code: def _pred_joint(self, logit, label, hc, mask):
      g, hc = self.prediction(label, hc, mask)
      j = self.joint(logit, g)[0]
      j = j.pad(((0, 1), (0, 1), (0, 0)))
      out = j.cat(hc, dim=2)
      return out.realize()
  
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 5 for calling the RNNT obj's underlying member method code with example usage: obj._pred_joint(logit, label, hc, mask) and returns: out