u-net_brain_mri_vaiq_int8.default.onnx.torch.elide.mlir

module {
  func.func @torch_jit(%arg0: !torch.vtensor<[32,3,256,256],f32>) -> !torch.vtensor<[32,1,256,256],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "pytorch", torch.onnx_meta.producer_version = "1.13.1"} {
    %float1.250000e-01 = torch.constant.float 1.250000e-01
    %float4.882810e-04 = torch.constant.float 4.8828125E-4
    %float3.125000e-02 = torch.constant.float 3.125000e-02
    %float1.953130e-03 = torch.constant.float 0.001953125
    %float3.906250e-03 = torch.constant.float 3.906250e-03
    %float9.765620e-04 = torch.constant.float 9.765625E-4
    %float7.812500e-03 = torch.constant.float 7.812500e-03
    %true = torch.constant.bool true
    %int2 = torch.constant.int 2
    %false = torch.constant.bool false
    %int0 = torch.constant.int 0
    %int1 = torch.constant.int 1
    %0 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x3x3x3xf32>) : !torch.vtensor<[32,3,3,3],f32>
    %1 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32xf32>) : !torch.vtensor<[32],f32>
    %2 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x32x3x3xf32>) : !torch.vtensor<[32,32,3,3],f32>
    %3 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32xf32>) : !torch.vtensor<[32],f32>
    %4 = torch.vtensor.literal(dense_resource<__elided__> : tensor<64x32x3x3xf32>) : !torch.vtensor<[64,32,3,3],f32>
    %5 = torch.vtensor.literal(dense_resource<__elided__> : tensor<64xf32>) : !torch.vtensor<[64],f32>
    %6 = torch.vtensor.literal(dense_resource<__elided__> : tensor<64x64x3x3xf32>) : !torch.vtensor<[64,64,3,3],f32>
    %7 = torch.vtensor.literal(dense_resource<__elided__> : tensor<64xf32>) : !torch.vtensor<[64],f32>
    %8 = torch.vtensor.literal(dense_resource<__elided__> : tensor<128x64x3x3xf32>) : !torch.vtensor<[128,64,3,3],f32>
    %9 = torch.vtensor.literal(dense_resource<__elided__> : tensor<128xf32>) : !torch.vtensor<[128],f32>
    %10 = torch.vtensor.literal(dense_resource<__elided__> : tensor<128x128x3x3xf32>) : !torch.vtensor<[128,128,3,3],f32>
    %11 = torch.vtensor.literal(dense_resource<__elided__> : tensor<128xf32>) : !torch.vtensor<[128],f32>
    %12 = torch.vtensor.literal(dense_resource<__elided__> : tensor<256x128x3x3xf32>) : !torch.vtensor<[256,128,3,3],f32>
    %13 = torch.vtensor.literal(dense_resource<__elided__> : tensor<256xf32>) : !torch.vtensor<[256],f32>
    %14 = torch.vtensor.literal(dense_resource<__elided__> : tensor<256x256x3x3xf32>) : !torch.vtensor<[256,256,3,3],f32>
    %15 = torch.vtensor.literal(dense_resource<__elided__> : tensor<256xf32>) : !torch.vtensor<[256],f32>
    %16 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x256x3x3xf32>) : !torch.vtensor<[512,256,3,3],f32>
    %17 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32>
    %18 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x512x3x3xf32>) : !torch.vtensor<[512,512,3,3],f32>
    %19 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512xf32>) : !torch.vtensor<[512],f32>
    %20 = torch.vtensor.literal(dense_resource<__elided__> : tensor<512x256x2x2xf32>) : !torch.vtensor<[512,256,2,2],f32>
    %21 = torch.vtensor.literal(dense_resource<__elided__> : tensor<256xf32>) : !torch.vtensor<[256],f32>
    %22 = torch.vtensor.literal(dense_resource<__elided__> : tensor<256x512x3x3xf32>) : !torch.vtensor<[256,512,3,3],f32>
    %23 = torch.vtensor.literal(dense_resource<__elided__> : tensor<256xf32>) : !torch.vtensor<[256],f32>
    %24 = torch.vtensor.literal(dense_resource<__elided__> : tensor<256x256x3x3xf32>) : !torch.vtensor<[256,256,3,3],f32>
    %25 = torch.vtensor.literal(dense_resource<__elided__> : tensor<256xf32>) : !torch.vtensor<[256],f32>
    %26 = torch.vtensor.literal(dense_resource<__elided__> : tensor<256x128x2x2xf32>) : !torch.vtensor<[256,128,2,2],f32>
    %27 = torch.vtensor.literal(dense_resource<__elided__> : tensor<128xf32>) : !torch.vtensor<[128],f32>
    %28 = torch.vtensor.literal(dense_resource<__elided__> : tensor<128x256x3x3xf32>) : !torch.vtensor<[128,256,3,3],f32>
    %29 = torch.vtensor.literal(dense_resource<__elided__> : tensor<128xf32>) : !torch.vtensor<[128],f32>
    %30 = torch.vtensor.literal(dense_resource<__elided__> : tensor<128x128x3x3xf32>) : !torch.vtensor<[128,128,3,3],f32>
    %31 = torch.vtensor.literal(dense_resource<__elided__> : tensor<128xf32>) : !torch.vtensor<[128],f32>
    %32 = torch.vtensor.literal(dense_resource<__elided__> : tensor<128x64x2x2xf32>) : !torch.vtensor<[128,64,2,2],f32>
    %33 = torch.vtensor.literal(dense_resource<__elided__> : tensor<64xf32>) : !torch.vtensor<[64],f32>
    %34 = torch.vtensor.literal(dense_resource<__elided__> : tensor<64x128x3x3xf32>) : !torch.vtensor<[64,128,3,3],f32>
    %35 = torch.vtensor.literal(dense_resource<__elided__> : tensor<64xf32>) : !torch.vtensor<[64],f32>
    %36 = torch.vtensor.literal(dense_resource<__elided__> : tensor<64x64x3x3xf32>) : !torch.vtensor<[64,64,3,3],f32>
    %37 = torch.vtensor.literal(dense_resource<__elided__> : tensor<64xf32>) : !torch.vtensor<[64],f32>
    %38 = torch.vtensor.literal(dense_resource<__elided__> : tensor<64x32x2x2xf32>) : !torch.vtensor<[64,32,2,2],f32>
    %39 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32xf32>) : !torch.vtensor<[32],f32>
    %40 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x64x3x3xf32>) : !torch.vtensor<[32,64,3,3],f32>
    %41 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32xf32>) : !torch.vtensor<[32],f32>
    %42 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32x32x3x3xf32>) : !torch.vtensor<[32,32,3,3],f32>
    %43 = torch.vtensor.literal(dense_resource<__elided__> : tensor<32xf32>) : !torch.vtensor<[32],f32>
    %44 = torch.vtensor.literal(dense_resource<__elided__> : tensor<1x32x1x1xf32>) : !torch.vtensor<[1,32,1,1],f32>
    %45 = torch.vtensor.literal(dense<-0.3984375> : tensor<1xf32>) : !torch.vtensor<[1],f32>
    %int12 = torch.constant.int 12
    %float1.562500e-02 = torch.constant.float 1.562500e-02
    %46 = torch.aten.quantize_per_tensor %arg0, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,3,256,256],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,3,256,256],!torch.qint8>
    %47 = torch.aten.int_repr %46 : !torch.vtensor<[32,3,256,256],!torch.qint8> -> !torch.vtensor<[32,3,256,256],si8>
    %48 = torch.aten._make_per_tensor_quantized_tensor %47, %float1.562500e-02, %int0 : !torch.vtensor<[32,3,256,256],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,3,256,256],!torch.qint8>
    %49 = torch.aten.dequantize.self %48 : !torch.vtensor<[32,3,256,256],!torch.qint8> -> !torch.vtensor<[32,3,256,256],f32>
    %50 = torch.aten.quantize_per_tensor %0, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[32,3,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,3,3,3],!torch.qint8>
    %51 = torch.aten.int_repr %50 : !torch.vtensor<[32,3,3,3],!torch.qint8> -> !torch.vtensor<[32,3,3,3],si8>
    %52 = torch.aten._make_per_tensor_quantized_tensor %51, %float7.812500e-03, %int0 : !torch.vtensor<[32,3,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,3,3,3],!torch.qint8>
    %53 = torch.aten.dequantize.self %52 : !torch.vtensor<[32,3,3,3],!torch.qint8> -> !torch.vtensor<[32,3,3,3],f32>
    %54 = torch.aten.quantize_per_tensor %1, %float9.765620e-04, %int0, %int12 : !torch.vtensor<[32],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32],!torch.qint8>
    %55 = torch.aten.int_repr %54 : !torch.vtensor<[32],!torch.qint8> -> !torch.vtensor<[32],si8>
    %56 = torch.aten._make_per_tensor_quantized_tensor %55, %float9.765620e-04, %int0 : !torch.vtensor<[32],si8>, !torch.float, !torch.int -> !torch.vtensor<[32],!torch.qint8>
