code: def __init__(
      self,
      input_dim,
      transform_activation=F.relu,
      gate_activation=F.softmax,
      # Srivastava et al. (2015) recommend initializing bT to a negative
      # value, in order to militate the initial behavior towards carry.
      # We initialized bT to a small interval around −2
      gate_bias=-2,
  ):
      super().__init__()
      self.highway_transform_activation = transform_activation
      self.highway_gate_activation = gate_activation
      self.highway_transform = nn.Linear(input_dim, input_dim)
      self.highway_gate = nn.Linear(input_dim, input_dim)
      self.highway_gate.bias.data.fill_(gate_bias)
  
imports: import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from pytorch_translate import common_layers, rnn, utils
  from pytorch_translate.data.dictionary import TAGS
  from torch.nn.utils.rnn import pack_padded_sequence
label_desc: Use image node_id 1 to create a new HighwayLayer object from inherited base classes: nn with example: obj = HighwayLayer(input_dim, transform_activation, gate_activation, gate_bias)