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@AmosLewis
Created April 6, 2023 20:55
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#loc = loc(unknown)
module attributes {torch.debug_module_name = "_lambda"} {
func.func @forward(%arg0: !torch.vtensor<[1,15],si64> loc(unknown), %arg1: !torch.vtensor<[1,4],si64> loc(unknown)) -> !torch.vtensor<[1,4,32128],f32> {
%int512 = torch.constant.int 512 loc(#loc1)
%int0 = torch.constant.int 0 loc(#loc2)
%int1 = torch.constant.int 1 loc(#loc3)
%int-1 = torch.constant.int -1 loc(#loc4)
%true = torch.constant.bool true loc(#loc5)
%int4 = torch.constant.int 4 loc(#loc6)
%false = torch.constant.bool false loc(#loc7)
%none = torch.constant.none loc(#loc)
%int15 = torch.constant.int 15 loc(#loc8)
%0 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%1 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x2048xf32>) : !torch.vtensor<[512,2048],f32> loc(#loc)
%2 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2048x512xf32>) : !torch.vtensor<[2048,512],f32> loc(#loc)
%3 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%4 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%5 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%6 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%7 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%8 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%9 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%10 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%11 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%12 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%13 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%14 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x2048xf32>) : !torch.vtensor<[512,2048],f32> loc(#loc)
%15 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2048x512xf32>) : !torch.vtensor<[2048,512],f32> loc(#loc)
%16 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%17 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%18 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%19 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%20 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%21 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%22 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%23 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%24 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%25 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%26 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%27 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x2048xf32>) : !torch.vtensor<[512,2048],f32> loc(#loc)
%28 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2048x512xf32>) : !torch.vtensor<[2048,512],f32> loc(#loc)
%29 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%30 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%31 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%32 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%33 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%34 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%35 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%36 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%37 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%38 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%39 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%40 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x2048xf32>) : !torch.vtensor<[512,2048],f32> loc(#loc)
%41 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2048x512xf32>) : !torch.vtensor<[2048,512],f32> loc(#loc)
%42 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%43 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%44 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%45 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%46 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%47 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%48 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%49 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%50 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%51 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%52 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%53 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x2048xf32>) : !torch.vtensor<[512,2048],f32> loc(#loc)
%54 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2048x512xf32>) : !torch.vtensor<[2048,512],f32> loc(#loc)
%55 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%56 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%57 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%58 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%59 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%60 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%61 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%62 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%63 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%64 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%65 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%66 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x2048xf32>) : !torch.vtensor<[512,2048],f32> loc(#loc)
%67 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2048x512xf32>) : !torch.vtensor<[2048,512],f32> loc(#loc)
%68 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%69 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%70 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%71 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%72 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%73 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%74 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%75 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x8xf32>) : !torch.vtensor<[32,8],f32> loc(#loc)
%76 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%77 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%78 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%79 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%80 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%81 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x2048xf32>) : !torch.vtensor<[512,2048],f32> loc(#loc)
%82 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2048x512xf32>) : !torch.vtensor<[2048,512],f32> loc(#loc)
%83 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%84 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%85 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%86 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%87 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%88 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%89 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x2048xf32>) : !torch.vtensor<[512,2048],f32> loc(#loc)
%90 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2048x512xf32>) : !torch.vtensor<[2048,512],f32> loc(#loc)
%91 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%92 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%93 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%94 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%95 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%96 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%97 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x2048xf32>) : !torch.vtensor<[512,2048],f32> loc(#loc)
%98 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2048x512xf32>) : !torch.vtensor<[2048,512],f32> loc(#loc)
%99 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%100 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%101 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%102 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%103 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%104 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%105 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x2048xf32>) : !torch.vtensor<[512,2048],f32> loc(#loc)
%106 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2048x512xf32>) : !torch.vtensor<[2048,512],f32> loc(#loc)
%107 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%108 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%109 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%110 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%111 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%112 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%113 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x2048xf32>) : !torch.vtensor<[512,2048],f32> loc(#loc)
%114 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2048x512xf32>) : !torch.vtensor<[2048,512],f32> loc(#loc)
%115 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%116 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%117 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%118 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%119 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%120 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%121 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x2048xf32>) : !torch.vtensor<[512,2048],f32> loc(#loc)
%122 = torch.vtensor.literal(dense_resource<__elided__> : tensor<2048x512xf32>) : !torch.vtensor<[2048,512],f32> loc(#loc)
%123 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%124 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%125 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x8xf32>) : !torch.vtensor<[32,8],f32> loc(#loc)
%126 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%127 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%128 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512xf32>) : !torch.vtensor<[512,512],f32> loc(#loc)
%129 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32> loc(#loc)
%130 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32128x512xf32>) : !torch.vtensor<[32128,512],f32> loc(#loc)
%131 = torch.vtensor.literal(dense<0> : tensor<si64>) : !torch.vtensor<[],si64> loc(#loc)
%int-100 = torch.constant.int -100 loc(#loc9)
%float-3.402820e38 = torch.constant.float -3.4028234663852886E+38 loc(#loc10)
%int6 = torch.constant.int 6 loc(#loc11)
%int9223372036854775807 = torch.constant.int 9223372036854775807 loc(#loc12)
%int2 = torch.constant.int 2 loc(#loc13)
%int3 = torch.constant.int 3 loc(#loc14)
%float1.000000e00 = torch.constant.float 1.000000e+00 loc(#loc15)
%float9.999990e-07 = torch.constant.float 9.9999999999999995E-7 loc(#loc16)
%int8 = torch.constant.int 8 loc(#loc17)
%int64 = torch.constant.int 64 loc(#loc18)
%int16 = torch.constant.int 16 loc(#loc19)
%float2.772590e00 = torch.constant.float 2.7725887222397811 loc(#loc20)
%int2048 = torch.constant.int 2048 loc(#loc21)
%float2.079440e00 = torch.constant.float 2.0794415416798357 loc(#loc22)
%int31 = torch.constant.int 31 loc(#loc23)
%float4.419420e-02 = torch.constant.float 0.044194173824159223 loc(#loc24)
%int32128 = torch.constant.int 32128 loc(#loc25)
%cpu = torch.constant.device "cpu" loc(#loc)
%132 = torch.prim.ListConstruct %int1, %int4 : (!torch.int, !torch.int) -> !torch.list<int> loc(#loc1268)
%133 = torch.aten.zeros %132, %int4, %int0, %cpu, %false : !torch.list<int>, !torch.int, !torch.int, !torch.Device, !torch.bool -> !torch.vtensor<[1,4],si64> loc(#loc29)
%134 = torch.aten.slice.Tensor %arg1, %int1, %int0, %int-1, %int1 : !torch.vtensor<[1,4],si64>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[1,3],si64> loc(#loc30)
%135 = torch.aten.clone %134, %none : !torch.vtensor<[1,3],si64>, !torch.none -> !torch.vtensor<[1,3],si64> loc(#loc31)
%136 = torch.aten.slice.Tensor %133, %int1, %int1, %int9223372036854775807, %int1 : !torch.vtensor<[1,4],si64>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[1,3],si64> loc(#loc32)
%137 = torch.aten.arange.start_step %int1, %int4, %int1, %none, %none, %none, %none : !torch.int, !torch.int, !torch.int, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[3],si64> loc(#loc28)
%138 = torch.prim.ListConstruct %137 : (!torch.vtensor<[3],si64>) -> !torch.list<optional<vtensor>> loc(#loc28)
%139 = torch.aten._index_put_impl %133, %138, %135, %false, %false : !torch.vtensor<[1,4],si64>, !torch.list<optional<vtensor>>, !torch.vtensor<[1,3],si64>, !torch.bool, !torch.bool -> !torch.vtensor<[1,4],si64> loc(#loc28)
%140 = torch.aten.clone %131, %none : !torch.vtensor<[],si64>, !torch.none -> !torch.vtensor<[],si64> loc(#loc33)
%141 = torch.aten.slice.Tensor %139, %int1, %int0, %int1, %int1 : !torch.vtensor<[1,4],si64>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[1,1],si64> loc(#loc34)
%142 = torch.aten.squeeze.dim %141, %int1 : !torch.vtensor<[1,1],si64>, !torch.int -> !torch.vtensor<[1],si64> loc(#loc34)
%143 = torch.prim.NumToTensor.Scalar %int0 : !torch.int -> !torch.vtensor<[],si64> loc(#loc34)
%144 = torch.prim.ListConstruct %143 : (!torch.vtensor<[],si64>) -> !torch.list<optional<vtensor>> loc(#loc35)
%145 = torch.aten._index_put_impl %139, %144, %140, %false, %false : !torch.vtensor<[1,4],si64>, !torch.list<optional<vtensor>>, !torch.vtensor<[],si64>, !torch.bool, !torch.bool -> !torch.vtensor<[1,4],si64> loc(#loc35)
%146 = torch.aten.eq.Scalar %145, %int-100 : !torch.vtensor<[1,4],si64>, !torch.int -> !torch.vtensor<[1,4],i1> loc(#loc36)
%147 = torch.prim.ListConstruct : () -> !torch.list<int> loc(#loc37)
%148 = torch.prim.NumToTensor.Scalar %int0 : !torch.int -> !torch.vtensor<[],si64> loc(#loc37)
%149 = torch.aten.broadcast_to %148, %147 : !torch.vtensor<[],si64>, !torch.list<int> -> !torch.vtensor<[],si64> loc(#loc37)
%150 = torch.aten.where.self %146, %149, %145 : !torch.vtensor<[1,4],i1>, !torch.vtensor<[],si64>, !torch.vtensor<[1,4],si64> -> !torch.vtensor<[1,4],si64> loc(#loc37)
%151 = torch.prim.ListConstruct %int-1, %int15 : (!torch.int, !torch.int) -> !torch.list<int> loc(#loc)
%152 = torch.aten.view %arg0, %151 : !torch.vtensor<[1,15],si64>, !torch.list<int> -> !torch.vtensor<[1,15],si64> loc(#loc38)
%153 = torch.aten.embedding %130, %152, %int-1, %false, %false : !torch.vtensor<[32128,512],f32>, !torch.vtensor<[1,15],si64>, !torch.int, !torch.bool, !torch.bool -> !torch.vtensor<[1,15,512],f32> loc(#loc39)
%154 = torch.prim.ListConstruct %int1, %int15 : (!torch.int, !torch.int) -> !torch.list<int> loc(#loc1269)
%155 = torch.aten.ones %154, %none, %none, %cpu, %false : !torch.list<int>, !torch.none, !torch.none, !torch.Device, !torch.bool -> !torch.vtensor<[1,15],f32> loc(#loc43)
%156 = torch.aten.unsqueeze %155, %int1 : !torch.vtensor<[1,15],f32>, !torch.int -> !torch.vtensor<[1,1,15],f32> loc(#loc44)
%157 = torch.aten.unsqueeze %156, %int2 : !torch.vtensor<[1,1,15],f32>, !torch.int -> !torch.vtensor<[1,1,1,15],f32> loc(#loc45)
%158 = torch.aten.rsub.Scalar %157, %float1.000000e00, %int1 : !torch.vtensor<[1,1,1,15],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,1,1,15],f32> loc(#loc46)
%159 = torch.aten.mul.Scalar %158, %float-3.402820e38 : !torch.vtensor<[1,1,1,15],f32>, !torch.float -> !torch.vtensor<[1,1,1,15],f32> loc(#loc47)
%160 = torch.aten.pow.Tensor_Scalar %153, %int2 : !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc48)
%161 = torch.prim.ListConstruct %int-1 : (!torch.int) -> !torch.list<int> loc(#loc)
%162 = torch.aten.sum.dim_IntList %160, %161, %true, %none : !torch.vtensor<[1,15,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,15,1],f32> loc(#loc49)
%163 = torch.aten.div.Scalar %162, %int512 : !torch.vtensor<[1,15,1],f32>, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc49)
%164 = torch.aten.add.Scalar %163, %float9.999990e-07, %int1 : !torch.vtensor<[1,15,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc50)
%165 = torch.aten.rsqrt %164 : !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,1],f32> loc(#loc51)
%166 = torch.aten.mul.Tensor %153, %165 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc52)
%167 = torch.aten.mul.Tensor %129, %166 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,15,512],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc53)
%168 = torch.aten.transpose.int %128, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc54)
%169 = torch.prim.ListConstruct %int15, %int512 : (!torch.int, !torch.int) -> !torch.list<int> loc(#loc1270)
%170 = torch.aten.view %167, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc57)
%171 = torch.aten.mm %170, %168 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc58)
%172 = torch.prim.ListConstruct %int1, %int15, %int512 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1271)
%173 = torch.aten.view %171, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc61)
%174 = torch.prim.ListConstruct %int1, %int-1, %int8, %int64 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc)
%175 = torch.aten.view %173, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc62)
%176 = torch.aten.transpose.int %175, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc63)
%177 = torch.aten.transpose.int %127, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc64)
%178 = torch.aten.view %167, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc65)
%179 = torch.aten.mm %178, %177 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc66)
%180 = torch.aten.view %179, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc67)
%181 = torch.aten.view %180, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc68)
%182 = torch.aten.transpose.int %181, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc69)
%183 = torch.aten.transpose.int %126, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc70)
%184 = torch.aten.view %167, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc71)
%185 = torch.aten.mm %184, %183 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc72)
%186 = torch.aten.view %185, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc73)
%187 = torch.aten.view %186, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc74)
%188 = torch.aten.transpose.int %187, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc75)
%189 = torch.aten.transpose.int %182, %int3, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,15],f32> loc(#loc76)
%190 = torch.prim.ListConstruct %int1, %int8, %int15, %int64 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1272)
%191 = torch.aten.broadcast_to %176, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc79)
%192 = torch.prim.ListConstruct %int8, %int15, %int64 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1273)
%193 = torch.aten.view %191, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc80)
%194 = torch.prim.ListConstruct %int1, %int8, %int64, %int15 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1274)
%195 = torch.aten.broadcast_to %189, %194 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,15],f32> loc(#loc81)
%196 = torch.prim.ListConstruct %int8, %int64, %int15 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1275)
%197 = torch.aten.view %195, %196 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[8,64,15],f32> loc(#loc82)
%198 = torch.aten.bmm %193, %197 : !torch.vtensor<[8,15,64],f32>, !torch.vtensor<[8,64,15],f32> -> !torch.vtensor<[8,15,15],f32> loc(#loc83)
%199 = torch.prim.ListConstruct %int1, %int8, %int15, %int15 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1276)
%200 = torch.aten.view %198, %199 : !torch.vtensor<[8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc87)
%201 = torch.aten.arange.start_step %int0, %int15, %int1, %int4, %none, %cpu, %false : !torch.int, !torch.int, !torch.int, !torch.int, !torch.none, !torch.Device, !torch.bool -> !torch.vtensor<[15],si64> loc(#loc88)
%202 = torch.aten.unsqueeze %201, %int1 : !torch.vtensor<[15],si64>, !torch.int -> !torch.vtensor<[15,1],si64> loc(#loc89)
%203 = torch.aten.arange.start_step %int0, %int15, %int1, %int4, %none, %cpu, %false : !torch.int, !torch.int, !torch.int, !torch.int, !torch.none, !torch.Device, !torch.bool -> !torch.vtensor<[15],si64> loc(#loc90)
%204 = torch.aten.unsqueeze %203, %int0 : !torch.vtensor<[15],si64>, !torch.int -> !torch.vtensor<[1,15],si64> loc(#loc91)
%205 = torch.aten.sub.Tensor %204, %202, %int1 : !torch.vtensor<[1,15],si64>, !torch.vtensor<[15,1],si64>, !torch.int -> !torch.vtensor<[15,15],si64> loc(#loc92)
%206 = torch.aten.gt.Scalar %205, %int0 : !torch.vtensor<[15,15],si64>, !torch.int -> !torch.vtensor<[15,15],i1> loc(#loc93)
%207 = torch.aten.to.dtype %206, %int4, %false, %false, %none : !torch.vtensor<[15,15],i1>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[15,15],si64> loc(#loc94)
%208 = torch.aten.mul.Scalar %207, %int16 : !torch.vtensor<[15,15],si64>, !torch.int -> !torch.vtensor<[15,15],si64> loc(#loc95)
%209 = torch.aten.add.Scalar %208, %int0, %int1 : !torch.vtensor<[15,15],si64>, !torch.int, !torch.int -> !torch.vtensor<[15,15],si64> loc(#loc96)
%210 = torch.aten.abs %205 : !torch.vtensor<[15,15],si64> -> !torch.vtensor<[15,15],si64> loc(#loc97)
%211 = torch.aten.lt.Scalar %210, %int8 : !torch.vtensor<[15,15],si64>, !torch.int -> !torch.vtensor<[15,15],i1> loc(#loc98)
%212 = torch.aten.to.dtype %210, %int6, %false, %false, %none : !torch.vtensor<[15,15],si64>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[15,15],f32> loc(#loc99)
%213 = torch.aten.div.Scalar %212, %int8 : !torch.vtensor<[15,15],f32>, !torch.int -> !torch.vtensor<[15,15],f32> loc(#loc100)
%214 = torch.aten.log %213 : !torch.vtensor<[15,15],f32> -> !torch.vtensor<[15,15],f32> loc(#loc101)
%215 = torch.aten.div.Scalar %214, %float2.772590e00 : !torch.vtensor<[15,15],f32>, !torch.float -> !torch.vtensor<[15,15],f32> loc(#loc102)
%216 = torch.aten.mul.Scalar %215, %int8 : !torch.vtensor<[15,15],f32>, !torch.int -> !torch.vtensor<[15,15],f32> loc(#loc103)
%217 = torch.aten.to.dtype %216, %int4, %false, %false, %none : !torch.vtensor<[15,15],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[15,15],si64> loc(#loc104)
%218 = torch.aten.add.Scalar %217, %int8, %int1 : !torch.vtensor<[15,15],si64>, !torch.int, !torch.int -> !torch.vtensor<[15,15],si64> loc(#loc105)
%219 = torch.prim.NumToTensor.Scalar %int15 : !torch.int -> !torch.vtensor<[],si64> loc(#loc106)
%220 = torch.prim.ListConstruct %int15, %int15 : (!torch.int, !torch.int) -> !torch.list<int> loc(#loc106)
%221 = torch.aten.broadcast_to %219, %220 : !torch.vtensor<[],si64>, !torch.list<int> -> !torch.vtensor<[15,15],si64> loc(#loc106)
%222 = torch.aten.minimum %218, %221 : !torch.vtensor<[15,15],si64>, !torch.vtensor<[15,15],si64> -> !torch.vtensor<[15,15],si64> loc(#loc107)
%223 = torch.aten.where.self %211, %210, %222 : !torch.vtensor<[15,15],i1>, !torch.vtensor<[15,15],si64>, !torch.vtensor<[15,15],si64> -> !torch.vtensor<[15,15],si64> loc(#loc108)
%224 = torch.aten.add.Tensor %209, %223, %int1 : !torch.vtensor<[15,15],si64>, !torch.vtensor<[15,15],si64>, !torch.int -> !torch.vtensor<[15,15],si64> loc(#loc109)
%225 = torch.aten.embedding %125, %224, %int-1, %false, %false : !torch.vtensor<[32,8],f32>, !torch.vtensor<[15,15],si64>, !torch.int, !torch.bool, !torch.bool -> !torch.vtensor<[15,15,8],f32> loc(#loc110)
%226 = torch.prim.ListConstruct %int2, %int0, %int1 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc)
%227 = torch.aten.permute %225, %226 : !torch.vtensor<[15,15,8],f32>, !torch.list<int> -> !torch.vtensor<[8,15,15],f32> loc(#loc111)
%228 = torch.aten.unsqueeze %227, %int0 : !torch.vtensor<[8,15,15],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc86)
%229 = torch.aten.add.Tensor %228, %159, %int1 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,1,1,15],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc112)
%230 = torch.aten.add.Tensor %200, %229, %int1 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,15],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc113)
%values, %indices = torch.aten.max.dim %230, %int-1, %true : !torch.vtensor<[1,8,15,15],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,15,1],f32>, !torch.vtensor<[1,8,15,1],si64> loc(#loc114)
%231 = torch.aten.sub.Tensor %230, %values, %int1 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,1],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc115)
%232 = torch.aten.exp %231 : !torch.vtensor<[1,8,15,15],f32> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc116)
%233 = torch.aten.sum.dim_IntList %232, %161, %true, %none : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,15,1],f32> loc(#loc117)
%234 = torch.aten.div.Tensor %232, %233 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,1],f32> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc118)
%235 = torch.aten.broadcast_to %234, %199 : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc119)
%236 = torch.prim.ListConstruct %int8, %int15, %int15 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1277)
%237 = torch.aten.view %235, %236 : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[8,15,15],f32> loc(#loc120)
%238 = torch.aten.broadcast_to %188, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc121)
%239 = torch.aten.view %238, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc122)
%240 = torch.aten.bmm %237, %239 : !torch.vtensor<[8,15,15],f32>, !torch.vtensor<[8,15,64],f32> -> !torch.vtensor<[8,15,64],f32> loc(#loc123)
%241 = torch.aten.view %240, %190 : !torch.vtensor<[8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc124)
%242 = torch.aten.transpose.int %241, %int1, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,15,8,64],f32> loc(#loc125)
%243 = torch.aten.clone %242, %int0 : !torch.vtensor<[1,15,8,64],f32>, !torch.int -> !torch.vtensor<[1,15,8,64],f32> loc(#loc126)
%244 = torch.prim.ListConstruct %int1, %int-1, %int512 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc)
%245 = torch.aten.view %243, %244 : !torch.vtensor<[1,15,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc60)
%246 = torch.aten.transpose.int %124, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc127)
%247 = torch.aten.view %245, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc128)
%248 = torch.aten.mm %247, %246 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc129)
%249 = torch.aten.view %248, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc130)
%250 = torch.aten.add.Tensor %153, %249, %int1 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc131)
%251 = torch.aten.pow.Tensor_Scalar %250, %int2 : !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc132)
%252 = torch.aten.sum.dim_IntList %251, %161, %true, %none : !torch.vtensor<[1,15,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,15,1],f32> loc(#loc133)
%253 = torch.aten.div.Scalar %252, %int512 : !torch.vtensor<[1,15,1],f32>, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc133)
%254 = torch.aten.add.Scalar %253, %float9.999990e-07, %int1 : !torch.vtensor<[1,15,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc134)
%255 = torch.aten.rsqrt %254 : !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,1],f32> loc(#loc135)
%256 = torch.aten.mul.Tensor %250, %255 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc136)