    %57 = torch.aten.dequantize.self %56 : !torch.vtensor<[32],!torch.qint8> -> !torch.vtensor<[32],f32>
    %58 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
    %59 = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<int>
    %60 = torch.aten.convolution %49, %53, %57, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,3,256,256],f32>, !torch.vtensor<[32,3,3,3],f32>, !torch.vtensor<[32],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,32,256,256],f32>
    %61 = torch.aten.relu %60 : !torch.vtensor<[32,32,256,256],f32> -> !torch.vtensor<[32,32,256,256],f32>
    %62 = torch.aten.quantize_per_tensor %61, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[32,32,256,256],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,32,256,256],!torch.qint8>
    %63 = torch.aten.int_repr %62 : !torch.vtensor<[32,32,256,256],!torch.qint8> -> !torch.vtensor<[32,32,256,256],si8>
    %64 = torch.aten._make_per_tensor_quantized_tensor %63, %float7.812500e-03, %int0 : !torch.vtensor<[32,32,256,256],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,32,256,256],!torch.qint8>
    %65 = torch.aten.dequantize.self %64 : !torch.vtensor<[32,32,256,256],!torch.qint8> -> !torch.vtensor<[32,32,256,256],f32>
    %66 = torch.aten.quantize_per_tensor %2, %float3.906250e-03, %int0, %int12 : !torch.vtensor<[32,32,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,32,3,3],!torch.qint8>
    %67 = torch.aten.int_repr %66 : !torch.vtensor<[32,32,3,3],!torch.qint8> -> !torch.vtensor<[32,32,3,3],si8>
    %68 = torch.aten._make_per_tensor_quantized_tensor %67, %float3.906250e-03, %int0 : !torch.vtensor<[32,32,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,32,3,3],!torch.qint8>
    %69 = torch.aten.dequantize.self %68 : !torch.vtensor<[32,32,3,3],!torch.qint8> -> !torch.vtensor<[32,32,3,3],f32>
    %70 = torch.aten.quantize_per_tensor %3, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[32],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32],!torch.qint8>
    %71 = torch.aten.int_repr %70 : !torch.vtensor<[32],!torch.qint8> -> !torch.vtensor<[32],si8>
    %72 = torch.aten._make_per_tensor_quantized_tensor %71, %float7.812500e-03, %int0 : !torch.vtensor<[32],si8>, !torch.float, !torch.int -> !torch.vtensor<[32],!torch.qint8>
    %73 = torch.aten.dequantize.self %72 : !torch.vtensor<[32],!torch.qint8> -> !torch.vtensor<[32],f32>
    %74 = torch.aten.convolution %65, %69, %73, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,32,256,256],f32>, !torch.vtensor<[32,32,3,3],f32>, !torch.vtensor<[32],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,32,256,256],f32>
    %75 = torch.aten.relu %74 : !torch.vtensor<[32,32,256,256],f32> -> !torch.vtensor<[32,32,256,256],f32>
    %76 = torch.aten.quantize_per_tensor %75, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,32,256,256],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,32,256,256],!torch.qint8>
    %77 = torch.aten.int_repr %76 : !torch.vtensor<[32,32,256,256],!torch.qint8> -> !torch.vtensor<[32,32,256,256],si8>
    %78 = torch.aten._make_per_tensor_quantized_tensor %77, %float1.562500e-02, %int0 : !torch.vtensor<[32,32,256,256],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,32,256,256],!torch.qint8>
    %79 = torch.aten.dequantize.self %78 : !torch.vtensor<[32,32,256,256],!torch.qint8> -> !torch.vtensor<[32,32,256,256],f32>
    %80 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<int>
    %81 = torch.aten.max_pool2d %79, %80, %80, %59, %58, %false : !torch.vtensor<[32,32,256,256],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool -> !torch.vtensor<[32,32,128,128],f32>
    %82 = torch.aten.quantize_per_tensor %81, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,32,128,128],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,32,128,128],!torch.qint8>
    %83 = torch.aten.int_repr %82 : !torch.vtensor<[32,32,128,128],!torch.qint8> -> !torch.vtensor<[32,32,128,128],si8>
    %84 = torch.aten._make_per_tensor_quantized_tensor %83, %float1.562500e-02, %int0 : !torch.vtensor<[32,32,128,128],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,32,128,128],!torch.qint8>
    %85 = torch.aten.dequantize.self %84 : !torch.vtensor<[32,32,128,128],!torch.qint8> -> !torch.vtensor<[32,32,128,128],f32>
    %86 = torch.aten.quantize_per_tensor %4, %float3.906250e-03, %int0, %int12 : !torch.vtensor<[64,32,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[64,32,3,3],!torch.qint8>
    %87 = torch.aten.int_repr %86 : !torch.vtensor<[64,32,3,3],!torch.qint8> -> !torch.vtensor<[64,32,3,3],si8>
    %88 = torch.aten._make_per_tensor_quantized_tensor %87, %float3.906250e-03, %int0 : !torch.vtensor<[64,32,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[64,32,3,3],!torch.qint8>
    %89 = torch.aten.dequantize.self %88 : !torch.vtensor<[64,32,3,3],!torch.qint8> -> !torch.vtensor<[64,32,3,3],f32>
    %90 = torch.aten.quantize_per_tensor %5, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[64],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[64],!torch.qint8>
    %91 = torch.aten.int_repr %90 : !torch.vtensor<[64],!torch.qint8> -> !torch.vtensor<[64],si8>
    %92 = torch.aten._make_per_tensor_quantized_tensor %91, %float7.812500e-03, %int0 : !torch.vtensor<[64],si8>, !torch.float, !torch.int -> !torch.vtensor<[64],!torch.qint8>
    %93 = torch.aten.dequantize.self %92 : !torch.vtensor<[64],!torch.qint8> -> !torch.vtensor<[64],f32>
    %94 = torch.aten.convolution %85, %89, %93, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,32,128,128],f32>, !torch.vtensor<[64,32,3,3],f32>, !torch.vtensor<[64],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,64,128,128],f32>
    %95 = torch.aten.relu %94 : !torch.vtensor<[32,64,128,128],f32> -> !torch.vtensor<[32,64,128,128],f32>
    %96 = torch.aten.quantize_per_tensor %95, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,64,128,128],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,64,128,128],!torch.qint8>
    %97 = torch.aten.int_repr %96 : !torch.vtensor<[32,64,128,128],!torch.qint8> -> !torch.vtensor<[32,64,128,128],si8>
    %98 = torch.aten._make_per_tensor_quantized_tensor %97, %float1.562500e-02, %int0 : !torch.vtensor<[32,64,128,128],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,64,128,128],!torch.qint8>
    %99 = torch.aten.dequantize.self %98 : !torch.vtensor<[32,64,128,128],!torch.qint8> -> !torch.vtensor<[32,64,128,128],f32>
    %100 = torch.aten.quantize_per_tensor %6, %float3.906250e-03, %int0, %int12 : !torch.vtensor<[64,64,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[64,64,3,3],!torch.qint8>
    %101 = torch.aten.int_repr %100 : !torch.vtensor<[64,64,3,3],!torch.qint8> -> !torch.vtensor<[64,64,3,3],si8>
    %102 = torch.aten._make_per_tensor_quantized_tensor %101, %float3.906250e-03, %int0 : !torch.vtensor<[64,64,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[64,64,3,3],!torch.qint8>
    %103 = torch.aten.dequantize.self %102 : !torch.vtensor<[64,64,3,3],!torch.qint8> -> !torch.vtensor<[64,64,3,3],f32>
    %104 = torch.aten.quantize_per_tensor %7, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[64],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[64],!torch.qint8>
    %105 = torch.aten.int_repr %104 : !torch.vtensor<[64],!torch.qint8> -> !torch.vtensor<[64],si8>
    %106 = torch.aten._make_per_tensor_quantized_tensor %105, %float7.812500e-03, %int0 : !torch.vtensor<[64],si8>, !torch.float, !torch.int -> !torch.vtensor<[64],!torch.qint8>
    %107 = torch.aten.dequantize.self %106 : !torch.vtensor<[64],!torch.qint8> -> !torch.vtensor<[64],f32>
