MobilenetV3Module.mlir

#loc0 = loc(unknown)
module attributes {torch.debug_module_name = "MobilenetV3Module"} {
  func @forward(%arg0: !torch.vtensor<[?,3,?,?],f32> loc(unknown)) -> !torch.vtensor {
    %0 = torch.vtensor.literal(dense<0.000000e+00> : tensor<1000xf32>) : !torch.vtensor<[1000],f32> loc(#loc0)
    %1 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<1000x1024xf32>) : !torch.vtensor<[1000,1024],f32> loc(#loc0)
    %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor<1024xf32>) : !torch.vtensor<[1024],f32> loc(#loc0)
    %3 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<1024x576xf32>) : !torch.vtensor<[1024,576],f32> loc(#loc0)
    %4 = torch.vtensor.literal(dense<0.000000e+00> : tensor<576xf32>) : !torch.vtensor<[576],f32> loc(#loc0)
    %5 = torch.vtensor.literal(dense<1.000000e+00> : tensor<576xf32>) : !torch.vtensor<[576],f32> loc(#loc0)
    %none = torch.constant.none loc(#loc1)
    %6 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<576x96x1x1xf32>) : !torch.vtensor<[576,96,1,1],f32> loc(#loc0)
    %7 = torch.vtensor.literal(dense<0.000000e+00> : tensor<96xf32>) : !torch.vtensor<[96],f32> loc(#loc0)
    %8 = torch.vtensor.literal(dense<1.000000e+00> : tensor<96xf32>) : !torch.vtensor<[96],f32> loc(#loc0)
    %9 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<96x576x1x1xf32>) : !torch.vtensor<[96,576,1,1],f32> loc(#loc0)
    %10 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<576x144x1x1xf32>) : !torch.vtensor<[576,144,1,1],f32> loc(#loc0)
    %11 = torch.vtensor.literal(dense<0.000000e+00> : tensor<144xf32>) : !torch.vtensor<[144],f32> loc(#loc0)
    %12 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<144x576x1x1xf32>) : !torch.vtensor<[144,576,1,1],f32> loc(#loc0)
    %13 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<576x1x5x5xf32>) : !torch.vtensor<[576,1,5,5],f32> loc(#loc0)
    %14 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<576x96x1x1xf32>) : !torch.vtensor<[576,96,1,1],f32> loc(#loc0)
    %15 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<96x576x1x1xf32>) : !torch.vtensor<[96,576,1,1],f32> loc(#loc0)
    %16 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<576x144x1x1xf32>) : !torch.vtensor<[576,144,1,1],f32> loc(#loc0)
    %17 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<144x576x1x1xf32>) : !torch.vtensor<[144,576,1,1],f32> loc(#loc0)
    %18 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<576x1x5x5xf32>) : !torch.vtensor<[576,1,5,5],f32> loc(#loc0)
    %19 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<576x96x1x1xf32>) : !torch.vtensor<[576,96,1,1],f32> loc(#loc0)
    %20 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<96x288x1x1xf32>) : !torch.vtensor<[96,288,1,1],f32> loc(#loc0)
    %21 = torch.vtensor.literal(dense<0.000000e+00> : tensor<288xf32>) : !torch.vtensor<[288],f32> loc(#loc0)
    %22 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<288x72x1x1xf32>) : !torch.vtensor<[288,72,1,1],f32> loc(#loc0)
    %23 = torch.vtensor.literal(dense<0.000000e+00> : tensor<72xf32>) : !torch.vtensor<[72],f32> loc(#loc0)
    %24 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<72x288x1x1xf32>) : !torch.vtensor<[72,288,1,1],f32> loc(#loc0)
    %25 = torch.vtensor.literal(dense<1.000000e+00> : tensor<288xf32>) : !torch.vtensor<[288],f32> loc(#loc0)
    %26 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<288x1x5x5xf32>) : !torch.vtensor<[288,1,5,5],f32> loc(#loc0)
    %27 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<288x48x1x1xf32>) : !torch.vtensor<[288,48,1,1],f32> loc(#loc0)
    %28 = torch.vtensor.literal(dense<0.000000e+00> : tensor<48xf32>) : !torch.vtensor<[48],f32> loc(#loc0)
    %29 = torch.vtensor.literal(dense<1.000000e+00> : tensor<48xf32>) : !torch.vtensor<[48],f32> loc(#loc0)
    %30 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<48x144x1x1xf32>) : !torch.vtensor<[48,144,1,1],f32> loc(#loc0)
    %31 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<144x40x1x1xf32>) : !torch.vtensor<[144,40,1,1],f32> loc(#loc0)
    %32 = torch.vtensor.literal(dense<0.000000e+00> : tensor<40xf32>) : !torch.vtensor<[40],f32> loc(#loc0)
    %33 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<40x144x1x1xf32>) : !torch.vtensor<[40,144,1,1],f32> loc(#loc0)
    %34 = torch.vtensor.literal(dense<1.000000e+00> : tensor<144xf32>) : !torch.vtensor<[144],f32> loc(#loc0)
    %35 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<144x1x5x5xf32>) : !torch.vtensor<[144,1,5,5],f32> loc(#loc0)
    %36 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<144x48x1x1xf32>) : !torch.vtensor<[144,48,1,1],f32> loc(#loc0)
    %37 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<48x120x1x1xf32>) : !torch.vtensor<[48,120,1,1],f32> loc(#loc0)
    %38 = torch.vtensor.literal(dense<0.000000e+00> : tensor<120xf32>) : !torch.vtensor<[120],f32> loc(#loc0)
    %39 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<120x32x1x1xf32>) : !torch.vtensor<[120,32,1,1],f32> loc(#loc0)
    %40 = torch.vtensor.literal(dense<0.000000e+00> : tensor<32xf32>) : !torch.vtensor<[32],f32> loc(#loc0)
    %41 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<32x120x1x1xf32>) : !torch.vtensor<[32,120,1,1],f32> loc(#loc0)
    %42 = torch.vtensor.literal(dense<1.000000e+00> : tensor<120xf32>) : !torch.vtensor<[120],f32> loc(#loc0)
    %43 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<120x1x5x5xf32>) : !torch.vtensor<[120,1,5,5],f32> loc(#loc0)
    %44 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<120x40x1x1xf32>) : !torch.vtensor<[120,40,1,1],f32> loc(#loc0)
    %45 = torch.vtensor.literal(dense<1.000000e+00> : tensor<40xf32>) : !torch.vtensor<[40],f32> loc(#loc0)
    %46 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<40x240x1x1xf32>) : !torch.vtensor<[40,240,1,1],f32> loc(#loc0)
    %47 = torch.vtensor.literal(dense<0.000000e+00> : tensor<240xf32>) : !torch.vtensor<[240],f32> loc(#loc0)
    %48 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<240x64x1x1xf32>) : !torch.vtensor<[240,64,1,1],f32> loc(#loc0)
    %49 = torch.vtensor.literal(dense<0.000000e+00> : tensor<64xf32>) : !torch.vtensor<[64],f32> loc(#loc0)
    %50 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<64x240x1x1xf32>) : !torch.vtensor<[64,240,1,1],f32> loc(#loc0)
    %51 = torch.vtensor.literal(dense<1.000000e+00> : tensor<240xf32>) : !torch.vtensor<[240],f32> loc(#loc0)
    %52 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<240x1x5x5xf32>) : !torch.vtensor<[240,1,5,5],f32> loc(#loc0)
    %53 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<240x40x1x1xf32>) : !torch.vtensor<[240,40,1,1],f32> loc(#loc0)
    %54 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<40x240x1x1xf32>) : !torch.vtensor<[40,240,1,1],f32> loc(#loc0)
    %55 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<240x64x1x1xf32>) : !torch.vtensor<[240,64,1,1],f32> loc(#loc0)
    %56 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<64x240x1x1xf32>) : !torch.vtensor<[64,240,1,1],f32> loc(#loc0)
    %57 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<240x1x5x5xf32>) : !torch.vtensor<[240,1,5,5],f32> loc(#loc0)
    %58 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<240x40x1x1xf32>) : !torch.vtensor<[240,40,1,1],f32> loc(#loc0)
    %59 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<40x96x1x1xf32>) : !torch.vtensor<[40,96,1,1],f32> loc(#loc0)
    %60 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<96x24x1x1xf32>) : !torch.vtensor<[96,24,1,1],f32> loc(#loc0)
    %61 = torch.vtensor.literal(dense<0.000000e+00> : tensor<24xf32>) : !torch.vtensor<[24],f32> loc(#loc0)
    %62 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<24x96x1x1xf32>) : !torch.vtensor<[24,96,1,1],f32> loc(#loc0)
    %63 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<96x1x5x5xf32>) : !torch.vtensor<[96,1,5,5],f32> loc(#loc0)
    %64 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<96x24x1x1xf32>) : !torch.vtensor<[96,24,1,1],f32> loc(#loc0)
    %65 = torch.vtensor.literal(dense<1.000000e+00> : tensor<24xf32>) : !torch.vtensor<[24],f32> loc(#loc0)
    %66 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<24x88x1x1xf32>) : !torch.vtensor<[24,88,1,1],f32> loc(#loc0)
    %67 = torch.vtensor.literal(dense<0.000000e+00> : tensor<88xf32>) : !torch.vtensor<[88],f32> loc(#loc0)
    %68 = torch.vtensor.literal(dense<1.000000e+00> : tensor<88xf32>) : !torch.vtensor<[88],f32> loc(#loc0)
    %69 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<88x1x3x3xf32>) : !torch.vtensor<[88,1,3,3],f32> loc(#loc0)
