code: def spec_rnnt():
      from extra.models.rnnt import RNNT
  
      mdl = RNNT()
      # mdl.load_from_pretrained()
      x = Tensor.randn(220, 1, 240)
      y = Tensor.randn(1, 220)
      test_model(mdl, x, y)
  
file_path: tinygrad/examples/mlperf/model_spec.py
imports: from tinygrad import Tensor, GlobalCounters
  from tinygrad.helpers import getenv
  import numpy
label_desc: Use image node_id 5 for calling a global function with example usage: spec_rnnt() without return types