    %108 = torch.aten.convolution %99, %103, %107, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,64,128,128],f32>, !torch.vtensor<[64,64,3,3],f32>, !torch.vtensor<[64],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,64,128,128],f32>
    %109 = torch.aten.relu %108 : !torch.vtensor<[32,64,128,128],f32> -> !torch.vtensor<[32,64,128,128],f32>
    %110 = torch.aten.quantize_per_tensor %109, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,64,128,128],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,64,128,128],!torch.qint8>
    %111 = torch.aten.int_repr %110 : !torch.vtensor<[32,64,128,128],!torch.qint8> -> !torch.vtensor<[32,64,128,128],si8>
    %112 = torch.aten._make_per_tensor_quantized_tensor %111, %float1.562500e-02, %int0 : !torch.vtensor<[32,64,128,128],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,64,128,128],!torch.qint8>
    %113 = torch.aten.dequantize.self %112 : !torch.vtensor<[32,64,128,128],!torch.qint8> -> !torch.vtensor<[32,64,128,128],f32>
    %114 = torch.aten.max_pool2d %113, %80, %80, %59, %58, %false : !torch.vtensor<[32,64,128,128],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool -> !torch.vtensor<[32,64,64,64],f32>
    %115 = torch.aten.quantize_per_tensor %114, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,64,64,64],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,64,64,64],!torch.qint8>
    %116 = torch.aten.int_repr %115 : !torch.vtensor<[32,64,64,64],!torch.qint8> -> !torch.vtensor<[32,64,64,64],si8>
    %117 = torch.aten._make_per_tensor_quantized_tensor %116, %float1.562500e-02, %int0 : !torch.vtensor<[32,64,64,64],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,64,64,64],!torch.qint8>
    %118 = torch.aten.dequantize.self %117 : !torch.vtensor<[32,64,64,64],!torch.qint8> -> !torch.vtensor<[32,64,64,64],f32>
    %119 = torch.aten.quantize_per_tensor %8, %float1.953130e-03, %int0, %int12 : !torch.vtensor<[128,64,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[128,64,3,3],!torch.qint8>
    %120 = torch.aten.int_repr %119 : !torch.vtensor<[128,64,3,3],!torch.qint8> -> !torch.vtensor<[128,64,3,3],si8>
    %121 = torch.aten._make_per_tensor_quantized_tensor %120, %float1.953130e-03, %int0 : !torch.vtensor<[128,64,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[128,64,3,3],!torch.qint8>
    %122 = torch.aten.dequantize.self %121 : !torch.vtensor<[128,64,3,3],!torch.qint8> -> !torch.vtensor<[128,64,3,3],f32>
    %123 = torch.aten.quantize_per_tensor %9, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[128],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[128],!torch.qint8>
    %124 = torch.aten.int_repr %123 : !torch.vtensor<[128],!torch.qint8> -> !torch.vtensor<[128],si8>
    %125 = torch.aten._make_per_tensor_quantized_tensor %124, %float7.812500e-03, %int0 : !torch.vtensor<[128],si8>, !torch.float, !torch.int -> !torch.vtensor<[128],!torch.qint8>
    %126 = torch.aten.dequantize.self %125 : !torch.vtensor<[128],!torch.qint8> -> !torch.vtensor<[128],f32>
    %127 = torch.aten.convolution %118, %122, %126, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,64,64,64],f32>, !torch.vtensor<[128,64,3,3],f32>, !torch.vtensor<[128],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,128,64,64],f32>
    %128 = torch.aten.relu %127 : !torch.vtensor<[32,128,64,64],f32> -> !torch.vtensor<[32,128,64,64],f32>
    %129 = torch.aten.quantize_per_tensor %128, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,128,64,64],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,128,64,64],!torch.qint8>
    %130 = torch.aten.int_repr %129 : !torch.vtensor<[32,128,64,64],!torch.qint8> -> !torch.vtensor<[32,128,64,64],si8>
    %131 = torch.aten._make_per_tensor_quantized_tensor %130, %float1.562500e-02, %int0 : !torch.vtensor<[32,128,64,64],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,128,64,64],!torch.qint8>
    %132 = torch.aten.dequantize.self %131 : !torch.vtensor<[32,128,64,64],!torch.qint8> -> !torch.vtensor<[32,128,64,64],f32>
    %133 = torch.aten.quantize_per_tensor %10, %float1.953130e-03, %int0, %int12 : !torch.vtensor<[128,128,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[128,128,3,3],!torch.qint8>
    %134 = torch.aten.int_repr %133 : !torch.vtensor<[128,128,3,3],!torch.qint8> -> !torch.vtensor<[128,128,3,3],si8>
    %135 = torch.aten._make_per_tensor_quantized_tensor %134, %float1.953130e-03, %int0 : !torch.vtensor<[128,128,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[128,128,3,3],!torch.qint8>
    %136 = torch.aten.dequantize.self %135 : !torch.vtensor<[128,128,3,3],!torch.qint8> -> !torch.vtensor<[128,128,3,3],f32>
    %137 = torch.aten.quantize_per_tensor %11, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[128],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[128],!torch.qint8>
    %138 = torch.aten.int_repr %137 : !torch.vtensor<[128],!torch.qint8> -> !torch.vtensor<[128],si8>
    %139 = torch.aten._make_per_tensor_quantized_tensor %138, %float1.562500e-02, %int0 : !torch.vtensor<[128],si8>, !torch.float, !torch.int -> !torch.vtensor<[128],!torch.qint8>
    %140 = torch.aten.dequantize.self %139 : !torch.vtensor<[128],!torch.qint8> -> !torch.vtensor<[128],f32>
    %141 = torch.aten.convolution %132, %136, %140, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,128,64,64],f32>, !torch.vtensor<[128,128,3,3],f32>, !torch.vtensor<[128],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,128,64,64],f32>
    %142 = torch.aten.relu %141 : !torch.vtensor<[32,128,64,64],f32> -> !torch.vtensor<[32,128,64,64],f32>
    %143 = torch.aten.quantize_per_tensor %142, %float3.125000e-02, %int0, %int12 : !torch.vtensor<[32,128,64,64],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,128,64,64],!torch.qint8>
    %144 = torch.aten.int_repr %143 : !torch.vtensor<[32,128,64,64],!torch.qint8> -> !torch.vtensor<[32,128,64,64],si8>
    %145 = torch.aten._make_per_tensor_quantized_tensor %144, %float3.125000e-02, %int0 : !torch.vtensor<[32,128,64,64],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,128,64,64],!torch.qint8>
    %146 = torch.aten.dequantize.self %145 : !torch.vtensor<[32,128,64,64],!torch.qint8> -> !torch.vtensor<[32,128,64,64],f32>
    %147 = torch.aten.max_pool2d %146, %80, %80, %59, %58, %false : !torch.vtensor<[32,128,64,64],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool -> !torch.vtensor<[32,128,32,32],f32>
    %148 = torch.aten.quantize_per_tensor %147, %float3.125000e-02, %int0, %int12 : !torch.vtensor<[32,128,32,32],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,128,32,32],!torch.qint8>
    %149 = torch.aten.int_repr %148 : !torch.vtensor<[32,128,32,32],!torch.qint8> -> !torch.vtensor<[32,128,32,32],si8>
    %150 = torch.aten._make_per_tensor_quantized_tensor %149, %float3.125000e-02, %int0 : !torch.vtensor<[32,128,32,32],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,128,32,32],!torch.qint8>
    %151 = torch.aten.dequantize.self %150 : !torch.vtensor<[32,128,32,32],!torch.qint8> -> !torch.vtensor<[32,128,32,32],f32>
    %152 = torch.aten.quantize_per_tensor %12, %float9.765620e-04, %int0, %int12 : !torch.vtensor<[256,128,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[256,128,3,3],!torch.qint8>
    %153 = torch.aten.int_repr %152 : !torch.vtensor<[256,128,3,3],!torch.qint8> -> !torch.vtensor<[256,128,3,3],si8>
    %154 = torch.aten._make_per_tensor_quantized_tensor %153, %float9.765620e-04, %int0 : !torch.vtensor<[256,128,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[256,128,3,3],!torch.qint8>
    %155 = torch.aten.dequantize.self %154 : !torch.vtensor<[256,128,3,3],!torch.qint8> -> !torch.vtensor<[256,128,3,3],f32>