    %70 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<88x24x1x1xf32>) : !torch.vtensor<[88,24,1,1],f32> loc(#loc0)
    %71 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<24x72x1x1xf32>) : !torch.vtensor<[24,72,1,1],f32> loc(#loc0)
    %72 = torch.vtensor.literal(dense<1.000000e+00> : tensor<72xf32>) : !torch.vtensor<[72],f32> loc(#loc0)
    %73 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<72x1x3x3xf32>) : !torch.vtensor<[72,1,3,3],f32> loc(#loc0)
    %74 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<72x16x1x1xf32>) : !torch.vtensor<[72,16,1,1],f32> loc(#loc0)
    %75 = torch.vtensor.literal(dense<0.000000e+00> : tensor<16xf32>) : !torch.vtensor<[16],f32> loc(#loc0)
    %76 = torch.vtensor.literal(dense<1.000000e+00> : tensor<16xf32>) : !torch.vtensor<[16],f32> loc(#loc0)
    %77 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<16x16x1x1xf32>) : !torch.vtensor<[16,16,1,1],f32> loc(#loc0)
    %78 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<16x8x1x1xf32>) : !torch.vtensor<[16,8,1,1],f32> loc(#loc0)
    %79 = torch.vtensor.literal(dense<0.000000e+00> : tensor<8xf32>) : !torch.vtensor<[8],f32> loc(#loc0)
    %80 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<8x16x1x1xf32>) : !torch.vtensor<[8,16,1,1],f32> loc(#loc0)
    %81 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<16x1x3x3xf32>) : !torch.vtensor<[16,1,3,3],f32> loc(#loc0)
    %82 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<16x3x3x3xf32>) : !torch.vtensor<[16,3,3,3],f32> loc(#loc0)
    %str = torch.constant.str "dropout probability has to be between 0 and 1, but got {}" loc(#loc2)
    %float0.000000e00 = torch.constant.float 0.000000e+00 loc(#loc3)
    %float1.000000e00 = torch.constant.float 1.000000e+00 loc(#loc4)
    %float2.000000e-01 = torch.constant.float 2.000000e-01 loc(#loc5)
    %int1 = torch.constant.int 1 loc(#loc6)
    %str_0 = torch.constant.str "AssertionError: " loc(#loc7)
    %int2 = torch.constant.int 2 loc(#loc8)
    %int16 = torch.constant.int 16 loc(#loc9)
    %int72 = torch.constant.int 72 loc(#loc9)
    %int88 = torch.constant.int 88 loc(#loc9)
    %int96 = torch.constant.int 96 loc(#loc9)
    %int240 = torch.constant.int 240 loc(#loc9)
    %int120 = torch.constant.int 120 loc(#loc9)
    %int144 = torch.constant.int 144 loc(#loc9)
    %int288 = torch.constant.int 288 loc(#loc9)
    %int576 = torch.constant.int 576 loc(#loc9)
    %float1.000000e-02 = torch.constant.float 1.000000e-02 loc(#loc10)
    %float1.000000e-03 = torch.constant.float 1.000000e-03 loc(#loc11)
    %int0 = torch.constant.int 0 loc(#loc12)
    %int-1 = torch.constant.int -1 loc(#loc13)
    %true = torch.constant.bool true loc(#loc14)
    %false = torch.constant.bool false loc(#loc15)
    %83 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc16)
    %84 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc16)
    %85 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc16)
    %86 = torch.aten.conv2d %arg0, %82, %none, %83, %84, %85, %int1 : !torch.vtensor<[?,3,?,?],f32>, !torch.vtensor<[16,3,3,3],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,16,?,?],f32> loc(#loc17)
    %87 = torch.aten.batch_norm %86, %76, %75, %75, %76, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,16,?,?],f32>, !torch.vtensor<[16],f32>, !torch.vtensor<[16],f32>, !torch.vtensor<[16],f32>, !torch.vtensor<[16],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,16,?,?],f32> loc(#loc18)
    %88 = torch.copy.to_tensor %87 : !torch.tensor<[?,16,?,?],f32> loc(#loc18)
    %89 = torch.operator "aten.hardswish_"(%88) : (!torch.tensor<[?,16,?,?],f32>) -> !torch.tensor loc(#loc19)
    %90 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %91 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %92 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %93 = torch.copy.to_vtensor %89 : !torch.vtensor loc(#loc21)
    %94 = torch.aten.conv2d %93, %81, %none, %90, %91, %92, %int16 : !torch.vtensor, !torch.vtensor<[16,1,3,3],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %95 = torch.aten.batch_norm %94, %76, %75, %75, %76, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[16],f32>, !torch.vtensor<[16],f32>, !torch.vtensor<[16],f32>, !torch.vtensor<[16],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %96 = torch.aten.relu %95 : !torch.vtensor<[?,?,?,?],unk> -> !torch.vtensor<[?,?,?,?],unk> loc(#loc23)
    %97 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc24)
    %98 = torch.aten.adaptive_avg_pool2d %96, %97 : !torch.vtensor<[?,?,?,?],unk>, !torch.list<!torch.int> -> !torch.vtensor<[?,?,1,1],unk> loc(#loc25)
    %99 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %100 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %101 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %102 = torch.aten.conv2d %98, %80, %79, %99, %100, %101, %int1 : !torch.vtensor<[?,?,1,1],unk>, !torch.vtensor<[8,16,1,1],f32>, !torch.vtensor<[8],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,8,1,1],unk> loc(#loc27)
    %103 = torch.aten.relu %102 : !torch.vtensor<[?,8,1,1],unk> -> !torch.vtensor<[?,8,1,1],unk> loc(#loc28)
    %104 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %105 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %106 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %107 = torch.aten.conv2d %103, %78, %75, %104, %105, %106, %int1 : !torch.vtensor<[?,8,1,1],unk>, !torch.vtensor<[16,8,1,1],f32>, !torch.vtensor<[16],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,16,1,1],unk> loc(#loc30)
    %108 = torch.copy.to_tensor %107 : !torch.tensor<[?,16,1,1],unk> loc(#loc30)
    %109 = torch.operator "aten.hardsigmoid"(%108) : (!torch.tensor<[?,16,1,1],unk>) -> !torch.tensor loc(#loc31)
    %110 = torch.copy.to_vtensor %109 : !torch.vtensor loc(#loc32)
    %111 = torch.aten.mul.Tensor %110, %96 : !torch.vtensor, !torch.vtensor<[?,?,?,?],unk> -> !torch.vtensor loc(#loc32)
    %112 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %113 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %114 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %115 = torch.aten.conv2d %111, %77, %none, %112, %113, %114, %int1 : !torch.vtensor, !torch.vtensor<[16,16,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %116 = torch.aten.batch_norm %115, %76, %75, %75, %76, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[16],f32>, !torch.vtensor<[16],f32>, !torch.vtensor<[16],f32>, !torch.vtensor<[16],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %117 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %118 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %119 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %120 = torch.aten.conv2d %116, %74, %none, %117, %118, %119, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[72,16,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,72,?,?],unk> loc(#loc21)
    %121 = torch.aten.batch_norm %120, %72, %23, %23, %72, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,72,?,?],unk>, !torch.vtensor<[72],f32>, !torch.vtensor<[72],f32>, !torch.vtensor<[72],f32>, !torch.vtensor<[72],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,72,?,?],unk> loc(#loc22)
    %122 = torch.aten.relu %121 : !torch.vtensor<[?,72,?,?],unk> -> !torch.vtensor<[?,72,?,?],unk> loc(#loc23)
    %123 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %124 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %125 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %126 = torch.aten.conv2d %122, %73, %none, %123, %124, %125, %int72 : !torch.vtensor<[?,72,?,?],unk>, !torch.vtensor<[72,1,3,3],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,72,?,?],unk> loc(#loc21)
    %127 = torch.aten.batch_norm %126, %72, %23, %23, %72, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,72,?,?],unk>, !torch.vtensor<[72],f32>, !torch.vtensor<[72],f32>, !torch.vtensor<[72],f32>, !torch.vtensor<[72],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,72,?,?],unk> loc(#loc22)
    %128 = torch.aten.relu %127 : !torch.vtensor<[?,72,?,?],unk> -> !torch.vtensor<[?,72,?,?],unk> loc(#loc23)
    %129 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %130 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %131 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %132 = torch.aten.conv2d %128, %71, %none, %129, %130, %131, %int1 : !torch.vtensor<[?,72,?,?],unk>, !torch.vtensor<[24,72,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,24,?,?],unk> loc(#loc21)
    %133 = torch.aten.batch_norm %132, %65, %61, %61, %65, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,24,?,?],unk>, !torch.vtensor<[24],f32>, !torch.vtensor<[24],f32>, !torch.vtensor<[24],f32>, !torch.vtensor<[24],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,24,?,?],unk> loc(#loc22)
