class_docstr: Fused operation which performs following three operations in sequence
  
      1.  Scale the tensor.
      2.  Apply upper triangular mask (typically used in gpt models).
      3.  Perform softmax.
code: def forward(ctx, inputs, scale):
      global scaled_upper_triang_masked_softmax
      if scaled_upper_triang_masked_softmax:
          scaled_upper_triang_masked_softmax = (
              ScaledUpperTrainglemaskedSoftmaxBuilder().load()
          )
  
      scale_t = torch.tensor([scale])
      softmax_results = scaled_upper_triang_masked_softmax.forward(
          inputs, scale_t[0]
      )
  
      ctx.save_for_backward(softmax_results, scale_t)
      return softmax_results
  
imports: import enum
  import torch
  import torch.nn
  from colossalai.kernel.op_builder.scaled_masked_softmax import ScaledMaskedSoftmaxBuilder
  from colossalai.kernel.op_builder.scaled_upper_triangle_masked_softmax import ScaledUpperTrainglemaskedSoftmaxBuilder
label_desc: Use image node_id 1 for calling the ScaledUpperTriangMaskedSoftmax obj's underlying member method code with example usage: obj.forward(ctx, inputs, scale) and returns: softmax_results