    %156 = torch.aten.quantize_per_tensor %13, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[256],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[256],!torch.qint8>
    %157 = torch.aten.int_repr %156 : !torch.vtensor<[256],!torch.qint8> -> !torch.vtensor<[256],si8>
    %158 = torch.aten._make_per_tensor_quantized_tensor %157, %float7.812500e-03, %int0 : !torch.vtensor<[256],si8>, !torch.float, !torch.int -> !torch.vtensor<[256],!torch.qint8>
    %159 = torch.aten.dequantize.self %158 : !torch.vtensor<[256],!torch.qint8> -> !torch.vtensor<[256],f32>
    %160 = torch.aten.convolution %151, %155, %159, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,128,32,32],f32>, !torch.vtensor<[256,128,3,3],f32>, !torch.vtensor<[256],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,256,32,32],f32>
    %161 = torch.aten.relu %160 : !torch.vtensor<[32,256,32,32],f32> -> !torch.vtensor<[32,256,32,32],f32>
    %162 = torch.aten.quantize_per_tensor %161, %float3.125000e-02, %int0, %int12 : !torch.vtensor<[32,256,32,32],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,256,32,32],!torch.qint8>
    %163 = torch.aten.int_repr %162 : !torch.vtensor<[32,256,32,32],!torch.qint8> -> !torch.vtensor<[32,256,32,32],si8>
    %164 = torch.aten._make_per_tensor_quantized_tensor %163, %float3.125000e-02, %int0 : !torch.vtensor<[32,256,32,32],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,256,32,32],!torch.qint8>
    %165 = torch.aten.dequantize.self %164 : !torch.vtensor<[32,256,32,32],!torch.qint8> -> !torch.vtensor<[32,256,32,32],f32>
    %166 = torch.aten.quantize_per_tensor %14, %float1.953130e-03, %int0, %int12 : !torch.vtensor<[256,256,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[256,256,3,3],!torch.qint8>
    %167 = torch.aten.int_repr %166 : !torch.vtensor<[256,256,3,3],!torch.qint8> -> !torch.vtensor<[256,256,3,3],si8>
    %168 = torch.aten._make_per_tensor_quantized_tensor %167, %float1.953130e-03, %int0 : !torch.vtensor<[256,256,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[256,256,3,3],!torch.qint8>
    %169 = torch.aten.dequantize.self %168 : !torch.vtensor<[256,256,3,3],!torch.qint8> -> !torch.vtensor<[256,256,3,3],f32>
    %170 = torch.aten.quantize_per_tensor %15, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[256],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[256],!torch.qint8>
    %171 = torch.aten.int_repr %170 : !torch.vtensor<[256],!torch.qint8> -> !torch.vtensor<[256],si8>
    %172 = torch.aten._make_per_tensor_quantized_tensor %171, %float1.562500e-02, %int0 : !torch.vtensor<[256],si8>, !torch.float, !torch.int -> !torch.vtensor<[256],!torch.qint8>
    %173 = torch.aten.dequantize.self %172 : !torch.vtensor<[256],!torch.qint8> -> !torch.vtensor<[256],f32>
    %174 = torch.aten.convolution %165, %169, %173, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,256,32,32],f32>, !torch.vtensor<[256,256,3,3],f32>, !torch.vtensor<[256],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,256,32,32],f32>
    %175 = torch.aten.relu %174 : !torch.vtensor<[32,256,32,32],f32> -> !torch.vtensor<[32,256,32,32],f32>
    %176 = torch.aten.quantize_per_tensor %175, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,256,32,32],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,256,32,32],!torch.qint8>
    %177 = torch.aten.int_repr %176 : !torch.vtensor<[32,256,32,32],!torch.qint8> -> !torch.vtensor<[32,256,32,32],si8>
    %178 = torch.aten._make_per_tensor_quantized_tensor %177, %float1.562500e-02, %int0 : !torch.vtensor<[32,256,32,32],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,256,32,32],!torch.qint8>
    %179 = torch.aten.dequantize.self %178 : !torch.vtensor<[32,256,32,32],!torch.qint8> -> !torch.vtensor<[32,256,32,32],f32>
    %180 = torch.aten.max_pool2d %179, %80, %80, %59, %58, %false : !torch.vtensor<[32,256,32,32],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool -> !torch.vtensor<[32,256,16,16],f32>
    %181 = torch.aten.quantize_per_tensor %180, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,256,16,16],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,256,16,16],!torch.qint8>
    %182 = torch.aten.int_repr %181 : !torch.vtensor<[32,256,16,16],!torch.qint8> -> !torch.vtensor<[32,256,16,16],si8>
    %183 = torch.aten._make_per_tensor_quantized_tensor %182, %float1.562500e-02, %int0 : !torch.vtensor<[32,256,16,16],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,256,16,16],!torch.qint8>
    %184 = torch.aten.dequantize.self %183 : !torch.vtensor<[32,256,16,16],!torch.qint8> -> !torch.vtensor<[32,256,16,16],f32>
    %185 = torch.aten.quantize_per_tensor %16, %float4.882810e-04, %int0, %int12 : !torch.vtensor<[512,256,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[512,256,3,3],!torch.qint8>
    %186 = torch.aten.int_repr %185 : !torch.vtensor<[512,256,3,3],!torch.qint8> -> !torch.vtensor<[512,256,3,3],si8>
    %187 = torch.aten._make_per_tensor_quantized_tensor %186, %float4.882810e-04, %int0 : !torch.vtensor<[512,256,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[512,256,3,3],!torch.qint8>
    %188 = torch.aten.dequantize.self %187 : !torch.vtensor<[512,256,3,3],!torch.qint8> -> !torch.vtensor<[512,256,3,3],f32>
    %189 = torch.aten.quantize_per_tensor %17, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[512],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[512],!torch.qint8>
    %190 = torch.aten.int_repr %189 : !torch.vtensor<[512],!torch.qint8> -> !torch.vtensor<[512],si8>
    %191 = torch.aten._make_per_tensor_quantized_tensor %190, %float7.812500e-03, %int0 : !torch.vtensor<[512],si8>, !torch.float, !torch.int -> !torch.vtensor<[512],!torch.qint8>
    %192 = torch.aten.dequantize.self %191 : !torch.vtensor<[512],!torch.qint8> -> !torch.vtensor<[512],f32>
    %193 = torch.aten.convolution %184, %188, %192, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,256,16,16],f32>, !torch.vtensor<[512,256,3,3],f32>, !torch.vtensor<[512],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,512,16,16],f32>
    %194 = torch.aten.relu %193 : !torch.vtensor<[32,512,16,16],f32> -> !torch.vtensor<[32,512,16,16],f32>
    %195 = torch.aten.quantize_per_tensor %194, %float3.125000e-02, %int0, %int12 : !torch.vtensor<[32,512,16,16],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,512,16,16],!torch.qint8>
    %196 = torch.aten.int_repr %195 : !torch.vtensor<[32,512,16,16],!torch.qint8> -> !torch.vtensor<[32,512,16,16],si8>
    %197 = torch.aten._make_per_tensor_quantized_tensor %196, %float3.125000e-02, %int0 : !torch.vtensor<[32,512,16,16],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,512,16,16],!torch.qint8>
    %198 = torch.aten.dequantize.self %197 : !torch.vtensor<[32,512,16,16],!torch.qint8> -> !torch.vtensor<[32,512,16,16],f32>
    %199 = torch.aten.quantize_per_tensor %18, %float9.765620e-04, %int0, %int12 : !torch.vtensor<[512,512,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[512,512,3,3],!torch.qint8>
    %200 = torch.aten.int_repr %199 : !torch.vtensor<[512,512,3,3],!torch.qint8> -> !torch.vtensor<[512,512,3,3],si8>
    %201 = torch.aten._make_per_tensor_quantized_tensor %200, %float9.765620e-04, %int0 : !torch.vtensor<[512,512,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[512,512,3,3],!torch.qint8>
    %202 = torch.aten.dequantize.self %201 : !torch.vtensor<[512,512,3,3],!torch.qint8> -> !torch.vtensor<[512,512,3,3],f32>
    %203 = torch.aten.quantize_per_tensor %19, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[512],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[512],!torch.qint8>
    %204 = torch.aten.int_repr %203 : !torch.vtensor<[512],!torch.qint8> -> !torch.vtensor<[512],si8>
