class_docstr: Currently only support index in dimension 0 with a 2-dimension tensor.
  The shape of indexed in1 must be same with in2. Now this kernel does not support broadcast.
  The datatype must be float32 or float16.
code: def backward(ctx, grad_out):
      in1, in2, idx1 = ctx.for_backwards
  
      grad_in1, grad_in2 = index_mul_2d_backward(
          in1, in2, idx1, grad_out
      )
  
      return grad_in1, grad_in2, None
  
file_path: apex/apex/contrib/index_mul_2d/index_mul_2d.py
imports: import torch
  import fused_index_mul_2d
label_desc: Use image node_id 2 for calling the IndexMul2d_ obj's underlying member method code with example usage: obj.backward(ctx, grad_out) and returns: grad_in1,  grad_in2,  None