    %134 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %135 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %136 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %137 = torch.aten.conv2d %133, %70, %none, %134, %135, %136, %int1 : !torch.vtensor<[?,24,?,?],unk>, !torch.vtensor<[88,24,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,88,?,?],unk> loc(#loc21)
    %138 = torch.aten.batch_norm %137, %68, %67, %67, %68, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,88,?,?],unk>, !torch.vtensor<[88],f32>, !torch.vtensor<[88],f32>, !torch.vtensor<[88],f32>, !torch.vtensor<[88],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,88,?,?],unk> loc(#loc22)
    %139 = torch.aten.relu %138 : !torch.vtensor<[?,88,?,?],unk> -> !torch.vtensor<[?,88,?,?],unk> loc(#loc23)
    %140 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %141 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %142 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %143 = torch.aten.conv2d %139, %69, %none, %140, %141, %142, %int88 : !torch.vtensor<[?,88,?,?],unk>, !torch.vtensor<[88,1,3,3],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,88,?,?],unk> loc(#loc21)
    %144 = torch.aten.batch_norm %143, %68, %67, %67, %68, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,88,?,?],unk>, !torch.vtensor<[88],f32>, !torch.vtensor<[88],f32>, !torch.vtensor<[88],f32>, !torch.vtensor<[88],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,88,?,?],unk> loc(#loc22)
    %145 = torch.aten.relu %144 : !torch.vtensor<[?,88,?,?],unk> -> !torch.vtensor<[?,88,?,?],unk> loc(#loc23)
    %146 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %147 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %148 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %149 = torch.aten.conv2d %145, %66, %none, %146, %147, %148, %int1 : !torch.vtensor<[?,88,?,?],unk>, !torch.vtensor<[24,88,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,24,?,?],unk> loc(#loc21)
    %150 = torch.aten.batch_norm %149, %65, %61, %61, %65, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,24,?,?],unk>, !torch.vtensor<[24],f32>, !torch.vtensor<[24],f32>, !torch.vtensor<[24],f32>, !torch.vtensor<[24],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,24,?,?],unk> loc(#loc22)
    %151 = torch.aten.add.Tensor %150, %133, %int1 : !torch.vtensor<[?,24,?,?],unk>, !torch.vtensor<[?,24,?,?],unk>, !torch.int -> !torch.vtensor<[?,24,?,?],unk> loc(#loc33)
    %152 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %153 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %154 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %155 = torch.aten.conv2d %151, %64, %none, %152, %153, %154, %int1 : !torch.vtensor<[?,24,?,?],unk>, !torch.vtensor<[96,24,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,96,?,?],unk> loc(#loc21)
    %156 = torch.aten.batch_norm %155, %8, %7, %7, %8, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,96,?,?],unk>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,96,?,?],unk> loc(#loc22)
    %157 = torch.copy.to_tensor %156 : !torch.tensor<[?,96,?,?],unk> loc(#loc22)
    %158 = torch.operator "aten.hardswish_"(%157) : (!torch.tensor<[?,96,?,?],unk>) -> !torch.tensor loc(#loc34)
    %159 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %160 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %161 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %162 = torch.copy.to_vtensor %158 : !torch.vtensor loc(#loc21)
    %163 = torch.aten.conv2d %162, %63, %none, %159, %160, %161, %int96 : !torch.vtensor, !torch.vtensor<[96,1,5,5],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %164 = torch.aten.batch_norm %163, %8, %7, %7, %8, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %165 = torch.copy.to_tensor %164 : !torch.tensor<[?,?,?,?],unk> loc(#loc22)
    %166 = torch.operator "aten.hardswish_"(%165) : (!torch.tensor<[?,?,?,?],unk>) -> !torch.tensor loc(#loc34)
    %167 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc24)
    %168 = torch.copy.to_vtensor %166 : !torch.vtensor loc(#loc35)
    %169 = torch.aten.dim %168 : !torch.vtensor -> !torch.int loc(#loc35)
    %170 = torch.aten.gt.int %169, %int2 : !torch.int, !torch.int -> !torch.bool loc(#loc35)
    torch.prim.If %170 -> () {
      torch.prim.If.yield loc(#loc36)
    } else {
      torch.prim.RaiseException %str_0, %none : !torch.str, !torch.none loc(#loc36)
      torch.prim.If.yield loc(#loc36)
    } loc(#loc36)
    %171 = torch.copy.to_vtensor %166 : !torch.vtensor loc(#loc25)
    %172 = torch.aten.adaptive_avg_pool2d %171, %167 : !torch.vtensor, !torch.list<!torch.int> -> !torch.vtensor loc(#loc25)
    %173 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %174 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %175 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %176 = torch.aten.conv2d %172, %62, %61, %173, %174, %175, %int1 : !torch.vtensor, !torch.vtensor<[24,96,1,1],f32>, !torch.vtensor<[24],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc27)
    %177 = torch.aten.relu %176 : !torch.vtensor<[?,?,?,?],unk> -> !torch.vtensor<[?,?,?,?],unk> loc(#loc28)
    %178 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %179 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %180 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %181 = torch.aten.conv2d %177, %60, %7, %178, %179, %180, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[96,24,1,1],f32>, !torch.vtensor<[96],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,96,?,?],unk> loc(#loc30)
    %182 = torch.copy.to_tensor %181 : !torch.tensor<[?,96,?,?],unk> loc(#loc30)
    %183 = torch.operator "aten.hardsigmoid"(%182) : (!torch.tensor<[?,96,?,?],unk>) -> !torch.tensor loc(#loc31)
    %184 = torch.copy.to_vtensor %183 : !torch.vtensor loc(#loc32)
    %185 = torch.copy.to_vtensor %166 : !torch.vtensor loc(#loc32)
    %186 = torch.aten.mul.Tensor %184, %185 : !torch.vtensor, !torch.vtensor -> !torch.vtensor loc(#loc32)
    %187 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %188 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %189 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %190 = torch.aten.conv2d %186, %59, %none, %187, %188, %189, %int1 : !torch.vtensor, !torch.vtensor<[40,96,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %191 = torch.aten.batch_norm %190, %45, %32, %32, %45, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[40],f32>, !torch.vtensor<[40],f32>, !torch.vtensor<[40],f32>, !torch.vtensor<[40],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %192 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %193 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %194 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %195 = torch.aten.conv2d %191, %58, %none, %192, %193, %194, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[240,40,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,240,?,?],unk> loc(#loc21)
    %196 = torch.aten.batch_norm %195, %51, %47, %47, %51, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,240,?,?],unk>, !torch.vtensor<[240],f32>, !torch.vtensor<[240],f32>, !torch.vtensor<[240],f32>, !torch.vtensor<[240],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,240,?,?],unk> loc(#loc22)
    %197 = torch.copy.to_tensor %196 : !torch.tensor<[?,240,?,?],unk> loc(#loc22)
    %198 = torch.operator "aten.hardswish_"(%197) : (!torch.tensor<[?,240,?,?],unk>) -> !torch.tensor loc(#loc34)
    %199 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %200 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %201 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %202 = torch.copy.to_vtensor %198 : !torch.vtensor loc(#loc21)
    %203 = torch.aten.conv2d %202, %57, %none, %199, %200, %201, %int240 : !torch.vtensor, !torch.vtensor<[240,1,5,5],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %204 = torch.aten.batch_norm %203, %51, %47, %47, %51, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[240],f32>, !torch.vtensor<[240],f32>, !torch.vtensor<[240],f32>, !torch.vtensor<[240],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %205 = torch.copy.to_tensor %204 : !torch.tensor<[?,?,?,?],unk> loc(#loc22)
    %206 = torch.operator "aten.hardswish_"(%205) : (!torch.tensor<[?,?,?,?],unk>) -> !torch.tensor loc(#loc34)
    %207 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc24)
    %208 = torch.copy.to_vtensor %206 : !torch.vtensor loc(#loc35)
    %209 = torch.aten.dim %208 : !torch.vtensor -> !torch.int loc(#loc35)