    %205 = torch.aten._make_per_tensor_quantized_tensor %204, %float7.812500e-03, %int0 : !torch.vtensor<[512],si8>, !torch.float, !torch.int -> !torch.vtensor<[512],!torch.qint8>
    %206 = torch.aten.dequantize.self %205 : !torch.vtensor<[512],!torch.qint8> -> !torch.vtensor<[512],f32>
    %207 = torch.aten.convolution %198, %202, %206, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,512,16,16],f32>, !torch.vtensor<[512,512,3,3],f32>, !torch.vtensor<[512],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,512,16,16],f32>
    %208 = torch.aten.relu %207 : !torch.vtensor<[32,512,16,16],f32> -> !torch.vtensor<[32,512,16,16],f32>
    %209 = torch.aten.quantize_per_tensor %208, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,512,16,16],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,512,16,16],!torch.qint8>
    %210 = torch.aten.int_repr %209 : !torch.vtensor<[32,512,16,16],!torch.qint8> -> !torch.vtensor<[32,512,16,16],si8>
    %211 = torch.aten._make_per_tensor_quantized_tensor %210, %float1.562500e-02, %int0 : !torch.vtensor<[32,512,16,16],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,512,16,16],!torch.qint8>
    %212 = torch.aten.dequantize.self %211 : !torch.vtensor<[32,512,16,16],!torch.qint8> -> !torch.vtensor<[32,512,16,16],f32>
    %213 = torch.aten.quantize_per_tensor %20, %float1.953130e-03, %int0, %int12 : !torch.vtensor<[512,256,2,2],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[512,256,2,2],!torch.qint8>
    %214 = torch.aten.int_repr %213 : !torch.vtensor<[512,256,2,2],!torch.qint8> -> !torch.vtensor<[512,256,2,2],si8>
    %215 = torch.aten._make_per_tensor_quantized_tensor %214, %float1.953130e-03, %int0 : !torch.vtensor<[512,256,2,2],si8>, !torch.float, !torch.int -> !torch.vtensor<[512,256,2,2],!torch.qint8>
    %216 = torch.aten.dequantize.self %215 : !torch.vtensor<[512,256,2,2],!torch.qint8> -> !torch.vtensor<[512,256,2,2],f32>
    %217 = torch.aten.quantize_per_tensor %21, %float4.882810e-04, %int0, %int12 : !torch.vtensor<[256],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[256],!torch.qint8>
    %218 = torch.aten.int_repr %217 : !torch.vtensor<[256],!torch.qint8> -> !torch.vtensor<[256],si8>
    %219 = torch.aten._make_per_tensor_quantized_tensor %218, %float4.882810e-04, %int0 : !torch.vtensor<[256],si8>, !torch.float, !torch.int -> !torch.vtensor<[256],!torch.qint8>
    %220 = torch.aten.dequantize.self %219 : !torch.vtensor<[256],!torch.qint8> -> !torch.vtensor<[256],f32>
    %221 = torch.aten.convolution %212, %216, %220, %80, %59, %58, %true, %59, %int1 : !torch.vtensor<[32,512,16,16],f32>, !torch.vtensor<[512,256,2,2],f32>, !torch.vtensor<[256],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,256,32,32],f32>
    %222 = torch.prim.ListConstruct %221, %179 : (!torch.vtensor<[32,256,32,32],f32>, !torch.vtensor<[32,256,32,32],f32>) -> !torch.list<vtensor>
    %223 = torch.aten.cat %222, %int1 : !torch.list<vtensor>, !torch.int -> !torch.vtensor<[32,512,32,32],f32>
    %224 = torch.aten.quantize_per_tensor %223, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,512,32,32],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,512,32,32],!torch.qint8>
    %225 = torch.aten.int_repr %224 : !torch.vtensor<[32,512,32,32],!torch.qint8> -> !torch.vtensor<[32,512,32,32],si8>
    %226 = torch.aten._make_per_tensor_quantized_tensor %225, %float1.562500e-02, %int0 : !torch.vtensor<[32,512,32,32],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,512,32,32],!torch.qint8>
    %227 = torch.aten.dequantize.self %226 : !torch.vtensor<[32,512,32,32],!torch.qint8> -> !torch.vtensor<[32,512,32,32],f32>
    %228 = torch.aten.quantize_per_tensor %22, %float4.882810e-04, %int0, %int12 : !torch.vtensor<[256,512,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[256,512,3,3],!torch.qint8>
    %229 = torch.aten.int_repr %228 : !torch.vtensor<[256,512,3,3],!torch.qint8> -> !torch.vtensor<[256,512,3,3],si8>
    %230 = torch.aten._make_per_tensor_quantized_tensor %229, %float4.882810e-04, %int0 : !torch.vtensor<[256,512,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[256,512,3,3],!torch.qint8>
    %231 = torch.aten.dequantize.self %230 : !torch.vtensor<[256,512,3,3],!torch.qint8> -> !torch.vtensor<[256,512,3,3],f32>
    %232 = torch.aten.quantize_per_tensor %23, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[256],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[256],!torch.qint8>
    %233 = torch.aten.int_repr %232 : !torch.vtensor<[256],!torch.qint8> -> !torch.vtensor<[256],si8>
    %234 = torch.aten._make_per_tensor_quantized_tensor %233, %float1.562500e-02, %int0 : !torch.vtensor<[256],si8>, !torch.float, !torch.int -> !torch.vtensor<[256],!torch.qint8>
    %235 = torch.aten.dequantize.self %234 : !torch.vtensor<[256],!torch.qint8> -> !torch.vtensor<[256],f32>
    %236 = torch.aten.convolution %227, %231, %235, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,512,32,32],f32>, !torch.vtensor<[256,512,3,3],f32>, !torch.vtensor<[256],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,256,32,32],f32>
    %237 = torch.aten.relu %236 : !torch.vtensor<[32,256,32,32],f32> -> !torch.vtensor<[32,256,32,32],f32>
    %238 = torch.aten.quantize_per_tensor %237, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,256,32,32],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,256,32,32],!torch.qint8>
    %239 = torch.aten.int_repr %238 : !torch.vtensor<[32,256,32,32],!torch.qint8> -> !torch.vtensor<[32,256,32,32],si8>
    %240 = torch.aten._make_per_tensor_quantized_tensor %239, %float1.562500e-02, %int0 : !torch.vtensor<[32,256,32,32],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,256,32,32],!torch.qint8>
    %241 = torch.aten.dequantize.self %240 : !torch.vtensor<[32,256,32,32],!torch.qint8> -> !torch.vtensor<[32,256,32,32],f32>
    %242 = torch.aten.quantize_per_tensor %24, %float9.765620e-04, %int0, %int12 : !torch.vtensor<[256,256,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[256,256,3,3],!torch.qint8>
    %243 = torch.aten.int_repr %242 : !torch.vtensor<[256,256,3,3],!torch.qint8> -> !torch.vtensor<[256,256,3,3],si8>
    %244 = torch.aten._make_per_tensor_quantized_tensor %243, %float9.765620e-04, %int0 : !torch.vtensor<[256,256,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[256,256,3,3],!torch.qint8>
    %245 = torch.aten.dequantize.self %244 : !torch.vtensor<[256,256,3,3],!torch.qint8> -> !torch.vtensor<[256,256,3,3],f32>
    %246 = torch.aten.quantize_per_tensor %25, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[256],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[256],!torch.qint8>
    %247 = torch.aten.int_repr %246 : !torch.vtensor<[256],!torch.qint8> -> !torch.vtensor<[256],si8>
    %248 = torch.aten._make_per_tensor_quantized_tensor %247, %float7.812500e-03, %int0 : !torch.vtensor<[256],si8>, !torch.float, !torch.int -> !torch.vtensor<[256],!torch.qint8>
    %249 = torch.aten.dequantize.self %248 : !torch.vtensor<[256],!torch.qint8> -> !torch.vtensor<[256],f32>
    %250 = torch.aten.convolution %241, %245, %249, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,256,32,32],f32>, !torch.vtensor<[256,256,3,3],f32>, !torch.vtensor<[256],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,256,32,32],f32>
    %251 = torch.aten.relu %250 : !torch.vtensor<[32,256,32,32],f32> -> !torch.vtensor<[32,256,32,32],f32>
    %252 = torch.aten.quantize_per_tensor %251, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,256,32,32],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,256,32,32],!torch.qint8>
    %253 = torch.aten.int_repr %252 : !torch.vtensor<[32,256,32,32],!torch.qint8> -> !torch.vtensor<[32,256,32,32],si8>