%257 = torch.aten.mul.Tensor %123, %256 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,15,512],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc137)
%258 = torch.aten.transpose.int %122, %int0, %int1 : !torch.vtensor<[2048,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,2048],f32> loc(#loc138)
%259 = torch.aten.view %257, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc139)
%260 = torch.aten.mm %259, %258 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,2048],f32> -> !torch.vtensor<[15,2048],f32> loc(#loc140)
%261 = torch.prim.ListConstruct %int1, %int15, %int2048 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1278)
%262 = torch.aten.view %260, %261 : !torch.vtensor<[15,2048],f32>, !torch.list<int> -> !torch.vtensor<[1,15,2048],f32> loc(#loc143)
%263 = torch.aten.relu %262 : !torch.vtensor<[1,15,2048],f32> -> !torch.vtensor<[1,15,2048],f32> loc(#loc142)
%264 = torch.aten.transpose.int %121, %int0, %int1 : !torch.vtensor<[512,2048],f32>, !torch.int, !torch.int -> !torch.vtensor<[2048,512],f32> loc(#loc144)
%265 = torch.prim.ListConstruct %int15, %int2048 : (!torch.int, !torch.int) -> !torch.list<int> loc(#loc1279)
%266 = torch.aten.view %263, %265 : !torch.vtensor<[1,15,2048],f32>, !torch.list<int> -> !torch.vtensor<[15,2048],f32> loc(#loc145)
%267 = torch.aten.mm %266, %264 : !torch.vtensor<[15,2048],f32>, !torch.vtensor<[2048,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc146)
%268 = torch.aten.view %267, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc147)
%269 = torch.aten.add.Tensor %250, %268, %int1 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc148)
%270 = torch.aten.pow.Tensor_Scalar %269, %int2 : !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc149)
%271 = torch.aten.sum.dim_IntList %270, %161, %true, %none : !torch.vtensor<[1,15,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,15,1],f32> loc(#loc150)
%272 = torch.aten.div.Scalar %271, %int512 : !torch.vtensor<[1,15,1],f32>, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc150)
%273 = torch.aten.add.Scalar %272, %float9.999990e-07, %int1 : !torch.vtensor<[1,15,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc151)
%274 = torch.aten.rsqrt %273 : !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,1],f32> loc(#loc152)
%275 = torch.aten.mul.Tensor %269, %274 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc153)
%276 = torch.aten.mul.Tensor %120, %275 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,15,512],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc154)
%277 = torch.aten.transpose.int %119, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc155)
%278 = torch.aten.view %276, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc156)
%279 = torch.aten.mm %278, %277 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc157)
%280 = torch.aten.view %279, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc158)
%281 = torch.aten.view %280, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc159)
%282 = torch.aten.transpose.int %281, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc160)
%283 = torch.aten.transpose.int %118, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc161)
%284 = torch.aten.view %276, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc162)
%285 = torch.aten.mm %284, %283 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc163)
%286 = torch.aten.view %285, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc164)
%287 = torch.aten.view %286, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc165)
%288 = torch.aten.transpose.int %287, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc166)
%289 = torch.aten.transpose.int %117, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc167)
%290 = torch.aten.view %276, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc168)
%291 = torch.aten.mm %290, %289 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc169)
%292 = torch.aten.view %291, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc170)
%293 = torch.aten.view %292, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc171)
%294 = torch.aten.transpose.int %293, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc172)
%295 = torch.aten.transpose.int %288, %int3, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,15],f32> loc(#loc173)
%296 = torch.aten.broadcast_to %282, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc174)
%297 = torch.aten.view %296, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc175)
%298 = torch.aten.broadcast_to %295, %194 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,15],f32> loc(#loc176)
%299 = torch.aten.view %298, %196 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[8,64,15],f32> loc(#loc177)
%300 = torch.aten.bmm %297, %299 : !torch.vtensor<[8,15,64],f32>, !torch.vtensor<[8,64,15],f32> -> !torch.vtensor<[8,15,15],f32> loc(#loc178)
%301 = torch.aten.view %300, %199 : !torch.vtensor<[8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc179)
%302 = torch.aten.add.Tensor %301, %229, %int1 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,15],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc180)
%values_0, %indices_1 = torch.aten.max.dim %302, %int-1, %true : !torch.vtensor<[1,8,15,15],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,15,1],f32>, !torch.vtensor<[1,8,15,1],si64> loc(#loc181)
%303 = torch.aten.sub.Tensor %302, %values_0, %int1 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,1],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc182)
%304 = torch.aten.exp %303 : !torch.vtensor<[1,8,15,15],f32> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc183)
%305 = torch.aten.sum.dim_IntList %304, %161, %true, %none : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,15,1],f32> loc(#loc184)
%306 = torch.aten.div.Tensor %304, %305 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,1],f32> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc185)
%307 = torch.aten.broadcast_to %306, %199 : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc186)
%308 = torch.aten.view %307, %236 : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[8,15,15],f32> loc(#loc187)
%309 = torch.aten.broadcast_to %294, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc188)
%310 = torch.aten.view %309, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc189)
%311 = torch.aten.bmm %308, %310 : !torch.vtensor<[8,15,15],f32>, !torch.vtensor<[8,15,64],f32> -> !torch.vtensor<[8,15,64],f32> loc(#loc190)
%312 = torch.aten.view %311, %190 : !torch.vtensor<[8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc191)
%313 = torch.aten.transpose.int %312, %int1, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,15,8,64],f32> loc(#loc192)
%314 = torch.aten.clone %313, %int0 : !torch.vtensor<[1,15,8,64],f32>, !torch.int -> !torch.vtensor<[1,15,8,64],f32> loc(#loc193)
%315 = torch.aten.view %314, %244 : !torch.vtensor<[1,15,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc194)
%316 = torch.aten.transpose.int %116, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc195)
%317 = torch.aten.view %315, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc196)
%318 = torch.aten.mm %317, %316 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc197)
%319 = torch.aten.view %318, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc198)
%320 = torch.aten.add.Tensor %269, %319, %int1 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc199)
%321 = torch.aten.pow.Tensor_Scalar %320, %int2 : !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc200)
%322 = torch.aten.sum.dim_IntList %321, %161, %true, %none : !torch.vtensor<[1,15,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,15,1],f32> loc(#loc201)
%323 = torch.aten.div.Scalar %322, %int512 : !torch.vtensor<[1,15,1],f32>, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc201)
%324 = torch.aten.add.Scalar %323, %float9.999990e-07, %int1 : !torch.vtensor<[1,15,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc202)
%325 = torch.aten.rsqrt %324 : !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,1],f32> loc(#loc203)
%326 = torch.aten.mul.Tensor %320, %325 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc204)
%327 = torch.aten.mul.Tensor %115, %326 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,15,512],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc205)
%328 = torch.aten.transpose.int %114, %int0, %int1 : !torch.vtensor<[2048,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,2048],f32> loc(#loc206)
%329 = torch.aten.view %327, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc207)
%330 = torch.aten.mm %329, %328 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,2048],f32> -> !torch.vtensor<[15,2048],f32> loc(#loc208)
%331 = torch.aten.view %330, %261 : !torch.vtensor<[15,2048],f32>, !torch.list<int> -> !torch.vtensor<[1,15,2048],f32> loc(#loc209)
%332 = torch.aten.relu %331 : !torch.vtensor<[1,15,2048],f32> -> !torch.vtensor<[1,15,2048],f32> loc(#loc210)
%333 = torch.aten.transpose.int %113, %int0, %int1 : !torch.vtensor<[512,2048],f32>, !torch.int, !torch.int -> !torch.vtensor<[2048,512],f32> loc(#loc211)
%334 = torch.aten.view %332, %265 : !torch.vtensor<[1,15,2048],f32>, !torch.list<int> -> !torch.vtensor<[15,2048],f32> loc(#loc212)
%335 = torch.aten.mm %334, %333 : !torch.vtensor<[15,2048],f32>, !torch.vtensor<[2048,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc213)
%336 = torch.aten.view %335, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc214)
%337 = torch.aten.add.Tensor %320, %336, %int1 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc215)
%338 = torch.aten.pow.Tensor_Scalar %337, %int2 : !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc216)
%339 = torch.aten.sum.dim_IntList %338, %161, %true, %none : !torch.vtensor<[1,15,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,15,1],f32> loc(#loc217)
%340 = torch.aten.div.Scalar %339, %int512 : !torch.vtensor<[1,15,1],f32>, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc217)
%341 = torch.aten.add.Scalar %340, %float9.999990e-07, %int1 : !torch.vtensor<[1,15,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc218)
%342 = torch.aten.rsqrt %341 : !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,1],f32> loc(#loc219)
%343 = torch.aten.mul.Tensor %337, %342 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc220)
%344 = torch.aten.mul.Tensor %112, %343 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,15,512],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc221)
%345 = torch.aten.transpose.int %111, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc222)
%346 = torch.aten.view %344, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc223)
%347 = torch.aten.mm %346, %345 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc224)
%348 = torch.aten.view %347, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc225)
%349 = torch.aten.view %348, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc226)
%350 = torch.aten.transpose.int %349, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc227)
%351 = torch.aten.transpose.int %110, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc228)
%352 = torch.aten.view %344, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc229)
%353 = torch.aten.mm %352, %351 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc230)
%354 = torch.aten.view %353, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc231)
%355 = torch.aten.view %354, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc232)
%356 = torch.aten.transpose.int %355, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc233)
%357 = torch.aten.transpose.int %109, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc234)
%358 = torch.aten.view %344, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc235)
%359 = torch.aten.mm %358, %357 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc236)
%360 = torch.aten.view %359, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc237)
%361 = torch.aten.view %360, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc238)
%362 = torch.aten.transpose.int %361, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc239)
%363 = torch.aten.transpose.int %356, %int3, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,15],f32> loc(#loc240)
%364 = torch.aten.broadcast_to %350, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc241)
%365 = torch.aten.view %364, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc242)
%366 = torch.aten.broadcast_to %363, %194 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,15],f32> loc(#loc243)
%367 = torch.aten.view %366, %196 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[8,64,15],f32> loc(#loc244)
%368 = torch.aten.bmm %365, %367 : !torch.vtensor<[8,15,64],f32>, !torch.vtensor<[8,64,15],f32> -> !torch.vtensor<[8,15,15],f32> loc(#loc245)
%369 = torch.aten.view %368, %199 : !torch.vtensor<[8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc246)
%370 = torch.aten.add.Tensor %369, %229, %int1 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,15],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc247)
%values_2, %indices_3 = torch.aten.max.dim %370, %int-1, %true : !torch.vtensor<[1,8,15,15],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,15,1],f32>, !torch.vtensor<[1,8,15,1],si64> loc(#loc248)
%371 = torch.aten.sub.Tensor %370, %values_2, %int1 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,1],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc249)
%372 = torch.aten.exp %371 : !torch.vtensor<[1,8,15,15],f32> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc250)
%373 = torch.aten.sum.dim_IntList %372, %161, %true, %none : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,15,1],f32> loc(#loc251)
%374 = torch.aten.div.Tensor %372, %373 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,1],f32> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc252)
%375 = torch.aten.broadcast_to %374, %199 : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc253)
%376 = torch.aten.view %375, %236 : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[8,15,15],f32> loc(#loc254)
%377 = torch.aten.broadcast_to %362, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc255)
%378 = torch.aten.view %377, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc256)
%379 = torch.aten.bmm %376, %378 : !torch.vtensor<[8,15,15],f32>, !torch.vtensor<[8,15,64],f32> -> !torch.vtensor<[8,15,64],f32> loc(#loc257)
%380 = torch.aten.view %379, %190 : !torch.vtensor<[8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc258)
%381 = torch.aten.transpose.int %380, %int1, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,15,8,64],f32> loc(#loc259)
%382 = torch.aten.clone %381, %int0 : !torch.vtensor<[1,15,8,64],f32>, !torch.int -> !torch.vtensor<[1,15,8,64],f32> loc(#loc260)
%383 = torch.aten.view %382, %244 : !torch.vtensor<[1,15,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc261)
%384 = torch.aten.transpose.int %108, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc262)
%385 = torch.aten.view %383, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc263)
%386 = torch.aten.mm %385, %384 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc264)
%387 = torch.aten.view %386, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc265)
%388 = torch.aten.add.Tensor %337, %387, %int1 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc266)
%389 = torch.aten.pow.Tensor_Scalar %388, %int2 : !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc267)
%390 = torch.aten.sum.dim_IntList %389, %161, %true, %none : !torch.vtensor<[1,15,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,15,1],f32> loc(#loc268)
%391 = torch.aten.div.Scalar %390, %int512 : !torch.vtensor<[1,15,1],f32>, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc268)
%392 = torch.aten.add.Scalar %391, %float9.999990e-07, %int1 : !torch.vtensor<[1,15,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc269)
%393 = torch.aten.rsqrt %392 : !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,1],f32> loc(#loc270)
%394 = torch.aten.mul.Tensor %388, %393 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc271)
%395 = torch.aten.mul.Tensor %107, %394 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,15,512],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc272)
%396 = torch.aten.transpose.int %106, %int0, %int1 : !torch.vtensor<[2048,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,2048],f32> loc(#loc273)
%397 = torch.aten.view %395, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc274)
%398 = torch.aten.mm %397, %396 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,2048],f32> -> !torch.vtensor<[15,2048],f32> loc(#loc275)
%399 = torch.aten.view %398, %261 : !torch.vtensor<[15,2048],f32>, !torch.list<int> -> !torch.vtensor<[1,15,2048],f32> loc(#loc276)
%400 = torch.aten.relu %399 : !torch.vtensor<[1,15,2048],f32> -> !torch.vtensor<[1,15,2048],f32> loc(#loc277)
%401 = torch.aten.transpose.int %105, %int0, %int1 : !torch.vtensor<[512,2048],f32>, !torch.int, !torch.int -> !torch.vtensor<[2048,512],f32> loc(#loc278)
%402 = torch.aten.view %400, %265 : !torch.vtensor<[1,15,2048],f32>, !torch.list<int> -> !torch.vtensor<[15,2048],f32> loc(#loc279)
%403 = torch.aten.mm %402, %401 : !torch.vtensor<[15,2048],f32>, !torch.vtensor<[2048,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc280)
%404 = torch.aten.view %403, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc281)
%405 = torch.aten.add.Tensor %388, %404, %int1 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc282)
%406 = torch.aten.pow.Tensor_Scalar %405, %int2 : !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc283)
%407 = torch.aten.sum.dim_IntList %406, %161, %true, %none : !torch.vtensor<[1,15,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,15,1],f32> loc(#loc284)
%408 = torch.aten.div.Scalar %407, %int512 : !torch.vtensor<[1,15,1],f32>, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc284)
%409 = torch.aten.add.Scalar %408, %float9.999990e-07, %int1 : !torch.vtensor<[1,15,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc285)
%410 = torch.aten.rsqrt %409 : !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,1],f32> loc(#loc286)
%411 = torch.aten.mul.Tensor %405, %410 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc287)
%412 = torch.aten.mul.Tensor %104, %411 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,15,512],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc288)
%413 = torch.aten.transpose.int %103, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc289)
%414 = torch.aten.view %412, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc290)
%415 = torch.aten.mm %414, %413 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc291)
%416 = torch.aten.view %415, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc292)
%417 = torch.aten.view %416, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc293)
%418 = torch.aten.transpose.int %417, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc294)
%419 = torch.aten.transpose.int %102, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc295)
%420 = torch.aten.view %412, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc296)
%421 = torch.aten.mm %420, %419 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc297)
%422 = torch.aten.view %421, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc298)
%423 = torch.aten.view %422, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc299)
%424 = torch.aten.transpose.int %423, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc300)
%425 = torch.aten.transpose.int %101, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc301)
%426 = torch.aten.view %412, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc302)
%427 = torch.aten.mm %426, %425 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc303)
%428 = torch.aten.view %427, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc304)
%429 = torch.aten.view %428, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc305)
%430 = torch.aten.transpose.int %429, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc306)
%431 = torch.aten.transpose.int %424, %int3, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,15],f32> loc(#loc307)
%432 = torch.aten.broadcast_to %418, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc308)
%433 = torch.aten.view %432, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc309)
%434 = torch.aten.broadcast_to %431, %194 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,15],f32> loc(#loc310)
%435 = torch.aten.view %434, %196 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[8,64,15],f32> loc(#loc311)
%436 = torch.aten.bmm %433, %435 : !torch.vtensor<[8,15,64],f32>, !torch.vtensor<[8,64,15],f32> -> !torch.vtensor<[8,15,15],f32> loc(#loc312)
%437 = torch.aten.view %436, %199 : !torch.vtensor<[8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc313)
%438 = torch.aten.add.Tensor %437, %229, %int1 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,15],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc314)
%values_4, %indices_5 = torch.aten.max.dim %438, %int-1, %true : !torch.vtensor<[1,8,15,15],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,15,1],f32>, !torch.vtensor<[1,8,15,1],si64> loc(#loc315)
%439 = torch.aten.sub.Tensor %438, %values_4, %int1 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,1],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc316)
%440 = torch.aten.exp %439 : !torch.vtensor<[1,8,15,15],f32> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc317)
%441 = torch.aten.sum.dim_IntList %440, %161, %true, %none : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,15,1],f32> loc(#loc318)
%442 = torch.aten.div.Tensor %440, %441 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,1],f32> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc319)
%443 = torch.aten.broadcast_to %442, %199 : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc320)
%444 = torch.aten.view %443, %236 : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[8,15,15],f32> loc(#loc321)
%445 = torch.aten.broadcast_to %430, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc322)
%446 = torch.aten.view %445, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc323)
%447 = torch.aten.bmm %444, %446 : !torch.vtensor<[8,15,15],f32>, !torch.vtensor<[8,15,64],f32> -> !torch.vtensor<[8,15,64],f32> loc(#loc324)
%448 = torch.aten.view %447, %190 : !torch.vtensor<[8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc325)
%449 = torch.aten.transpose.int %448, %int1, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,15,8,64],f32> loc(#loc326)
%450 = torch.aten.clone %449, %int0 : !torch.vtensor<[1,15,8,64],f32>, !torch.int -> !torch.vtensor<[1,15,8,64],f32> loc(#loc327)
%451 = torch.aten.view %450, %244 : !torch.vtensor<[1,15,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc328)
%452 = torch.aten.transpose.int %100, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc329)
%453 = torch.aten.view %451, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc330)
%454 = torch.aten.mm %453, %452 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc331)
%455 = torch.aten.view %454, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc332)
%456 = torch.aten.add.Tensor %405, %455, %int1 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc333)
%457 = torch.aten.pow.Tensor_Scalar %456, %int2 : !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc334)
%458 = torch.aten.sum.dim_IntList %457, %161, %true, %none : !torch.vtensor<[1,15,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,15,1],f32> loc(#loc335)
%459 = torch.aten.div.Scalar %458, %int512 : !torch.vtensor<[1,15,1],f32>, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc335)
%460 = torch.aten.add.Scalar %459, %float9.999990e-07, %int1 : !torch.vtensor<[1,15,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc336)
%461 = torch.aten.rsqrt %460 : !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,1],f32> loc(#loc337)
%462 = torch.aten.mul.Tensor %456, %461 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc338)
%463 = torch.aten.mul.Tensor %99, %462 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,15,512],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc339)
%464 = torch.aten.transpose.int %98, %int0, %int1 : !torch.vtensor<[2048,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,2048],f32> loc(#loc340)
%465 = torch.aten.view %463, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc341)
%466 = torch.aten.mm %465, %464 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,2048],f32> -> !torch.vtensor<[15,2048],f32> loc(#loc342)
%467 = torch.aten.view %466, %261 : !torch.vtensor<[15,2048],f32>, !torch.list<int> -> !torch.vtensor<[1,15,2048],f32> loc(#loc343)
%468 = torch.aten.relu %467 : !torch.vtensor<[1,15,2048],f32> -> !torch.vtensor<[1,15,2048],f32> loc(#loc344)
%469 = torch.aten.transpose.int %97, %int0, %int1 : !torch.vtensor<[512,2048],f32>, !torch.int, !torch.int -> !torch.vtensor<[2048,512],f32> loc(#loc345)
%470 = torch.aten.view %468, %265 : !torch.vtensor<[1,15,2048],f32>, !torch.list<int> -> !torch.vtensor<[15,2048],f32> loc(#loc346)
%471 = torch.aten.mm %470, %469 : !torch.vtensor<[15,2048],f32>, !torch.vtensor<[2048,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc347)
%472 = torch.aten.view %471, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc348)
%473 = torch.aten.add.Tensor %456, %472, %int1 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc349)
%474 = torch.aten.pow.Tensor_Scalar %473, %int2 : !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc350)
%475 = torch.aten.sum.dim_IntList %474, %161, %true, %none : !torch.vtensor<[1,15,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,15,1],f32> loc(#loc351)
%476 = torch.aten.div.Scalar %475, %int512 : !torch.vtensor<[1,15,1],f32>, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc351)
%477 = torch.aten.add.Scalar %476, %float9.999990e-07, %int1 : !torch.vtensor<[1,15,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc352)
%478 = torch.aten.rsqrt %477 : !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,1],f32> loc(#loc353)
%479 = torch.aten.mul.Tensor %473, %478 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc354)
%480 = torch.aten.mul.Tensor %96, %479 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,15,512],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc355)
%481 = torch.aten.transpose.int %95, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc356)
%482 = torch.aten.view %480, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc357)
%483 = torch.aten.mm %482, %481 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc358)
%484 = torch.aten.view %483, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc359)
%485 = torch.aten.view %484, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc360)
%486 = torch.aten.transpose.int %485, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc361)
