code: def decode(
      params: Dict[str, Any],
      inputs: Array,
      decode_rng: PRNGKey,
      ctable: CTable,
  ) -> Array:
      """Decodes inputs."""
      init_decoder_input = ctable.one_hot(ctable.encode("=")[0:1])
      init_decoder_inputs = jnp.tile(
          init_decoder_input,
          (inputs.shape[0], ctable.max_output_len, 1),
      )
      model = get_model(ctable, teacher_force=False)
      _, predictions = model.apply(
          {"params": params},
          inputs,
          init_decoder_inputs,
          rngs={"lstm": decode_rng},
      )
      return predictions
  
imports: import functools
  from typing import Any, Dict, Tuple
  from absl import app
  from absl import flags
  from absl import logging
  from clu import metric_writers
  from flax import linen
  from flax.training import train_state
  import jax
  import jax.numpy
  import optax
  import models
  from input_pipeline import CharacterTable
  from input_pipeline import get_sequence_lengths
  from input_pipeline import mask_sequences
label_desc: Use image node_id 8 for calling a global function with example usage: decode(params, inputs, decode_rng, ctable) and returns: predictions