    %254 = torch.aten._make_per_tensor_quantized_tensor %253, %float1.562500e-02, %int0 : !torch.vtensor<[32,256,32,32],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,256,32,32],!torch.qint8>
    %255 = torch.aten.dequantize.self %254 : !torch.vtensor<[32,256,32,32],!torch.qint8> -> !torch.vtensor<[32,256,32,32],f32>
    %256 = torch.aten.quantize_per_tensor %26, %float1.953130e-03, %int0, %int12 : !torch.vtensor<[256,128,2,2],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[256,128,2,2],!torch.qint8>
    %257 = torch.aten.int_repr %256 : !torch.vtensor<[256,128,2,2],!torch.qint8> -> !torch.vtensor<[256,128,2,2],si8>
    %258 = torch.aten._make_per_tensor_quantized_tensor %257, %float1.953130e-03, %int0 : !torch.vtensor<[256,128,2,2],si8>, !torch.float, !torch.int -> !torch.vtensor<[256,128,2,2],!torch.qint8>
    %259 = torch.aten.dequantize.self %258 : !torch.vtensor<[256,128,2,2],!torch.qint8> -> !torch.vtensor<[256,128,2,2],f32>
    %260 = torch.aten.quantize_per_tensor %27, %float9.765620e-04, %int0, %int12 : !torch.vtensor<[128],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[128],!torch.qint8>
    %261 = torch.aten.int_repr %260 : !torch.vtensor<[128],!torch.qint8> -> !torch.vtensor<[128],si8>
    %262 = torch.aten._make_per_tensor_quantized_tensor %261, %float9.765620e-04, %int0 : !torch.vtensor<[128],si8>, !torch.float, !torch.int -> !torch.vtensor<[128],!torch.qint8>
    %263 = torch.aten.dequantize.self %262 : !torch.vtensor<[128],!torch.qint8> -> !torch.vtensor<[128],f32>
    %264 = torch.aten.convolution %255, %259, %263, %80, %59, %58, %true, %59, %int1 : !torch.vtensor<[32,256,32,32],f32>, !torch.vtensor<[256,128,2,2],f32>, !torch.vtensor<[128],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,128,64,64],f32>
    %265 = torch.prim.ListConstruct %264, %146 : (!torch.vtensor<[32,128,64,64],f32>, !torch.vtensor<[32,128,64,64],f32>) -> !torch.list<vtensor>
    %266 = torch.aten.cat %265, %int1 : !torch.list<vtensor>, !torch.int -> !torch.vtensor<[32,256,64,64],f32>
    %267 = torch.aten.quantize_per_tensor %266, %float3.125000e-02, %int0, %int12 : !torch.vtensor<[32,256,64,64],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,256,64,64],!torch.qint8>
    %268 = torch.aten.int_repr %267 : !torch.vtensor<[32,256,64,64],!torch.qint8> -> !torch.vtensor<[32,256,64,64],si8>
    %269 = torch.aten._make_per_tensor_quantized_tensor %268, %float3.125000e-02, %int0 : !torch.vtensor<[32,256,64,64],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,256,64,64],!torch.qint8>
    %270 = torch.aten.dequantize.self %269 : !torch.vtensor<[32,256,64,64],!torch.qint8> -> !torch.vtensor<[32,256,64,64],f32>
    %271 = torch.aten.quantize_per_tensor %28, %float9.765620e-04, %int0, %int12 : !torch.vtensor<[128,256,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[128,256,3,3],!torch.qint8>
    %272 = torch.aten.int_repr %271 : !torch.vtensor<[128,256,3,3],!torch.qint8> -> !torch.vtensor<[128,256,3,3],si8>
    %273 = torch.aten._make_per_tensor_quantized_tensor %272, %float9.765620e-04, %int0 : !torch.vtensor<[128,256,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[128,256,3,3],!torch.qint8>
    %274 = torch.aten.dequantize.self %273 : !torch.vtensor<[128,256,3,3],!torch.qint8> -> !torch.vtensor<[128,256,3,3],f32>
    %275 = torch.aten.quantize_per_tensor %29, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[128],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[128],!torch.qint8>
    %276 = torch.aten.int_repr %275 : !torch.vtensor<[128],!torch.qint8> -> !torch.vtensor<[128],si8>
    %277 = torch.aten._make_per_tensor_quantized_tensor %276, %float7.812500e-03, %int0 : !torch.vtensor<[128],si8>, !torch.float, !torch.int -> !torch.vtensor<[128],!torch.qint8>
    %278 = torch.aten.dequantize.self %277 : !torch.vtensor<[128],!torch.qint8> -> !torch.vtensor<[128],f32>
    %279 = torch.aten.convolution %270, %274, %278, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,256,64,64],f32>, !torch.vtensor<[128,256,3,3],f32>, !torch.vtensor<[128],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,128,64,64],f32>
    %280 = torch.aten.relu %279 : !torch.vtensor<[32,128,64,64],f32> -> !torch.vtensor<[32,128,64,64],f32>
    %281 = torch.aten.quantize_per_tensor %280, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,128,64,64],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,128,64,64],!torch.qint8>
    %282 = torch.aten.int_repr %281 : !torch.vtensor<[32,128,64,64],!torch.qint8> -> !torch.vtensor<[32,128,64,64],si8>
    %283 = torch.aten._make_per_tensor_quantized_tensor %282, %float1.562500e-02, %int0 : !torch.vtensor<[32,128,64,64],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,128,64,64],!torch.qint8>
    %284 = torch.aten.dequantize.self %283 : !torch.vtensor<[32,128,64,64],!torch.qint8> -> !torch.vtensor<[32,128,64,64],f32>
    %285 = torch.aten.quantize_per_tensor %30, %float1.953130e-03, %int0, %int12 : !torch.vtensor<[128,128,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[128,128,3,3],!torch.qint8>
    %286 = torch.aten.int_repr %285 : !torch.vtensor<[128,128,3,3],!torch.qint8> -> !torch.vtensor<[128,128,3,3],si8>
    %287 = torch.aten._make_per_tensor_quantized_tensor %286, %float1.953130e-03, %int0 : !torch.vtensor<[128,128,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[128,128,3,3],!torch.qint8>
    %288 = torch.aten.dequantize.self %287 : !torch.vtensor<[128,128,3,3],!torch.qint8> -> !torch.vtensor<[128,128,3,3],f32>
    %289 = torch.aten.quantize_per_tensor %31, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[128],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[128],!torch.qint8>
    %290 = torch.aten.int_repr %289 : !torch.vtensor<[128],!torch.qint8> -> !torch.vtensor<[128],si8>
    %291 = torch.aten._make_per_tensor_quantized_tensor %290, %float7.812500e-03, %int0 : !torch.vtensor<[128],si8>, !torch.float, !torch.int -> !torch.vtensor<[128],!torch.qint8>
    %292 = torch.aten.dequantize.self %291 : !torch.vtensor<[128],!torch.qint8> -> !torch.vtensor<[128],f32>
    %293 = torch.aten.convolution %284, %288, %292, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,128,64,64],f32>, !torch.vtensor<[128,128,3,3],f32>, !torch.vtensor<[128],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,128,64,64],f32>
    %294 = torch.aten.relu %293 : !torch.vtensor<[32,128,64,64],f32> -> !torch.vtensor<[32,128,64,64],f32>
    %295 = torch.aten.quantize_per_tensor %294, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,128,64,64],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,128,64,64],!torch.qint8>
    %296 = torch.aten.int_repr %295 : !torch.vtensor<[32,128,64,64],!torch.qint8> -> !torch.vtensor<[32,128,64,64],si8>
    %297 = torch.aten._make_per_tensor_quantized_tensor %296, %float1.562500e-02, %int0 : !torch.vtensor<[32,128,64,64],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,128,64,64],!torch.qint8>
    %298 = torch.aten.dequantize.self %297 : !torch.vtensor<[32,128,64,64],!torch.qint8> -> !torch.vtensor<[32,128,64,64],f32>
    %299 = torch.aten.quantize_per_tensor %32, %float1.953130e-03, %int0, %int12 : !torch.vtensor<[128,64,2,2],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[128,64,2,2],!torch.qint8>
    %300 = torch.aten.int_repr %299 : !torch.vtensor<[128,64,2,2],!torch.qint8> -> !torch.vtensor<[128,64,2,2],si8>
    %301 = torch.aten._make_per_tensor_quantized_tensor %300, %float1.953130e-03, %int0 : !torch.vtensor<[128,64,2,2],si8>, !torch.float, !torch.int -> !torch.vtensor<[128,64,2,2],!torch.qint8>