%487 = torch.aten.transpose.int %94, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc362)
%488 = torch.aten.view %480, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc363)
%489 = torch.aten.mm %488, %487 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc364)
%490 = torch.aten.view %489, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc365)
%491 = torch.aten.view %490, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc366)
%492 = torch.aten.transpose.int %491, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc367)
%493 = torch.aten.transpose.int %93, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc368)
%494 = torch.aten.view %480, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc369)
%495 = torch.aten.mm %494, %493 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc370)
%496 = torch.aten.view %495, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc371)
%497 = torch.aten.view %496, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc372)
%498 = torch.aten.transpose.int %497, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc373)
%499 = torch.aten.transpose.int %492, %int3, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,15],f32> loc(#loc374)
%500 = torch.aten.broadcast_to %486, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc375)
%501 = torch.aten.view %500, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc376)
%502 = torch.aten.broadcast_to %499, %194 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,15],f32> loc(#loc377)
%503 = torch.aten.view %502, %196 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[8,64,15],f32> loc(#loc378)
%504 = torch.aten.bmm %501, %503 : !torch.vtensor<[8,15,64],f32>, !torch.vtensor<[8,64,15],f32> -> !torch.vtensor<[8,15,15],f32> loc(#loc379)
%505 = torch.aten.view %504, %199 : !torch.vtensor<[8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc380)
%506 = torch.aten.add.Tensor %505, %229, %int1 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,15],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc381)
%values_6, %indices_7 = torch.aten.max.dim %506, %int-1, %true : !torch.vtensor<[1,8,15,15],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,15,1],f32>, !torch.vtensor<[1,8,15,1],si64> loc(#loc382)
%507 = torch.aten.sub.Tensor %506, %values_6, %int1 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,1],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc383)
%508 = torch.aten.exp %507 : !torch.vtensor<[1,8,15,15],f32> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc384)
%509 = torch.aten.sum.dim_IntList %508, %161, %true, %none : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,15,1],f32> loc(#loc385)
%510 = torch.aten.div.Tensor %508, %509 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,1],f32> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc386)
%511 = torch.aten.broadcast_to %510, %199 : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc387)
%512 = torch.aten.view %511, %236 : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[8,15,15],f32> loc(#loc388)
%513 = torch.aten.broadcast_to %498, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc389)
%514 = torch.aten.view %513, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc390)
%515 = torch.aten.bmm %512, %514 : !torch.vtensor<[8,15,15],f32>, !torch.vtensor<[8,15,64],f32> -> !torch.vtensor<[8,15,64],f32> loc(#loc391)
%516 = torch.aten.view %515, %190 : !torch.vtensor<[8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc392)
%517 = torch.aten.transpose.int %516, %int1, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,15,8,64],f32> loc(#loc393)
%518 = torch.aten.clone %517, %int0 : !torch.vtensor<[1,15,8,64],f32>, !torch.int -> !torch.vtensor<[1,15,8,64],f32> loc(#loc394)
%519 = torch.aten.view %518, %244 : !torch.vtensor<[1,15,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc395)
%520 = torch.aten.transpose.int %92, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc396)
%521 = torch.aten.view %519, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc397)
%522 = torch.aten.mm %521, %520 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc398)
%523 = torch.aten.view %522, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc399)
%524 = torch.aten.add.Tensor %473, %523, %int1 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc400)
%525 = torch.aten.pow.Tensor_Scalar %524, %int2 : !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc401)
%526 = torch.aten.sum.dim_IntList %525, %161, %true, %none : !torch.vtensor<[1,15,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,15,1],f32> loc(#loc402)
%527 = torch.aten.div.Scalar %526, %int512 : !torch.vtensor<[1,15,1],f32>, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc402)
%528 = torch.aten.add.Scalar %527, %float9.999990e-07, %int1 : !torch.vtensor<[1,15,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc403)
%529 = torch.aten.rsqrt %528 : !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,1],f32> loc(#loc404)
%530 = torch.aten.mul.Tensor %524, %529 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc405)
%531 = torch.aten.mul.Tensor %91, %530 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,15,512],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc406)
%532 = torch.aten.transpose.int %90, %int0, %int1 : !torch.vtensor<[2048,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,2048],f32> loc(#loc407)
%533 = torch.aten.view %531, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc408)
%534 = torch.aten.mm %533, %532 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,2048],f32> -> !torch.vtensor<[15,2048],f32> loc(#loc409)
%535 = torch.aten.view %534, %261 : !torch.vtensor<[15,2048],f32>, !torch.list<int> -> !torch.vtensor<[1,15,2048],f32> loc(#loc410)
%536 = torch.aten.relu %535 : !torch.vtensor<[1,15,2048],f32> -> !torch.vtensor<[1,15,2048],f32> loc(#loc411)
%537 = torch.aten.transpose.int %89, %int0, %int1 : !torch.vtensor<[512,2048],f32>, !torch.int, !torch.int -> !torch.vtensor<[2048,512],f32> loc(#loc412)
%538 = torch.aten.view %536, %265 : !torch.vtensor<[1,15,2048],f32>, !torch.list<int> -> !torch.vtensor<[15,2048],f32> loc(#loc413)
%539 = torch.aten.mm %538, %537 : !torch.vtensor<[15,2048],f32>, !torch.vtensor<[2048,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc414)
%540 = torch.aten.view %539, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc415)
%541 = torch.aten.add.Tensor %524, %540, %int1 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc416)
%542 = torch.aten.pow.Tensor_Scalar %541, %int2 : !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc417)
%543 = torch.aten.sum.dim_IntList %542, %161, %true, %none : !torch.vtensor<[1,15,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,15,1],f32> loc(#loc418)
%544 = torch.aten.div.Scalar %543, %int512 : !torch.vtensor<[1,15,1],f32>, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc418)
%545 = torch.aten.add.Scalar %544, %float9.999990e-07, %int1 : !torch.vtensor<[1,15,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc419)
%546 = torch.aten.rsqrt %545 : !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,1],f32> loc(#loc420)
%547 = torch.aten.mul.Tensor %541, %546 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc421)
%548 = torch.aten.mul.Tensor %88, %547 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,15,512],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc422)
%549 = torch.aten.transpose.int %87, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc423)
%550 = torch.aten.view %548, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc424)
%551 = torch.aten.mm %550, %549 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc425)
%552 = torch.aten.view %551, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc426)
%553 = torch.aten.view %552, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc427)
%554 = torch.aten.transpose.int %553, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc428)
%555 = torch.aten.transpose.int %86, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc429)
%556 = torch.aten.view %548, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc430)
%557 = torch.aten.mm %556, %555 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc431)
%558 = torch.aten.view %557, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc432)
%559 = torch.aten.view %558, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc433)
%560 = torch.aten.transpose.int %559, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc434)
%561 = torch.aten.transpose.int %85, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc435)
%562 = torch.aten.view %548, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc436)
%563 = torch.aten.mm %562, %561 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc437)
%564 = torch.aten.view %563, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc438)
%565 = torch.aten.view %564, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc439)
%566 = torch.aten.transpose.int %565, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc440)
%567 = torch.aten.transpose.int %560, %int3, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,15],f32> loc(#loc441)
%568 = torch.aten.broadcast_to %554, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc442)
%569 = torch.aten.view %568, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc443)
%570 = torch.aten.broadcast_to %567, %194 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,15],f32> loc(#loc444)
%571 = torch.aten.view %570, %196 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[8,64,15],f32> loc(#loc445)
%572 = torch.aten.bmm %569, %571 : !torch.vtensor<[8,15,64],f32>, !torch.vtensor<[8,64,15],f32> -> !torch.vtensor<[8,15,15],f32> loc(#loc446)
%573 = torch.aten.view %572, %199 : !torch.vtensor<[8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc447)
%574 = torch.aten.add.Tensor %573, %229, %int1 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,15],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc448)
%values_8, %indices_9 = torch.aten.max.dim %574, %int-1, %true : !torch.vtensor<[1,8,15,15],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,15,1],f32>, !torch.vtensor<[1,8,15,1],si64> loc(#loc449)
%575 = torch.aten.sub.Tensor %574, %values_8, %int1 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,1],f32>, !torch.int -> !torch.vtensor<[1,8,15,15],f32> loc(#loc450)
%576 = torch.aten.exp %575 : !torch.vtensor<[1,8,15,15],f32> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc451)
%577 = torch.aten.sum.dim_IntList %576, %161, %true, %none : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,15,1],f32> loc(#loc452)
%578 = torch.aten.div.Tensor %576, %577 : !torch.vtensor<[1,8,15,15],f32>, !torch.vtensor<[1,8,15,1],f32> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc453)
%579 = torch.aten.broadcast_to %578, %199 : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,15],f32> loc(#loc454)
%580 = torch.aten.view %579, %236 : !torch.vtensor<[1,8,15,15],f32>, !torch.list<int> -> !torch.vtensor<[8,15,15],f32> loc(#loc455)
%581 = torch.aten.broadcast_to %566, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc456)
%582 = torch.aten.view %581, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc457)
%583 = torch.aten.bmm %580, %582 : !torch.vtensor<[8,15,15],f32>, !torch.vtensor<[8,15,64],f32> -> !torch.vtensor<[8,15,64],f32> loc(#loc458)
%584 = torch.aten.view %583, %190 : !torch.vtensor<[8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc459)
%585 = torch.aten.transpose.int %584, %int1, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,15,8,64],f32> loc(#loc460)
%586 = torch.aten.clone %585, %int0 : !torch.vtensor<[1,15,8,64],f32>, !torch.int -> !torch.vtensor<[1,15,8,64],f32> loc(#loc461)
%587 = torch.aten.view %586, %244 : !torch.vtensor<[1,15,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc462)
%588 = torch.aten.transpose.int %84, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc463)
%589 = torch.aten.view %587, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc464)
%590 = torch.aten.mm %589, %588 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc465)
%591 = torch.aten.view %590, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc466)
%592 = torch.aten.add.Tensor %541, %591, %int1 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc467)
%593 = torch.aten.pow.Tensor_Scalar %592, %int2 : !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc468)
%594 = torch.aten.sum.dim_IntList %593, %161, %true, %none : !torch.vtensor<[1,15,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,15,1],f32> loc(#loc469)
%595 = torch.aten.div.Scalar %594, %int512 : !torch.vtensor<[1,15,1],f32>, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc469)
%596 = torch.aten.add.Scalar %595, %float9.999990e-07, %int1 : !torch.vtensor<[1,15,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc470)
%597 = torch.aten.rsqrt %596 : !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,1],f32> loc(#loc471)
%598 = torch.aten.mul.Tensor %592, %597 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc472)
%599 = torch.aten.mul.Tensor %83, %598 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,15,512],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc473)
%600 = torch.aten.transpose.int %82, %int0, %int1 : !torch.vtensor<[2048,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,2048],f32> loc(#loc474)
%601 = torch.aten.view %599, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc475)
%602 = torch.aten.mm %601, %600 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,2048],f32> -> !torch.vtensor<[15,2048],f32> loc(#loc476)
%603 = torch.aten.view %602, %261 : !torch.vtensor<[15,2048],f32>, !torch.list<int> -> !torch.vtensor<[1,15,2048],f32> loc(#loc477)
%604 = torch.aten.relu %603 : !torch.vtensor<[1,15,2048],f32> -> !torch.vtensor<[1,15,2048],f32> loc(#loc478)
%605 = torch.aten.transpose.int %81, %int0, %int1 : !torch.vtensor<[512,2048],f32>, !torch.int, !torch.int -> !torch.vtensor<[2048,512],f32> loc(#loc479)
%606 = torch.aten.view %604, %265 : !torch.vtensor<[1,15,2048],f32>, !torch.list<int> -> !torch.vtensor<[15,2048],f32> loc(#loc480)
%607 = torch.aten.mm %606, %605 : !torch.vtensor<[15,2048],f32>, !torch.vtensor<[2048,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc481)
%608 = torch.aten.view %607, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc482)
%609 = torch.aten.add.Tensor %592, %608, %int1 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc483)
%610 = torch.aten.pow.Tensor_Scalar %609, %int2 : !torch.vtensor<[1,15,512],f32>, !torch.int -> !torch.vtensor<[1,15,512],f32> loc(#loc484)
%611 = torch.aten.sum.dim_IntList %610, %161, %true, %none : !torch.vtensor<[1,15,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,15,1],f32> loc(#loc485)
%612 = torch.aten.div.Scalar %611, %int512 : !torch.vtensor<[1,15,1],f32>, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc485)
%613 = torch.aten.add.Scalar %612, %float9.999990e-07, %int1 : !torch.vtensor<[1,15,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,15,1],f32> loc(#loc486)
%614 = torch.aten.rsqrt %613 : !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,1],f32> loc(#loc487)
%615 = torch.aten.mul.Tensor %609, %614 : !torch.vtensor<[1,15,512],f32>, !torch.vtensor<[1,15,1],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc488)
%616 = torch.aten.mul.Tensor %80, %615 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,15,512],f32> -> !torch.vtensor<[1,15,512],f32> loc(#loc489)
%617 = torch.prim.ListConstruct %int-1, %int4 : (!torch.int, !torch.int) -> !torch.list<int> loc(#loc)
%618 = torch.aten.view %150, %617 : !torch.vtensor<[1,4],si64>, !torch.list<int> -> !torch.vtensor<[1,4],si64> loc(#loc490)
%619 = torch.aten.embedding %130, %618, %int-1, %false, %false : !torch.vtensor<[32128,512],f32>, !torch.vtensor<[1,4],si64>, !torch.int, !torch.bool, !torch.bool -> !torch.vtensor<[1,4,512],f32> loc(#loc491)
%620 = torch.aten.ones %132, %none, %none, %cpu, %false : !torch.list<int>, !torch.none, !torch.none, !torch.Device, !torch.bool -> !torch.vtensor<[1,4],f32> loc(#loc492)
%621 = torch.aten.ones %154, %int4, %none, %cpu, %false : !torch.list<int>, !torch.int, !torch.none, !torch.Device, !torch.bool -> !torch.vtensor<[1,15],si64> loc(#loc493)
%622 = torch.aten.arange.start_step %int0, %int4, %int1, %none, %none, %cpu, %false : !torch.int, !torch.int, !torch.int, !torch.none, !torch.none, !torch.Device, !torch.bool -> !torch.vtensor<[4],si64> loc(#loc494)
%623 = torch.aten.unsqueeze %622, %int0 : !torch.vtensor<[4],si64>, !torch.int -> !torch.vtensor<[1,4],si64> loc(#loc495)
%624 = torch.aten.unsqueeze %623, %int1 : !torch.vtensor<[1,4],si64>, !torch.int -> !torch.vtensor<[1,1,4],si64> loc(#loc496)
%625 = torch.prim.ListConstruct %int1, %int1, %int1, %int1, %int1, %int4 : (!torch.int, !torch.int, !torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc497)
%626 = torch.prim.ListConstruct %int1, %int1, %int4, %int1, %int1, %int4 : (!torch.int, !torch.int, !torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc497)
%627 = torch.prim.ListConstruct %int1, %int4, %int4 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc497)
%628 = torch.aten.view %624, %625 : !torch.vtensor<[1,1,4],si64>, !torch.list<int> -> !torch.vtensor<[1,1,1,1,1,4],si64> loc(#loc497)
%629 = torch.aten.broadcast_to %628, %626 : !torch.vtensor<[1,1,1,1,1,4],si64>, !torch.list<int> -> !torch.vtensor<[1,1,4,1,1,4],si64> loc(#loc497)
%630 = torch.aten.view %629, %627 : !torch.vtensor<[1,1,4,1,1,4],si64>, !torch.list<int> -> !torch.vtensor<[1,4,4],si64> loc(#loc497)
%631 = torch.aten.unsqueeze %622, %int0 : !torch.vtensor<[4],si64>, !torch.int -> !torch.vtensor<[1,4],si64> loc(#loc498)
%632 = torch.aten.unsqueeze %631, %int2 : !torch.vtensor<[1,4],si64>, !torch.int -> !torch.vtensor<[1,4,1],si64> loc(#loc499)
%633 = torch.aten.le.Tensor %630, %632 : !torch.vtensor<[1,4,4],si64>, !torch.vtensor<[1,4,1],si64> -> !torch.vtensor<[1,4,4],i1> loc(#loc500)
%634 = torch.aten.to.dtype %633, %int6, %false, %false, %none : !torch.vtensor<[1,4,4],i1>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[1,4,4],f32> loc(#loc501)
%635 = torch.aten.unsqueeze %634, %int1 : !torch.vtensor<[1,4,4],f32>, !torch.int -> !torch.vtensor<[1,1,4,4],f32> loc(#loc502)
%636 = torch.aten.unsqueeze %620, %int1 : !torch.vtensor<[1,4],f32>, !torch.int -> !torch.vtensor<[1,1,4],f32> loc(#loc503)
%637 = torch.aten.unsqueeze %636, %int2 : !torch.vtensor<[1,1,4],f32>, !torch.int -> !torch.vtensor<[1,1,1,4],f32> loc(#loc504)
%638 = torch.aten.mul.Tensor %635, %637 : !torch.vtensor<[1,1,4,4],f32>, !torch.vtensor<[1,1,1,4],f32> -> !torch.vtensor<[1,1,4,4],f32> loc(#loc505)
%639 = torch.aten.rsub.Scalar %638, %float1.000000e00, %int1 : !torch.vtensor<[1,1,4,4],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,1,4,4],f32> loc(#loc506)
%640 = torch.aten.mul.Scalar %639, %float-3.402820e38 : !torch.vtensor<[1,1,4,4],f32>, !torch.float -> !torch.vtensor<[1,1,4,4],f32> loc(#loc507)
%641 = torch.aten.unsqueeze %621, %int1 : !torch.vtensor<[1,15],si64>, !torch.int -> !torch.vtensor<[1,1,15],si64> loc(#loc508)
%642 = torch.aten.unsqueeze %641, %int2 : !torch.vtensor<[1,1,15],si64>, !torch.int -> !torch.vtensor<[1,1,1,15],si64> loc(#loc509)
%643 = torch.aten.to.dtype %642, %int6, %false, %false, %none : !torch.vtensor<[1,1,1,15],si64>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[1,1,1,15],f32> loc(#loc510)
%644 = torch.aten.rsub.Scalar %643, %float1.000000e00, %int1 : !torch.vtensor<[1,1,1,15],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,1,1,15],f32> loc(#loc511)
%645 = torch.aten.mul.Scalar %644, %float-3.402820e38 : !torch.vtensor<[1,1,1,15],f32>, !torch.float -> !torch.vtensor<[1,1,1,15],f32> loc(#loc512)
%646 = torch.aten.pow.Tensor_Scalar %619, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc513)
%647 = torch.aten.sum.dim_IntList %646, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc514)
%648 = torch.aten.div.Scalar %647, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc514)
%649 = torch.aten.add.Scalar %648, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc515)
%650 = torch.aten.rsqrt %649 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc516)
%651 = torch.aten.mul.Tensor %619, %650 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc517)
%652 = torch.aten.mul.Tensor %79, %651 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc518)
%653 = torch.aten.transpose.int %78, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc519)
%654 = torch.prim.ListConstruct %int4, %int512 : (!torch.int, !torch.int) -> !torch.list<int> loc(#loc1280)
%655 = torch.aten.view %652, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc520)
%656 = torch.aten.mm %655, %653 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc521)
%657 = torch.prim.ListConstruct %int1, %int4, %int512 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1281)
%658 = torch.aten.view %656, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc523)
%659 = torch.aten.view %658, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc524)
%660 = torch.aten.transpose.int %659, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc525)
%661 = torch.aten.transpose.int %77, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc526)
%662 = torch.aten.view %652, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc527)
%663 = torch.aten.mm %662, %661 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc528)
%664 = torch.aten.view %663, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc529)
%665 = torch.aten.view %664, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc530)
%666 = torch.aten.transpose.int %665, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc531)
%667 = torch.aten.transpose.int %76, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc532)
%668 = torch.aten.view %652, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc533)
%669 = torch.aten.mm %668, %667 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc534)
%670 = torch.aten.view %669, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc535)
%671 = torch.aten.view %670, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc536)
%672 = torch.aten.transpose.int %671, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc537)
%673 = torch.aten.transpose.int %666, %int3, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,4],f32> loc(#loc538)
%674 = torch.prim.ListConstruct %int1, %int8, %int4, %int64 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1282)
%675 = torch.aten.broadcast_to %660, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc539)
%676 = torch.prim.ListConstruct %int8, %int4, %int64 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1283)
%677 = torch.aten.view %675, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc540)
%678 = torch.prim.ListConstruct %int1, %int8, %int64, %int4 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1284)
%679 = torch.aten.broadcast_to %673, %678 : !torch.vtensor<[1,8,64,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,4],f32> loc(#loc541)
%680 = torch.prim.ListConstruct %int8, %int64, %int4 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1285)
%681 = torch.aten.view %679, %680 : !torch.vtensor<[1,8,64,4],f32>, !torch.list<int> -> !torch.vtensor<[8,64,4],f32> loc(#loc542)
%682 = torch.aten.bmm %677, %681 : !torch.vtensor<[8,4,64],f32>, !torch.vtensor<[8,64,4],f32> -> !torch.vtensor<[8,4,4],f32> loc(#loc543)
%683 = torch.prim.ListConstruct %int1, %int8, %int4, %int4 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1286)
%684 = torch.aten.view %682, %683 : !torch.vtensor<[8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc545)
%685 = torch.aten.arange.start_step %int0, %int4, %int1, %int4, %none, %cpu, %false : !torch.int, !torch.int, !torch.int, !torch.int, !torch.none, !torch.Device, !torch.bool -> !torch.vtensor<[4],si64> loc(#loc546)
%686 = torch.aten.unsqueeze %685, %int1 : !torch.vtensor<[4],si64>, !torch.int -> !torch.vtensor<[4,1],si64> loc(#loc547)
%687 = torch.aten.arange.start_step %int0, %int4, %int1, %int4, %none, %cpu, %false : !torch.int, !torch.int, !torch.int, !torch.int, !torch.none, !torch.Device, !torch.bool -> !torch.vtensor<[4],si64> loc(#loc548)
%688 = torch.aten.unsqueeze %687, %int0 : !torch.vtensor<[4],si64>, !torch.int -> !torch.vtensor<[1,4],si64> loc(#loc549)
%689 = torch.aten.sub.Tensor %688, %686, %int1 : !torch.vtensor<[1,4],si64>, !torch.vtensor<[4,1],si64>, !torch.int -> !torch.vtensor<[4,4],si64> loc(#loc550)
%690 = torch.prim.NumToTensor.Scalar %int0 : !torch.int -> !torch.vtensor<[],si64> loc(#loc551)
%691 = torch.prim.ListConstruct %int4, %int4 : (!torch.int, !torch.int) -> !torch.list<int> loc(#loc551)
%692 = torch.aten.broadcast_to %690, %691 : !torch.vtensor<[],si64>, !torch.list<int> -> !torch.vtensor<[4,4],si64> loc(#loc551)
%693 = torch.aten.minimum %689, %692 : !torch.vtensor<[4,4],si64>, !torch.vtensor<[4,4],si64> -> !torch.vtensor<[4,4],si64> loc(#loc552)
%694 = torch.aten.neg %693 : !torch.vtensor<[4,4],si64> -> !torch.vtensor<[4,4],si64> loc(#loc553)
%695 = torch.aten.lt.Scalar %694, %int16 : !torch.vtensor<[4,4],si64>, !torch.int -> !torch.vtensor<[4,4],i1> loc(#loc554)
%696 = torch.aten.to.dtype %694, %int6, %false, %false, %none : !torch.vtensor<[4,4],si64>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[4,4],f32> loc(#loc555)
%697 = torch.aten.div.Scalar %696, %int16 : !torch.vtensor<[4,4],f32>, !torch.int -> !torch.vtensor<[4,4],f32> loc(#loc556)
%698 = torch.aten.log %697 : !torch.vtensor<[4,4],f32> -> !torch.vtensor<[4,4],f32> loc(#loc557)
%699 = torch.aten.div.Scalar %698, %float2.079440e00 : !torch.vtensor<[4,4],f32>, !torch.float -> !torch.vtensor<[4,4],f32> loc(#loc558)
%700 = torch.aten.mul.Scalar %699, %int16 : !torch.vtensor<[4,4],f32>, !torch.int -> !torch.vtensor<[4,4],f32> loc(#loc559)
%701 = torch.aten.to.dtype %700, %int4, %false, %false, %none : !torch.vtensor<[4,4],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[4,4],si64> loc(#loc560)
%702 = torch.aten.add.Scalar %701, %int16, %int1 : !torch.vtensor<[4,4],si64>, !torch.int, !torch.int -> !torch.vtensor<[4,4],si64> loc(#loc561)
%703 = torch.prim.NumToTensor.Scalar %int31 : !torch.int -> !torch.vtensor<[],si64> loc(#loc562)
%704 = torch.aten.broadcast_to %703, %691 : !torch.vtensor<[],si64>, !torch.list<int> -> !torch.vtensor<[4,4],si64> loc(#loc562)
%705 = torch.aten.minimum %702, %704 : !torch.vtensor<[4,4],si64>, !torch.vtensor<[4,4],si64> -> !torch.vtensor<[4,4],si64> loc(#loc563)
%706 = torch.aten.where.self %695, %694, %705 : !torch.vtensor<[4,4],i1>, !torch.vtensor<[4,4],si64>, !torch.vtensor<[4,4],si64> -> !torch.vtensor<[4,4],si64> loc(#loc564)
%707 = torch.aten.add.Scalar %706, %int0, %int1 : !torch.vtensor<[4,4],si64>, !torch.int, !torch.int -> !torch.vtensor<[4,4],si64> loc(#loc565)
