = rngs.fork()
          dropout_key = jax.random.split(rngs["dropout"], cfg.layers)
  
          def scan_fn(x, s: tp.Tuple[jax.Array, nnx.State]):
              dropout_key, state = s
              rngs = rngsdef.merge({"dropout": dropout_key})
              y, (state, _) = static.apply(state)(cfg, x, rngs=rngs)
              return y, state
  
          x, state = jax.lax.scan(
              scan_fn,
              x,
              (dropout_key, state),
          )
          self.layers.update(state)
      else:
          assert isinstance(self.layers, nnx.Sequence)
          for decoder_block in self.layers:
              x = decoder_block(cfg, x, rngs=rngs)
  
      x = jnp.einsum("bse,ev->bsv", x, self.unembed)
      return x
  
imports: import dataclasses
  import typing
  import jax
  import jax.numpy
  import numpy
  from jax.sharding import PartitionSpec
  from flax.experimental import nnx
label_desc: Use image node_id 2 for calling the Decoder obj's underlying member method code with example usage: obj.__call__(cfg, x) and returns: x, y,  state