code: def __init__(self, cfg, name=None):
      super(PositionwiseFeedForwardLayer, self).__init__()
      initializer = nn.initializer.TruncatedNormal(
          std=cfg["initializer_range"]
      )
      d_model = cfg["hidden_size"]
      d_ffn = cfg.get("intermediate_size", 4 * d_model)
      self.act = ACT_DICT[cfg["hidden_act"]]()
      self.i = _build_linear(
          d_model,
          d_ffn,
          append_name(name, "fc_0"),
          initializer,
      )
      self.o = _build_linear(
          d_ffn, d_model, append_name(name, "fc_1"), initializer
      )
      prob = cfg.get("intermediate_dropout_prob", 0.0)
      self.dropout = nn.Dropout(p=prob)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import json
  import logging
  import math
  import six
  import numpy
  import paddle
  from paddle import nn
  from paddle.nn import functional
  from disco_diffusion_ernievil_base.vit_b_16x.ernievil2.transformers.file_utils import _fetch_from_remote, add_docstring
label_desc: Use image node_id 1 to create a new PositionwiseFeedForwardLayer object from inherited base classes: nn with example: obj = PositionwiseFeedForwardLayer(cfg, name)