docstr: Generates input examples for tracing etc.
  Returns:
      A tuple of input examples.
docstr_tok: ["Generates","input","examples","for","tracing","etc",".","Returns",":","A","tuple","of","input","examples","."]
code: def input_example(self, max_batch=1, max_dim=256):
      """
      Generates input examples for tracing etc.
      Returns:
          A tuple of input examples.
      """
      sample = next(self.parameters())
      input_ids = torch.randint(
          low=0,
          high=2048,
          size=(max_batch, max_dim, 1024),
          device=sample.device,
      )
      encoder_mask = torch.randint(
          low=0, high=1, size=(max_batch, max_dim), device=sample.device
      )
      return tuple([input_ids, encoder_mask, input_ids, encoder_mask])
  
file_path: NeMo/nemo/collections/asr/modules/transformer/transformer_decoders.py
imports: import copy
  import torch
  import torch.nn
  from nemo.collections.asr.modules.transformer.transformer_modules import MultiHeadAttention, PositionWiseFF
  from nemo.collections.common.parts import form_attention_mask
label_desc: Use image node_id 4 for calling the TransformerDecoder obj's underlying member method code with example usage: obj.input_example(max_batch, max_dim) and returns: tuple