class_docstr: A two-layer Feed-Forward-Network.
class_docstr_tok: ["A","two-layer","Feed-Forward-Network","."]
docstr: The implementation of PositionwiseFeedForward.
  Args:
    inputs: [batch_size, seq_x_len, d_model]
  Return:
    ffn: [batch_size, seq_x_len, d_model]
docstr_tok: ["The","implementation","of","PositionwiseFeedForward",".","Args",":","inputs",":","[","batch_size",",","seq_x_len",",","d_model","]","Return",":","ffn",":","[","batch_size",",","seq_x_len",",","d_model","]"]
code: def call(self, inputs, training=None, mask=None):
      """
      The implementation of PositionwiseFeedForward.
      Args:
        inputs: [batch_size, seq_x_len, d_model]
      Return:
        ffn: [batch_size, seq_x_len, d_model]
      """
      ffn = self.dense2(self.dense1(inputs))
      return ffn
  
file_path: delta/delta/layers/sub_tf.py
imports: from absl import logging
  import delta.compat
  import numpy
  from delta.layers.base_layer import Layer
  from delta.layers.utils_tf import shape_list
label_desc: Use image node_id 2 for calling the PositionwiseFeedForward obj's underlying member method code with example usage: obj.call(inputs, training, mask) and returns: ffn