code: def upper_triangular_mask(F, d):
      mask = F.zeros_like(F.eye(d))
      for k in range(d - 1):
          mask = mask + F.eye(d, d, k + 1)
      return mask * LARGE_NEGATIVE_VALUE
  
imports: from typing import List, Optional, Tuple
  import mxnet
  from gluonts.core.component import validated
  from gluonts.itertools import prod
  from gluonts.mx import Tensor
  from gluonts.mx.block.feature import FeatureEmbedder
  from gluonts.mx.block.scaler import MeanScaler, NOPScaler
  from gluonts.mx.distribution import DistributionOutput
  from gluonts.mx.util import weighted_average
  from .trans_decoder import TransformerDecoder
  from .trans_encoder import TransformerEncoder
label_desc: Use image node_id 4 for calling the TransformerNetwork obj's underlying member method code with example usage: obj.upper_triangular_mask(F, d) and returns: unknown