deberta_torch_small.mlir

func.func @forward(%arg0: !torch.vtensor<[1,128],si64>) -> !torch.vtensor<[1,128,1],f32>{
  %int1 = torch.constant.int 1
  %int32 = torch.constant.int 32
  %int128 = torch.constant.int 128
  %float1.000000e00 = torch.constant.float 1.000000e+00
  %0 = torch.vtensor.literal(dense<0.000000e+00> : tensor<2xf32>) : !torch.vtensor<[2],f32>
  %1 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2x32xf32>) : !torch.vtensor<[2,32],f32>
  %2 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x32xf32>) : !torch.vtensor<[32,32],f32>
  %3 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x37xf32>) : !torch.vtensor<[32,37],f32>
  %4 = torch.vtensor.literal(dense_resource<__elided__> : tensor<37x32xf32>) : !torch.vtensor<[37,32],f32>
  %5 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x32xf32>) : !torch.vtensor<[32,32],f32>
  %6 = torch.vtensor.literal(dense_resource<__elided__> : tensor<96x32xf32>) : !torch.vtensor<[96,32],f32>
  %7 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x37xf32>) : !torch.vtensor<[32,37],f32>
  %8 = torch.vtensor.literal(dense_resource<__elided__> : tensor<37x32xf32>) : !torch.vtensor<[37,32],f32>
  %9 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x32xf32>) : !torch.vtensor<[32,32],f32>
  %10 = torch.vtensor.literal(dense_resource<__elided__> : tensor<96x32xf32>) : !torch.vtensor<[96,32],f32>
  %11 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x37xf32>) : !torch.vtensor<[32,37],f32>
  %12 = torch.vtensor.literal(dense_resource<__elided__> : tensor<37x32xf32>) : !torch.vtensor<[37,32],f32>
  %13 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x32xf32>) : !torch.vtensor<[32,32],f32>
  %14 = torch.vtensor.literal(dense_resource<__elided__> : tensor<96x32xf32>) : !torch.vtensor<[96,32],f32>
  %15 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x37xf32>) : !torch.vtensor<[32,37],f32>
  %16 = torch.vtensor.literal(dense_resource<__elided__> : tensor<37x32xf32>) : !torch.vtensor<[37,32],f32>
  %17 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x32xf32>) : !torch.vtensor<[32,32],f32>
  %18 = torch.vtensor.literal(dense_resource<__elided__> : tensor<96x32xf32>) : !torch.vtensor<[96,32],f32>
  %19 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x37xf32>) : !torch.vtensor<[32,37],f32>
  %20 = torch.vtensor.literal(dense<0.000000e+00> : tensor<37xf32>) : !torch.vtensor<[37],f32>
  %21 = torch.vtensor.literal(dense_resource<__elided__> : tensor<37x32xf32>) : !torch.vtensor<[37,32],f32>
  %22 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x32xf32>) : !torch.vtensor<[32,32],f32>
  %23 = torch.vtensor.literal(dense<-3.40282347E+38> : tensor<f32>) : !torch.vtensor<[],f32>
  %24 = torch.vtensor.literal(dense_resource<__elided__> : tensor<96x32xf32>) : !torch.vtensor<[96,32],f32>
  %25 = torch.vtensor.literal(dense<0.000000e+00> : tensor<32xf32>) : !torch.vtensor<[32],f32>
  %26 = torch.vtensor.literal(dense<1.000000e+00> : tensor<32xf32>) : !torch.vtensor<[32],f32>
  %27 = torch.vtensor.literal(dense_resource<__elided__> : tensor<16x32xf32>) : !torch.vtensor<[16,32],f32>
  %28 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x32xf32>) : !torch.vtensor<[512,32],f32>
  %29 = torch.vtensor.literal(dense_resource<__elided__> : tensor<1000x32xf32>) : !torch.vtensor<[1000,32],f32>
  %30 = torch.vtensor.literal(dense_resource<__elided__> : tensor<1x512xsi64>) : !torch.vtensor<[1,512],si64>
  %false = torch.constant.bool false
  %none = torch.constant.none
  %int-1 = torch.constant.int -1
  %true = torch.constant.bool true
  %int-2 = torch.constant.int -2
  %int11 = torch.constant.int 11
  %str = torch.constant.str "none"
  %int0 = torch.constant.int 0
  %int9223372036854775807 = torch.constant.int 9223372036854775807
  %int2 = torch.constant.int 2
  %float9.999990e-08 = torch.constant.float 9.9999999999999995E-8
  %int96 = torch.constant.int 96
  %int4 = torch.constant.int 4
  %int3 = torch.constant.int 3
  %int8 = torch.constant.int 8
  %int16 = torch.constant.int 16
  %int24 = torch.constant.int 24
  %float4.000000e00 = torch.constant.float 4.000000e+00
  %int37 = torch.constant.int 37
  %cpu = torch.constant.device "cpu"
  %31 = torch.prim.ListConstruct %int1, %int128 : (!torch.int, !torch.int) -> !torch.list<int>