%708 = torch.aten.embedding %75, %707, %int-1, %false, %false : !torch.vtensor<[32,8],f32>, !torch.vtensor<[4,4],si64>, !torch.int, !torch.bool, !torch.bool -> !torch.vtensor<[4,4,8],f32> loc(#loc566)
%709 = torch.aten.permute %708, %226 : !torch.vtensor<[4,4,8],f32>, !torch.list<int> -> !torch.vtensor<[8,4,4],f32> loc(#loc567)
%710 = torch.aten.unsqueeze %709, %int0 : !torch.vtensor<[8,4,4],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc544)
%711 = torch.aten.add.Tensor %710, %640, %int1 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,1,4,4],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc568)
%712 = torch.aten.add.Tensor %684, %711, %int1 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,4],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc569)
%values_10, %indices_11 = torch.aten.max.dim %712, %int-1, %true : !torch.vtensor<[1,8,4,4],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,4,1],f32>, !torch.vtensor<[1,8,4,1],si64> loc(#loc570)
%713 = torch.aten.sub.Tensor %712, %values_10, %int1 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,1],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc571)
%714 = torch.aten.exp %713 : !torch.vtensor<[1,8,4,4],f32> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc572)
%715 = torch.aten.sum.dim_IntList %714, %161, %true, %none : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,4,1],f32> loc(#loc573)
%716 = torch.aten.div.Tensor %714, %715 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,1],f32> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc574)
%717 = torch.aten.broadcast_to %716, %683 : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc575)
%718 = torch.prim.ListConstruct %int8, %int4, %int4 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1287)
%719 = torch.aten.view %717, %718 : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[8,4,4],f32> loc(#loc576)
%720 = torch.aten.broadcast_to %672, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc577)
%721 = torch.aten.view %720, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc578)
%722 = torch.aten.bmm %719, %721 : !torch.vtensor<[8,4,4],f32>, !torch.vtensor<[8,4,64],f32> -> !torch.vtensor<[8,4,64],f32> loc(#loc579)
%723 = torch.aten.view %722, %674 : !torch.vtensor<[8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc580)
%724 = torch.aten.transpose.int %723, %int1, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc581)
%725 = torch.aten.clone %724, %int0 : !torch.vtensor<[1,4,8,64],f32>, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc582)
%726 = torch.aten.view %725, %244 : !torch.vtensor<[1,4,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc522)
%727 = torch.aten.transpose.int %74, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc583)
%728 = torch.aten.view %726, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc584)
%729 = torch.aten.mm %728, %727 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc585)
%730 = torch.aten.view %729, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc586)
%731 = torch.aten.add.Tensor %619, %730, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc587)
%732 = torch.aten.pow.Tensor_Scalar %731, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc588)
%733 = torch.aten.sum.dim_IntList %732, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc589)
%734 = torch.aten.div.Scalar %733, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc589)
%735 = torch.aten.add.Scalar %734, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc590)
%736 = torch.aten.rsqrt %735 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc591)
%737 = torch.aten.mul.Tensor %731, %736 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc592)
%738 = torch.aten.mul.Tensor %73, %737 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc593)
%739 = torch.aten.transpose.int %72, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc594)
%740 = torch.aten.view %738, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc595)
%741 = torch.aten.mm %740, %739 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc596)
%742 = torch.aten.view %741, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc597)
%743 = torch.aten.view %742, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc598)
%744 = torch.aten.transpose.int %743, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc599)
%745 = torch.aten.transpose.int %71, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc600)
%746 = torch.aten.view %616, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc601)
%747 = torch.aten.mm %746, %745 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc602)
%748 = torch.aten.view %747, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc603)
%749 = torch.aten.view %748, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc604)
%750 = torch.aten.transpose.int %749, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc605)
%751 = torch.aten.transpose.int %70, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc606)
%752 = torch.aten.view %616, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc607)
%753 = torch.aten.mm %752, %751 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc608)
%754 = torch.aten.view %753, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc609)
%755 = torch.aten.view %754, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc610)
%756 = torch.aten.transpose.int %755, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc611)
%757 = torch.aten.transpose.int %750, %int3, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,15],f32> loc(#loc612)
%758 = torch.aten.broadcast_to %744, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc613)
%759 = torch.aten.view %758, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc614)
%760 = torch.aten.broadcast_to %757, %194 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,15],f32> loc(#loc615)
%761 = torch.aten.view %760, %196 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[8,64,15],f32> loc(#loc616)
%762 = torch.aten.bmm %759, %761 : !torch.vtensor<[8,4,64],f32>, !torch.vtensor<[8,64,15],f32> -> !torch.vtensor<[8,4,15],f32> loc(#loc617)
%763 = torch.prim.ListConstruct %int1, %int8, %int4, %int15 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1288)
%764 = torch.aten.view %762, %763 : !torch.vtensor<[8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc621)
%765 = torch.aten.zeros %763, %int6, %none, %cpu, %false : !torch.list<int>, !torch.int, !torch.none, !torch.Device, !torch.bool -> !torch.vtensor<[1,8,4,15],f32> loc(#loc622)
%766 = torch.aten.add.Tensor %765, %645, %int1 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,1,1,15],f32>, !torch.int -> !torch.vtensor<[1,8,4,15],f32> loc(#loc620)
%767 = torch.aten.add.Tensor %764, %766, %int1 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,15],f32>, !torch.int -> !torch.vtensor<[1,8,4,15],f32> loc(#loc623)
%values_12, %indices_13 = torch.aten.max.dim %767, %int-1, %true : !torch.vtensor<[1,8,4,15],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,4,1],f32>, !torch.vtensor<[1,8,4,1],si64> loc(#loc624)
%768 = torch.aten.sub.Tensor %767, %values_12, %int1 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,1],f32>, !torch.int -> !torch.vtensor<[1,8,4,15],f32> loc(#loc625)
%769 = torch.aten.exp %768 : !torch.vtensor<[1,8,4,15],f32> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc626)
%770 = torch.aten.sum.dim_IntList %769, %161, %true, %none : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,4,1],f32> loc(#loc627)
%771 = torch.aten.div.Tensor %769, %770 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,1],f32> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc628)
%772 = torch.aten.broadcast_to %771, %763 : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc629)
%773 = torch.prim.ListConstruct %int8, %int4, %int15 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1289)
%774 = torch.aten.view %772, %773 : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[8,4,15],f32> loc(#loc630)
%775 = torch.aten.broadcast_to %756, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc631)
%776 = torch.aten.view %775, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc632)
%777 = torch.aten.bmm %774, %776 : !torch.vtensor<[8,4,15],f32>, !torch.vtensor<[8,15,64],f32> -> !torch.vtensor<[8,4,64],f32> loc(#loc633)
%778 = torch.aten.view %777, %674 : !torch.vtensor<[8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc634)
%779 = torch.aten.transpose.int %778, %int1, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc635)
%780 = torch.aten.clone %779, %int0 : !torch.vtensor<[1,4,8,64],f32>, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc636)
%781 = torch.aten.view %780, %244 : !torch.vtensor<[1,4,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc637)
%782 = torch.aten.transpose.int %69, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc638)
%783 = torch.aten.view %781, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc639)
%784 = torch.aten.mm %783, %782 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc640)
%785 = torch.aten.view %784, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc641)
%786 = torch.aten.add.Tensor %731, %785, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc642)
%787 = torch.aten.pow.Tensor_Scalar %786, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc643)
%788 = torch.aten.sum.dim_IntList %787, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc644)
%789 = torch.aten.div.Scalar %788, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc644)
%790 = torch.aten.add.Scalar %789, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc645)
%791 = torch.aten.rsqrt %790 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc646)
%792 = torch.aten.mul.Tensor %786, %791 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc647)
%793 = torch.aten.mul.Tensor %68, %792 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc648)
%794 = torch.aten.transpose.int %67, %int0, %int1 : !torch.vtensor<[2048,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,2048],f32> loc(#loc649)
%795 = torch.aten.view %793, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc650)
%796 = torch.aten.mm %795, %794 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,2048],f32> -> !torch.vtensor<[4,2048],f32> loc(#loc651)
%797 = torch.prim.ListConstruct %int1, %int4, %int2048 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1290)
%798 = torch.aten.view %796, %797 : !torch.vtensor<[4,2048],f32>, !torch.list<int> -> !torch.vtensor<[1,4,2048],f32> loc(#loc653)
%799 = torch.aten.relu %798 : !torch.vtensor<[1,4,2048],f32> -> !torch.vtensor<[1,4,2048],f32> loc(#loc652)
%800 = torch.aten.transpose.int %66, %int0, %int1 : !torch.vtensor<[512,2048],f32>, !torch.int, !torch.int -> !torch.vtensor<[2048,512],f32> loc(#loc654)
%801 = torch.prim.ListConstruct %int4, %int2048 : (!torch.int, !torch.int) -> !torch.list<int> loc(#loc1291)
%802 = torch.aten.view %799, %801 : !torch.vtensor<[1,4,2048],f32>, !torch.list<int> -> !torch.vtensor<[4,2048],f32> loc(#loc655)
%803 = torch.aten.mm %802, %800 : !torch.vtensor<[4,2048],f32>, !torch.vtensor<[2048,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc656)
%804 = torch.aten.view %803, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc657)
%805 = torch.aten.add.Tensor %786, %804, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc658)
%806 = torch.aten.pow.Tensor_Scalar %805, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc659)
%807 = torch.aten.sum.dim_IntList %806, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc660)
%808 = torch.aten.div.Scalar %807, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc660)
%809 = torch.aten.add.Scalar %808, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc661)
%810 = torch.aten.rsqrt %809 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc662)
%811 = torch.aten.mul.Tensor %805, %810 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc663)
%812 = torch.aten.mul.Tensor %65, %811 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc664)
%813 = torch.aten.transpose.int %64, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc665)
%814 = torch.aten.view %812, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc666)
%815 = torch.aten.mm %814, %813 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc667)
%816 = torch.aten.view %815, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc668)
%817 = torch.aten.view %816, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc669)
%818 = torch.aten.transpose.int %817, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc670)
%819 = torch.aten.transpose.int %63, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc671)
%820 = torch.aten.view %812, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc672)
%821 = torch.aten.mm %820, %819 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc673)
%822 = torch.aten.view %821, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc674)
%823 = torch.aten.view %822, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc675)
%824 = torch.aten.transpose.int %823, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc676)
%825 = torch.aten.transpose.int %62, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc677)
%826 = torch.aten.view %812, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc678)
%827 = torch.aten.mm %826, %825 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc679)
%828 = torch.aten.view %827, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc680)
%829 = torch.aten.view %828, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc681)
%830 = torch.aten.transpose.int %829, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc682)
%831 = torch.aten.transpose.int %824, %int3, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,4],f32> loc(#loc683)
%832 = torch.aten.broadcast_to %818, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc684)
%833 = torch.aten.view %832, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc685)
%834 = torch.aten.broadcast_to %831, %678 : !torch.vtensor<[1,8,64,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,4],f32> loc(#loc686)
%835 = torch.aten.view %834, %680 : !torch.vtensor<[1,8,64,4],f32>, !torch.list<int> -> !torch.vtensor<[8,64,4],f32> loc(#loc687)
%836 = torch.aten.bmm %833, %835 : !torch.vtensor<[8,4,64],f32>, !torch.vtensor<[8,64,4],f32> -> !torch.vtensor<[8,4,4],f32> loc(#loc688)
%837 = torch.aten.view %836, %683 : !torch.vtensor<[8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc689)
%838 = torch.aten.add.Tensor %837, %711, %int1 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,4],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc690)
%values_14, %indices_15 = torch.aten.max.dim %838, %int-1, %true : !torch.vtensor<[1,8,4,4],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,4,1],f32>, !torch.vtensor<[1,8,4,1],si64> loc(#loc691)
%839 = torch.aten.sub.Tensor %838, %values_14, %int1 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,1],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc692)
%840 = torch.aten.exp %839 : !torch.vtensor<[1,8,4,4],f32> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc693)
%841 = torch.aten.sum.dim_IntList %840, %161, %true, %none : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,4,1],f32> loc(#loc694)
%842 = torch.aten.div.Tensor %840, %841 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,1],f32> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc695)
%843 = torch.aten.broadcast_to %842, %683 : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc696)
%844 = torch.aten.view %843, %718 : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[8,4,4],f32> loc(#loc697)
%845 = torch.aten.broadcast_to %830, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc698)
%846 = torch.aten.view %845, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc699)
%847 = torch.aten.bmm %844, %846 : !torch.vtensor<[8,4,4],f32>, !torch.vtensor<[8,4,64],f32> -> !torch.vtensor<[8,4,64],f32> loc(#loc700)
%848 = torch.aten.view %847, %674 : !torch.vtensor<[8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc701)
%849 = torch.aten.transpose.int %848, %int1, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc702)
%850 = torch.aten.clone %849, %int0 : !torch.vtensor<[1,4,8,64],f32>, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc703)
%851 = torch.aten.view %850, %244 : !torch.vtensor<[1,4,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc704)
%852 = torch.aten.transpose.int %61, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc705)
%853 = torch.aten.view %851, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc706)
%854 = torch.aten.mm %853, %852 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc707)
%855 = torch.aten.view %854, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc708)
%856 = torch.aten.add.Tensor %805, %855, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc709)
%857 = torch.aten.pow.Tensor_Scalar %856, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc710)
%858 = torch.aten.sum.dim_IntList %857, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc711)
%859 = torch.aten.div.Scalar %858, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc711)
%860 = torch.aten.add.Scalar %859, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc712)
%861 = torch.aten.rsqrt %860 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc713)
%862 = torch.aten.mul.Tensor %856, %861 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc714)
%863 = torch.aten.mul.Tensor %60, %862 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc715)
%864 = torch.aten.transpose.int %59, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc716)
%865 = torch.aten.view %863, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc717)
%866 = torch.aten.mm %865, %864 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc718)
%867 = torch.aten.view %866, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc719)
%868 = torch.aten.view %867, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc720)
%869 = torch.aten.transpose.int %868, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc721)
%870 = torch.aten.transpose.int %58, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc722)
%871 = torch.aten.view %616, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc723)
%872 = torch.aten.mm %871, %870 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc724)
%873 = torch.aten.view %872, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc725)
%874 = torch.aten.view %873, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc726)
%875 = torch.aten.transpose.int %874, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc727)
%876 = torch.aten.transpose.int %57, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc728)
%877 = torch.aten.view %616, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc729)
%878 = torch.aten.mm %877, %876 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc730)
%879 = torch.aten.view %878, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc731)
%880 = torch.aten.view %879, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc732)
%881 = torch.aten.transpose.int %880, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc733)
%882 = torch.aten.transpose.int %875, %int3, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,15],f32> loc(#loc734)
%883 = torch.aten.broadcast_to %869, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc735)
%884 = torch.aten.view %883, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc736)
%885 = torch.aten.broadcast_to %882, %194 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,15],f32> loc(#loc737)
%886 = torch.aten.view %885, %196 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[8,64,15],f32> loc(#loc738)
%887 = torch.aten.bmm %884, %886 : !torch.vtensor<[8,4,64],f32>, !torch.vtensor<[8,64,15],f32> -> !torch.vtensor<[8,4,15],f32> loc(#loc739)
%888 = torch.aten.view %887, %763 : !torch.vtensor<[8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc740)
%889 = torch.aten.add.Tensor %888, %766, %int1 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,15],f32>, !torch.int -> !torch.vtensor<[1,8,4,15],f32> loc(#loc741)
%values_16, %indices_17 = torch.aten.max.dim %889, %int-1, %true : !torch.vtensor<[1,8,4,15],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,4,1],f32>, !torch.vtensor<[1,8,4,1],si64> loc(#loc742)
%890 = torch.aten.sub.Tensor %889, %values_16, %int1 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,1],f32>, !torch.int -> !torch.vtensor<[1,8,4,15],f32> loc(#loc743)
%891 = torch.aten.exp %890 : !torch.vtensor<[1,8,4,15],f32> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc744)
%892 = torch.aten.sum.dim_IntList %891, %161, %true, %none : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,4,1],f32> loc(#loc745)
%893 = torch.aten.div.Tensor %891, %892 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,1],f32> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc746)
%894 = torch.aten.broadcast_to %893, %763 : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc747)
%895 = torch.aten.view %894, %773 : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[8,4,15],f32> loc(#loc748)
%896 = torch.aten.broadcast_to %881, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc749)
%897 = torch.aten.view %896, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc750)
%898 = torch.aten.bmm %895, %897 : !torch.vtensor<[8,4,15],f32>, !torch.vtensor<[8,15,64],f32> -> !torch.vtensor<[8,4,64],f32> loc(#loc751)
%899 = torch.aten.view %898, %674 : !torch.vtensor<[8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc752)
%900 = torch.aten.transpose.int %899, %int1, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc753)
%901 = torch.aten.clone %900, %int0 : !torch.vtensor<[1,4,8,64],f32>, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc754)
%902 = torch.aten.view %901, %244 : !torch.vtensor<[1,4,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc755)
%903 = torch.aten.transpose.int %56, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc756)
%904 = torch.aten.view %902, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc757)
%905 = torch.aten.mm %904, %903 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc758)
%906 = torch.aten.view %905, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc759)
%907 = torch.aten.add.Tensor %856, %906, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc760)
%908 = torch.aten.pow.Tensor_Scalar %907, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc761)
%909 = torch.aten.sum.dim_IntList %908, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc762)
%910 = torch.aten.div.Scalar %909, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc762)
%911 = torch.aten.add.Scalar %910, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc763)
%912 = torch.aten.rsqrt %911 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc764)
%913 = torch.aten.mul.Tensor %907, %912 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc765)
%914 = torch.aten.mul.Tensor %55, %913 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc766)
%915 = torch.aten.transpose.int %54, %int0, %int1 : !torch.vtensor<[2048,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,2048],f32> loc(#loc767)
%916 = torch.aten.view %914, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc768)
%917 = torch.aten.mm %916, %915 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,2048],f32> -> !torch.vtensor<[4,2048],f32> loc(#loc769)
%918 = torch.aten.view %917, %797 : !torch.vtensor<[4,2048],f32>, !torch.list<int> -> !torch.vtensor<[1,4,2048],f32> loc(#loc770)
%919 = torch.aten.relu %918 : !torch.vtensor<[1,4,2048],f32> -> !torch.vtensor<[1,4,2048],f32> loc(#loc771)
%920 = torch.aten.transpose.int %53, %int0, %int1 : !torch.vtensor<[512,2048],f32>, !torch.int, !torch.int -> !torch.vtensor<[2048,512],f32> loc(#loc772)
%921 = torch.aten.view %919, %801 : !torch.vtensor<[1,4,2048],f32>, !torch.list<int> -> !torch.vtensor<[4,2048],f32> loc(#loc773)
%922 = torch.aten.mm %921, %920 : !torch.vtensor<[4,2048],f32>, !torch.vtensor<[2048,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc774)
%923 = torch.aten.view %922, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc775)
%924 = torch.aten.add.Tensor %907, %923, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc776)
%925 = torch.aten.pow.Tensor_Scalar %924, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc777)
%926 = torch.aten.sum.dim_IntList %925, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc778)
%927 = torch.aten.div.Scalar %926, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc778)
%928 = torch.aten.add.Scalar %927, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc779)
%929 = torch.aten.rsqrt %928 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc780)
%930 = torch.aten.mul.Tensor %924, %929 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc781)
%931 = torch.aten.mul.Tensor %52, %930 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc782)
%932 = torch.aten.transpose.int %51, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc783)
%933 = torch.aten.view %931, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc784)
%934 = torch.aten.mm %933, %932 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc785)
%935 = torch.aten.view %934, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc786)
%936 = torch.aten.view %935, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc787)
%937 = torch.aten.transpose.int %936, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc788)
%938 = torch.aten.transpose.int %50, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc789)
%939 = torch.aten.view %931, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc790)
%940 = torch.aten.mm %939, %938 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc791)
%941 = torch.aten.view %940, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc792)
%942 = torch.aten.view %941, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc793)
%943 = torch.aten.transpose.int %942, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc794)
%944 = torch.aten.transpose.int %49, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc795)
%945 = torch.aten.view %931, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc796)
%946 = torch.aten.mm %945, %944 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc797)
%947 = torch.aten.view %946, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc798)
%948 = torch.aten.view %947, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc799)
%949 = torch.aten.transpose.int %948, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc800)
%950 = torch.aten.transpose.int %943, %int3, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,4],f32> loc(#loc801)
%951 = torch.aten.broadcast_to %937, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc802)
%952 = torch.aten.view %951, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc803)
