class_docstr: The atom Encoder used in OGB molecule dataset.
  
  Args:
      emb_dim (int): Output embedding dimension
      num_classes: None
class_docstr_tok: ["The","atom","Encoder","used","in","OGB","molecule","dataset",".","Args",":","emb_dim","(","int",")",":","Output","embedding","dimension","num_classes",":","None"]
code: def forward(self, batch):
      encoded_features = 0
      for i in range(batch.node_feature.shape[1]):
          encoded_features += self.atom_embedding_list[i](
              batch.node_feature[:, i]
          )
      batch.node_feature = encoded_features
      return batch
  
file_path: GraphGym/graphgym/models/feature_encoder.py
imports: import torch
  from ogb.utils.features import get_atom_feature_dims, get_bond_feature_dims
  import graphgym.register
label_desc: Use image node_id 2 for calling the AtomEncoder obj's underlying member method code with example usage: obj.forward(batch) and returns: batch