class_docstr: A standard multi-layer perceptron 
class_docstr_tok: ["A","standard","multi-layer","perceptron"]
code: def _build(self):
      self.layers.append(
          layers.Dense(
              input_dim=self.input_dim,
              output_dim=self.dims[1],
              act=tf.nn.relu,
              dropout=self.placeholders["dropout"],
              sparse_inputs=False,
              logging=self.logging,
          )
      )
  
      self.layers.append(
          layers.Dense(
              input_dim=self.dims[1],
              output_dim=self.output_dim,
              act=lambda x: x,
              dropout=self.placeholders["dropout"],
              logging=self.logging,
          )
      )
  
imports: from collections import namedtuple
  import tensorflow
  import math
  import graphsage.layers
  import graphsage.metrics
  from .prediction import BipartiteEdgePredLayer
  from .aggregators import MeanAggregator, MaxPoolingAggregator, MeanPoolingAggregator, SeqAggregator, GCNAggregator
label_desc: Use image node_id 4 for calling the MLP obj's underlying member method code with example usage: obj._build() without return types