class_docstr: A class to normalize specgrams for each freq bin, channel.
class_docstr_tok: ["A","class","to","normalize","specgrams","for","each","freq","bin",",","channel","."]
code: def compute(self, data_np):
      # data_np: [N, time, freq, channels]
      normalizer = []
      for f in range(data_np.shape[2]):
          m_a, m_b = _range_normalizer(
              data_np[:, :, f, 0], self._margin
          )
          p_a, p_b = _range_normalizer(
              data_np[:, :, f, 1], self._margin
          )
          normalizer.append([m_a, m_b, p_a, p_b])
      return np.asarray(normalizer)
  
imports: import io
  import os
  from absl import logging
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the SpecgramsFreqNormalizer obj's underlying member method code with example usage: obj.compute(data_np) and returns: np