code: def inputs(self):
      return [
          tf.TensorSpec(
              [None, None, FEATUREDIM], tf.float32, "feat"
          ),  # bxmaxseqx39
          tf.TensorSpec(
              [None, None], tf.int64, "labelidx"
          ),  # label is b x maxlen, sparse
          tf.TensorSpec([None], tf.int32, "labelvalue"),
          tf.TensorSpec([None], tf.int64, "labelshape"),
          tf.TensorSpec([None], tf.int32, "seqlen"),  # b
      ]
  
file_path: tensorpack/examples/CTC-TIMIT/train-timit.py
imports: import argparse
  import os
  import tensorflow
  from tensorpack import *
  from tensorpack.tfutils.gradproc import GlobalNormClip, SummaryGradient
  from timitdata import TIMITBatch
label_desc: Use image node_id 1 for calling the Model obj's underlying member method code with example usage: obj.inputs() and returns: list