code: def forward(self, x, encoder_padding_mask):
      seq_len, _, _ = x.size()
      attn_mask = x.new_ones([seq_len, seq_len]).triu(1)
      attn_mask = attn_mask.masked_fill(attn_mask.bool(), float("-inf"))
      return super().forward(x, encoder_padding_mask, attn_mask)
  
file_path: fairseq/examples/simultaneous_translation/modules/monotonic_transformer_layer.py
imports: from fairseq.modules import TransformerDecoderLayer, TransformerEncoderLayer
  from .None import build_monotonic_attention
  from typing import Dict, Optional, List
  from torch import Tensor
  import torch
label_desc: Use image node_id 1 for calling the TransformerMonotonicEncoderLayer obj's underlying member method code with example usage: obj.forward(x, encoder_padding_mask) and returns: super