    %210 = torch.aten.gt.int %209, %int2 : !torch.int, !torch.int -> !torch.bool loc(#loc35)
    torch.prim.If %210 -> () {
      torch.prim.If.yield loc(#loc36)
    } else {
      torch.prim.RaiseException %str_0, %none : !torch.str, !torch.none loc(#loc36)
      torch.prim.If.yield loc(#loc36)
    } loc(#loc36)
    %211 = torch.copy.to_vtensor %206 : !torch.vtensor loc(#loc25)
    %212 = torch.aten.adaptive_avg_pool2d %211, %207 : !torch.vtensor, !torch.list<!torch.int> -> !torch.vtensor loc(#loc25)
    %213 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %214 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %215 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %216 = torch.aten.conv2d %212, %56, %49, %213, %214, %215, %int1 : !torch.vtensor, !torch.vtensor<[64,240,1,1],f32>, !torch.vtensor<[64],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc27)
    %217 = torch.aten.relu %216 : !torch.vtensor<[?,?,?,?],unk> -> !torch.vtensor<[?,?,?,?],unk> loc(#loc28)
    %218 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %219 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %220 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %221 = torch.aten.conv2d %217, %55, %47, %218, %219, %220, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[240,64,1,1],f32>, !torch.vtensor<[240],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,240,?,?],unk> loc(#loc30)
    %222 = torch.copy.to_tensor %221 : !torch.tensor<[?,240,?,?],unk> loc(#loc30)
    %223 = torch.operator "aten.hardsigmoid"(%222) : (!torch.tensor<[?,240,?,?],unk>) -> !torch.tensor loc(#loc31)
    %224 = torch.copy.to_vtensor %223 : !torch.vtensor loc(#loc32)
    %225 = torch.copy.to_vtensor %206 : !torch.vtensor loc(#loc32)
    %226 = torch.aten.mul.Tensor %224, %225 : !torch.vtensor, !torch.vtensor -> !torch.vtensor loc(#loc32)
    %227 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %228 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %229 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %230 = torch.aten.conv2d %226, %54, %none, %227, %228, %229, %int1 : !torch.vtensor, !torch.vtensor<[40,240,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %231 = torch.aten.batch_norm %230, %45, %32, %32, %45, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[40],f32>, !torch.vtensor<[40],f32>, !torch.vtensor<[40],f32>, !torch.vtensor<[40],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %232 = torch.aten.add.Tensor %231, %191, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[?,?,?,?],unk>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc33)
    %233 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %234 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %235 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %236 = torch.aten.conv2d %232, %53, %none, %233, %234, %235, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[240,40,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,240,?,?],unk> loc(#loc21)
    %237 = torch.aten.batch_norm %236, %51, %47, %47, %51, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,240,?,?],unk>, !torch.vtensor<[240],f32>, !torch.vtensor<[240],f32>, !torch.vtensor<[240],f32>, !torch.vtensor<[240],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,240,?,?],unk> loc(#loc22)
    %238 = torch.copy.to_tensor %237 : !torch.tensor<[?,240,?,?],unk> loc(#loc22)
    %239 = torch.operator "aten.hardswish_"(%238) : (!torch.tensor<[?,240,?,?],unk>) -> !torch.tensor loc(#loc34)
    %240 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %241 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %242 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %243 = torch.copy.to_vtensor %239 : !torch.vtensor loc(#loc21)
    %244 = torch.aten.conv2d %243, %52, %none, %240, %241, %242, %int240 : !torch.vtensor, !torch.vtensor<[240,1,5,5],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %245 = torch.aten.batch_norm %244, %51, %47, %47, %51, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[240],f32>, !torch.vtensor<[240],f32>, !torch.vtensor<[240],f32>, !torch.vtensor<[240],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %246 = torch.copy.to_tensor %245 : !torch.tensor<[?,?,?,?],unk> loc(#loc22)
    %247 = torch.operator "aten.hardswish_"(%246) : (!torch.tensor<[?,?,?,?],unk>) -> !torch.tensor loc(#loc34)
    %248 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc24)
    %249 = torch.copy.to_vtensor %247 : !torch.vtensor loc(#loc35)
    %250 = torch.aten.dim %249 : !torch.vtensor -> !torch.int loc(#loc35)
    %251 = torch.aten.gt.int %250, %int2 : !torch.int, !torch.int -> !torch.bool loc(#loc35)
    torch.prim.If %251 -> () {
      torch.prim.If.yield loc(#loc36)
    } else {
      torch.prim.RaiseException %str_0, %none : !torch.str, !torch.none loc(#loc36)
      torch.prim.If.yield loc(#loc36)
    } loc(#loc36)
    %252 = torch.copy.to_vtensor %247 : !torch.vtensor loc(#loc25)
    %253 = torch.aten.adaptive_avg_pool2d %252, %248 : !torch.vtensor, !torch.list<!torch.int> -> !torch.vtensor loc(#loc25)
    %254 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %255 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %256 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %257 = torch.aten.conv2d %253, %50, %49, %254, %255, %256, %int1 : !torch.vtensor, !torch.vtensor<[64,240,1,1],f32>, !torch.vtensor<[64],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc27)
    %258 = torch.aten.relu %257 : !torch.vtensor<[?,?,?,?],unk> -> !torch.vtensor<[?,?,?,?],unk> loc(#loc28)
    %259 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %260 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %261 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %262 = torch.aten.conv2d %258, %48, %47, %259, %260, %261, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[240,64,1,1],f32>, !torch.vtensor<[240],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,240,?,?],unk> loc(#loc30)
    %263 = torch.copy.to_tensor %262 : !torch.tensor<[?,240,?,?],unk> loc(#loc30)
    %264 = torch.operator "aten.hardsigmoid"(%263) : (!torch.tensor<[?,240,?,?],unk>) -> !torch.tensor loc(#loc31)
    %265 = torch.copy.to_vtensor %264 : !torch.vtensor loc(#loc32)
    %266 = torch.copy.to_vtensor %247 : !torch.vtensor loc(#loc32)
    %267 = torch.aten.mul.Tensor %265, %266 : !torch.vtensor, !torch.vtensor -> !torch.vtensor loc(#loc32)
    %268 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %269 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %270 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %271 = torch.aten.conv2d %267, %46, %none, %268, %269, %270, %int1 : !torch.vtensor, !torch.vtensor<[40,240,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %272 = torch.aten.batch_norm %271, %45, %32, %32, %45, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[40],f32>, !torch.vtensor<[40],f32>, !torch.vtensor<[40],f32>, !torch.vtensor<[40],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %273 = torch.aten.add.Tensor %272, %232, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[?,?,?,?],unk>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc33)
    %274 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %275 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %276 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %277 = torch.aten.conv2d %273, %44, %none, %274, %275, %276, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[120,40,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,120,?,?],unk> loc(#loc21)
    %278 = torch.aten.batch_norm %277, %42, %38, %38, %42, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,120,?,?],unk>, !torch.vtensor<[120],f32>, !torch.vtensor<[120],f32>, !torch.vtensor<[120],f32>, !torch.vtensor<[120],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,120,?,?],unk> loc(#loc22)
    %279 = torch.copy.to_tensor %278 : !torch.tensor<[?,120,?,?],unk> loc(#loc22)
    %280 = torch.operator "aten.hardswish_"(%279) : (!torch.tensor<[?,120,?,?],unk>) -> !torch.tensor loc(#loc34)
    %281 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %282 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %283 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %284 = torch.copy.to_vtensor %280 : !torch.vtensor loc(#loc21)
    %285 = torch.aten.conv2d %284, %43, %none, %281, %282, %283, %int120 : !torch.vtensor, !torch.vtensor<[120,1,5,5],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %286 = torch.aten.batch_norm %285, %42, %38, %38, %42, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[120],f32>, !torch.vtensor<[120],f32>, !torch.vtensor<[120],f32>, !torch.vtensor<[120],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %287 = torch.copy.to_tensor %286 : !torch.tensor<[?,?,?,?],unk> loc(#loc22)