  %32 = torch.aten.ones %31, %none, %none, %cpu, %false : !torch.list<int>, !torch.none, !torch.none, !torch.Device, !torch.bool -> !torch.vtensor<[1,128],f32>
  %33 = torch.aten.zeros %31, %int4, %none, %cpu, %false : !torch.list<int>, !torch.int, !torch.none, !torch.Device, !torch.bool -> !torch.vtensor<[1,128],si64>
  %34 = torch.aten.slice.Tensor %30, %int0, %int0, %int9223372036854775807, %int1 : !torch.vtensor<[1,512],si64>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[1,512],si64>
  %35 = torch.aten.slice.Tensor %34, %int1, %int0, %int128, %int1 : !torch.vtensor<[1,512],si64>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[1,128],si64>
  %36 = torch.aten.embedding %29, %arg0, %int0, %false, %false : !torch.vtensor<[1000,32],f32>, !torch.vtensor<[1,128],si64>, !torch.int, !torch.bool, !torch.bool -> !torch.vtensor<[1,128,32],f32>
  %37 = torch.aten.embedding %28, %35, %int-1, %false, %false : !torch.vtensor<[512,32],f32>, !torch.vtensor<[1,128],si64>, !torch.int, !torch.bool, !torch.bool -> !torch.vtensor<[1,128,32],f32>
  %38 = torch.aten.add.Tensor %36, %37, %int1 : !torch.vtensor<[1,128,32],f32>, !torch.vtensor<[1,128,32],f32>, !torch.int -> !torch.vtensor<[1,128,32],f32>
  %39 = torch.aten.embedding %27, %33, %int-1, %false, %false : !torch.vtensor<[16,32],f32>, !torch.vtensor<[1,128],si64>, !torch.int, !torch.bool, !torch.bool -> !torch.vtensor<[1,128,32],f32>
  %40 = torch.aten.add.Tensor %38, %39, %int1 : !torch.vtensor<[1,128,32],f32>, !torch.vtensor<[1,128,32],f32>, !torch.int -> !torch.vtensor<[1,128,32],f32>
  %41 = torch.prim.ListConstruct %int-1 : (!torch.int) -> !torch.list<int>
  %42 = torch.aten.sum.dim_IntList %40, %41, %true, %none : !torch.vtensor<[1,128,32],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,128,1],f32>
  %43 = torch.aten.div.Scalar %42, %int32 : !torch.vtensor<[1,128,1],f32>, !torch.int -> !torch.vtensor<[1,128,1],f32>
  %44 = torch.aten.sub.Tensor %40, %43, %int1 : !torch.vtensor<[1,128,32],f32>, !torch.vtensor<[1,128,1],f32>, !torch.int -> !torch.vtensor<[1,128,32],f32>
  %45 = torch.aten.pow.Tensor_Scalar %44, %int2 : !torch.vtensor<[1,128,32],f32>, !torch.int -> !torch.vtensor<[1,128,32],f32>
  %46 = torch.aten.sum.dim_IntList %45, %41, %true, %none : !torch.vtensor<[1,128,32],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,128,1],f32>
  %47 = torch.aten.div.Scalar %46, %int32 : !torch.vtensor<[1,128,1],f32>, !torch.int -> !torch.vtensor<[1,128,1],f32>
  %48 = torch.aten.sub.Tensor %40, %43, %int1 : !torch.vtensor<[1,128,32],f32>, !torch.vtensor<[1,128,1],f32>, !torch.int -> !torch.vtensor<[1,128,32],f32>
  %49 = torch.aten.add.Scalar %47, %float9.999990e-08, %int1 : !torch.vtensor<[1,128,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,128,1],f32>
  %50 = torch.aten.sqrt %49 : !torch.vtensor<[1,128,1],f32> -> !torch.vtensor<[1,128,1],f32>
  %51 = torch.aten.div.Tensor %48, %50 : !torch.vtensor<[1,128,32],f32>, !torch.vtensor<[1,128,1],f32> -> !torch.vtensor<[1,128,32],f32>
  %52 = torch.aten.mul.Tensor %26, %51 : !torch.vtensor<[32],f32>, !torch.vtensor<[1,128,32],f32> -> !torch.vtensor<[1,128,32],f32>
  %53 = torch.aten.add.Tensor %52, %25, %int1 : !torch.vtensor<[1,128,32],f32>, !torch.vtensor<[32],f32>, !torch.int -> !torch.vtensor<[1,128,32],f32>
  %54 = torch.aten.unsqueeze %32, %int2 : !torch.vtensor<[1,128],f32>, !torch.int -> !torch.vtensor<[1,128,1],f32>
  %55 = torch.aten.mul.Tensor %53, %54 : !torch.vtensor<[1,128,32],f32>, !torch.vtensor<[1,128,1],f32> -> !torch.vtensor<[1,128,32],f32>
  %56 = torch.aten.unsqueeze %32, %int1 : !torch.vtensor<[1,128],f32>, !torch.int -> !torch.vtensor<[1,1,128],f32>
  %57 = torch.aten.unsqueeze %56, %int2 : !torch.vtensor<[1,1,128],f32>, !torch.int -> !torch.vtensor<[1,1,1,128],f32>
  %58 = torch.aten.squeeze.dim %57, %int-2 : !torch.vtensor<[1,1,1,128],f32>, !torch.int -> !torch.vtensor<[1,1,128],f32>
  %59 = torch.aten.unsqueeze %58, %int-1 : !torch.vtensor<[1,1,128],f32>, !torch.int -> !torch.vtensor<[1,1,128,1],f32>
  %60 = torch.aten.mul.Tensor %57, %59 : !torch.vtensor<[1,1,1,128],f32>, !torch.vtensor<[1,1,128,1],f32> -> !torch.vtensor<[1,1,128,128],f32>
  %61 = torch.prim.NumToTensor.Scalar %int0 : !torch.int -> !torch.vtensor<[],si64>
  %62 = torch.aten.to.dtype %61, %int1, %false, %false, %none : !torch.vtensor<[],si64>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[],si8>
  return %54 : !torch.vtensor<[1,128,1],f32>
}