class_docstr: ImNet layer keras implementation.
    
docstr: Forward method.
  
  Args:
    x: `[batch_size, dim+in_features]` tensor, inputs to decode.
    training: bool, flag indicating training phase.
  Returns:
    x_: output through this layer.
docstr_tok: ["Forward","method",".","Args",":","x",":","`","[","batch_size",",","dim+in_features","]","`","tensor",",","inputs","to","decode",".","training",":","bool",",","flag","indicating","training","phase",".","Returns",":","x_",":","output","through","this","layer","."]
code: def call(self, x, training=False):
      """Forward method.
  
      Args:
        x: `[batch_size, dim+in_features]` tensor, inputs to decode.
        training: bool, flag indicating training phase.
      Returns:
        x_: output through this layer.
      """
      x_ = x
      for dense in self.fc[:4]:
          x_ = self.activ(dense(x_))
          x_ = tf.concat([x_, x], axis=-1)
      x_ = self.activ(self.fc4(x_))
      x_ = self.fc5(x_)
      return x_
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the ImNet obj's underlying member method code with example usage: obj.call(x, training) and returns: x_