    %288 = torch.operator "aten.hardswish_"(%287) : (!torch.tensor<[?,?,?,?],unk>) -> !torch.tensor loc(#loc34)
    %289 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc24)
    %290 = torch.copy.to_vtensor %288 : !torch.vtensor loc(#loc35)
    %291 = torch.aten.dim %290 : !torch.vtensor -> !torch.int loc(#loc35)
    %292 = torch.aten.gt.int %291, %int2 : !torch.int, !torch.int -> !torch.bool loc(#loc35)
    torch.prim.If %292 -> () {
      torch.prim.If.yield loc(#loc36)
    } else {
      torch.prim.RaiseException %str_0, %none : !torch.str, !torch.none loc(#loc36)
      torch.prim.If.yield loc(#loc36)
    } loc(#loc36)
    %293 = torch.copy.to_vtensor %288 : !torch.vtensor loc(#loc25)
    %294 = torch.aten.adaptive_avg_pool2d %293, %289 : !torch.vtensor, !torch.list<!torch.int> -> !torch.vtensor loc(#loc25)
    %295 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %296 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %297 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %298 = torch.aten.conv2d %294, %41, %40, %295, %296, %297, %int1 : !torch.vtensor, !torch.vtensor<[32,120,1,1],f32>, !torch.vtensor<[32],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc27)
    %299 = torch.aten.relu %298 : !torch.vtensor<[?,?,?,?],unk> -> !torch.vtensor<[?,?,?,?],unk> loc(#loc28)
    %300 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %301 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %302 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %303 = torch.aten.conv2d %299, %39, %38, %300, %301, %302, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[120,32,1,1],f32>, !torch.vtensor<[120],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,120,?,?],unk> loc(#loc30)
    %304 = torch.copy.to_tensor %303 : !torch.tensor<[?,120,?,?],unk> loc(#loc30)
    %305 = torch.operator "aten.hardsigmoid"(%304) : (!torch.tensor<[?,120,?,?],unk>) -> !torch.tensor loc(#loc31)
    %306 = torch.copy.to_vtensor %305 : !torch.vtensor loc(#loc32)
    %307 = torch.copy.to_vtensor %288 : !torch.vtensor loc(#loc32)
    %308 = torch.aten.mul.Tensor %306, %307 : !torch.vtensor, !torch.vtensor -> !torch.vtensor loc(#loc32)
    %309 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %310 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %311 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %312 = torch.aten.conv2d %308, %37, %none, %309, %310, %311, %int1 : !torch.vtensor, !torch.vtensor<[48,120,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %313 = torch.aten.batch_norm %312, %29, %28, %28, %29, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[48],f32>, !torch.vtensor<[48],f32>, !torch.vtensor<[48],f32>, !torch.vtensor<[48],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %314 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %315 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %316 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %317 = torch.aten.conv2d %313, %36, %none, %314, %315, %316, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[144,48,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,144,?,?],unk> loc(#loc21)
    %318 = torch.aten.batch_norm %317, %34, %11, %11, %34, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,144,?,?],unk>, !torch.vtensor<[144],f32>, !torch.vtensor<[144],f32>, !torch.vtensor<[144],f32>, !torch.vtensor<[144],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,144,?,?],unk> loc(#loc22)
    %319 = torch.copy.to_tensor %318 : !torch.tensor<[?,144,?,?],unk> loc(#loc22)
    %320 = torch.operator "aten.hardswish_"(%319) : (!torch.tensor<[?,144,?,?],unk>) -> !torch.tensor loc(#loc34)
    %321 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %322 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %323 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %324 = torch.copy.to_vtensor %320 : !torch.vtensor loc(#loc21)
    %325 = torch.aten.conv2d %324, %35, %none, %321, %322, %323, %int144 : !torch.vtensor, !torch.vtensor<[144,1,5,5],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %326 = torch.aten.batch_norm %325, %34, %11, %11, %34, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[144],f32>, !torch.vtensor<[144],f32>, !torch.vtensor<[144],f32>, !torch.vtensor<[144],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %327 = torch.copy.to_tensor %326 : !torch.tensor<[?,?,?,?],unk> loc(#loc22)
    %328 = torch.operator "aten.hardswish_"(%327) : (!torch.tensor<[?,?,?,?],unk>) -> !torch.tensor loc(#loc34)
    %329 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc24)
    %330 = torch.copy.to_vtensor %328 : !torch.vtensor loc(#loc35)
    %331 = torch.aten.dim %330 : !torch.vtensor -> !torch.int loc(#loc35)
    %332 = torch.aten.gt.int %331, %int2 : !torch.int, !torch.int -> !torch.bool loc(#loc35)
    torch.prim.If %332 -> () {
      torch.prim.If.yield loc(#loc36)
    } else {
      torch.prim.RaiseException %str_0, %none : !torch.str, !torch.none loc(#loc36)
      torch.prim.If.yield loc(#loc36)
    } loc(#loc36)
    %333 = torch.copy.to_vtensor %328 : !torch.vtensor loc(#loc25)
    %334 = torch.aten.adaptive_avg_pool2d %333, %329 : !torch.vtensor, !torch.list<!torch.int> -> !torch.vtensor loc(#loc25)
    %335 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %336 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %337 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %338 = torch.aten.conv2d %334, %33, %32, %335, %336, %337, %int1 : !torch.vtensor, !torch.vtensor<[40,144,1,1],f32>, !torch.vtensor<[40],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc27)
    %339 = torch.aten.relu %338 : !torch.vtensor<[?,?,?,?],unk> -> !torch.vtensor<[?,?,?,?],unk> loc(#loc28)
    %340 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %341 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %342 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %343 = torch.aten.conv2d %339, %31, %11, %340, %341, %342, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[144,40,1,1],f32>, !torch.vtensor<[144],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,144,?,?],unk> loc(#loc30)
    %344 = torch.copy.to_tensor %343 : !torch.tensor<[?,144,?,?],unk> loc(#loc30)
    %345 = torch.operator "aten.hardsigmoid"(%344) : (!torch.tensor<[?,144,?,?],unk>) -> !torch.tensor loc(#loc31)
    %346 = torch.copy.to_vtensor %345 : !torch.vtensor loc(#loc32)
    %347 = torch.copy.to_vtensor %328 : !torch.vtensor loc(#loc32)
    %348 = torch.aten.mul.Tensor %346, %347 : !torch.vtensor, !torch.vtensor -> !torch.vtensor loc(#loc32)
    %349 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %350 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %351 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %352 = torch.aten.conv2d %348, %30, %none, %349, %350, %351, %int1 : !torch.vtensor, !torch.vtensor<[48,144,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %353 = torch.aten.batch_norm %352, %29, %28, %28, %29, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[48],f32>, !torch.vtensor<[48],f32>, !torch.vtensor<[48],f32>, !torch.vtensor<[48],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %354 = torch.aten.add.Tensor %353, %313, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[?,?,?,?],unk>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc33)
    %355 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %356 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %357 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %358 = torch.aten.conv2d %354, %27, %none, %355, %356, %357, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[288,48,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,288,?,?],unk> loc(#loc21)
    %359 = torch.aten.batch_norm %358, %25, %21, %21, %25, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,288,?,?],unk>, !torch.vtensor<[288],f32>, !torch.vtensor<[288],f32>, !torch.vtensor<[288],f32>, !torch.vtensor<[288],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,288,?,?],unk> loc(#loc22)
    %360 = torch.copy.to_tensor %359 : !torch.tensor<[?,288,?,?],unk> loc(#loc22)
    %361 = torch.operator "aten.hardswish_"(%360) : (!torch.tensor<[?,288,?,?],unk>) -> !torch.tensor loc(#loc34)
    %362 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %363 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %364 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %365 = torch.copy.to_vtensor %361 : !torch.vtensor loc(#loc21)
