class_docstr: Input:
      x: default node feature. the first and second column represents node type and node attributes.
      depth: The depth of the node in the AST.
  
  Output:
      emb_dim-dimensional vector
code: def forward(self, x, depth):
      depth[depth > self.max_depth] = self.max_depth
      return (
          self.type_encoder(x[:, 0])
          + self.attribute_encoder(x[:, 1])
          + self.depth_encoder(depth)
      )
  
file_path: ogb/examples/graphproppred/code2/utils.py
imports: import torch
  from collections import Counter
  import numpy
  import torch
label_desc: Use image node_id 2 for calling the ASTNodeEncoder obj's underlying member method code with example usage: obj.forward(x, depth) and returns: unknown