class_docstr: Base class for TIMIT problems.
class_docstr_tok: ["Base","class","for","TIMIT","problems","."]
code: def preprocess_example(self, example, mode, hparams):
      example = super(AudioTimitProblem, self).preprocess_example(
          example, mode, hparams
      )
      # Reshape audio to proper shape
      sample_count = tf.to_int32(example.pop("audio/sample_count"))
      sample_width = tf.to_int32(example.pop("audio/sample_width"))
      channel_count = 1
      example["inputs"] = tf.reshape(
          example["inputs"], [sample_count, sample_width, channel_count]
      )
      return example
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the AudioTimitProblem obj's underlying member method code with example usage: obj.preprocess_example(example, mode, hparams) and returns: example