class_docstr: Dense layer.
class_docstr_tok: ["Dense","layer","."]
code: def _call(self, inputs):
      x = inputs
  
      x = tf.nn.dropout(x, 1 - self.dropout)
  
      # transform
      output = tf.matmul(x, self.vars["weights"])
  
      # bias
      if self.bias:
          output += self.vars["bias"]
  
      return self.act(output)
  
file_path: GraphSAGE/graphsage/layers.py
imports: from __future__ import division
  from __future__ import print_function
  import tensorflow
  from graphsage.inits import zeros
label_desc: Use image node_id 2 for calling the Dense obj's underlying member method code with example usage: obj._call(inputs) and returns: self