code: def decode(self, x, x_lens):
      logits, logit_lens = self.encoder(x, x_lens)
      outputs = []
      for b in range(logits.shape[0]):
          inseq = logits[b, :, :].unsqueeze(1)
          logit_len = logit_lens[b]
          seq = self._greedy_decode(
              inseq, int(np.ceil(logit_len.numpy()).item())
          )
          outputs.append(seq)
      return outputs
  
imports: from tinygrad.tensor import Tensor
  from tinygrad.jit import TinyJit
  from tinygrad.nn import Linear, Embedding
  from tinygrad.helpers import fetch
  import numpy
  from pathlib import Path
label_desc: Use image node_id 3 for calling the RNNT obj's underlying member method code with example usage: obj.decode(x, x_lens) and returns: outputs