    %366 = torch.aten.conv2d %365, %26, %none, %362, %363, %364, %int288 : !torch.vtensor, !torch.vtensor<[288,1,5,5],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %367 = torch.aten.batch_norm %366, %25, %21, %21, %25, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[288],f32>, !torch.vtensor<[288],f32>, !torch.vtensor<[288],f32>, !torch.vtensor<[288],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %368 = torch.copy.to_tensor %367 : !torch.tensor<[?,?,?,?],unk> loc(#loc22)
    %369 = torch.operator "aten.hardswish_"(%368) : (!torch.tensor<[?,?,?,?],unk>) -> !torch.tensor loc(#loc34)
    %370 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc24)
    %371 = torch.copy.to_vtensor %369 : !torch.vtensor loc(#loc35)
    %372 = torch.aten.dim %371 : !torch.vtensor -> !torch.int loc(#loc35)
    %373 = torch.aten.gt.int %372, %int2 : !torch.int, !torch.int -> !torch.bool loc(#loc35)
    torch.prim.If %373 -> () {
      torch.prim.If.yield loc(#loc36)
    } else {
      torch.prim.RaiseException %str_0, %none : !torch.str, !torch.none loc(#loc36)
      torch.prim.If.yield loc(#loc36)
    } loc(#loc36)
    %374 = torch.copy.to_vtensor %369 : !torch.vtensor loc(#loc25)
    %375 = torch.aten.adaptive_avg_pool2d %374, %370 : !torch.vtensor, !torch.list<!torch.int> -> !torch.vtensor loc(#loc25)
    %376 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %377 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %378 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %379 = torch.aten.conv2d %375, %24, %23, %376, %377, %378, %int1 : !torch.vtensor, !torch.vtensor<[72,288,1,1],f32>, !torch.vtensor<[72],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc27)
    %380 = torch.aten.relu %379 : !torch.vtensor<[?,?,?,?],unk> -> !torch.vtensor<[?,?,?,?],unk> loc(#loc28)
    %381 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %382 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %383 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %384 = torch.aten.conv2d %380, %22, %21, %381, %382, %383, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[288,72,1,1],f32>, !torch.vtensor<[288],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,288,?,?],unk> loc(#loc30)
    %385 = torch.copy.to_tensor %384 : !torch.tensor<[?,288,?,?],unk> loc(#loc30)
    %386 = torch.operator "aten.hardsigmoid"(%385) : (!torch.tensor<[?,288,?,?],unk>) -> !torch.tensor loc(#loc31)
    %387 = torch.copy.to_vtensor %386 : !torch.vtensor loc(#loc32)
    %388 = torch.copy.to_vtensor %369 : !torch.vtensor loc(#loc32)
    %389 = torch.aten.mul.Tensor %387, %388 : !torch.vtensor, !torch.vtensor -> !torch.vtensor loc(#loc32)
    %390 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %391 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %392 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %393 = torch.aten.conv2d %389, %20, %none, %390, %391, %392, %int1 : !torch.vtensor, !torch.vtensor<[96,288,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %394 = torch.aten.batch_norm %393, %8, %7, %7, %8, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %395 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %396 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %397 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %398 = torch.aten.conv2d %394, %19, %none, %395, %396, %397, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[576,96,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,576,?,?],unk> loc(#loc21)
    %399 = torch.aten.batch_norm %398, %5, %4, %4, %5, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,576,?,?],unk>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,576,?,?],unk> loc(#loc22)
    %400 = torch.copy.to_tensor %399 : !torch.tensor<[?,576,?,?],unk> loc(#loc22)
    %401 = torch.operator "aten.hardswish_"(%400) : (!torch.tensor<[?,576,?,?],unk>) -> !torch.tensor loc(#loc34)
    %402 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %403 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %404 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %405 = torch.copy.to_vtensor %401 : !torch.vtensor loc(#loc21)
    %406 = torch.aten.conv2d %405, %18, %none, %402, %403, %404, %int576 : !torch.vtensor, !torch.vtensor<[576,1,5,5],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %407 = torch.aten.batch_norm %406, %5, %4, %4, %5, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %408 = torch.copy.to_tensor %407 : !torch.tensor<[?,?,?,?],unk> loc(#loc22)
    %409 = torch.operator "aten.hardswish_"(%408) : (!torch.tensor<[?,?,?,?],unk>) -> !torch.tensor loc(#loc34)
    %410 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc24)
    %411 = torch.copy.to_vtensor %409 : !torch.vtensor loc(#loc35)
    %412 = torch.aten.dim %411 : !torch.vtensor -> !torch.int loc(#loc35)
    %413 = torch.aten.gt.int %412, %int2 : !torch.int, !torch.int -> !torch.bool loc(#loc35)
    torch.prim.If %413 -> () {
      torch.prim.If.yield loc(#loc36)
    } else {
      torch.prim.RaiseException %str_0, %none : !torch.str, !torch.none loc(#loc36)
      torch.prim.If.yield loc(#loc36)
    } loc(#loc36)
    %414 = torch.copy.to_vtensor %409 : !torch.vtensor loc(#loc25)
    %415 = torch.aten.adaptive_avg_pool2d %414, %410 : !torch.vtensor, !torch.list<!torch.int> -> !torch.vtensor loc(#loc25)
    %416 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %417 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %418 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %419 = torch.aten.conv2d %415, %17, %11, %416, %417, %418, %int1 : !torch.vtensor, !torch.vtensor<[144,576,1,1],f32>, !torch.vtensor<[144],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc27)
    %420 = torch.aten.relu %419 : !torch.vtensor<[?,?,?,?],unk> -> !torch.vtensor<[?,?,?,?],unk> loc(#loc28)
    %421 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %422 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %423 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %424 = torch.aten.conv2d %420, %16, %4, %421, %422, %423, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[576,144,1,1],f32>, !torch.vtensor<[576],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,576,?,?],unk> loc(#loc30)
    %425 = torch.copy.to_tensor %424 : !torch.tensor<[?,576,?,?],unk> loc(#loc30)
    %426 = torch.operator "aten.hardsigmoid"(%425) : (!torch.tensor<[?,576,?,?],unk>) -> !torch.tensor loc(#loc31)
    %427 = torch.copy.to_vtensor %426 : !torch.vtensor loc(#loc32)
    %428 = torch.copy.to_vtensor %409 : !torch.vtensor loc(#loc32)
    %429 = torch.aten.mul.Tensor %427, %428 : !torch.vtensor, !torch.vtensor -> !torch.vtensor loc(#loc32)
    %430 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %431 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %432 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %433 = torch.aten.conv2d %429, %15, %none, %430, %431, %432, %int1 : !torch.vtensor, !torch.vtensor<[96,576,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %434 = torch.aten.batch_norm %433, %8, %7, %7, %8, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %435 = torch.aten.add.Tensor %434, %394, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[?,?,?,?],unk>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc33)
    %436 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %437 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %438 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %439 = torch.aten.conv2d %435, %14, %none, %436, %437, %438, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[576,96,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,576,?,?],unk> loc(#loc21)
    %440 = torch.aten.batch_norm %439, %5, %4, %4, %5, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,576,?,?],unk>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,576,?,?],unk> loc(#loc22)
    %441 = torch.copy.to_tensor %440 : !torch.tensor<[?,576,?,?],unk> loc(#loc22)
    %442 = torch.operator "aten.hardswish_"(%441) : (!torch.tensor<[?,576,?,?],unk>) -> !torch.tensor loc(#loc34)
    %443 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %444 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %445 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %446 = torch.copy.to_vtensor %442 : !torch.vtensor loc(#loc21)
    %447 = torch.aten.conv2d %446, %13, %none, %443, %444, %445, %int576 : !torch.vtensor, !torch.vtensor<[576,1,5,5],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %448 = torch.aten.batch_norm %447, %5, %4, %4, %5, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %449 = torch.copy.to_tensor %448 : !torch.tensor<[?,?,?,?],unk> loc(#loc22)
    %450 = torch.operator "aten.hardswish_"(%449) : (!torch.tensor<[?,?,?,?],unk>) -> !torch.tensor loc(#loc34)
