class_docstr: PatchDiscriminator architecture.
  
  Implemented as a compare_gan layer. This has the benefit that we can use
  spectral_norm from that framework.
class_docstr_tok: ["PatchDiscriminator","architecture",".","Implemented","as","a","compare_gan","layer",".","This","has","the","benefit","that","we","can","use","spectral_norm","from","that","framework","."]
docstr: Instantiate discriminator.
  
  Args:
    name: Name of the layer.
    num_filters_base: Number of base filters. will be multiplied as we
      go down in resolution.
    num_layers: Number of downscaling convolutions.
docstr_tok: ["Instantiate","discriminator",".","Args",":","name",":","Name","of","the","layer",".","num_filters_base",":","Number","of","base","filters",".","will","be","multiplied","as","we","go","down","in","resolution",".","num_layers",":","Number","of","downscaling","convolutions","."]
code: def __init__(
      self,
      name,
      num_filters_base=64,
      num_layers=3,
  ):
      """Instantiate discriminator.
  
      Args:
        name: Name of the layer.
        num_filters_base: Number of base filters. will be multiplied as we
          go down in resolution.
        num_layers: Number of downscaling convolutions.
      """
  
      super(_PatchDiscriminatorCompareGANImpl, self).__init__(
          name, batch_norm_fn=None, layer_norm=False, spectral_norm=True
      )
  
      self._num_layers = num_layers
      self._num_filters_base = num_filters_base
  
imports: import collections
  from compare_gan.architectures import abstract_arch
  from compare_gan.architectures import arch_ops
  import numpy
  import tensorflow.compat.v1
  import tensorflow_compression
  from hific.helpers import ModelMode
label_desc: Use image node_id 1 to create a new _PatchDiscriminatorCompareGANImpl object from inherited base classes: abstract_arch with example: obj = _PatchDiscriminatorCompareGANImpl(name, num_filters_base, num_layers)