class_docstr: Point-wise feed-forward layer is implemented by two dense layers.
  
  Args:
      input_tensor (torch.Tensor): the input of the point-wise feed-forward layer
  
  Returns:
      hidden_states (torch.Tensor): the output of the point-wise feed-forward layer
class_docstr_tok: ["Point-wise","feed-forward","layer","is","implemented","by","two","dense","layers",".","Args",":","input_tensor","(","torch.Tensor",")",":","the","input","of","the","point-wise","feed-forward","layer","Returns",":","hidden_states","(","torch.Tensor",")",":","the","output","of","the","point-wise","feed-forward","layer"]
code: def get_hidden_act(self, act):
      ACT2FN = {
          "gelu": self.gelu,
          "relu": fn.relu,
          "swish": self.swish,
          "tanh": torch.tanh,
          "sigmoid": torch.sigmoid,
      }
      return ACT2FN[act]
  
imports: import random
  import numpy
  import torch
  from torch import nn
  import torch.nn.functional
  import math
  import torch.nn.functional
  from recbole.model.abstract_recommender import SequentialRecommender
  from recbole.model.loss import BPRLoss
  from recbole.data.interaction import Interaction
label_desc: Use image node_id 2 for calling the FeedForward obj's underlying member method code with example usage: obj.get_hidden_act(act) and returns: ACT2FN