%953 = torch.aten.broadcast_to %950, %678 : !torch.vtensor<[1,8,64,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,4],f32> loc(#loc804)
%954 = torch.aten.view %953, %680 : !torch.vtensor<[1,8,64,4],f32>, !torch.list<int> -> !torch.vtensor<[8,64,4],f32> loc(#loc805)
%955 = torch.aten.bmm %952, %954 : !torch.vtensor<[8,4,64],f32>, !torch.vtensor<[8,64,4],f32> -> !torch.vtensor<[8,4,4],f32> loc(#loc806)
%956 = torch.aten.view %955, %683 : !torch.vtensor<[8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc807)
%957 = torch.aten.add.Tensor %956, %711, %int1 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,4],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc808)
%values_18, %indices_19 = torch.aten.max.dim %957, %int-1, %true : !torch.vtensor<[1,8,4,4],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,4,1],f32>, !torch.vtensor<[1,8,4,1],si64> loc(#loc809)
%958 = torch.aten.sub.Tensor %957, %values_18, %int1 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,1],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc810)
%959 = torch.aten.exp %958 : !torch.vtensor<[1,8,4,4],f32> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc811)
%960 = torch.aten.sum.dim_IntList %959, %161, %true, %none : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,4,1],f32> loc(#loc812)
%961 = torch.aten.div.Tensor %959, %960 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,1],f32> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc813)
%962 = torch.aten.broadcast_to %961, %683 : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc814)
%963 = torch.aten.view %962, %718 : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[8,4,4],f32> loc(#loc815)
%964 = torch.aten.broadcast_to %949, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc816)
%965 = torch.aten.view %964, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc817)
%966 = torch.aten.bmm %963, %965 : !torch.vtensor<[8,4,4],f32>, !torch.vtensor<[8,4,64],f32> -> !torch.vtensor<[8,4,64],f32> loc(#loc818)
%967 = torch.aten.view %966, %674 : !torch.vtensor<[8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc819)
%968 = torch.aten.transpose.int %967, %int1, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc820)
%969 = torch.aten.clone %968, %int0 : !torch.vtensor<[1,4,8,64],f32>, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc821)
%970 = torch.aten.view %969, %244 : !torch.vtensor<[1,4,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc822)
%971 = torch.aten.transpose.int %48, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc823)
%972 = torch.aten.view %970, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc824)
%973 = torch.aten.mm %972, %971 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc825)
%974 = torch.aten.view %973, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc826)
%975 = torch.aten.add.Tensor %924, %974, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc827)
%976 = torch.aten.pow.Tensor_Scalar %975, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc828)
%977 = torch.aten.sum.dim_IntList %976, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc829)
%978 = torch.aten.div.Scalar %977, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc829)
%979 = torch.aten.add.Scalar %978, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc830)
%980 = torch.aten.rsqrt %979 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc831)
%981 = torch.aten.mul.Tensor %975, %980 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc832)
%982 = torch.aten.mul.Tensor %47, %981 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc833)
%983 = torch.aten.transpose.int %46, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc834)
%984 = torch.aten.view %982, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc835)
%985 = torch.aten.mm %984, %983 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc836)
%986 = torch.aten.view %985, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc837)
%987 = torch.aten.view %986, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc838)
%988 = torch.aten.transpose.int %987, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc839)
%989 = torch.aten.transpose.int %45, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc840)
%990 = torch.aten.view %616, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc841)
%991 = torch.aten.mm %990, %989 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc842)
%992 = torch.aten.view %991, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc843)
%993 = torch.aten.view %992, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc844)
%994 = torch.aten.transpose.int %993, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc845)
%995 = torch.aten.transpose.int %44, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc846)
%996 = torch.aten.view %616, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc847)
%997 = torch.aten.mm %996, %995 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc848)
%998 = torch.aten.view %997, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc849)
%999 = torch.aten.view %998, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc850)
%1000 = torch.aten.transpose.int %999, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc851)
%1001 = torch.aten.transpose.int %994, %int3, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,15],f32> loc(#loc852)
%1002 = torch.aten.broadcast_to %988, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc853)
%1003 = torch.aten.view %1002, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc854)
%1004 = torch.aten.broadcast_to %1001, %194 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,15],f32> loc(#loc855)
%1005 = torch.aten.view %1004, %196 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[8,64,15],f32> loc(#loc856)
%1006 = torch.aten.bmm %1003, %1005 : !torch.vtensor<[8,4,64],f32>, !torch.vtensor<[8,64,15],f32> -> !torch.vtensor<[8,4,15],f32> loc(#loc857)
%1007 = torch.aten.view %1006, %763 : !torch.vtensor<[8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc858)
%1008 = torch.aten.add.Tensor %1007, %766, %int1 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,15],f32>, !torch.int -> !torch.vtensor<[1,8,4,15],f32> loc(#loc859)
%values_20, %indices_21 = torch.aten.max.dim %1008, %int-1, %true : !torch.vtensor<[1,8,4,15],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,4,1],f32>, !torch.vtensor<[1,8,4,1],si64> loc(#loc860)
%1009 = torch.aten.sub.Tensor %1008, %values_20, %int1 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,1],f32>, !torch.int -> !torch.vtensor<[1,8,4,15],f32> loc(#loc861)
%1010 = torch.aten.exp %1009 : !torch.vtensor<[1,8,4,15],f32> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc862)
%1011 = torch.aten.sum.dim_IntList %1010, %161, %true, %none : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,4,1],f32> loc(#loc863)
%1012 = torch.aten.div.Tensor %1010, %1011 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,1],f32> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc864)
%1013 = torch.aten.broadcast_to %1012, %763 : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc865)
%1014 = torch.aten.view %1013, %773 : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[8,4,15],f32> loc(#loc866)
%1015 = torch.aten.broadcast_to %1000, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc867)
%1016 = torch.aten.view %1015, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc868)
%1017 = torch.aten.bmm %1014, %1016 : !torch.vtensor<[8,4,15],f32>, !torch.vtensor<[8,15,64],f32> -> !torch.vtensor<[8,4,64],f32> loc(#loc869)
%1018 = torch.aten.view %1017, %674 : !torch.vtensor<[8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc870)
%1019 = torch.aten.transpose.int %1018, %int1, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc871)
%1020 = torch.aten.clone %1019, %int0 : !torch.vtensor<[1,4,8,64],f32>, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc872)
%1021 = torch.aten.view %1020, %244 : !torch.vtensor<[1,4,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc873)
%1022 = torch.aten.transpose.int %43, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc874)
%1023 = torch.aten.view %1021, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc875)
%1024 = torch.aten.mm %1023, %1022 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc876)
%1025 = torch.aten.view %1024, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc877)
%1026 = torch.aten.add.Tensor %975, %1025, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc878)
%1027 = torch.aten.pow.Tensor_Scalar %1026, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc879)
%1028 = torch.aten.sum.dim_IntList %1027, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc880)
%1029 = torch.aten.div.Scalar %1028, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc880)
%1030 = torch.aten.add.Scalar %1029, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc881)
%1031 = torch.aten.rsqrt %1030 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc882)
%1032 = torch.aten.mul.Tensor %1026, %1031 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc883)
%1033 = torch.aten.mul.Tensor %42, %1032 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc884)
%1034 = torch.aten.transpose.int %41, %int0, %int1 : !torch.vtensor<[2048,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,2048],f32> loc(#loc885)
%1035 = torch.aten.view %1033, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc886)
%1036 = torch.aten.mm %1035, %1034 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,2048],f32> -> !torch.vtensor<[4,2048],f32> loc(#loc887)
%1037 = torch.aten.view %1036, %797 : !torch.vtensor<[4,2048],f32>, !torch.list<int> -> !torch.vtensor<[1,4,2048],f32> loc(#loc888)
%1038 = torch.aten.relu %1037 : !torch.vtensor<[1,4,2048],f32> -> !torch.vtensor<[1,4,2048],f32> loc(#loc889)
%1039 = torch.aten.transpose.int %40, %int0, %int1 : !torch.vtensor<[512,2048],f32>, !torch.int, !torch.int -> !torch.vtensor<[2048,512],f32> loc(#loc890)
%1040 = torch.aten.view %1038, %801 : !torch.vtensor<[1,4,2048],f32>, !torch.list<int> -> !torch.vtensor<[4,2048],f32> loc(#loc891)
%1041 = torch.aten.mm %1040, %1039 : !torch.vtensor<[4,2048],f32>, !torch.vtensor<[2048,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc892)
%1042 = torch.aten.view %1041, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc893)
%1043 = torch.aten.add.Tensor %1026, %1042, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc894)
%1044 = torch.aten.pow.Tensor_Scalar %1043, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc895)
%1045 = torch.aten.sum.dim_IntList %1044, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc896)
%1046 = torch.aten.div.Scalar %1045, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc896)
%1047 = torch.aten.add.Scalar %1046, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc897)
%1048 = torch.aten.rsqrt %1047 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc898)
%1049 = torch.aten.mul.Tensor %1043, %1048 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc899)
%1050 = torch.aten.mul.Tensor %39, %1049 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc900)
%1051 = torch.aten.transpose.int %38, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc901)
%1052 = torch.aten.view %1050, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc902)
%1053 = torch.aten.mm %1052, %1051 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc903)
%1054 = torch.aten.view %1053, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc904)
%1055 = torch.aten.view %1054, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc905)
%1056 = torch.aten.transpose.int %1055, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc906)
%1057 = torch.aten.transpose.int %37, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc907)
%1058 = torch.aten.view %1050, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc908)
%1059 = torch.aten.mm %1058, %1057 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc909)
%1060 = torch.aten.view %1059, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc910)
%1061 = torch.aten.view %1060, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc911)
%1062 = torch.aten.transpose.int %1061, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc912)
%1063 = torch.aten.transpose.int %36, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc913)
%1064 = torch.aten.view %1050, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc914)
%1065 = torch.aten.mm %1064, %1063 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc915)
%1066 = torch.aten.view %1065, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc916)
%1067 = torch.aten.view %1066, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc917)
%1068 = torch.aten.transpose.int %1067, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc918)
%1069 = torch.aten.transpose.int %1062, %int3, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,4],f32> loc(#loc919)
%1070 = torch.aten.broadcast_to %1056, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc920)
%1071 = torch.aten.view %1070, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc921)
%1072 = torch.aten.broadcast_to %1069, %678 : !torch.vtensor<[1,8,64,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,4],f32> loc(#loc922)
%1073 = torch.aten.view %1072, %680 : !torch.vtensor<[1,8,64,4],f32>, !torch.list<int> -> !torch.vtensor<[8,64,4],f32> loc(#loc923)
%1074 = torch.aten.bmm %1071, %1073 : !torch.vtensor<[8,4,64],f32>, !torch.vtensor<[8,64,4],f32> -> !torch.vtensor<[8,4,4],f32> loc(#loc924)
%1075 = torch.aten.view %1074, %683 : !torch.vtensor<[8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc925)
%1076 = torch.aten.add.Tensor %1075, %711, %int1 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,4],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc926)
%values_22, %indices_23 = torch.aten.max.dim %1076, %int-1, %true : !torch.vtensor<[1,8,4,4],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,4,1],f32>, !torch.vtensor<[1,8,4,1],si64> loc(#loc927)
%1077 = torch.aten.sub.Tensor %1076, %values_22, %int1 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,1],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc928)
%1078 = torch.aten.exp %1077 : !torch.vtensor<[1,8,4,4],f32> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc929)
%1079 = torch.aten.sum.dim_IntList %1078, %161, %true, %none : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,4,1],f32> loc(#loc930)
%1080 = torch.aten.div.Tensor %1078, %1079 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,1],f32> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc931)
%1081 = torch.aten.broadcast_to %1080, %683 : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc932)
%1082 = torch.aten.view %1081, %718 : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[8,4,4],f32> loc(#loc933)
%1083 = torch.aten.broadcast_to %1068, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc934)
%1084 = torch.aten.view %1083, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc935)
%1085 = torch.aten.bmm %1082, %1084 : !torch.vtensor<[8,4,4],f32>, !torch.vtensor<[8,4,64],f32> -> !torch.vtensor<[8,4,64],f32> loc(#loc936)
%1086 = torch.aten.view %1085, %674 : !torch.vtensor<[8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc937)
%1087 = torch.aten.transpose.int %1086, %int1, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc938)
%1088 = torch.aten.clone %1087, %int0 : !torch.vtensor<[1,4,8,64],f32>, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc939)
%1089 = torch.aten.view %1088, %244 : !torch.vtensor<[1,4,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc940)
%1090 = torch.aten.transpose.int %35, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc941)
%1091 = torch.aten.view %1089, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc942)
%1092 = torch.aten.mm %1091, %1090 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc943)
%1093 = torch.aten.view %1092, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc944)
%1094 = torch.aten.add.Tensor %1043, %1093, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc945)
%1095 = torch.aten.pow.Tensor_Scalar %1094, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc946)
%1096 = torch.aten.sum.dim_IntList %1095, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc947)
%1097 = torch.aten.div.Scalar %1096, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc947)
%1098 = torch.aten.add.Scalar %1097, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc948)
%1099 = torch.aten.rsqrt %1098 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc949)
%1100 = torch.aten.mul.Tensor %1094, %1099 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc950)
%1101 = torch.aten.mul.Tensor %34, %1100 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc951)
%1102 = torch.aten.transpose.int %33, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc952)
%1103 = torch.aten.view %1101, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc953)
%1104 = torch.aten.mm %1103, %1102 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc954)
%1105 = torch.aten.view %1104, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc955)
%1106 = torch.aten.view %1105, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc956)
%1107 = torch.aten.transpose.int %1106, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc957)
%1108 = torch.aten.transpose.int %32, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc958)
%1109 = torch.aten.view %616, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc959)
%1110 = torch.aten.mm %1109, %1108 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc960)
%1111 = torch.aten.view %1110, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc961)
%1112 = torch.aten.view %1111, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc962)
%1113 = torch.aten.transpose.int %1112, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc963)
%1114 = torch.aten.transpose.int %31, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc964)
%1115 = torch.aten.view %616, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc965)
%1116 = torch.aten.mm %1115, %1114 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc966)
%1117 = torch.aten.view %1116, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc967)
%1118 = torch.aten.view %1117, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc968)
%1119 = torch.aten.transpose.int %1118, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc969)
%1120 = torch.aten.transpose.int %1113, %int3, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,15],f32> loc(#loc970)
%1121 = torch.aten.broadcast_to %1107, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc971)
%1122 = torch.aten.view %1121, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc972)
%1123 = torch.aten.broadcast_to %1120, %194 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,15],f32> loc(#loc973)
%1124 = torch.aten.view %1123, %196 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[8,64,15],f32> loc(#loc974)
%1125 = torch.aten.bmm %1122, %1124 : !torch.vtensor<[8,4,64],f32>, !torch.vtensor<[8,64,15],f32> -> !torch.vtensor<[8,4,15],f32> loc(#loc975)
%1126 = torch.aten.view %1125, %763 : !torch.vtensor<[8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc976)
%1127 = torch.aten.add.Tensor %1126, %766, %int1 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,15],f32>, !torch.int -> !torch.vtensor<[1,8,4,15],f32> loc(#loc977)
%values_24, %indices_25 = torch.aten.max.dim %1127, %int-1, %true : !torch.vtensor<[1,8,4,15],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,4,1],f32>, !torch.vtensor<[1,8,4,1],si64> loc(#loc978)
%1128 = torch.aten.sub.Tensor %1127, %values_24, %int1 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,1],f32>, !torch.int -> !torch.vtensor<[1,8,4,15],f32> loc(#loc979)
%1129 = torch.aten.exp %1128 : !torch.vtensor<[1,8,4,15],f32> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc980)
%1130 = torch.aten.sum.dim_IntList %1129, %161, %true, %none : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,4,1],f32> loc(#loc981)
%1131 = torch.aten.div.Tensor %1129, %1130 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,1],f32> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc982)
%1132 = torch.aten.broadcast_to %1131, %763 : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc983)
%1133 = torch.aten.view %1132, %773 : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[8,4,15],f32> loc(#loc984)
%1134 = torch.aten.broadcast_to %1119, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc985)
%1135 = torch.aten.view %1134, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc986)
%1136 = torch.aten.bmm %1133, %1135 : !torch.vtensor<[8,4,15],f32>, !torch.vtensor<[8,15,64],f32> -> !torch.vtensor<[8,4,64],f32> loc(#loc987)
%1137 = torch.aten.view %1136, %674 : !torch.vtensor<[8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc988)
%1138 = torch.aten.transpose.int %1137, %int1, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc989)
%1139 = torch.aten.clone %1138, %int0 : !torch.vtensor<[1,4,8,64],f32>, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc990)
%1140 = torch.aten.view %1139, %244 : !torch.vtensor<[1,4,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc991)
%1141 = torch.aten.transpose.int %30, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc992)
%1142 = torch.aten.view %1140, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc993)
%1143 = torch.aten.mm %1142, %1141 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc994)
%1144 = torch.aten.view %1143, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc995)
%1145 = torch.aten.add.Tensor %1094, %1144, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc996)
%1146 = torch.aten.pow.Tensor_Scalar %1145, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc997)
%1147 = torch.aten.sum.dim_IntList %1146, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc998)
%1148 = torch.aten.div.Scalar %1147, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc998)
%1149 = torch.aten.add.Scalar %1148, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc999)
%1150 = torch.aten.rsqrt %1149 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc1000)
%1151 = torch.aten.mul.Tensor %1145, %1150 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1001)
%1152 = torch.aten.mul.Tensor %29, %1151 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1002)
%1153 = torch.aten.transpose.int %28, %int0, %int1 : !torch.vtensor<[2048,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,2048],f32> loc(#loc1003)
%1154 = torch.aten.view %1152, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1004)
%1155 = torch.aten.mm %1154, %1153 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,2048],f32> -> !torch.vtensor<[4,2048],f32> loc(#loc1005)
%1156 = torch.aten.view %1155, %797 : !torch.vtensor<[4,2048],f32>, !torch.list<int> -> !torch.vtensor<[1,4,2048],f32> loc(#loc1006)
%1157 = torch.aten.relu %1156 : !torch.vtensor<[1,4,2048],f32> -> !torch.vtensor<[1,4,2048],f32> loc(#loc1007)
%1158 = torch.aten.transpose.int %27, %int0, %int1 : !torch.vtensor<[512,2048],f32>, !torch.int, !torch.int -> !torch.vtensor<[2048,512],f32> loc(#loc1008)
%1159 = torch.aten.view %1157, %801 : !torch.vtensor<[1,4,2048],f32>, !torch.list<int> -> !torch.vtensor<[4,2048],f32> loc(#loc1009)
%1160 = torch.aten.mm %1159, %1158 : !torch.vtensor<[4,2048],f32>, !torch.vtensor<[2048,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1010)
%1161 = torch.aten.view %1160, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1011)
%1162 = torch.aten.add.Tensor %1145, %1161, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1012)
%1163 = torch.aten.pow.Tensor_Scalar %1162, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1013)
%1164 = torch.aten.sum.dim_IntList %1163, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc1014)
%1165 = torch.aten.div.Scalar %1164, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1014)
%1166 = torch.aten.add.Scalar %1165, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1015)
%1167 = torch.aten.rsqrt %1166 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc1016)
%1168 = torch.aten.mul.Tensor %1162, %1167 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1017)
%1169 = torch.aten.mul.Tensor %26, %1168 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1018)
%1170 = torch.aten.transpose.int %25, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1019)
%1171 = torch.aten.view %1169, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1020)
%1172 = torch.aten.mm %1171, %1170 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1021)
%1173 = torch.aten.view %1172, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1022)
%1174 = torch.aten.view %1173, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1023)
%1175 = torch.aten.transpose.int %1174, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1024)
%1176 = torch.aten.transpose.int %24, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1025)
%1177 = torch.aten.view %1169, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1026)
%1178 = torch.aten.mm %1177, %1176 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1027)
%1179 = torch.aten.view %1178, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1028)
%1180 = torch.aten.view %1179, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1029)
%1181 = torch.aten.transpose.int %1180, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1030)
%1182 = torch.aten.transpose.int %23, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1031)
%1183 = torch.aten.view %1169, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1032)
%1184 = torch.aten.mm %1183, %1182 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1033)
%1185 = torch.aten.view %1184, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1034)
%1186 = torch.aten.view %1185, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1035)
%1187 = torch.aten.transpose.int %1186, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1036)
%1188 = torch.aten.transpose.int %1181, %int3, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,4],f32> loc(#loc1037)
%1189 = torch.aten.broadcast_to %1175, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1038)
%1190 = torch.aten.view %1189, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc1039)
%1191 = torch.aten.broadcast_to %1188, %678 : !torch.vtensor<[1,8,64,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,4],f32> loc(#loc1040)
%1192 = torch.aten.view %1191, %680 : !torch.vtensor<[1,8,64,4],f32>, !torch.list<int> -> !torch.vtensor<[8,64,4],f32> loc(#loc1041)
%1193 = torch.aten.bmm %1190, %1192 : !torch.vtensor<[8,4,64],f32>, !torch.vtensor<[8,64,4],f32> -> !torch.vtensor<[8,4,4],f32> loc(#loc1042)
%1194 = torch.aten.view %1193, %683 : !torch.vtensor<[8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc1043)