    %451 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc24)
    %452 = torch.copy.to_vtensor %450 : !torch.vtensor loc(#loc35)
    %453 = torch.aten.dim %452 : !torch.vtensor -> !torch.int loc(#loc35)
    %454 = torch.aten.gt.int %453, %int2 : !torch.int, !torch.int -> !torch.bool loc(#loc35)
    torch.prim.If %454 -> () {
      torch.prim.If.yield loc(#loc36)
    } else {
      torch.prim.RaiseException %str_0, %none : !torch.str, !torch.none loc(#loc36)
      torch.prim.If.yield loc(#loc36)
    } loc(#loc36)
    %455 = torch.copy.to_vtensor %450 : !torch.vtensor loc(#loc25)
    %456 = torch.aten.adaptive_avg_pool2d %455, %451 : !torch.vtensor, !torch.list<!torch.int> -> !torch.vtensor loc(#loc25)
    %457 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %458 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %459 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc26)
    %460 = torch.aten.conv2d %456, %12, %11, %457, %458, %459, %int1 : !torch.vtensor, !torch.vtensor<[144,576,1,1],f32>, !torch.vtensor<[144],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc27)
    %461 = torch.aten.relu %460 : !torch.vtensor<[?,?,?,?],unk> -> !torch.vtensor<[?,?,?,?],unk> loc(#loc28)
    %462 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %463 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %464 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc29)
    %465 = torch.aten.conv2d %461, %10, %4, %462, %463, %464, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[576,144,1,1],f32>, !torch.vtensor<[576],f32>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,576,?,?],unk> loc(#loc30)
    %466 = torch.copy.to_tensor %465 : !torch.tensor<[?,576,?,?],unk> loc(#loc30)
    %467 = torch.operator "aten.hardsigmoid"(%466) : (!torch.tensor<[?,576,?,?],unk>) -> !torch.tensor loc(#loc31)
    %468 = torch.copy.to_vtensor %467 : !torch.vtensor loc(#loc32)
    %469 = torch.copy.to_vtensor %450 : !torch.vtensor loc(#loc32)
    %470 = torch.aten.mul.Tensor %468, %469 : !torch.vtensor, !torch.vtensor -> !torch.vtensor loc(#loc32)
    %471 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %472 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %473 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc20)
    %474 = torch.aten.conv2d %470, %9, %none, %471, %472, %473, %int1 : !torch.vtensor, !torch.vtensor<[96,576,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc21)
    %475 = torch.aten.batch_norm %474, %8, %7, %7, %8, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.vtensor<[96],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,?,?,?],unk> loc(#loc22)
    %476 = torch.aten.add.Tensor %475, %435, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[?,?,?,?],unk>, !torch.int -> !torch.vtensor<[?,?,?,?],unk> loc(#loc33)
    %477 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc16)
    %478 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc16)
    %479 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc16)
    %480 = torch.aten.conv2d %476, %6, %none, %477, %478, %479, %int1 : !torch.vtensor<[?,?,?,?],unk>, !torch.vtensor<[576,96,1,1],f32>, !torch.none, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.list<!torch.int>, !torch.int -> !torch.vtensor<[?,576,?,?],unk> loc(#loc17)
    %481 = torch.aten.batch_norm %480, %5, %4, %4, %5, %false, %float1.000000e-02, %float1.000000e-03, %true : !torch.vtensor<[?,576,?,?],unk>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.vtensor<[576],f32>, !torch.bool, !torch.float, !torch.float, !torch.bool -> !torch.vtensor<[?,576,?,?],unk> loc(#loc18)
    %482 = torch.copy.to_tensor %481 : !torch.tensor<[?,576,?,?],unk> loc(#loc18)
    %483 = torch.operator "aten.hardswish_"(%482) : (!torch.tensor<[?,576,?,?],unk>) -> !torch.tensor loc(#loc19)
    %484 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<!torch.int> loc(#loc37)
    %485 = torch.copy.to_vtensor %483 : !torch.vtensor loc(#loc38)
    %486 = torch.aten.dim %485 : !torch.vtensor -> !torch.int loc(#loc38)
    %487 = torch.aten.gt.int %486, %int2 : !torch.int, !torch.int -> !torch.bool loc(#loc38)
    torch.prim.If %487 -> () {
      torch.prim.If.yield loc(#loc39)
    } else {
      torch.prim.RaiseException %str_0, %none : !torch.str, !torch.none loc(#loc39)
      torch.prim.If.yield loc(#loc39)
    } loc(#loc39)
    %488 = torch.copy.to_vtensor %483 : !torch.vtensor loc(#loc40)
    %489 = torch.aten.adaptive_avg_pool2d %488, %484 : !torch.vtensor, !torch.list<!torch.int> -> !torch.vtensor loc(#loc40)
    %490 = torch.aten.flatten.using_ints %489, %int1, %int-1 : !torch.vtensor, !torch.int, !torch.int -> !torch.vtensor loc(#loc41)
    %491 = torch.aten.linear %490, %3, %2 : !torch.vtensor, !torch.vtensor<[1024,576],f32>, !torch.vtensor<[1024],f32> -> !torch.vtensor loc(#loc42)
    %492 = torch.copy.to_tensor %491 : !torch.tensor loc(#loc42)
    %493 = torch.operator "aten.hardswish_"(%492) : (!torch.tensor) -> !torch.tensor loc(#loc43)
    %494 = torch.operator "aten.lt.float"(%float2.000000e-01, %float0.000000e00) : (!torch.float, !torch.float) -> !torch.bool loc(#loc44)
    %495 = torch.prim.If %494 -> (!torch.bool) {
      torch.prim.If.yield %true : !torch.bool loc(#loc44)
    } else {
      %499 = torch.operator "aten.gt.float"(%float2.000000e-01, %float1.000000e00) : (!torch.float, !torch.float) -> !torch.bool loc(#loc45)
      torch.prim.If.yield %499 : !torch.bool loc(#loc44)
    } loc(#loc44)
    torch.prim.If %495 -> () {
      %499 = torch.aten.format(%str, %float2.000000e-01) : !torch.str, !torch.float -> !torch.str loc(#loc2)
      torch.prim.RaiseException %499, %none : !torch.str, !torch.none loc(#loc47)
      torch.prim.If.yield loc(#loc46)
    } else {
      torch.prim.If.yield loc(#loc46)
    } loc(#loc46)
    %496 = torch.operator "aten.dropout_"(%493, %float2.000000e-01, %false) : (!torch.tensor, !torch.float, !torch.bool) -> !torch.tensor loc(#loc48)
    %497 = torch.copy.to_vtensor %496 : !torch.vtensor loc(#loc42)
    %498 = torch.aten.linear %497, %1, %0 : !torch.vtensor, !torch.vtensor<[1000,1024],f32>, !torch.vtensor<[1000],f32> -> !torch.vtensor loc(#loc42)
    return %498 : !torch.vtensor loc(#loc0)
  } loc(#loc0)
} loc(#loc0)
#loc1 = loc(callsite(callsite(callsite(callsite(callsite(callsite(unknown at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/batchnorm.py":135:8) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc2 = loc(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":1278:25 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/dropout.py":58:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":229:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc3 = loc(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":1277:11 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/dropout.py":58:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":229:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc4 = loc(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":1277:22 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/dropout.py":58:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":229:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc5 = loc(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/dropout.py":58:32 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":229:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc6 = loc(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":227:29 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc7 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(unknown at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/pooling.py":1179:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":155:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":162:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc8 = loc(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":443:45 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":447:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc9 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":444:53 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":447:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc10 = loc(callsite(callsite(callsite(callsite(callsite(unknown at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc11 = loc(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/batchnorm.py":179:12 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc12 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":2383:22 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":2419:8) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/batchnorm.py":168:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc13 = loc(callsite(callsite(unknown at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc14 = loc(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/batchnorm.py":159:26 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc15 = loc(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/batchnorm.py":161:27 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc16 = loc(callsite(callsite(callsite(callsite(callsite(callsite(unknown at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":447:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc17 = loc(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":443:15 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":447:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc18 = loc(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":2421:11 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/batchnorm.py":168:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc19 = loc(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":2074:15 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/activation.py":475:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc20 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(unknown at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":447:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc21 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":443:15 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":447:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc22 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":2421:11 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/batchnorm.py":168:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc23 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":1440:17 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/activation.py":98:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc24 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(unknown at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":155:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":162:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc25 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":1241:11 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/pooling.py":1179:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":155:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":162:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc26 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(unknown at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":447:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":156:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":162:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc27 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":443:15 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":447:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":156:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":162:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc28 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":1442:17 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/activation.py":98:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":157:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":162:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc29 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(unknown at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":447:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":158:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":162:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc30 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":443:15 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/conv.py":447:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":158:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":162:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc31 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":1967:11 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/activation.py":332:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":159:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":162:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc32 = loc(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":163:15 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc33 = loc(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":127:12 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc34 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":2074:15 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/activation.py":475:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc35 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite("<string>":5:9 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/pooling.py":1179:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":155:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":162:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc36 = loc(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite(callsite("<string>":5:2 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/pooling.py":1179:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":155:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/ops/misc.py":162:16) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":125:17) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":224:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc37 = loc(callsite(callsite(callsite(unknown at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":226:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc38 = loc(callsite(callsite(callsite(callsite("<string>":5:9 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/pooling.py":1179:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":226:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc39 = loc(callsite(callsite(callsite(callsite("<string>":5:2 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/pooling.py":1179:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":226:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc40 = loc(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":1241:11 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/pooling.py":1179:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":226:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc41 = loc(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":227:12 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc42 = loc(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/linear.py":103:15 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":229:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc43 = loc(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":2074:15 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/activation.py":475:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":229:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc44 = loc(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":1277:7 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/dropout.py":58:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":229:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc45 = loc(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":1277:18 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/dropout.py":58:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":229:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc46 = loc(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":1277:4 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/dropout.py":58:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":229:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc47 = loc(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":1278:8 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/dropout.py":58:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":229:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))
#loc48 = loc(callsite(callsite(callsite(callsite(callsite("/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/functional.py":1279:11 at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/dropout.py":58:15) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torch/nn/modules/container.py":141:20) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":229:12) at "/home/prashant/torch-mlir/mlir_venv/lib/python3.9/site-packages/torchvision/models/mobilenetv3.py":234:15) at "/home/prashant/torch-mlir/e2e_testing/torchscript/vision_models.py":122:15))