code: def __init__(
      self, c_in, d_model, embed_type="fixed", freq="h", dropout=0.1
  ):
      super(DataEmbedding_wo_pos, self).__init__()
  
      self.value_embedding = TokenEmbedding(c_in=c_in, d_model=d_model)
      self.position_embedding = PositionalEmbedding(d_model=d_model)
      self.temporal_embedding = (
          TemporalEmbedding(
              d_model=d_model, embed_type=embed_type, freq=freq
          )
          if embed_type != "timeF"
          else TimeFeatureEmbedding(
              d_model=d_model, embed_type=embed_type, freq=freq
          )
      )
      self.dropout = nn.Dropout(p=dropout)
  
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 DataEmbedding_wo_pos object from inherited base classes: nn with example: obj = DataEmbedding_wo_pos(c_in, d_model, embed_type, freq, dropout)