%1195 = torch.aten.add.Tensor %1194, %711, %int1 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,4],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc1044)
%values_26, %indices_27 = torch.aten.max.dim %1195, %int-1, %true : !torch.vtensor<[1,8,4,4],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,4,1],f32>, !torch.vtensor<[1,8,4,1],si64> loc(#loc1045)
%1196 = torch.aten.sub.Tensor %1195, %values_26, %int1 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,1],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc1046)
%1197 = torch.aten.exp %1196 : !torch.vtensor<[1,8,4,4],f32> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc1047)
%1198 = torch.aten.sum.dim_IntList %1197, %161, %true, %none : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,4,1],f32> loc(#loc1048)
%1199 = torch.aten.div.Tensor %1197, %1198 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,1],f32> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc1049)
%1200 = torch.aten.broadcast_to %1199, %683 : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc1050)
%1201 = torch.aten.view %1200, %718 : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[8,4,4],f32> loc(#loc1051)
%1202 = torch.aten.broadcast_to %1187, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1052)
%1203 = torch.aten.view %1202, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc1053)
%1204 = torch.aten.bmm %1201, %1203 : !torch.vtensor<[8,4,4],f32>, !torch.vtensor<[8,4,64],f32> -> !torch.vtensor<[8,4,64],f32> loc(#loc1054)
%1205 = torch.aten.view %1204, %674 : !torch.vtensor<[8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1055)
%1206 = torch.aten.transpose.int %1205, %int1, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1056)
%1207 = torch.aten.clone %1206, %int0 : !torch.vtensor<[1,4,8,64],f32>, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1057)
%1208 = torch.aten.view %1207, %244 : !torch.vtensor<[1,4,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1058)
%1209 = torch.aten.transpose.int %22, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1059)
%1210 = torch.aten.view %1208, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1060)
%1211 = torch.aten.mm %1210, %1209 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1061)
%1212 = torch.aten.view %1211, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1062)
%1213 = torch.aten.add.Tensor %1162, %1212, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1063)
%1214 = torch.aten.pow.Tensor_Scalar %1213, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1064)
%1215 = torch.aten.sum.dim_IntList %1214, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc1065)
%1216 = torch.aten.div.Scalar %1215, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1065)
%1217 = torch.aten.add.Scalar %1216, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1066)
%1218 = torch.aten.rsqrt %1217 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc1067)
%1219 = torch.aten.mul.Tensor %1213, %1218 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1068)
%1220 = torch.aten.mul.Tensor %21, %1219 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1069)
%1221 = torch.aten.transpose.int %20, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1070)
%1222 = torch.aten.view %1220, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1071)
%1223 = torch.aten.mm %1222, %1221 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1072)
%1224 = torch.aten.view %1223, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1073)
%1225 = torch.aten.view %1224, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1074)
%1226 = torch.aten.transpose.int %1225, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1075)
%1227 = torch.aten.transpose.int %19, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1076)
%1228 = torch.aten.view %616, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc1077)
%1229 = torch.aten.mm %1228, %1227 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc1078)
%1230 = torch.aten.view %1229, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc1079)
%1231 = torch.aten.view %1230, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc1080)
%1232 = torch.aten.transpose.int %1231, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc1081)
%1233 = torch.aten.transpose.int %18, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1082)
%1234 = torch.aten.view %616, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc1083)
%1235 = torch.aten.mm %1234, %1233 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc1084)
%1236 = torch.aten.view %1235, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc1085)
%1237 = torch.aten.view %1236, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc1086)
%1238 = torch.aten.transpose.int %1237, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc1087)
%1239 = torch.aten.transpose.int %1232, %int3, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,15],f32> loc(#loc1088)
%1240 = torch.aten.broadcast_to %1226, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1089)
%1241 = torch.aten.view %1240, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc1090)
%1242 = torch.aten.broadcast_to %1239, %194 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,15],f32> loc(#loc1091)
%1243 = torch.aten.view %1242, %196 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[8,64,15],f32> loc(#loc1092)
%1244 = torch.aten.bmm %1241, %1243 : !torch.vtensor<[8,4,64],f32>, !torch.vtensor<[8,64,15],f32> -> !torch.vtensor<[8,4,15],f32> loc(#loc1093)
%1245 = torch.aten.view %1244, %763 : !torch.vtensor<[8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc1094)
%1246 = torch.aten.add.Tensor %1245, %766, %int1 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,15],f32>, !torch.int -> !torch.vtensor<[1,8,4,15],f32> loc(#loc1095)
%values_28, %indices_29 = torch.aten.max.dim %1246, %int-1, %true : !torch.vtensor<[1,8,4,15],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,4,1],f32>, !torch.vtensor<[1,8,4,1],si64> loc(#loc1096)
%1247 = torch.aten.sub.Tensor %1246, %values_28, %int1 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,1],f32>, !torch.int -> !torch.vtensor<[1,8,4,15],f32> loc(#loc1097)
%1248 = torch.aten.exp %1247 : !torch.vtensor<[1,8,4,15],f32> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc1098)
%1249 = torch.aten.sum.dim_IntList %1248, %161, %true, %none : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,4,1],f32> loc(#loc1099)
%1250 = torch.aten.div.Tensor %1248, %1249 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,1],f32> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc1100)
%1251 = torch.aten.broadcast_to %1250, %763 : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc1101)
%1252 = torch.aten.view %1251, %773 : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[8,4,15],f32> loc(#loc1102)
%1253 = torch.aten.broadcast_to %1238, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc1103)
%1254 = torch.aten.view %1253, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc1104)
%1255 = torch.aten.bmm %1252, %1254 : !torch.vtensor<[8,4,15],f32>, !torch.vtensor<[8,15,64],f32> -> !torch.vtensor<[8,4,64],f32> loc(#loc1105)
%1256 = torch.aten.view %1255, %674 : !torch.vtensor<[8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1106)
%1257 = torch.aten.transpose.int %1256, %int1, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1107)
%1258 = torch.aten.clone %1257, %int0 : !torch.vtensor<[1,4,8,64],f32>, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1108)
%1259 = torch.aten.view %1258, %244 : !torch.vtensor<[1,4,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1109)
%1260 = torch.aten.transpose.int %17, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1110)
%1261 = torch.aten.view %1259, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1111)
%1262 = torch.aten.mm %1261, %1260 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1112)
%1263 = torch.aten.view %1262, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1113)
%1264 = torch.aten.add.Tensor %1213, %1263, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1114)
%1265 = torch.aten.pow.Tensor_Scalar %1264, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1115)
%1266 = torch.aten.sum.dim_IntList %1265, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc1116)
%1267 = torch.aten.div.Scalar %1266, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1116)
%1268 = torch.aten.add.Scalar %1267, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1117)
%1269 = torch.aten.rsqrt %1268 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc1118)
%1270 = torch.aten.mul.Tensor %1264, %1269 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1119)
%1271 = torch.aten.mul.Tensor %16, %1270 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1120)
%1272 = torch.aten.transpose.int %15, %int0, %int1 : !torch.vtensor<[2048,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,2048],f32> loc(#loc1121)
%1273 = torch.aten.view %1271, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1122)
%1274 = torch.aten.mm %1273, %1272 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,2048],f32> -> !torch.vtensor<[4,2048],f32> loc(#loc1123)
%1275 = torch.aten.view %1274, %797 : !torch.vtensor<[4,2048],f32>, !torch.list<int> -> !torch.vtensor<[1,4,2048],f32> loc(#loc1124)
%1276 = torch.aten.relu %1275 : !torch.vtensor<[1,4,2048],f32> -> !torch.vtensor<[1,4,2048],f32> loc(#loc1125)
%1277 = torch.aten.transpose.int %14, %int0, %int1 : !torch.vtensor<[512,2048],f32>, !torch.int, !torch.int -> !torch.vtensor<[2048,512],f32> loc(#loc1126)
%1278 = torch.aten.view %1276, %801 : !torch.vtensor<[1,4,2048],f32>, !torch.list<int> -> !torch.vtensor<[4,2048],f32> loc(#loc1127)
%1279 = torch.aten.mm %1278, %1277 : !torch.vtensor<[4,2048],f32>, !torch.vtensor<[2048,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1128)
%1280 = torch.aten.view %1279, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1129)
%1281 = torch.aten.add.Tensor %1264, %1280, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1130)
%1282 = torch.aten.pow.Tensor_Scalar %1281, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1131)
%1283 = torch.aten.sum.dim_IntList %1282, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc1132)
%1284 = torch.aten.div.Scalar %1283, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1132)
%1285 = torch.aten.add.Scalar %1284, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1133)
%1286 = torch.aten.rsqrt %1285 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc1134)
%1287 = torch.aten.mul.Tensor %1281, %1286 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1135)
%1288 = torch.aten.mul.Tensor %13, %1287 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1136)
%1289 = torch.aten.transpose.int %12, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1137)
%1290 = torch.aten.view %1288, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1138)
%1291 = torch.aten.mm %1290, %1289 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1139)
%1292 = torch.aten.view %1291, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1140)
%1293 = torch.aten.view %1292, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1141)
%1294 = torch.aten.transpose.int %1293, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1142)
%1295 = torch.aten.transpose.int %11, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1143)
%1296 = torch.aten.view %1288, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1144)
%1297 = torch.aten.mm %1296, %1295 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1145)
%1298 = torch.aten.view %1297, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1146)
%1299 = torch.aten.view %1298, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1147)
%1300 = torch.aten.transpose.int %1299, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1148)
%1301 = torch.aten.transpose.int %10, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1149)
%1302 = torch.aten.view %1288, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1150)
%1303 = torch.aten.mm %1302, %1301 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1151)
%1304 = torch.aten.view %1303, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1152)
%1305 = torch.aten.view %1304, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1153)
%1306 = torch.aten.transpose.int %1305, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1154)
%1307 = torch.aten.transpose.int %1300, %int3, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,4],f32> loc(#loc1155)
%1308 = torch.aten.broadcast_to %1294, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1156)
%1309 = torch.aten.view %1308, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc1157)
%1310 = torch.aten.broadcast_to %1307, %678 : !torch.vtensor<[1,8,64,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,4],f32> loc(#loc1158)
%1311 = torch.aten.view %1310, %680 : !torch.vtensor<[1,8,64,4],f32>, !torch.list<int> -> !torch.vtensor<[8,64,4],f32> loc(#loc1159)
%1312 = torch.aten.bmm %1309, %1311 : !torch.vtensor<[8,4,64],f32>, !torch.vtensor<[8,64,4],f32> -> !torch.vtensor<[8,4,4],f32> loc(#loc1160)
%1313 = torch.aten.view %1312, %683 : !torch.vtensor<[8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc1161)
%1314 = torch.aten.add.Tensor %1313, %711, %int1 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,4],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc1162)
%values_30, %indices_31 = torch.aten.max.dim %1314, %int-1, %true : !torch.vtensor<[1,8,4,4],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,4,1],f32>, !torch.vtensor<[1,8,4,1],si64> loc(#loc1163)
%1315 = torch.aten.sub.Tensor %1314, %values_30, %int1 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,1],f32>, !torch.int -> !torch.vtensor<[1,8,4,4],f32> loc(#loc1164)
%1316 = torch.aten.exp %1315 : !torch.vtensor<[1,8,4,4],f32> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc1165)
%1317 = torch.aten.sum.dim_IntList %1316, %161, %true, %none : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,4,1],f32> loc(#loc1166)
%1318 = torch.aten.div.Tensor %1316, %1317 : !torch.vtensor<[1,8,4,4],f32>, !torch.vtensor<[1,8,4,1],f32> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc1167)
%1319 = torch.aten.broadcast_to %1318, %683 : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,4],f32> loc(#loc1168)
%1320 = torch.aten.view %1319, %718 : !torch.vtensor<[1,8,4,4],f32>, !torch.list<int> -> !torch.vtensor<[8,4,4],f32> loc(#loc1169)
%1321 = torch.aten.broadcast_to %1306, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1170)
%1322 = torch.aten.view %1321, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc1171)
%1323 = torch.aten.bmm %1320, %1322 : !torch.vtensor<[8,4,4],f32>, !torch.vtensor<[8,4,64],f32> -> !torch.vtensor<[8,4,64],f32> loc(#loc1172)
%1324 = torch.aten.view %1323, %674 : !torch.vtensor<[8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1173)
%1325 = torch.aten.transpose.int %1324, %int1, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1174)
%1326 = torch.aten.clone %1325, %int0 : !torch.vtensor<[1,4,8,64],f32>, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1175)
%1327 = torch.aten.view %1326, %244 : !torch.vtensor<[1,4,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1176)
%1328 = torch.aten.transpose.int %9, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1177)
%1329 = torch.aten.view %1327, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1178)
%1330 = torch.aten.mm %1329, %1328 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1179)
%1331 = torch.aten.view %1330, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1180)
%1332 = torch.aten.add.Tensor %1281, %1331, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1181)
%1333 = torch.aten.pow.Tensor_Scalar %1332, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1182)
%1334 = torch.aten.sum.dim_IntList %1333, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc1183)
%1335 = torch.aten.div.Scalar %1334, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1183)
%1336 = torch.aten.add.Scalar %1335, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1184)
%1337 = torch.aten.rsqrt %1336 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc1185)
%1338 = torch.aten.mul.Tensor %1332, %1337 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1186)
%1339 = torch.aten.mul.Tensor %8, %1338 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1187)
%1340 = torch.aten.transpose.int %7, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1188)
%1341 = torch.aten.view %1339, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1189)
%1342 = torch.aten.mm %1341, %1340 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1190)
%1343 = torch.aten.view %1342, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1191)
%1344 = torch.aten.view %1343, %174 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1192)
%1345 = torch.aten.transpose.int %1344, %int1, %int2 : !torch.vtensor<[1,4,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1193)
%1346 = torch.aten.transpose.int %6, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1194)
%1347 = torch.aten.view %616, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc1195)
%1348 = torch.aten.mm %1347, %1346 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc1196)
%1349 = torch.aten.view %1348, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc1197)
%1350 = torch.aten.view %1349, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc1198)
%1351 = torch.aten.transpose.int %1350, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc1199)
%1352 = torch.aten.transpose.int %5, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1200)
%1353 = torch.aten.view %616, %169 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[15,512],f32> loc(#loc1201)
%1354 = torch.aten.mm %1353, %1352 : !torch.vtensor<[15,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[15,512],f32> loc(#loc1202)
%1355 = torch.aten.view %1354, %172 : !torch.vtensor<[15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,512],f32> loc(#loc1203)
%1356 = torch.aten.view %1355, %174 : !torch.vtensor<[1,15,512],f32>, !torch.list<int> -> !torch.vtensor<[1,15,8,64],f32> loc(#loc1204)
%1357 = torch.aten.transpose.int %1356, %int1, %int2 : !torch.vtensor<[1,15,8,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,15,64],f32> loc(#loc1205)
%1358 = torch.aten.transpose.int %1351, %int3, %int2 : !torch.vtensor<[1,8,15,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,8,64,15],f32> loc(#loc1206)
%1359 = torch.aten.broadcast_to %1345, %674 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1207)
%1360 = torch.aten.view %1359, %676 : !torch.vtensor<[1,8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[8,4,64],f32> loc(#loc1208)
%1361 = torch.aten.broadcast_to %1358, %194 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,64,15],f32> loc(#loc1209)
%1362 = torch.aten.view %1361, %196 : !torch.vtensor<[1,8,64,15],f32>, !torch.list<int> -> !torch.vtensor<[8,64,15],f32> loc(#loc1210)
%1363 = torch.aten.bmm %1360, %1362 : !torch.vtensor<[8,4,64],f32>, !torch.vtensor<[8,64,15],f32> -> !torch.vtensor<[8,4,15],f32> loc(#loc1211)
%1364 = torch.aten.view %1363, %763 : !torch.vtensor<[8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc1212)
%1365 = torch.aten.add.Tensor %1364, %766, %int1 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,15],f32>, !torch.int -> !torch.vtensor<[1,8,4,15],f32> loc(#loc1213)
%values_32, %indices_33 = torch.aten.max.dim %1365, %int-1, %true : !torch.vtensor<[1,8,4,15],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,8,4,1],f32>, !torch.vtensor<[1,8,4,1],si64> loc(#loc1214)
%1366 = torch.aten.sub.Tensor %1365, %values_32, %int1 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,1],f32>, !torch.int -> !torch.vtensor<[1,8,4,15],f32> loc(#loc1215)
%1367 = torch.aten.exp %1366 : !torch.vtensor<[1,8,4,15],f32> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc1216)
%1368 = torch.aten.sum.dim_IntList %1367, %161, %true, %none : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,8,4,1],f32> loc(#loc1217)
%1369 = torch.aten.div.Tensor %1367, %1368 : !torch.vtensor<[1,8,4,15],f32>, !torch.vtensor<[1,8,4,1],f32> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc1218)
%1370 = torch.aten.broadcast_to %1369, %763 : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,15],f32> loc(#loc1219)
%1371 = torch.aten.view %1370, %773 : !torch.vtensor<[1,8,4,15],f32>, !torch.list<int> -> !torch.vtensor<[8,4,15],f32> loc(#loc1220)
%1372 = torch.aten.broadcast_to %1357, %190 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,15,64],f32> loc(#loc1221)
%1373 = torch.aten.view %1372, %192 : !torch.vtensor<[1,8,15,64],f32>, !torch.list<int> -> !torch.vtensor<[8,15,64],f32> loc(#loc1222)
%1374 = torch.aten.bmm %1371, %1373 : !torch.vtensor<[8,4,15],f32>, !torch.vtensor<[8,15,64],f32> -> !torch.vtensor<[8,4,64],f32> loc(#loc1223)
%1375 = torch.aten.view %1374, %674 : !torch.vtensor<[8,4,64],f32>, !torch.list<int> -> !torch.vtensor<[1,8,4,64],f32> loc(#loc1224)
%1376 = torch.aten.transpose.int %1375, %int1, %int2 : !torch.vtensor<[1,8,4,64],f32>, !torch.int, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1225)
%1377 = torch.aten.clone %1376, %int0 : !torch.vtensor<[1,4,8,64],f32>, !torch.int -> !torch.vtensor<[1,4,8,64],f32> loc(#loc1226)
%1378 = torch.aten.view %1377, %244 : !torch.vtensor<[1,4,8,64],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1227)
%1379 = torch.aten.transpose.int %4, %int0, %int1 : !torch.vtensor<[512,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,512],f32> loc(#loc1228)
%1380 = torch.aten.view %1378, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1229)
%1381 = torch.aten.mm %1380, %1379 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1230)
%1382 = torch.aten.view %1381, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1231)
%1383 = torch.aten.add.Tensor %1332, %1382, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1232)
%1384 = torch.aten.pow.Tensor_Scalar %1383, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1233)
%1385 = torch.aten.sum.dim_IntList %1384, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc1234)
%1386 = torch.aten.div.Scalar %1385, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1234)
%1387 = torch.aten.add.Scalar %1386, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1235)
%1388 = torch.aten.rsqrt %1387 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc1236)
%1389 = torch.aten.mul.Tensor %1383, %1388 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1237)
%1390 = torch.aten.mul.Tensor %3, %1389 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1238)
%1391 = torch.aten.transpose.int %2, %int0, %int1 : !torch.vtensor<[2048,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,2048],f32> loc(#loc1239)
%1392 = torch.aten.view %1390, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1240)
%1393 = torch.aten.mm %1392, %1391 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,2048],f32> -> !torch.vtensor<[4,2048],f32> loc(#loc1241)
%1394 = torch.aten.view %1393, %797 : !torch.vtensor<[4,2048],f32>, !torch.list<int> -> !torch.vtensor<[1,4,2048],f32> loc(#loc1242)
%1395 = torch.aten.relu %1394 : !torch.vtensor<[1,4,2048],f32> -> !torch.vtensor<[1,4,2048],f32> loc(#loc1243)
%1396 = torch.aten.transpose.int %1, %int0, %int1 : !torch.vtensor<[512,2048],f32>, !torch.int, !torch.int -> !torch.vtensor<[2048,512],f32> loc(#loc1244)
%1397 = torch.aten.view %1395, %801 : !torch.vtensor<[1,4,2048],f32>, !torch.list<int> -> !torch.vtensor<[4,2048],f32> loc(#loc1245)
%1398 = torch.aten.mm %1397, %1396 : !torch.vtensor<[4,2048],f32>, !torch.vtensor<[2048,512],f32> -> !torch.vtensor<[4,512],f32> loc(#loc1246)
%1399 = torch.aten.view %1398, %657 : !torch.vtensor<[4,512],f32>, !torch.list<int> -> !torch.vtensor<[1,4,512],f32> loc(#loc1247)
%1400 = torch.aten.add.Tensor %1383, %1399, %int1 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1248)
%1401 = torch.aten.pow.Tensor_Scalar %1400, %int2 : !torch.vtensor<[1,4,512],f32>, !torch.int -> !torch.vtensor<[1,4,512],f32> loc(#loc1249)
%1402 = torch.aten.sum.dim_IntList %1401, %161, %true, %none : !torch.vtensor<[1,4,512],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,4,1],f32> loc(#loc1250)
%1403 = torch.aten.div.Scalar %1402, %int512 : !torch.vtensor<[1,4,1],f32>, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1250)
%1404 = torch.aten.add.Scalar %1403, %float9.999990e-07, %int1 : !torch.vtensor<[1,4,1],f32>, !torch.float, !torch.int -> !torch.vtensor<[1,4,1],f32> loc(#loc1251)
%1405 = torch.aten.rsqrt %1404 : !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,1],f32> loc(#loc1252)
%1406 = torch.aten.mul.Tensor %1400, %1405 : !torch.vtensor<[1,4,512],f32>, !torch.vtensor<[1,4,1],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1253)
%1407 = torch.aten.mul.Tensor %0, %1406 : !torch.vtensor<[512],f32>, !torch.vtensor<[1,4,512],f32> -> !torch.vtensor<[1,4,512],f32> loc(#loc1254)
%1408 = torch.aten.mul.Scalar %1407, %float4.419420e-02 : !torch.vtensor<[1,4,512],f32>, !torch.float -> !torch.vtensor<[1,4,512],f32> loc(#loc1255)
%1409 = torch.aten.transpose.int %130, %int0, %int1 : !torch.vtensor<[32128,512],f32>, !torch.int, !torch.int -> !torch.vtensor<[512,32128],f32> loc(#loc1256)
%1410 = torch.aten.view %1408, %654 : !torch.vtensor<[1,4,512],f32>, !torch.list<int> -> !torch.vtensor<[4,512],f32> loc(#loc1257)
%1411 = torch.aten.mm %1410, %1409 : !torch.vtensor<[4,512],f32>, !torch.vtensor<[512,32128],f32> -> !torch.vtensor<[4,32128],f32> loc(#loc1258)
%1412 = torch.prim.ListConstruct %int1, %int4, %int32128 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> loc(#loc1292)
%1413 = torch.aten.view %1411, %1412 : !torch.vtensor<[4,32128],f32>, !torch.list<int> -> !torch.vtensor<[1,4,32128],f32> loc(#loc1259)
return %1413 : !torch.vtensor<[1,4,32128],f32> loc(#loc)
} loc(#loc)
} loc(#loc)
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@AmosLewis
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➜ t5small git:(main) ✗ torch-mlir-opt -convert-torch-to-tosa t5small_torchbackend_0327_transformers4.26.0_elide.mlir
module attributes {torch.debug_module_name = "_lambda"} {
func.func @forward(%arg0: !torch.vtensor<[1,15],si64>, %arg1: !torch.vtensor<[1,4],si64>) -> !torch.vtensor<[1,4,32128],f32> {
%0 = torch_c.to_builtin_tensor %arg1 : !torch.vtensor<[1,4],si64> -> tensor<1x4xi64>
%1 = torch_c.to_builtin_tensor %arg0 : !torch.vtensor<[1,15],si64> -> tensor<1x15xi64>
%int512 = torch.constant.int 512
%2 = torch_c.to_i64 %int512
%int0 = torch.constant.int 0
%3 = torch_c.to_i64 %int0
%int1 = torch.constant.int 1
%4 = torch_c.to_i64 %int1
%int-1 = torch.constant.int -1
%5 = torch_c.to_i64 %int-1
%true = torch.constant.bool true
%int4 = torch.constant.int 4
%6 = torch_c.to_i64 %int4
%false = torch.constant.bool false
