class_docstr: fused operation: scaling + mask + softmax
  
  Arguments:
      input_in_fp16: flag to indicate if input in fp16 data format.
      input_in_bf16: flag to indicate if input in bf16 data format.
      attn_mask_type: attention mask type (pad or causal)
      scaled_masked_softmax_fusion: flag to indicate user want to use softmax fusion
      mask_func: mask function to be applied.
      softmax_in_fp32: if true, softmax in performed at fp32 precision.
      scale: scaling factor used in input tensor scaling.
code: def get_batch_per_block(sq, sk, b, np):
      import scaled_masked_softmax_cuda
  
      return scaled_masked_softmax_cuda.get_batch_per_block(
          sq, sk, b, np
      )
  
imports: import torch
  import torch.nn
  from megatron.core.transformer.enums import AttnMaskType
label_desc: Use image node_id 6 for calling the FusedScaleMaskSoftmax obj's underlying member method code with example usage: obj.get_batch_per_block(sq, sk, b, np) and returns: scaled_masked_softmax_cuda