class_docstr: Provides an encoder for integer node features.
  
  Args:
      emb_dim (int): The output embedding dimension.
      num_classes (int): The number of classes/integers.
  
  Example:
      >>> encoder = IntegerFeatureEncoder(emb_dim=16, num_classes=10)
      >>> batch = torch.randint(0, 10, (10, 2))
      >>> encoder(batch).size()
      torch.Size([10, 16])
code: def forward(self, batch):
      # Encode just the first dimension if more exist
      batch.x = self.encoder(batch.x[:, 0])
  
      return batch
  
file_path: pytorch_geometric/torch_geometric/graphgym/models/encoder.py
imports: import torch
  from torch_geometric.graphgym.register import register_edge_encoder, register_node_encoder
label_desc: Use image node_id 2 for calling the IntegerFeatureEncoder obj's underlying member method code with example usage: obj.forward(batch) and returns: batch