code: def __init__(
      self,
      n_aggregators,
      n_filters,
      n_propagate,
      simplified=False,
      collapse=None,
      input_format="xn",
      output_activation="tanh",
      mean_by_nvert=False,
      quantize_transforms=False,
      total_bits=None,
      int_bits=None,
      **kwargs,
  ):
      super().__init__(**kwargs)
  
      self._simplified = simplified
      self._output_activation = output_activation
      self._quantize_transforms = quantize_transforms
      self._total_bits = total_bits
      self._int_bits = int_bits
      self._setup_aux_params(collapse, input_format, mean_by_nvert)
      self._setup_transforms(n_aggregators, n_filters, n_propagate)
  
imports: import tensorflow.keras
  from qkeras import QActivation, QDense, ternary
label_desc: Use image node_id 1 to create a new GarNet object from inherited base classes: keras.layers with example: obj = GarNet(n_aggregators, n_filters, n_propagate, simplified, collapse, input_format, output_activation, mean_by_nvert, quantize_transforms, total_bits, int_bits)