%7 = torch_c.to_i1 %false
%none = torch.constant.none
%int15 = torch.constant.int 15
%8 = torch_c.to_i64 %int15
%9 = "tosa.const"() {value = dense_resource<elided> : tensor<512x2048xf32>} : () -> tensor<512x2048xf32>
%10 = "tosa.const"() {value = dense_resource<elided> : tensor<2048x512xf32>} : () -> tensor<2048x512xf32>
%11 = "tosa.const"() {value = dense_resource<elided> : tensor<32x8xf32>} : () -> tensor<32x8xf32>
%12 = "tosa.const"() {value = dense_resource<elided> : tensor<512x512xf32>} : () -> tensor<512x512xf32>
%13 = "tosa.const"() {value = dense_resource<elided> : tensor<512xf32>} : () -> tensor<512xf32>
%14 = "tosa.const"() {value = dense_resource<elided> : tensor<32128x512xf32>} : () -> tensor<32128x512xf32>
%15 = "tosa.const"() {value = dense<0> : tensor} : () -> tensor
%int-100 = torch.constant.int -100
%float-3.402820e38 = torch.constant.float -3.4028234663852886E+38
%int6 = torch.constant.int 6
%int9223372036854775807 = torch.constant.int 9223372036854775807
%int2 = torch.constant.int 2
%16 = torch_c.to_i64 %int2
%int3 = torch.constant.int 3
%float1.000000e00 = torch.constant.float 1.000000e+00
%float9.999990e-07 = torch.constant.float 9.9999999999999995E-7
%int8 = torch.constant.int 8
%17 = torch_c.to_i64 %int8
%int64 = torch.constant.int 64
%int16 = torch.constant.int 16
%float2.772590e00 = torch.constant.float 2.7725887222397811
%int2048 = torch.constant.int 2048
%float2.079440e00 = torch.constant.float 2.0794415416798357
%int31 = torch.constant.int 31
%float4.419420e-02 = torch.constant.float 0.044194173824159223
%int32128 = torch.constant.int 32128
%cpu = torch.constant.device "cpu"
%18 = torch.prim.ListConstruct %int1, %int4 : (!torch.int, !torch.int) -> !torch.list
%19 = "tosa.const"() {value = dense<0> : tensor<1x4xi32>} : () -> tensor<1x4xi32>
%20 = "tosa.cast"(%19) : (tensor<1x4xi32>) -> tensor<1x4xi64>
%21 = torch_c.from_builtin_tensor %20 : tensor<1x4xi64> -> !torch.vtensor<[1,4],si64>
%22 = "tosa.slice"(%0) {size = array<i64: 1, 3>, start = array<i64: 0, 0>} : (tensor<1x4xi64>) -> tensor<1x3xi64>
%23 = "tosa.cast"(%22) : (tensor<1x3xi64>) -> tensor<1x3xi64>
%24 = torch_c.from_builtin_tensor %23 : tensor<1x3xi64> -> !torch.vtensor<[1,3],si64>
%25 = "tosa.slice"(%20) {size = array<i64: 1, 9223372036854775806>, start = array<i64: 0, 1>} : (tensor<1x4xi64>) -> tensor<1x3xi64>
%26 = "tosa.const"() {value = dense<[1, 2, 3]> : tensor<3xi64>} : () -> tensor<3xi64>
%27 = "tosa.cast"(%26) : (tensor<3xi64>) -> tensor<3xi64>
%28 = torch_c.from_builtin_tensor %27 : tensor<3xi64> -> !torch.vtensor<[3],si64>
%29 = torch.prim.ListConstruct %28 : (!torch.vtensor<[3],si64>) -> !torch.list<optional>
%30 = torch.aten._index_put_impl %21, %29, %24, %false, %false : !torch.vtensor<[1,4],si64>, !torch.list<optional>, !torch.vtensor<[1,3],si64>, !torch.bool, !torch.bool -> !torch.vtensor<[1,4],si64>
%31 = torch_c.to_builtin_tensor %30 : !torch.vtensor<[1,4],si64> -> tensor<1x4xi64>
%32 = "tosa.cast"(%15) : (tensor) -> tensor
%33 = torch_c.from_builtin_tensor %32 : tensor -> !torch.vtensor<[],si64>
%34 = "tosa.slice"(%31) {size = array<i64: 1, 1>, start = array<i64: 0, 0>} : (tensor<1x4xi64>) -> tensor<1x1xi64>
%35 = "tosa.reshape"(%34) {new_shape = array<i64: 1>} : (tensor<1x1xi64>) -> tensor<1xi64>
%cast = tensor.cast %35 : tensor<1xi64> to tensor<1xi64>
%36 = "tosa.const"() {value = dense<0> : tensor} : () -> tensor
%37 = torch_c.from_builtin_tensor %36 : tensor -> !torch.vtensor<[],si64>
%38 = torch.prim.ListConstruct %37 : (!torch.vtensor<[],si64>) -> !torch.list<optional>
%39 = torch.aten._index_put_impl %30, %38, %33, %false, %false : !torch.vtensor<[1,4],si64>, !torch.list<optional>, !torch.vtensor<[],si64>, !torch.bool, !torch.bool -> !torch.vtensor<[1,4],si64>
%40 = torch_c.to_builtin_tensor %39 : !torch.vtensor<[1,4],si64> -> tensor<1x4xi64>
%41 = "tosa.const"() {value = dense<-100> : tensor} : () -> tensor
%42 = "tosa.equal"(%40, %41) : (tensor<1x4xi64>, tensor) -> tensor<1x4xi1>
%43 = torch.prim.ListConstruct : () -> !torch.list
%44 = "tosa.const"() {value = dense<0> : tensor} : () -> tensor
%45 = "tosa.select"(%42, %44, %40) : (tensor<1x4xi1>, tensor, tensor<1x4xi64>) -> tensor<1x4xi64>
%46 = torch.prim.ListConstruct %int-1, %int15 : (!torch.int, !torch.int) -> !torch.list
%47 = "tosa.reshape"(%1) {new_shape = array<i64: 1, 15>} : (tensor<1x15xi64>) -> tensor<1x15xi64>
%48 = "tosa.reshape"(%14) {new_shape = array<i64: 1, 32128, 512>} : (tensor<32128x512xf32>) -> tensor<1x32128x512xf32>
%49 = "tosa.reshape"(%47) {new_shape = array<i64: 1, 15>} : (tensor<1x15xi64>) -> tensor<1x15xi64>
%50 = "tosa.cast"(%49) : (tensor<1x15xi64>) -> tensor<1x15xi32>
%51 = "tosa.gather"(%48, %50) : (tensor<1x32128x512xf32>, tensor<1x15xi32>) -> tensor<1x15x512xf32>
%52 = "tosa.reshape"(%51) {new_shape = array<i64: 1, 15, 512>} : (tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%53 = torch.prim.ListConstruct %int1, %int15 : (!torch.int, !torch.int) -> !torch.list
%54 = "tosa.const"() {value = dense<1> : tensor<1x15xi32>} : () -> tensor<1x15xi32>
%55 = "tosa.cast"(%54) : (tensor<1x15xi32>) -> tensor<1x15xf32>
%56 = "tosa.reshape"(%55) {new_shape = array<i64: 1, 1, 15>} : (tensor<1x15xf32>) -> tensor<1x1x15xf32>
%57 = "tosa.reshape"(%56) {new_shape = array<i64: 1, 1, 1, 15>} : (tensor<1x1x15xf32>) -> tensor<1x1x1x15xf32>
%58 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%59 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%60 = "tosa.mul"(%57, %59) {shift = 0 : i32} : (tensor<1x1x1x15xf32>, tensor) -> tensor<1x1x1x15xf32>
%61 = "tosa.sub"(%58, %60) : (tensor, tensor<1x1x1x15xf32>) -> tensor<1x1x1x15xf32>
%62 = "tosa.const"() {value = dense<-3.40282347E+38> : tensor} : () -> tensor
%63 = "tosa.mul"(%61, %62) {shift = 0 : i32} : (tensor<1x1x1x15xf32>, tensor) -> tensor<1x1x1x15xf32>
%64 = "tosa.const"() {value = dense<2.000000e+00> : tensor} : () -> tensor
%65 = "tosa.pow"(%52, %64) : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%66 = torch.prim.ListConstruct %int-1 : (!torch.int) -> !torch.list
%67 = "tosa.reduce_sum"(%65) {axis = 2 : i64} : (tensor<1x15x512xf32>) -> tensor<1x15x1xf32>
%68 = "tosa.const"() {value = dense<5.120000e+02> : tensor} : () -> tensor
%69 = "tosa.reciprocal"(%68) : (tensor) -> tensor
%70 = "tosa.mul"(%67, %69) {shift = 0 : i32} : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%71 = "tosa.const"() {value = dense<9.99999997E-7> : tensor} : () -> tensor
%72 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%73 = "tosa.mul"(%71, %72) {shift = 0 : i32} : (tensor, tensor) -> tensor
%74 = "tosa.add"(%70, %73) : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%75 = "tosa.rsqrt"(%74) : (tensor<1x15x1xf32>) -> tensor<1x15x1xf32>
%76 = "tosa.mul"(%52, %75) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor<1x15x1xf32>) -> tensor<1x15x512xf32>
%77 = "tosa.mul"(%13, %76) {shift = 0 : i32} : (tensor<512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%78 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%79 = "tosa.transpose"(%12, %78) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%80 = torch.prim.ListConstruct %int15, %int512 : (!torch.int, !torch.int) -> !torch.list
%81 = "tosa.reshape"(%77) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%82 = "tosa.reshape"(%81) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%83 = "tosa.reshape"(%79) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%84 = "tosa.matmul"(%82, %83) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%85 = "tosa.reshape"(%84) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_0 = tensor.cast %85 : tensor<15x512xf32> to tensor<15x512xf32>
%86 = torch.prim.ListConstruct %int1, %int15, %int512 : (!torch.int, !torch.int, !torch.int) -> !torch.list
%87 = "tosa.reshape"(%cast_0) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%88 = torch.prim.ListConstruct %int1, %int-1, %int8, %int64 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list
%89 = "tosa.reshape"(%87) {new_shape = array<i64: 1, 15, 8, 64>} : (tensor<1x15x512xf32>) -> tensor<1x15x8x64xf32>
%90 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%91 = "tosa.transpose"(%89, %90) : (tensor<1x15x8x64xf32>, tensor<4xi32>) -> tensor<1x8x15x64xf32>
%92 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%93 = "tosa.transpose"(%12, %92) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%94 = "tosa.reshape"(%77) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%95 = "tosa.reshape"(%94) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%96 = "tosa.reshape"(%93) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%97 = "tosa.matmul"(%95, %96) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%98 = "tosa.reshape"(%97) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_1 = tensor.cast %98 : tensor<15x512xf32> to tensor<15x512xf32>
%99 = "tosa.reshape"(%cast_1) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%100 = "tosa.reshape"(%99) {new_shape = array<i64: 1, 15, 8, 64>} : (tensor<1x15x512xf32>) -> tensor<1x15x8x64xf32>
%101 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%102 = "tosa.transpose"(%100, %101) : (tensor<1x15x8x64xf32>, tensor<4xi32>) -> tensor<1x8x15x64xf32>
%103 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%104 = "tosa.transpose"(%12, %103) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%105 = "tosa.reshape"(%77) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%106 = "tosa.reshape"(%105) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%107 = "tosa.reshape"(%104) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%108 = "tosa.matmul"(%106, %107) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%109 = "tosa.reshape"(%108) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_2 = tensor.cast %109 : tensor<15x512xf32> to tensor<15x512xf32>
%110 = "tosa.reshape"(%cast_2) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%111 = "tosa.reshape"(%110) {new_shape = array<i64: 1, 15, 8, 64>} : (tensor<1x15x512xf32>) -> tensor<1x15x8x64xf32>
%112 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%113 = "tosa.transpose"(%111, %112) : (tensor<1x15x8x64xf32>, tensor<4xi32>) -> tensor<1x8x15x64xf32>
%114 = "tosa.const"() {value = dense<[0, 1, 3, 2]> : tensor<4xi32>} : () -> tensor<4xi32>
%115 = "tosa.transpose"(%102, %114) : (tensor<1x8x15x64xf32>, tensor<4xi32>) -> tensor<1x8x64x15xf32>
%116 = torch.prim.ListConstruct %int1, %int8, %int15, %int64 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list
%117 = torch.prim.ListConstruct %int8, %int15, %int64 : (!torch.int, !torch.int, !torch.int) -> !torch.list
%118 = "tosa.reshape"(%91) {new_shape = array<i64: 8, 15, 64>} : (tensor<1x8x15x64xf32>) -> tensor<8x15x64xf32>
%119 = torch.prim.ListConstruct %int1, %int8, %int64, %int15 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list
%120 = torch.prim.ListConstruct %int8, %int64, %int15 : (!torch.int, !torch.int, !torch.int) -> !torch.list
%121 = "tosa.reshape"(%115) {new_shape = array<i64: 8, 64, 15>} : (tensor<1x8x64x15xf32>) -> tensor<8x64x15xf32>
%122 = "tosa.matmul"(%118, %121) : (tensor<8x15x64xf32>, tensor<8x64x15xf32>) -> tensor<8x15x15xf32>
%cast_3 = tensor.cast %122 : tensor<8x15x15xf32> to tensor<8x15x15xf32>
%123 = torch.prim.ListConstruct %int1, %int8, %int15, %int15 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list
%124 = "tosa.reshape"(%cast_3) {new_shape = array<i64: 1, 8, 15, 15>} : (tensor<8x15x15xf32>) -> tensor<1x8x15x15xf32>
%125 = "tosa.const"() {value = dense<[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]> : tensor<15xi64>} : () -> tensor<15xi64>
%126 = "tosa.cast"(%125) : (tensor<15xi64>) -> tensor<15xi64>
%127 = "tosa.reshape"(%126) {new_shape = array<i64: 15, 1>} : (tensor<15xi64>) -> tensor<15x1xi64>
%128 = "tosa.const"() {value = dense<[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]> : tensor<15xi64>} : () -> tensor<15xi64>
%129 = "tosa.cast"(%128) : (tensor<15xi64>) -> tensor<15xi64>
%130 = "tosa.reshape"(%129) {new_shape = array<i64: 1, 15>} : (tensor<15xi64>) -> tensor<1x15xi64>
%131 = "tosa.cast"(%127) : (tensor<15x1xi64>) -> tensor<15x1xi32>
%132 = "tosa.const"() {value = dense<1> : tensor} : () -> tensor
%133 = "tosa.mul"(%131, %132) {shift = 0 : i32} : (tensor<15x1xi32>, tensor) -> tensor<15x1xi32>
%134 = "tosa.cast"(%130) : (tensor<1x15xi64>) -> tensor<1x15xi32>
%135 = "tosa.sub"(%134, %133) : (tensor<1x15xi32>, tensor<15x1xi32>) -> tensor<15x15xi32>
%136 = "tosa.cast"(%135) : (tensor<15x15xi32>) -> tensor<15x15xi64>
%137 = torch_c.from_builtin_tensor %136 : tensor<15x15xi64> -> !torch.vtensor<[15,15],si64>
%138 = "tosa.const"() {value = dense<0> : tensor} : () -> tensor
%139 = "tosa.greater"(%136, %138) : (tensor<15x15xi64>, tensor) -> tensor<15x15xi1>
%140 = "tosa.cast"(%139) : (tensor<15x15xi1>) -> tensor<15x15xi64>
%141 = "tosa.const"() {value = dense<16> : tensor} : () -> tensor
%142 = "tosa.mul"(%140, %141) {shift = 0 : i32} : (tensor<15x15xi64>, tensor) -> tensor<15x15xi64>
%143 = "tosa.const"() {value = dense<0> : tensor} : () -> tensor
%144 = "tosa.const"() {value = dense<1> : tensor} : () -> tensor
%145 = "tosa.mul"(%143, %144) {shift = 0 : i32} : (tensor, tensor) -> tensor
%146 = "tosa.cast"(%142) : (tensor<15x15xi64>) -> tensor<15x15xi32>
%147 = "tosa.add"(%146, %145) : (tensor<15x15xi32>, tensor) -> tensor<15x15xi32>
%148 = "tosa.cast"(%147) : (tensor<15x15xi32>) -> tensor<15x15xi64>
%149 = torch.aten.abs %137 : !torch.vtensor<[15,15],si64> -> !torch.vtensor<[15,15],si64>
%150 = torch_c.to_builtin_tensor %149 : !torch.vtensor<[15,15],si64> -> tensor<15x15xi64>
%151 = "tosa.const"() {value = dense<8> : tensor} : () -> tensor
%152 = "tosa.greater"(%151, %150) : (tensor, tensor<15x15xi64>) -> tensor<15x15xi1>
%153 = "tosa.cast"(%150) : (tensor<15x15xi64>) -> tensor<15x15xf32>
%154 = "tosa.const"() {value = dense<8.000000e+00> : tensor} : () -> tensor
%155 = "tosa.reciprocal"(%154) : (tensor) -> tensor
%156 = "tosa.mul"(%153, %155) {shift = 0 : i32} : (tensor<15x15xf32>, tensor) -> tensor<15x15xf32>
%157 = "tosa.log"(%156) : (tensor<15x15xf32>) -> tensor<15x15xf32>
%158 = "tosa.const"() {value = dense<2.77258873> : tensor} : () -> tensor
%159 = "tosa.reciprocal"(%158) : (tensor) -> tensor
%160 = "tosa.mul"(%157, %159) {shift = 0 : i32} : (tensor<15x15xf32>, tensor) -> tensor<15x15xf32>
%161 = "tosa.const"() {value = dense<8.000000e+00> : tensor} : () -> tensor
%162 = "tosa.mul"(%160, %161) {shift = 0 : i32} : (tensor<15x15xf32>, tensor) -> tensor<15x15xf32>
%163 = "tosa.cast"(%162) : (tensor<15x15xf32>) -> tensor<15x15xi64>
%164 = "tosa.const"() {value = dense<8> : tensor} : () -> tensor
%165 = "tosa.const"() {value = dense<1> : tensor} : () -> tensor
%166 = "tosa.mul"(%164, %165) {shift = 0 : i32} : (tensor, tensor) -> tensor
%167 = "tosa.cast"(%163) : (tensor<15x15xi64>) -> tensor<15x15xi32>
%168 = "tosa.add"(%167, %166) : (tensor<15x15xi32>, tensor) -> tensor<15x15xi32>
%169 = "tosa.cast"(%168) : (tensor<15x15xi32>) -> tensor<15x15xi64>
%170 = "tosa.const"() {value = dense<15> : tensor} : () -> tensor
%171 = torch.prim.ListConstruct %int15, %int15 : (!torch.int, !torch.int) -> !torch.list
%172 = "tosa.const"() {value = dense<0> : tensor<15x15xi64>} : () -> tensor<15x15xi64>
%173 = "tosa.add"(%170, %172) : (tensor, tensor<15x15xi64>) -> tensor<15x15xi64>
%174 = "tosa.minimum"(%169, %173) : (tensor<15x15xi64>, tensor<15x15xi64>) -> tensor<15x15xi64>
%175 = "tosa.select"(%152, %150, %174) : (tensor<15x15xi1>, tensor<15x15xi64>, tensor<15x15xi64>) -> tensor<15x15xi64>
%176 = "tosa.cast"(%175) : (tensor<15x15xi64>) -> tensor<15x15xi32>
%177 = "tosa.const"() {value = dense<1> : tensor} : () -> tensor
%178 = "tosa.mul"(%176, %177) {shift = 0 : i32} : (tensor<15x15xi32>, tensor) -> tensor<15x15xi32>
%179 = "tosa.cast"(%148) : (tensor<15x15xi64>) -> tensor<15x15xi32>
%180 = "tosa.add"(%179, %178) : (tensor<15x15xi32>, tensor<15x15xi32>) -> tensor<15x15xi32>
%181 = "tosa.cast"(%180) : (tensor<15x15xi32>) -> tensor<15x15xi64>
%182 = "tosa.reshape"(%11) {new_shape = array<i64: 1, 32, 8>} : (tensor<32x8xf32>) -> tensor<1x32x8xf32>
%183 = "tosa.reshape"(%181) {new_shape = array<i64: 1, 225>} : (tensor<15x15xi64>) -> tensor<1x225xi64>
%184 = "tosa.cast"(%183) : (tensor<1x225xi64>) -> tensor<1x225xi32>
%185 = "tosa.gather"(%182, %184) : (tensor<1x32x8xf32>, tensor<1x225xi32>) -> tensor<1x225x8xf32>
%186 = "tosa.reshape"(%185) {new_shape = array<i64: 15, 15, 8>} : (tensor<1x225x8xf32>) -> tensor<15x15x8xf32>
%187 = torch.prim.ListConstruct %int2, %int0, %int1 : (!torch.int, !torch.int, !torch.int) -> !torch.list
%188 = "tosa.const"() {value = dense<[2, 0, 1]> : tensor<3xi64>} : () -> tensor<3xi64>
%189 = "tosa.transpose"(%186, %188) : (tensor<15x15x8xf32>, tensor<3xi64>) -> tensor<8x15x15xf32>
%190 = "tosa.reshape"(%189) {new_shape = array<i64: 1, 8, 15, 15>} : (tensor<8x15x15xf32>) -> tensor<1x8x15x15xf32>
%191 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%192 = "tosa.mul"(%63, %191) {shift = 0 : i32} : (tensor<1x1x1x15xf32>, tensor) -> tensor<1x1x1x15xf32>
%193 = "tosa.add"(%190, %192) : (tensor<1x8x15x15xf32>, tensor<1x1x1x15xf32>) -> tensor<1x8x15x15xf32>
%194 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%195 = "tosa.mul"(%193, %194) {shift = 0 : i32} : (tensor<1x8x15x15xf32>, tensor) -> tensor<1x8x15x15xf32>
%196 = "tosa.add"(%124, %195) : (tensor<1x8x15x15xf32>, tensor<1x8x15x15xf32>) -> tensor<1x8x15x15xf32>
%197 = "tosa.reduce_max"(%196) {axis = 3 : i64} : (tensor<1x8x15x15xf32>) -> tensor<1x8x15x1xf32>
%198 = "tosa.argmax"(%196) {axis = 3 : i64} : (tensor<1x8x15x15xf32>) -> tensor<1x8x15xi64>
%199 = "tosa.reshape"(%198) {new_shape = array<i64: 1, 8, 15, 1>} : (tensor<1x8x15xi64>) -> tensor<1x8x15x1xi64>
%200 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%201 = "tosa.mul"(%197, %200) {shift = 0 : i32} : (tensor<1x8x15x1xf32>, tensor) -> tensor<1x8x15x1xf32>
%202 = "tosa.sub"(%196, %201) : (tensor<1x8x15x15xf32>, tensor<1x8x15x1xf32>) -> tensor<1x8x15x15xf32>
%203 = "tosa.exp"(%202) : (tensor<1x8x15x15xf32>) -> tensor<1x8x15x15xf32>
%204 = "tosa.reduce_sum"(%203) {axis = 3 : i64} : (tensor<1x8x15x15xf32>) -> tensor<1x8x15x1xf32>
%205 = "tosa.reciprocal"(%204) : (tensor<1x8x15x1xf32>) -> tensor<1x8x15x1xf32>
%206 = "tosa.mul"(%203, %205) {shift = 0 : i32} : (tensor<1x8x15x15xf32>, tensor<1x8x15x1xf32>) -> tensor<1x8x15x15xf32>
%207 = torch.prim.ListConstruct %int8, %int15, %int15 : (!torch.int, !torch.int, !torch.int) -> !torch.list
%208 = "tosa.reshape"(%206) {new_shape = array<i64: 8, 15, 15>} : (tensor<1x8x15x15xf32>) -> tensor<8x15x15xf32>
%209 = "tosa.reshape"(%113) {new_shape = array<i64: 8, 15, 64>} : (tensor<1x8x15x64xf32>) -> tensor<8x15x64xf32>
%210 = "tosa.matmul"(%208, %209) : (tensor<8x15x15xf32>, tensor<8x15x64xf32>) -> tensor<8x15x64xf32>
%cast_4 = tensor.cast %210 : tensor<8x15x64xf32> to tensor<8x15x64xf32>
%211 = "tosa.reshape"(%cast_4) {new_shape = array<i64: 1, 8, 15, 64>} : (tensor<8x15x64xf32>) -> tensor<1x8x15x64xf32>
%212 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%213 = "tosa.transpose"(%211, %212) : (tensor<1x8x15x64xf32>, tensor<4xi32>) -> tensor<1x15x8x64xf32>
%214 = "tosa.cast"(%213) : (tensor<1x15x8x64xf32>) -> tensor<1x15x8x64xf32>
%215 = torch.prim.ListConstruct %int1, %int-1, %int512 : (!torch.int, !torch.int, !torch.int) -> !torch.list
%216 = "tosa.reshape"(%214) {new_shape = array<i64: 1, 15, 512>} : (tensor<1x15x8x64xf32>) -> tensor<1x15x512xf32>
%217 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%218 = "tosa.transpose"(%12, %217) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%219 = "tosa.reshape"(%216) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%220 = "tosa.reshape"(%219) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%221 = "tosa.reshape"(%218) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%222 = "tosa.matmul"(%220, %221) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%223 = "tosa.reshape"(%222) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_5 = tensor.cast %223 : tensor<15x512xf32> to tensor<15x512xf32>
%224 = "tosa.reshape"(%cast_5) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%225 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%226 = "tosa.mul"(%224, %225) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%227 = "tosa.add"(%52, %226) : (tensor<1x15x512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%228 = "tosa.const"() {value = dense<2.000000e+00> : tensor} : () -> tensor
%229 = "tosa.pow"(%227, %228) : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%230 = "tosa.reduce_sum"(%229) {axis = 2 : i64} : (tensor<1x15x512xf32>) -> tensor<1x15x1xf32>
%231 = "tosa.const"() {value = dense<5.120000e+02> : tensor} : () -> tensor
%232 = "tosa.reciprocal"(%231) : (tensor) -> tensor
%233 = "tosa.mul"(%230, %232) {shift = 0 : i32} : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%234 = "tosa.const"() {value = dense<9.99999997E-7> : tensor} : () -> tensor
%235 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%236 = "tosa.mul"(%234, %235) {shift = 0 : i32} : (tensor, tensor) -> tensor
%237 = "tosa.add"(%233, %236) : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%238 = "tosa.rsqrt"(%237) : (tensor<1x15x1xf32>) -> tensor<1x15x1xf32>
%239 = "tosa.mul"(%227, %238) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor<1x15x1xf32>) -> tensor<1x15x512xf32>
%240 = "tosa.mul"(%13, %239) {shift = 0 : i32} : (tensor<512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%241 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%242 = "tosa.transpose"(%10, %241) : (tensor<2048x512xf32>, tensor<2xi32>) -> tensor<512x2048xf32>
%243 = "tosa.reshape"(%240) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%244 = "tosa.reshape"(%243) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%245 = "tosa.reshape"(%242) {new_shape = array<i64: 1, 512, 2048>} : (tensor<512x2048xf32>) -> tensor<1x512x2048xf32>
%246 = "tosa.matmul"(%244, %245) : (tensor<1x15x512xf32>, tensor<1x512x2048xf32>) -> tensor<1x15x2048xf32>
%247 = "tosa.reshape"(%246) {new_shape = array<i64: 15, 2048>} : (tensor<1x15x2048xf32>) -> tensor<15x2048xf32>
%cast_6 = tensor.cast %247 : tensor<15x2048xf32> to tensor<15x2048xf32>
%248 = torch.prim.ListConstruct %int1, %int15, %int2048 : (!torch.int, !torch.int, !torch.int) -> !torch.list
%249 = "tosa.reshape"(%cast_6) {new_shape = array<i64: 1, 15, 2048>} : (tensor<15x2048xf32>) -> tensor<1x15x2048xf32>
%250 = "tosa.clamp"(%249) {max_fp = 3.40282347E+38 : f32, max_int = 2147483647 : i64, min_fp = 0.000000e+00 : f32, min_int = 0 : i64} : (tensor<1x15x2048xf32>) -> tensor<1x15x2048xf32>
%251 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%252 = "tosa.transpose"(%9, %251) : (tensor<512x2048xf32>, tensor<2xi32>) -> tensor<2048x512xf32>
%253 = torch.prim.ListConstruct %int15, %int2048 : (!torch.int, !torch.int) -> !torch.list
%254 = "tosa.reshape"(%250) {new_shape = array<i64: 15, 2048>} : (tensor<1x15x2048xf32>) -> tensor<15x2048xf32>
%255 = "tosa.reshape"(%254) {new_shape = array<i64: 1, 15, 2048>} : (tensor<15x2048xf32>) -> tensor<1x15x2048xf32>
%256 = "tosa.reshape"(%252) {new_shape = array<i64: 1, 2048, 512>} : (tensor<2048x512xf32>) -> tensor<1x2048x512xf32>
%257 = "tosa.matmul"(%255, %256) : (tensor<1x15x2048xf32>, tensor<1x2048x512xf32>) -> tensor<1x15x512xf32>
%258 = "tosa.reshape"(%257) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_7 = tensor.cast %258 : tensor<15x512xf32> to tensor<15x512xf32>
%259 = "tosa.reshape"(%cast_7) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%260 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%261 = "tosa.mul"(%259, %260) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%262 = "tosa.add"(%227, %261) : (tensor<1x15x512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%263 = "tosa.const"() {value = dense<2.000000e+00> : tensor} : () -> tensor
%264 = "tosa.pow"(%262, %263) : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%265 = "tosa.reduce_sum"(%264) {axis = 2 : i64} : (tensor<1x15x512xf32>) -> tensor<1x15x1xf32>
%266 = "tosa.const"() {value = dense<5.120000e+02> : tensor} : () -> tensor
%267 = "tosa.reciprocal"(%266) : (tensor) -> tensor
%268 = "tosa.mul"(%265, %267) {shift = 0 : i32} : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%269 = "tosa.const"() {value = dense<9.99999997E-7> : tensor} : () -> tensor
%270 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%271 = "tosa.mul"(%269, %270) {shift = 0 : i32} : (tensor, tensor) -> tensor
%272 = "tosa.add"(%268, %271) : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%273 = "tosa.rsqrt"(%272) : (tensor<1x15x1xf32>) -> tensor<1x15x1xf32>
%274 = "tosa.mul"(%262, %273) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor<1x15x1xf32>) -> tensor<1x15x512xf32>
%275 = "tosa.mul"(%13, %274) {shift = 0 : i32} : (tensor<512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%276 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%277 = "tosa.transpose"(%12, %276) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%278 = "tosa.reshape"(%275) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%279 = "tosa.reshape"(%278) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%280 = "tosa.reshape"(%277) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%281 = "tosa.matmul"(%279, %280) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%282 = "tosa.reshape"(%281) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_8 = tensor.cast %282 : tensor<15x512xf32> to tensor<15x512xf32>
%283 = "tosa.reshape"(%cast_8) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%284 = "tosa.reshape"(%283) {new_shape = array<i64: 1, 15, 8, 64>} : (tensor<1x15x512xf32>) -> tensor<1x15x8x64xf32>
%285 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%286 = "tosa.transpose"(%284, %285) : (tensor<1x15x8x64xf32>, tensor<4xi32>) -> tensor<1x8x15x64xf32>
%287 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%288 = "tosa.transpose"(%12, %287) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%289 = "tosa.reshape"(%275) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%290 = "tosa.reshape"(%289) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%291 = "tosa.reshape"(%288) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%292 = "tosa.matmul"(%290, %291) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%293 = "tosa.reshape"(%292) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_9 = tensor.cast %293 : tensor<15x512xf32> to tensor<15x512xf32>
%294 = "tosa.reshape"(%cast_9) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%295 = "tosa.reshape"(%294) {new_shape = array<i64: 1, 15, 8, 64>} : (tensor<1x15x512xf32>) -> tensor<1x15x8x64xf32>
%296 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%297 = "tosa.transpose"(%295, %296) : (tensor<1x15x8x64xf32>, tensor<4xi32>) -> tensor<1x8x15x64xf32>
