class_docstr: Do Delta_delta to features.
docstr: Caculate delta of feats.
  :param feat: a float tensor of size (num_frames, dim_feat).
  :param order: an int.
  :param window: an int.
  :return: A tensor with shape (num_frames, dim_feats, order + 1),
      containing delta of features of every frame in speech.
docstr_tok: ["Caculate","delta","of","feats",".",":","param","feat",":","a","float","tensor","of","size","(","num_frames",",","dim_feat",")",".",":","param","order",":","an","int",".",":","param","window",":","an","int",".",":","return",":","A","tensor","with","shape","(","num_frames",",","dim_feats",",","order","+","1",")",",","containing","delta","of","features","of","every","frame","in","speech","."]
code: def call(self, feat, order, window):
      """
      Caculate delta of feats.
      :param feat: a float tensor of size (num_frames, dim_feat).
      :param order: an int.
      :param window: an int.
      :return: A tensor with shape (num_frames, dim_feats, order + 1),
          containing delta of features of every frame in speech.
      """
  
      p = self.config
      with tf.name_scope("delta_delta"):
          delta_delta = py_x_ops.delta_delta(feat, order, window)
  
      n_frame, n_feats = feat.get_shape().as_list()
      delta_delta = tf.reshape(
          delta_delta, (n_frame, n_feats, order + 1)
      )
  
      return delta_delta
  
file_path: delta/delta/data/frontend/delta_delta.py
imports: import delta.compat
  from core.ops import py_x_ops
  from delta.utils.hparam import HParams
  from delta.data.frontend.base_frontend import BaseFrontend
label_desc: Use image node_id 3 for calling the DeltaDelta obj's underlying member method code with example usage: obj.call(feat, order, window) and returns: delta_delta