code: def __init__(self, d_model, embed_type="timeF", freq="h"):
      super(TimeFeatureEmbedding, self).__init__()
  
      freq_map = {
          "h": 4,
          "t": 5,
          "s": 6,
          "m": 1,
          "a": 1,
          "w": 2,
          "d": 3,
          "b": 3,
      }
      d_inp = freq_map[freq]
      self.embed = nn.Linear(d_inp, d_model, bias=False)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.utils import weight_norm
  import math
label_desc: Use image node_id 1 to create a new TimeFeatureEmbedding object from inherited base classes: nn with example: obj = TimeFeatureEmbedding(d_model, embed_type, freq)