%298 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%299 = "tosa.transpose"(%12, %298) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%300 = "tosa.reshape"(%275) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%301 = "tosa.reshape"(%300) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%302 = "tosa.reshape"(%299) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%303 = "tosa.matmul"(%301, %302) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%304 = "tosa.reshape"(%303) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_10 = tensor.cast %304 : tensor<15x512xf32> to tensor<15x512xf32>
%305 = "tosa.reshape"(%cast_10) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%306 = "tosa.reshape"(%305) {new_shape = array<i64: 1, 15, 8, 64>} : (tensor<1x15x512xf32>) -> tensor<1x15x8x64xf32>
%307 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%308 = "tosa.transpose"(%306, %307) : (tensor<1x15x8x64xf32>, tensor<4xi32>) -> tensor<1x8x15x64xf32>
%309 = "tosa.const"() {value = dense<[0, 1, 3, 2]> : tensor<4xi32>} : () -> tensor<4xi32>
%310 = "tosa.transpose"(%297, %309) : (tensor<1x8x15x64xf32>, tensor<4xi32>) -> tensor<1x8x64x15xf32>
%311 = "tosa.reshape"(%286) {new_shape = array<i64: 8, 15, 64>} : (tensor<1x8x15x64xf32>) -> tensor<8x15x64xf32>
%312 = "tosa.reshape"(%310) {new_shape = array<i64: 8, 64, 15>} : (tensor<1x8x64x15xf32>) -> tensor<8x64x15xf32>
%313 = "tosa.matmul"(%311, %312) : (tensor<8x15x64xf32>, tensor<8x64x15xf32>) -> tensor<8x15x15xf32>
%cast_11 = tensor.cast %313 : tensor<8x15x15xf32> to tensor<8x15x15xf32>
%314 = "tosa.reshape"(%cast_11) {new_shape = array<i64: 1, 8, 15, 15>} : (tensor<8x15x15xf32>) -> tensor<1x8x15x15xf32>
%315 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%316 = "tosa.mul"(%193, %315) {shift = 0 : i32} : (tensor<1x8x15x15xf32>, tensor) -> tensor<1x8x15x15xf32>
%317 = "tosa.add"(%314, %316) : (tensor<1x8x15x15xf32>, tensor<1x8x15x15xf32>) -> tensor<1x8x15x15xf32>
%318 = "tosa.reduce_max"(%317) {axis = 3 : i64} : (tensor<1x8x15x15xf32>) -> tensor<1x8x15x1xf32>
%319 = "tosa.argmax"(%317) {axis = 3 : i64} : (tensor<1x8x15x15xf32>) -> tensor<1x8x15xi64>
%320 = "tosa.reshape"(%319) {new_shape = array<i64: 1, 8, 15, 1>} : (tensor<1x8x15xi64>) -> tensor<1x8x15x1xi64>
%321 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%322 = "tosa.mul"(%318, %321) {shift = 0 : i32} : (tensor<1x8x15x1xf32>, tensor) -> tensor<1x8x15x1xf32>
%323 = "tosa.sub"(%317, %322) : (tensor<1x8x15x15xf32>, tensor<1x8x15x1xf32>) -> tensor<1x8x15x15xf32>
%324 = "tosa.exp"(%323) : (tensor<1x8x15x15xf32>) -> tensor<1x8x15x15xf32>
%325 = "tosa.reduce_sum"(%324) {axis = 3 : i64} : (tensor<1x8x15x15xf32>) -> tensor<1x8x15x1xf32>
%326 = "tosa.reciprocal"(%325) : (tensor<1x8x15x1xf32>) -> tensor<1x8x15x1xf32>
%327 = "tosa.mul"(%324, %326) {shift = 0 : i32} : (tensor<1x8x15x15xf32>, tensor<1x8x15x1xf32>) -> tensor<1x8x15x15xf32>
%328 = "tosa.reshape"(%327) {new_shape = array<i64: 8, 15, 15>} : (tensor<1x8x15x15xf32>) -> tensor<8x15x15xf32>
%329 = "tosa.reshape"(%308) {new_shape = array<i64: 8, 15, 64>} : (tensor<1x8x15x64xf32>) -> tensor<8x15x64xf32>
%330 = "tosa.matmul"(%328, %329) : (tensor<8x15x15xf32>, tensor<8x15x64xf32>) -> tensor<8x15x64xf32>
%cast_12 = tensor.cast %330 : tensor<8x15x64xf32> to tensor<8x15x64xf32>
%331 = "tosa.reshape"(%cast_12) {new_shape = array<i64: 1, 8, 15, 64>} : (tensor<8x15x64xf32>) -> tensor<1x8x15x64xf32>
%332 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%333 = "tosa.transpose"(%331, %332) : (tensor<1x8x15x64xf32>, tensor<4xi32>) -> tensor<1x15x8x64xf32>
%334 = "tosa.cast"(%333) : (tensor<1x15x8x64xf32>) -> tensor<1x15x8x64xf32>
%335 = "tosa.reshape"(%334) {new_shape = array<i64: 1, 15, 512>} : (tensor<1x15x8x64xf32>) -> tensor<1x15x512xf32>
%336 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%337 = "tosa.transpose"(%12, %336) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%338 = "tosa.reshape"(%335) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%339 = "tosa.reshape"(%338) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%340 = "tosa.reshape"(%337) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%341 = "tosa.matmul"(%339, %340) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%342 = "tosa.reshape"(%341) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_13 = tensor.cast %342 : tensor<15x512xf32> to tensor<15x512xf32>
%343 = "tosa.reshape"(%cast_13) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%344 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%345 = "tosa.mul"(%343, %344) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%346 = "tosa.add"(%262, %345) : (tensor<1x15x512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%347 = "tosa.const"() {value = dense<2.000000e+00> : tensor} : () -> tensor
%348 = "tosa.pow"(%346, %347) : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%349 = "tosa.reduce_sum"(%348) {axis = 2 : i64} : (tensor<1x15x512xf32>) -> tensor<1x15x1xf32>
%350 = "tosa.const"() {value = dense<5.120000e+02> : tensor} : () -> tensor
%351 = "tosa.reciprocal"(%350) : (tensor) -> tensor
%352 = "tosa.mul"(%349, %351) {shift = 0 : i32} : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%353 = "tosa.const"() {value = dense<9.99999997E-7> : tensor} : () -> tensor
%354 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%355 = "tosa.mul"(%353, %354) {shift = 0 : i32} : (tensor, tensor) -> tensor
%356 = "tosa.add"(%352, %355) : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%357 = "tosa.rsqrt"(%356) : (tensor<1x15x1xf32>) -> tensor<1x15x1xf32>
%358 = "tosa.mul"(%346, %357) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor<1x15x1xf32>) -> tensor<1x15x512xf32>
%359 = "tosa.mul"(%13, %358) {shift = 0 : i32} : (tensor<512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%360 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%361 = "tosa.transpose"(%10, %360) : (tensor<2048x512xf32>, tensor<2xi32>) -> tensor<512x2048xf32>
%362 = "tosa.reshape"(%359) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%363 = "tosa.reshape"(%362) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%364 = "tosa.reshape"(%361) {new_shape = array<i64: 1, 512, 2048>} : (tensor<512x2048xf32>) -> tensor<1x512x2048xf32>
%365 = "tosa.matmul"(%363, %364) : (tensor<1x15x512xf32>, tensor<1x512x2048xf32>) -> tensor<1x15x2048xf32>
%366 = "tosa.reshape"(%365) {new_shape = array<i64: 15, 2048>} : (tensor<1x15x2048xf32>) -> tensor<15x2048xf32>
%cast_14 = tensor.cast %366 : tensor<15x2048xf32> to tensor<15x2048xf32>
%367 = "tosa.reshape"(%cast_14) {new_shape = array<i64: 1, 15, 2048>} : (tensor<15x2048xf32>) -> tensor<1x15x2048xf32>
%368 = "tosa.clamp"(%367) {max_fp = 3.40282347E+38 : f32, max_int = 2147483647 : i64, min_fp = 0.000000e+00 : f32, min_int = 0 : i64} : (tensor<1x15x2048xf32>) -> tensor<1x15x2048xf32>
%369 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%370 = "tosa.transpose"(%9, %369) : (tensor<512x2048xf32>, tensor<2xi32>) -> tensor<2048x512xf32>
%371 = "tosa.reshape"(%368) {new_shape = array<i64: 15, 2048>} : (tensor<1x15x2048xf32>) -> tensor<15x2048xf32>
%372 = "tosa.reshape"(%371) {new_shape = array<i64: 1, 15, 2048>} : (tensor<15x2048xf32>) -> tensor<1x15x2048xf32>
%373 = "tosa.reshape"(%370) {new_shape = array<i64: 1, 2048, 512>} : (tensor<2048x512xf32>) -> tensor<1x2048x512xf32>
%374 = "tosa.matmul"(%372, %373) : (tensor<1x15x2048xf32>, tensor<1x2048x512xf32>) -> tensor<1x15x512xf32>
%375 = "tosa.reshape"(%374) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_15 = tensor.cast %375 : tensor<15x512xf32> to tensor<15x512xf32>
%376 = "tosa.reshape"(%cast_15) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%377 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%378 = "tosa.mul"(%376, %377) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%379 = "tosa.add"(%346, %378) : (tensor<1x15x512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%380 = "tosa.const"() {value = dense<2.000000e+00> : tensor} : () -> tensor
%381 = "tosa.pow"(%379, %380) : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%382 = "tosa.reduce_sum"(%381) {axis = 2 : i64} : (tensor<1x15x512xf32>) -> tensor<1x15x1xf32>
%383 = "tosa.const"() {value = dense<5.120000e+02> : tensor} : () -> tensor
%384 = "tosa.reciprocal"(%383) : (tensor) -> tensor
%385 = "tosa.mul"(%382, %384) {shift = 0 : i32} : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%386 = "tosa.const"() {value = dense<9.99999997E-7> : tensor} : () -> tensor
%387 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%388 = "tosa.mul"(%386, %387) {shift = 0 : i32} : (tensor, tensor) -> tensor
%389 = "tosa.add"(%385, %388) : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%390 = "tosa.rsqrt"(%389) : (tensor<1x15x1xf32>) -> tensor<1x15x1xf32>
%391 = "tosa.mul"(%379, %390) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor<1x15x1xf32>) -> tensor<1x15x512xf32>
%392 = "tosa.mul"(%13, %391) {shift = 0 : i32} : (tensor<512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%393 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%394 = "tosa.transpose"(%12, %393) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%395 = "tosa.reshape"(%392) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%396 = "tosa.reshape"(%395) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%397 = "tosa.reshape"(%394) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%398 = "tosa.matmul"(%396, %397) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%399 = "tosa.reshape"(%398) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_16 = tensor.cast %399 : tensor<15x512xf32> to tensor<15x512xf32>
%400 = "tosa.reshape"(%cast_16) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%401 = "tosa.reshape"(%400) {new_shape = array<i64: 1, 15, 8, 64>} : (tensor<1x15x512xf32>) -> tensor<1x15x8x64xf32>
%402 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%403 = "tosa.transpose"(%401, %402) : (tensor<1x15x8x64xf32>, tensor<4xi32>) -> tensor<1x8x15x64xf32>
%404 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%405 = "tosa.transpose"(%12, %404) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%406 = "tosa.reshape"(%392) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%407 = "tosa.reshape"(%406) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%408 = "tosa.reshape"(%405) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%409 = "tosa.matmul"(%407, %408) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%410 = "tosa.reshape"(%409) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_17 = tensor.cast %410 : tensor<15x512xf32> to tensor<15x512xf32>
%411 = "tosa.reshape"(%cast_17) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%412 = "tosa.reshape"(%411) {new_shape = array<i64: 1, 15, 8, 64>} : (tensor<1x15x512xf32>) -> tensor<1x15x8x64xf32>
%413 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%414 = "tosa.transpose"(%412, %413) : (tensor<1x15x8x64xf32>, tensor<4xi32>) -> tensor<1x8x15x64xf32>
%415 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%416 = "tosa.transpose"(%12, %415) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%417 = "tosa.reshape"(%392) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%418 = "tosa.reshape"(%417) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%419 = "tosa.reshape"(%416) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%420 = "tosa.matmul"(%418, %419) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%421 = "tosa.reshape"(%420) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_18 = tensor.cast %421 : tensor<15x512xf32> to tensor<15x512xf32>
%422 = "tosa.reshape"(%cast_18) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%423 = "tosa.reshape"(%422) {new_shape = array<i64: 1, 15, 8, 64>} : (tensor<1x15x512xf32>) -> tensor<1x15x8x64xf32>
%424 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%425 = "tosa.transpose"(%423, %424) : (tensor<1x15x8x64xf32>, tensor<4xi32>) -> tensor<1x8x15x64xf32>
%426 = "tosa.const"() {value = dense<[0, 1, 3, 2]> : tensor<4xi32>} : () -> tensor<4xi32>
%427 = "tosa.transpose"(%414, %426) : (tensor<1x8x15x64xf32>, tensor<4xi32>) -> tensor<1x8x64x15xf32>
%428 = "tosa.reshape"(%403) {new_shape = array<i64: 8, 15, 64>} : (tensor<1x8x15x64xf32>) -> tensor<8x15x64xf32>
%429 = "tosa.reshape"(%427) {new_shape = array<i64: 8, 64, 15>} : (tensor<1x8x64x15xf32>) -> tensor<8x64x15xf32>
%430 = "tosa.matmul"(%428, %429) : (tensor<8x15x64xf32>, tensor<8x64x15xf32>) -> tensor<8x15x15xf32>
%cast_19 = tensor.cast %430 : tensor<8x15x15xf32> to tensor<8x15x15xf32>
%431 = "tosa.reshape"(%cast_19) {new_shape = array<i64: 1, 8, 15, 15>} : (tensor<8x15x15xf32>) -> tensor<1x8x15x15xf32>
%432 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%433 = "tosa.mul"(%193, %432) {shift = 0 : i32} : (tensor<1x8x15x15xf32>, tensor) -> tensor<1x8x15x15xf32>
%434 = "tosa.add"(%431, %433) : (tensor<1x8x15x15xf32>, tensor<1x8x15x15xf32>) -> tensor<1x8x15x15xf32>
%435 = "tosa.reduce_max"(%434) {axis = 3 : i64} : (tensor<1x8x15x15xf32>) -> tensor<1x8x15x1xf32>
%436 = "tosa.argmax"(%434) {axis = 3 : i64} : (tensor<1x8x15x15xf32>) -> tensor<1x8x15xi64>
%437 = "tosa.reshape"(%436) {new_shape = array<i64: 1, 8, 15, 1>} : (tensor<1x8x15xi64>) -> tensor<1x8x15x1xi64>
%438 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%439 = "tosa.mul"(%435, %438) {shift = 0 : i32} : (tensor<1x8x15x1xf32>, tensor) -> tensor<1x8x15x1xf32>
%440 = "tosa.sub"(%434, %439) : (tensor<1x8x15x15xf32>, tensor<1x8x15x1xf32>) -> tensor<1x8x15x15xf32>
%441 = "tosa.exp"(%440) : (tensor<1x8x15x15xf32>) -> tensor<1x8x15x15xf32>
%442 = "tosa.reduce_sum"(%441) {axis = 3 : i64} : (tensor<1x8x15x15xf32>) -> tensor<1x8x15x1xf32>
%443 = "tosa.reciprocal"(%442) : (tensor<1x8x15x1xf32>) -> tensor<1x8x15x1xf32>
%444 = "tosa.mul"(%441, %443) {shift = 0 : i32} : (tensor<1x8x15x15xf32>, tensor<1x8x15x1xf32>) -> tensor<1x8x15x15xf32>
%445 = "tosa.reshape"(%444) {new_shape = array<i64: 8, 15, 15>} : (tensor<1x8x15x15xf32>) -> tensor<8x15x15xf32>
%446 = "tosa.reshape"(%425) {new_shape = array<i64: 8, 15, 64>} : (tensor<1x8x15x64xf32>) -> tensor<8x15x64xf32>
%447 = "tosa.matmul"(%445, %446) : (tensor<8x15x15xf32>, tensor<8x15x64xf32>) -> tensor<8x15x64xf32>
%cast_20 = tensor.cast %447 : tensor<8x15x64xf32> to tensor<8x15x64xf32>
%448 = "tosa.reshape"(%cast_20) {new_shape = array<i64: 1, 8, 15, 64>} : (tensor<8x15x64xf32>) -> tensor<1x8x15x64xf32>
%449 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%450 = "tosa.transpose"(%448, %449) : (tensor<1x8x15x64xf32>, tensor<4xi32>) -> tensor<1x15x8x64xf32>
%451 = "tosa.cast"(%450) : (tensor<1x15x8x64xf32>) -> tensor<1x15x8x64xf32>
%452 = "tosa.reshape"(%451) {new_shape = array<i64: 1, 15, 512>} : (tensor<1x15x8x64xf32>) -> tensor<1x15x512xf32>
%453 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%454 = "tosa.transpose"(%12, %453) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%455 = "tosa.reshape"(%452) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%456 = "tosa.reshape"(%455) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%457 = "tosa.reshape"(%454) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%458 = "tosa.matmul"(%456, %457) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%459 = "tosa.reshape"(%458) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_21 = tensor.cast %459 : tensor<15x512xf32> to tensor<15x512xf32>
%460 = "tosa.reshape"(%cast_21) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%461 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%462 = "tosa.mul"(%460, %461) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%463 = "tosa.add"(%379, %462) : (tensor<1x15x512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%464 = "tosa.const"() {value = dense<2.000000e+00> : tensor} : () -> tensor
%465 = "tosa.pow"(%463, %464) : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%466 = "tosa.reduce_sum"(%465) {axis = 2 : i64} : (tensor<1x15x512xf32>) -> tensor<1x15x1xf32>
%467 = "tosa.const"() {value = dense<5.120000e+02> : tensor} : () -> tensor
%468 = "tosa.reciprocal"(%467) : (tensor) -> tensor
%469 = "tosa.mul"(%466, %468) {shift = 0 : i32} : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%470 = "tosa.const"() {value = dense<9.99999997E-7> : tensor} : () -> tensor
%471 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%472 = "tosa.mul"(%470, %471) {shift = 0 : i32} : (tensor, tensor) -> tensor
%473 = "tosa.add"(%469, %472) : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%474 = "tosa.rsqrt"(%473) : (tensor<1x15x1xf32>) -> tensor<1x15x1xf32>
%475 = "tosa.mul"(%463, %474) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor<1x15x1xf32>) -> tensor<1x15x512xf32>
%476 = "tosa.mul"(%13, %475) {shift = 0 : i32} : (tensor<512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%477 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%478 = "tosa.transpose"(%10, %477) : (tensor<2048x512xf32>, tensor<2xi32>) -> tensor<512x2048xf32>
%479 = "tosa.reshape"(%476) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%480 = "tosa.reshape"(%479) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%481 = "tosa.reshape"(%478) {new_shape = array<i64: 1, 512, 2048>} : (tensor<512x2048xf32>) -> tensor<1x512x2048xf32>
%482 = "tosa.matmul"(%480, %481) : (tensor<1x15x512xf32>, tensor<1x512x2048xf32>) -> tensor<1x15x2048xf32>
%483 = "tosa.reshape"(%482) {new_shape = array<i64: 15, 2048>} : (tensor<1x15x2048xf32>) -> tensor<15x2048xf32>
%cast_22 = tensor.cast %483 : tensor<15x2048xf32> to tensor<15x2048xf32>
%484 = "tosa.reshape"(%cast_22) {new_shape = array<i64: 1, 15, 2048>} : (tensor<15x2048xf32>) -> tensor<1x15x2048xf32>
%485 = "tosa.clamp"(%484) {max_fp = 3.40282347E+38 : f32, max_int = 2147483647 : i64, min_fp = 0.000000e+00 : f32, min_int = 0 : i64} : (tensor<1x15x2048xf32>) -> tensor<1x15x2048xf32>
%486 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%487 = "tosa.transpose"(%9, %486) : (tensor<512x2048xf32>, tensor<2xi32>) -> tensor<2048x512xf32>
%488 = "tosa.reshape"(%485) {new_shape = array<i64: 15, 2048>} : (tensor<1x15x2048xf32>) -> tensor<15x2048xf32>
%489 = "tosa.reshape"(%488) {new_shape = array<i64: 1, 15, 2048>} : (tensor<15x2048xf32>) -> tensor<1x15x2048xf32>
%490 = "tosa.reshape"(%487) {new_shape = array<i64: 1, 2048, 512>} : (tensor<2048x512xf32>) -> tensor<1x2048x512xf32>
%491 = "tosa.matmul"(%489, %490) : (tensor<1x15x2048xf32>, tensor<1x2048x512xf32>) -> tensor<1x15x512xf32>
%492 = "tosa.reshape"(%491) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_23 = tensor.cast %492 : tensor<15x512xf32> to tensor<15x512xf32>
%493 = "tosa.reshape"(%cast_23) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%494 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%495 = "tosa.mul"(%493, %494) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%496 = "tosa.add"(%463, %495) : (tensor<1x15x512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%497 = "tosa.const"() {value = dense<2.000000e+00> : tensor} : () -> tensor
%498 = "tosa.pow"(%496, %497) : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%499 = "tosa.reduce_sum"(%498) {axis = 2 : i64} : (tensor<1x15x512xf32>) -> tensor<1x15x1xf32>
%500 = "tosa.const"() {value = dense<5.120000e+02> : tensor} : () -> tensor
%501 = "tosa.reciprocal"(%500) : (tensor) -> tensor
%502 = "tosa.mul"(%499, %501) {shift = 0 : i32} : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%503 = "tosa.const"() {value = dense<9.99999997E-7> : tensor} : () -> tensor
%504 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%505 = "tosa.mul"(%503, %504) {shift = 0 : i32} : (tensor, tensor) -> tensor
%506 = "tosa.add"(%502, %505) : (tensor<1x15x1xf32>, tensor) -> tensor<1x15x1xf32>
%507 = "tosa.rsqrt"(%506) : (tensor<1x15x1xf32>) -> tensor<1x15x1xf32>
%508 = "tosa.mul"(%496, %507) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor<1x15x1xf32>) -> tensor<1x15x512xf32>
%509 = "tosa.mul"(%13, %508) {shift = 0 : i32} : (tensor<512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%510 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%511 = "tosa.transpose"(%12, %510) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%512 = "tosa.reshape"(%509) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%513 = "tosa.reshape"(%512) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%514 = "tosa.reshape"(%511) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%515 = "tosa.matmul"(%513, %514) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%516 = "tosa.reshape"(%515) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_24 = tensor.cast %516 : tensor<15x512xf32> to tensor<15x512xf32>
%517 = "tosa.reshape"(%cast_24) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%518 = "tosa.reshape"(%517) {new_shape = array<i64: 1, 15, 8, 64>} : (tensor<1x15x512xf32>) -> tensor<1x15x8x64xf32>
%519 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%520 = "tosa.transpose"(%518, %519) : (tensor<1x15x8x64xf32>, tensor<4xi32>) -> tensor<1x8x15x64xf32>
%521 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%522 = "tosa.transpose"(%12, %521) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%523 = "tosa.reshape"(%509) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%524 = "tosa.reshape"(%523) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%525 = "tosa.reshape"(%522) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%526 = "tosa.matmul"(%524, %525) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%527 = "tosa.reshape"(%526) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_25 = tensor.cast %527 : tensor<15x512xf32> to tensor<15x512xf32>
%528 = "tosa.reshape"(%cast_25) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%529 = "tosa.reshape"(%528) {new_shape = array<i64: 1, 15, 8, 64>} : (tensor<1x15x512xf32>) -> tensor<1x15x8x64xf32>
%530 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%531 = "tosa.transpose"(%529, %530) : (tensor<1x15x8x64xf32>, tensor<4xi32>) -> tensor<1x8x15x64xf32>
%532 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%533 = "tosa.transpose"(%12, %532) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%534 = "tosa.reshape"(%509) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%535 = "tosa.reshape"(%534) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%536 = "tosa.reshape"(%533) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%537 = "tosa.matmul"(%535, %536) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%538 = "tosa.reshape"(%537) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_26 = tensor.cast %538 : tensor<15x512xf32> to tensor<15x512xf32>
%539 = "tosa.reshape"(%cast_26) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%540 = "tosa.reshape"(%539) {new_shape = array<i64: 1, 15, 8, 64>} : (tensor<1x15x512xf32>) -> tensor<1x15x8x64xf32>
%541 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%542 = "tosa.transpose"(%540, %541) : (tensor<1x15x8x64xf32>, tensor<4xi32>) -> tensor<1x8x15x64xf32>
%543 = "tosa.const"() {value = dense<[0, 1, 3, 2]> : tensor<4xi32>} : () -> tensor<4xi32>
%544 = "tosa.transpose"(%531, %543) : (tensor<1x8x15x64xf32>, tensor<4xi32>) -> tensor<1x8x64x15xf32>
%545 = "tosa.reshape"(%520) {new_shape = array<i64: 8, 15, 64>} : (tensor<1x8x15x64xf32>) -> tensor<8x15x64xf32>
%546 = "tosa.reshape"(%544) {new_shape = array<i64: 8, 64, 15>} : (tensor<1x8x64x15xf32>) -> tensor<8x64x15xf32>
%547 = "tosa.matmul"(%545, %546) : (tensor<8x15x64xf32>, tensor<8x64x15xf32>) -> tensor<8x15x15xf32>
%cast_27 = tensor.cast %547 : tensor<8x15x15xf32> to tensor<8x15x15xf32>
%548 = "tosa.reshape"(%cast_27) {new_shape = array<i64: 1, 8, 15, 15>} : (tensor<8x15x15xf32>) -> tensor<1x8x15x15xf32>
%549 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%550 = "tosa.mul"(%193, %549) {shift = 0 : i32} : (tensor<1x8x15x15xf32>, tensor) -> tensor<1x8x15x15xf32>
%551 = "tosa.add"(%548, %550) : (tensor<1x8x15x15xf32>, tensor<1x8x15x15xf32>) -> tensor<1x8x15x15xf32>
%552 = "tosa.reduce_max"(%551) {axis = 3 : i64} : (tensor<1x8x15x15xf32>) -> tensor<1x8x15x1xf32>
%553 = "tosa.argmax"(%551) {axis = 3 : i64} : (tensor<1x8x15x15xf32>) -> tensor<1x8x15xi64>
%554 = "tosa.reshape"(%553) {new_shape = array<i64: 1, 8, 15, 1>} : (tensor<1x8x15xi64>) -> tensor<1x8x15x1xi64>
%555 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%556 = "tosa.mul"(%552, %555) {shift = 0 : i32} : (tensor<1x8x15x1xf32>, tensor) -> tensor<1x8x15x1xf32>
%557 = "tosa.sub"(%551, %556) : (tensor<1x8x15x15xf32>, tensor<1x8x15x1xf32>) -> tensor<1x8x15x15xf32>
%558 = "tosa.exp"(%557) : (tensor<1x8x15x15xf32>) -> tensor<1x8x15x15xf32>
%559 = "tosa.reduce_sum"(%558) {axis = 3 : i64} : (tensor<1x8x15x15xf32>) -> tensor<1x8x15x1xf32>
%560 = "tosa.reciprocal"(%559) : (tensor<1x8x15x1xf32>) -> tensor<1x8x15x1xf32>
%561 = "tosa.mul"(%558, %560) {shift = 0 : i32} : (tensor<1x8x15x15xf32>, tensor<1x8x15x1xf32>) -> tensor<1x8x15x15xf32>
%562 = "tosa.reshape"(%561) {new_shape = array<i64: 8, 15, 15>} : (tensor<1x8x15x15xf32>) -> tensor<8x15x15xf32>
%563 = "tosa.reshape"(%542) {new_shape = array<i64: 8, 15, 64>} : (tensor<1x8x15x64xf32>) -> tensor<8x15x64xf32>
%564 = "tosa.matmul"(%562, %563) : (tensor<8x15x15xf32>, tensor<8x15x64xf32>) -> tensor<8x15x64xf32>
%cast_28 = tensor.cast %564 : tensor<8x15x64xf32> to tensor<8x15x64xf32>
%565 = "tosa.reshape"(%cast_28) {new_shape = array<i64: 1, 8, 15, 64>} : (tensor<8x15x64xf32>) -> tensor<1x8x15x64xf32>
%566 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%567 = "tosa.transpose"(%565, %566) : (tensor<1x8x15x64xf32>, tensor<4xi32>) -> tensor<1x15x8x64xf32>
%568 = "tosa.cast"(%567) : (tensor<1x15x8x64xf32>) -> tensor<1x15x8x64xf32>
%569 = "tosa.reshape"(%568) {new_shape = array<i64: 1, 15, 512>} : (tensor<1x15x8x64xf32>) -> tensor<1x15x512xf32>
%570 = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
%571 = "tosa.transpose"(%12, %570) : (tensor<512x512xf32>, tensor<2xi32>) -> tensor<512x512xf32>
%572 = "tosa.reshape"(%569) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%573 = "tosa.reshape"(%572) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%574 = "tosa.reshape"(%571) {new_shape = array<i64: 1, 512, 512>} : (tensor<512x512xf32>) -> tensor<1x512x512xf32>
%575 = "tosa.matmul"(%573, %574) : (tensor<1x15x512xf32>, tensor<1x512x512xf32>) -> tensor<1x15x512xf32>
%576 = "tosa.reshape"(%575) {new_shape = array<i64: 15, 512>} : (tensor<1x15x512xf32>) -> tensor<15x512xf32>
%cast_29 = tensor.cast %576 : tensor<15x512xf32> to tensor<15x512xf32>
%577 = "tosa.reshape"(%cast_29) {new_shape = array<i64: 1, 15, 512>} : (tensor<15x512xf32>) -> tensor<1x15x512xf32>
%578 = "tosa.const"() {value = dense<1.000000e+00> : tensor} : () -> tensor
%579 = "tosa.mul"(%577, %578) {shift = 0 : i32} : (tensor<1x15x512xf32>, tensor) -> tensor<1x15x512xf32>
%580 = "tosa.add"(%496, %579) : (tensor<1x15x512xf32>, tensor<1x15x512xf32>) -> tensor<1x15x512xf32>
%581 = "tosa.const"() {value = dense<2.000000e+00> : tensor} : () -> tensor

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