    %302 = torch.aten.dequantize.self %301 : !torch.vtensor<[128,64,2,2],!torch.qint8> -> !torch.vtensor<[128,64,2,2],f32>
    %303 = torch.aten.quantize_per_tensor %33, %float1.953130e-03, %int0, %int12 : !torch.vtensor<[64],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[64],!torch.qint8>
    %304 = torch.aten.int_repr %303 : !torch.vtensor<[64],!torch.qint8> -> !torch.vtensor<[64],si8>
    %305 = torch.aten._make_per_tensor_quantized_tensor %304, %float1.953130e-03, %int0 : !torch.vtensor<[64],si8>, !torch.float, !torch.int -> !torch.vtensor<[64],!torch.qint8>
    %306 = torch.aten.dequantize.self %305 : !torch.vtensor<[64],!torch.qint8> -> !torch.vtensor<[64],f32>
    %307 = torch.aten.convolution %298, %302, %306, %80, %59, %58, %true, %59, %int1 : !torch.vtensor<[32,128,64,64],f32>, !torch.vtensor<[128,64,2,2],f32>, !torch.vtensor<[64],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,64,128,128],f32>
    %308 = torch.prim.ListConstruct %307, %113 : (!torch.vtensor<[32,64,128,128],f32>, !torch.vtensor<[32,64,128,128],f32>) -> !torch.list<vtensor>
    %309 = torch.aten.cat %308, %int1 : !torch.list<vtensor>, !torch.int -> !torch.vtensor<[32,128,128,128],f32>
    %310 = torch.aten.quantize_per_tensor %309, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,128,128,128],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,128,128,128],!torch.qint8>
    %311 = torch.aten.int_repr %310 : !torch.vtensor<[32,128,128,128],!torch.qint8> -> !torch.vtensor<[32,128,128,128],si8>
    %312 = torch.aten._make_per_tensor_quantized_tensor %311, %float1.562500e-02, %int0 : !torch.vtensor<[32,128,128,128],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,128,128,128],!torch.qint8>
    %313 = torch.aten.dequantize.self %312 : !torch.vtensor<[32,128,128,128],!torch.qint8> -> !torch.vtensor<[32,128,128,128],f32>
    %314 = torch.aten.quantize_per_tensor %34, %float1.953130e-03, %int0, %int12 : !torch.vtensor<[64,128,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[64,128,3,3],!torch.qint8>
    %315 = torch.aten.int_repr %314 : !torch.vtensor<[64,128,3,3],!torch.qint8> -> !torch.vtensor<[64,128,3,3],si8>
    %316 = torch.aten._make_per_tensor_quantized_tensor %315, %float1.953130e-03, %int0 : !torch.vtensor<[64,128,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[64,128,3,3],!torch.qint8>
    %317 = torch.aten.dequantize.self %316 : !torch.vtensor<[64,128,3,3],!torch.qint8> -> !torch.vtensor<[64,128,3,3],f32>
    %318 = torch.aten.quantize_per_tensor %35, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[64],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[64],!torch.qint8>
    %319 = torch.aten.int_repr %318 : !torch.vtensor<[64],!torch.qint8> -> !torch.vtensor<[64],si8>
    %320 = torch.aten._make_per_tensor_quantized_tensor %319, %float7.812500e-03, %int0 : !torch.vtensor<[64],si8>, !torch.float, !torch.int -> !torch.vtensor<[64],!torch.qint8>
    %321 = torch.aten.dequantize.self %320 : !torch.vtensor<[64],!torch.qint8> -> !torch.vtensor<[64],f32>
    %322 = torch.aten.convolution %313, %317, %321, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,128,128,128],f32>, !torch.vtensor<[64,128,3,3],f32>, !torch.vtensor<[64],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,64,128,128],f32>
    %323 = torch.aten.relu %322 : !torch.vtensor<[32,64,128,128],f32> -> !torch.vtensor<[32,64,128,128],f32>
    %324 = torch.aten.quantize_per_tensor %323, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,64,128,128],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,64,128,128],!torch.qint8>
    %325 = torch.aten.int_repr %324 : !torch.vtensor<[32,64,128,128],!torch.qint8> -> !torch.vtensor<[32,64,128,128],si8>
    %326 = torch.aten._make_per_tensor_quantized_tensor %325, %float1.562500e-02, %int0 : !torch.vtensor<[32,64,128,128],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,64,128,128],!torch.qint8>
    %327 = torch.aten.dequantize.self %326 : !torch.vtensor<[32,64,128,128],!torch.qint8> -> !torch.vtensor<[32,64,128,128],f32>
    %328 = torch.aten.quantize_per_tensor %36, %float1.953130e-03, %int0, %int12 : !torch.vtensor<[64,64,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[64,64,3,3],!torch.qint8>
    %329 = torch.aten.int_repr %328 : !torch.vtensor<[64,64,3,3],!torch.qint8> -> !torch.vtensor<[64,64,3,3],si8>
    %330 = torch.aten._make_per_tensor_quantized_tensor %329, %float1.953130e-03, %int0 : !torch.vtensor<[64,64,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[64,64,3,3],!torch.qint8>
    %331 = torch.aten.dequantize.self %330 : !torch.vtensor<[64,64,3,3],!torch.qint8> -> !torch.vtensor<[64,64,3,3],f32>
    %332 = torch.aten.quantize_per_tensor %37, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[64],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[64],!torch.qint8>
    %333 = torch.aten.int_repr %332 : !torch.vtensor<[64],!torch.qint8> -> !torch.vtensor<[64],si8>
    %334 = torch.aten._make_per_tensor_quantized_tensor %333, %float7.812500e-03, %int0 : !torch.vtensor<[64],si8>, !torch.float, !torch.int -> !torch.vtensor<[64],!torch.qint8>
    %335 = torch.aten.dequantize.self %334 : !torch.vtensor<[64],!torch.qint8> -> !torch.vtensor<[64],f32>
    %336 = torch.aten.convolution %327, %331, %335, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,64,128,128],f32>, !torch.vtensor<[64,64,3,3],f32>, !torch.vtensor<[64],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,64,128,128],f32>
    %337 = torch.aten.relu %336 : !torch.vtensor<[32,64,128,128],f32> -> !torch.vtensor<[32,64,128,128],f32>
    %338 = torch.aten.quantize_per_tensor %337, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,64,128,128],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,64,128,128],!torch.qint8>
    %339 = torch.aten.int_repr %338 : !torch.vtensor<[32,64,128,128],!torch.qint8> -> !torch.vtensor<[32,64,128,128],si8>
    %340 = torch.aten._make_per_tensor_quantized_tensor %339, %float1.562500e-02, %int0 : !torch.vtensor<[32,64,128,128],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,64,128,128],!torch.qint8>
    %341 = torch.aten.dequantize.self %340 : !torch.vtensor<[32,64,128,128],!torch.qint8> -> !torch.vtensor<[32,64,128,128],f32>
    %342 = torch.aten.quantize_per_tensor %38, %float3.906250e-03, %int0, %int12 : !torch.vtensor<[64,32,2,2],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[64,32,2,2],!torch.qint8>
    %343 = torch.aten.int_repr %342 : !torch.vtensor<[64,32,2,2],!torch.qint8> -> !torch.vtensor<[64,32,2,2],si8>
    %344 = torch.aten._make_per_tensor_quantized_tensor %343, %float3.906250e-03, %int0 : !torch.vtensor<[64,32,2,2],si8>, !torch.float, !torch.int -> !torch.vtensor<[64,32,2,2],!torch.qint8>
    %345 = torch.aten.dequantize.self %344 : !torch.vtensor<[64,32,2,2],!torch.qint8> -> !torch.vtensor<[64,32,2,2],f32>
    %346 = torch.aten.quantize_per_tensor %39, %float1.953130e-03, %int0, %int12 : !torch.vtensor<[32],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32],!torch.qint8>
    %347 = torch.aten.int_repr %346 : !torch.vtensor<[32],!torch.qint8> -> !torch.vtensor<[32],si8>
    %348 = torch.aten._make_per_tensor_quantized_tensor %347, %float1.953130e-03, %int0 : !torch.vtensor<[32],si8>, !torch.float, !torch.int -> !torch.vtensor<[32],!torch.qint8>
    %349 = torch.aten.dequantize.self %348 : !torch.vtensor<[32],!torch.qint8> -> !torch.vtensor<[32],f32>
    %350 = torch.aten.convolution %341, %345, %349, %80, %59, %58, %true, %59, %int1 : !torch.vtensor<[32,64,128,128],f32>, !torch.vtensor<[64,32,2,2],f32>, !torch.vtensor<[32],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,32,256,256],f32>
