models/bls2017.py [72:88]:
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        activation=None))


class SynthesisTransform(tf.keras.Sequential):
  """The synthesis transform."""

  def __init__(self, num_filters):
    super().__init__(name="synthesis")
    self.add(tfc.SignalConv2D(
        num_filters, (5, 5), name="layer_0", corr=False, strides_up=2,
        padding="same_zeros", use_bias=True,
        activation=tfc.GDN(name="igdn_0", inverse=True)))
    self.add(tfc.SignalConv2D(
        num_filters, (5, 5), name="layer_1", corr=False, strides_up=2,
        padding="same_zeros", use_bias=True,
        activation=tfc.GDN(name="igdn_1", inverse=True)))
    self.add(tfc.SignalConv2D(
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models/bmshj2018.py [74:90]:
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        activation=None))


class SynthesisTransform(tf.keras.Sequential):
  """The synthesis transform."""

  def __init__(self, num_filters):
    super().__init__(name="synthesis")
    self.add(tfc.SignalConv2D(
        num_filters, (5, 5), name="layer_0", corr=False, strides_up=2,
        padding="same_zeros", use_bias=True,
        activation=tfc.GDN(name="igdn_0", inverse=True)))
    self.add(tfc.SignalConv2D(
        num_filters, (5, 5), name="layer_1", corr=False, strides_up=2,
        padding="same_zeros", use_bias=True,
        activation=tfc.GDN(name="igdn_1", inverse=True)))
    self.add(tfc.SignalConv2D(
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