class_docstr: Combines encoder_embedding with the encoder component
class_docstr_tok: ["Combines","encoder_embedding","with","the","encoder","component"]
code: def input_example(self, max_batch=1, max_dim=30000, seq_len=6):
      seq_len = random.randint(0, 128)
      return (
          torch.randint(0, max_dim, (max_batch, seq_len)).to(
              self.device
          ),
          torch.ones((max_batch, seq_len), dtype=int).to(self.device),
      )
  
imports: import random
  from typing import Dict, List, Optional
  import torch
  import torch.nn.functional
  from nemo.collections.nlp.modules.common.megatron.utils import build_position_ids
  from nemo.core.classes.exportable import Exportable
  from nemo.core.neural_types import ChannelType, EncodedRepresentation, MaskType, NeuralType
label_desc: Use image node_id 5 for calling the EncEmb obj's underlying member method code with example usage: obj.input_example(max_batch, max_dim, seq_len) and returns: torch,  torch