code: def block(x, filters, skipfilters, dilation, scope=None):
      x = tf.pad(x, [[0, 0], [dilation, 0], [0, 0]])
      f = conv1d(x, filters, 2, rate=dilation, scope="filter")
      g = conv1d(x, filters, 2, rate=dilation, scope="gate")
      o = tanh(f, name="filter/tanh") * sigmoid(g, name="gate/sigmoid")
      d = conv1d(o, filters, 1, scope="dense")
      s = conv1d(o, skipfilters, 1, scope="skip")
      return x[:, dilation:] + d, s
  
file_path: tensornets/tensornets/wavenets.py
imports: from __future__ import absolute_import
  from __future__ import division
  import tensorflow
  from .layers import conv1d
  from .ops import *
  from .utils import pad_info
  from .utils import set_args
  from .utils import var_scope
label_desc: Use image node_id 2 for calling a global function with example usage: block(x, filters, skipfilters, dilation, scope) and returns: unknown,  s