    %351 = torch.prim.ListConstruct %350, %79 : (!torch.vtensor<[32,32,256,256],f32>, !torch.vtensor<[32,32,256,256],f32>) -> !torch.list<vtensor>
    %352 = torch.aten.cat %351, %int1 : !torch.list<vtensor>, !torch.int -> !torch.vtensor<[32,64,256,256],f32>
    %353 = torch.aten.quantize_per_tensor %352, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32,64,256,256],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,64,256,256],!torch.qint8>
    %354 = torch.aten.int_repr %353 : !torch.vtensor<[32,64,256,256],!torch.qint8> -> !torch.vtensor<[32,64,256,256],si8>
    %355 = torch.aten._make_per_tensor_quantized_tensor %354, %float1.562500e-02, %int0 : !torch.vtensor<[32,64,256,256],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,64,256,256],!torch.qint8>
    %356 = torch.aten.dequantize.self %355 : !torch.vtensor<[32,64,256,256],!torch.qint8> -> !torch.vtensor<[32,64,256,256],f32>
    %357 = torch.aten.quantize_per_tensor %40, %float3.906250e-03, %int0, %int12 : !torch.vtensor<[32,64,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,64,3,3],!torch.qint8>
    %358 = torch.aten.int_repr %357 : !torch.vtensor<[32,64,3,3],!torch.qint8> -> !torch.vtensor<[32,64,3,3],si8>
    %359 = torch.aten._make_per_tensor_quantized_tensor %358, %float3.906250e-03, %int0 : !torch.vtensor<[32,64,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,64,3,3],!torch.qint8>
    %360 = torch.aten.dequantize.self %359 : !torch.vtensor<[32,64,3,3],!torch.qint8> -> !torch.vtensor<[32,64,3,3],f32>
    %361 = torch.aten.quantize_per_tensor %41, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32],!torch.qint8>
    %362 = torch.aten.int_repr %361 : !torch.vtensor<[32],!torch.qint8> -> !torch.vtensor<[32],si8>
    %363 = torch.aten._make_per_tensor_quantized_tensor %362, %float1.562500e-02, %int0 : !torch.vtensor<[32],si8>, !torch.float, !torch.int -> !torch.vtensor<[32],!torch.qint8>
    %364 = torch.aten.dequantize.self %363 : !torch.vtensor<[32],!torch.qint8> -> !torch.vtensor<[32],f32>
    %365 = torch.aten.convolution %356, %360, %364, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,64,256,256],f32>, !torch.vtensor<[32,64,3,3],f32>, !torch.vtensor<[32],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,32,256,256],f32>
    %366 = torch.aten.relu %365 : !torch.vtensor<[32,32,256,256],f32> -> !torch.vtensor<[32,32,256,256],f32>
    %367 = torch.aten.quantize_per_tensor %366, %float3.125000e-02, %int0, %int12 : !torch.vtensor<[32,32,256,256],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,32,256,256],!torch.qint8>
    %368 = torch.aten.int_repr %367 : !torch.vtensor<[32,32,256,256],!torch.qint8> -> !torch.vtensor<[32,32,256,256],si8>
    %369 = torch.aten._make_per_tensor_quantized_tensor %368, %float3.125000e-02, %int0 : !torch.vtensor<[32,32,256,256],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,32,256,256],!torch.qint8>
    %370 = torch.aten.dequantize.self %369 : !torch.vtensor<[32,32,256,256],!torch.qint8> -> !torch.vtensor<[32,32,256,256],f32>
    %371 = torch.aten.quantize_per_tensor %42, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[32,32,3,3],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,32,3,3],!torch.qint8>
    %372 = torch.aten.int_repr %371 : !torch.vtensor<[32,32,3,3],!torch.qint8> -> !torch.vtensor<[32,32,3,3],si8>
    %373 = torch.aten._make_per_tensor_quantized_tensor %372, %float7.812500e-03, %int0 : !torch.vtensor<[32,32,3,3],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,32,3,3],!torch.qint8>
    %374 = torch.aten.dequantize.self %373 : !torch.vtensor<[32,32,3,3],!torch.qint8> -> !torch.vtensor<[32,32,3,3],f32>
    %375 = torch.aten.quantize_per_tensor %43, %float1.562500e-02, %int0, %int12 : !torch.vtensor<[32],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32],!torch.qint8>
    %376 = torch.aten.int_repr %375 : !torch.vtensor<[32],!torch.qint8> -> !torch.vtensor<[32],si8>
    %377 = torch.aten._make_per_tensor_quantized_tensor %376, %float1.562500e-02, %int0 : !torch.vtensor<[32],si8>, !torch.float, !torch.int -> !torch.vtensor<[32],!torch.qint8>
    %378 = torch.aten.dequantize.self %377 : !torch.vtensor<[32],!torch.qint8> -> !torch.vtensor<[32],f32>
    %379 = torch.aten.convolution %370, %374, %378, %58, %58, %58, %false, %59, %int1 : !torch.vtensor<[32,32,256,256],f32>, !torch.vtensor<[32,32,3,3],f32>, !torch.vtensor<[32],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,32,256,256],f32>
    %380 = torch.aten.relu %379 : !torch.vtensor<[32,32,256,256],f32> -> !torch.vtensor<[32,32,256,256],f32>
    %381 = torch.aten.quantize_per_tensor %380, %float3.125000e-02, %int0, %int12 : !torch.vtensor<[32,32,256,256],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,32,256,256],!torch.qint8>
    %382 = torch.aten.int_repr %381 : !torch.vtensor<[32,32,256,256],!torch.qint8> -> !torch.vtensor<[32,32,256,256],si8>
    %383 = torch.aten._make_per_tensor_quantized_tensor %382, %float3.125000e-02, %int0 : !torch.vtensor<[32,32,256,256],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,32,256,256],!torch.qint8>
    %384 = torch.aten.dequantize.self %383 : !torch.vtensor<[32,32,256,256],!torch.qint8> -> !torch.vtensor<[32,32,256,256],f32>
    %385 = torch.aten.quantize_per_tensor %44, %float7.812500e-03, %int0, %int12 : !torch.vtensor<[1,32,1,1],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[1,32,1,1],!torch.qint8>
    %386 = torch.aten.int_repr %385 : !torch.vtensor<[1,32,1,1],!torch.qint8> -> !torch.vtensor<[1,32,1,1],si8>
    %387 = torch.aten._make_per_tensor_quantized_tensor %386, %float7.812500e-03, %int0 : !torch.vtensor<[1,32,1,1],si8>, !torch.float, !torch.int -> !torch.vtensor<[1,32,1,1],!torch.qint8>
    %388 = torch.aten.dequantize.self %387 : !torch.vtensor<[1,32,1,1],!torch.qint8> -> !torch.vtensor<[1,32,1,1],f32>
    %389 = torch.aten.quantize_per_tensor %45, %float3.906250e-03, %int0, %int12 : !torch.vtensor<[1],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[1],!torch.qint8>
    %390 = torch.aten.int_repr %389 : !torch.vtensor<[1],!torch.qint8> -> !torch.vtensor<[1],si8>
    %391 = torch.aten._make_per_tensor_quantized_tensor %390, %float3.906250e-03, %int0 : !torch.vtensor<[1],si8>, !torch.float, !torch.int -> !torch.vtensor<[1],!torch.qint8>
    %392 = torch.aten.dequantize.self %391 : !torch.vtensor<[1],!torch.qint8> -> !torch.vtensor<[1],f32>
    %393 = torch.aten.convolution %384, %388, %392, %58, %59, %58, %false, %59, %int1 : !torch.vtensor<[32,32,256,256],f32>, !torch.vtensor<[1,32,1,1],f32>, !torch.vtensor<[1],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,1,256,256],f32>
    %394 = torch.aten.quantize_per_tensor %393, %float1.250000e-01, %int0, %int12 : !torch.vtensor<[32,1,256,256],f32>, !torch.float, !torch.int, !torch.int -> !torch.vtensor<[32,1,256,256],!torch.qint8>
    %395 = torch.aten.int_repr %394 : !torch.vtensor<[32,1,256,256],!torch.qint8> -> !torch.vtensor<[32,1,256,256],si8>
    %396 = torch.aten._make_per_tensor_quantized_tensor %395, %float1.250000e-01, %int0 : !torch.vtensor<[32,1,256,256],si8>, !torch.float, !torch.int -> !torch.vtensor<[32,1,256,256],!torch.qint8>
    %397 = torch.aten.dequantize.self %396 : !torch.vtensor<[32,1,256,256],!torch.qint8> -> !torch.vtensor<[32,1,256,256],f32>
    %398 = torch.aten.sigmoid %397 : !torch.vtensor<[32,1,256,256],f32> -> !torch.vtensor<[32,1,256,256],f32>
    return %398 : !torch.vtensor<[32,1,256,256],f32>
  }
}

%221 = torch.aten.convolution %212, %216, %220, %80, %59, %58, %true, %59, %int1 : !torch.vtensor<[32,512,16,16],f32>, !torch.vtensor<[512,256,2,2],f32>, !torch.vtensor<[256],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int -> !torch.vtensor<[32,256,32,32],f32>