ResNet18 reduced to one BB, with all operators ranked+dtype'ed

resnet.mlir

func @forward(%arg0: tensor<?x3x?x?xf32>) -> tensor<?x?xf32> {
  %c-1_i64 = constant -1 : i64
  %c3_i64 = constant 3 : i64
  %cst = constant 1.000000e-05 : f64
  %bool_false = basicpy.bool_constant false
  %cst_0 = constant 1.000000e-01 : f64
  %bool_true = basicpy.bool_constant true
  %c0_i64 = constant 0 : i64
  %c1_i64 = constant 1 : i64
  %cst_1 = constant opaque<"_", "0xDEADBEEF"> : tensor<64x3x7x7xf32>
  %cst_2 = constant opaque<"_", "0xDEADBEEF"> : tensor<64x64x3x3xf32>
  %cst_3 = constant dense<1.000000e+00> : tensor<64xf32>
  %cst_4 = constant dense<0.000000e+00> : tensor<64xf32>
  %cst_5 = constant opaque<"_", "0xDEADBEEF"> : tensor<128x64x3x3xf32>
  %cst_6 = constant opaque<"_", "0xDEADBEEF"> : tensor<128x64x1x1xf32>
  %cst_7 = constant opaque<"_", "0xDEADBEEF"> : tensor<128x128x3x3xf32>
  %cst_8 = constant dense<1.000000e+00> : tensor<128xf32>
  %cst_9 = constant dense<0.000000e+00> : tensor<128xf32>
  %cst_10 = constant opaque<"_", "0xDEADBEEF"> : tensor<256x128x3x3xf32>
  %cst_11 = constant opaque<"_", "0xDEADBEEF"> : tensor<256x128x1x1xf32>
  %cst_12 = constant opaque<"_", "0xDEADBEEF"> : tensor<256x256x3x3xf32>
  %cst_13 = constant dense<1.000000e+00> : tensor<256xf32>
  %cst_14 = constant dense<0.000000e+00> : tensor<256xf32>
  %cst_15 = constant opaque<"_", "0xDEADBEEF"> : tensor<512x256x3x3xf32>
  %cst_16 = constant opaque<"_", "0xDEADBEEF"> : tensor<512x256x1x1xf32>
  %cst_17 = constant opaque<"_", "0xDEADBEEF"> : tensor<512x512x3x3xf32>
  %cst_18 = constant dense<1.000000e+00> : tensor<512xf32>
  %cst_19 = constant dense<0.000000e+00> : tensor<512xf32>
  %cst_20 = constant opaque<"_", "0xDEADBEEF"> : tensor<1000x512xf32>
  %cst_21 = constant opaque<"_", "0xDEADBEEF"> : tensor<1000xf32>
  %c2_i64 = constant 2 : i64
  %0 = basicpy.singleton : !basicpy.NoneType
  %1 = basicpy.build_list %c2_i64, %c2_i64 : (i64, i64) -> !basicpy.ListType
  %2 = basicpy.build_list %c3_i64, %c3_i64 : (i64, i64) -> !basicpy.ListType
  %3 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %4 = "aten.conv2d"(%arg0, %cst_1, %0, %1, %2, %3, %c1_i64) : (tensor<?x3x?x?xf32>, tensor<64x3x7x7xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %5 = numpy.tensor_static_info_cast %4 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %6 = numpy.tensor_static_info_cast %5 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %7 = numpy.tensor_static_info_cast %6 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %8 = numpy.create_array_from_tensor %7 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %9 = numpy.copy_to_tensor %8 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %10 = numpy.copy_to_tensor %8 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %11 = numpy.tensor_static_info_cast %10 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %12 = "aten.batch_norm"(%11, %cst_3, %cst_4, %cst_4, %cst_3, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %13 = numpy.tensor_static_info_cast %12 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %14 = numpy.tensor_static_info_cast %13 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %15 = numpy.tensor_static_info_cast %14 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %16 = numpy.create_array_from_tensor %15 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %17 = numpy.copy_to_tensor %16 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %18 = numpy.tensor_static_info_cast %17 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %19 = "aten.relu"(%18) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %20 = numpy.tensor_static_info_cast %19 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %20 overwrites %16 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %21 = basicpy.build_list %c3_i64, %c3_i64 : (i64, i64) -> !basicpy.ListType
  %22 = basicpy.build_list %c2_i64, %c2_i64 : (i64, i64) -> !basicpy.ListType
  %23 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %24 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %25 = torch.prim.unchecked_cast %22 : !basicpy.ListType -> !basicpy.ListType
  %26 = numpy.copy_to_tensor %16 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %27 = numpy.tensor_static_info_cast %26 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %28 = "aten.max_pool2d"(%27, %21, %25, %23, %24, %bool_false) : (tensor<?x?x?x?xf32>, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %29 = numpy.tensor_static_info_cast %28 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %30 = numpy.tensor_static_info_cast %29 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %31 = numpy.tensor_static_info_cast %30 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %32 = numpy.create_array_from_tensor %31 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %33 = basicpy.singleton : !basicpy.NoneType
  %34 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %35 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %36 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %37 = numpy.copy_to_tensor %32 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %38 = numpy.tensor_static_info_cast %37 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %39 = "aten.conv2d"(%38, %cst_2, %33, %34, %35, %36, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<64x64x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %40 = numpy.tensor_static_info_cast %39 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %41 = numpy.tensor_static_info_cast %40 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %42 = numpy.tensor_static_info_cast %41 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %43 = numpy.create_array_from_tensor %42 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %44 = numpy.copy_to_tensor %43 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %45 = numpy.copy_to_tensor %43 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %46 = numpy.tensor_static_info_cast %45 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %47 = "aten.batch_norm"(%46, %cst_3, %cst_4, %cst_4, %cst_3, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %48 = numpy.tensor_static_info_cast %47 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %49 = numpy.tensor_static_info_cast %48 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %50 = numpy.tensor_static_info_cast %49 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %51 = numpy.create_array_from_tensor %50 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %52 = numpy.copy_to_tensor %51 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %53 = numpy.tensor_static_info_cast %52 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %54 = "aten.relu"(%53) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %55 = numpy.tensor_static_info_cast %54 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %55 overwrites %51 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %56 = basicpy.singleton : !basicpy.NoneType
  %57 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %58 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %59 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %60 = numpy.copy_to_tensor %51 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %61 = numpy.tensor_static_info_cast %60 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %62 = "aten.conv2d"(%61, %cst_2, %56, %57, %58, %59, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<64x64x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %63 = numpy.tensor_static_info_cast %62 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %64 = numpy.tensor_static_info_cast %63 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %65 = numpy.tensor_static_info_cast %64 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %66 = numpy.create_array_from_tensor %65 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %67 = numpy.copy_to_tensor %66 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %68 = numpy.copy_to_tensor %66 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %69 = numpy.tensor_static_info_cast %68 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %70 = "aten.batch_norm"(%69, %cst_3, %cst_4, %cst_4, %cst_3, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %71 = numpy.tensor_static_info_cast %70 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %72 = numpy.tensor_static_info_cast %71 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %73 = numpy.tensor_static_info_cast %72 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %74 = numpy.create_array_from_tensor %73 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %75 = numpy.copy_to_tensor %74 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %76 = numpy.tensor_static_info_cast %75 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %77 = numpy.copy_to_tensor %32 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %78 = numpy.tensor_static_info_cast %77 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %79 = "aten.add"(%76, %78, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>, i64) -> tensor<?x?x?x?xf32>
  %80 = numpy.tensor_static_info_cast %79 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %80 overwrites %74 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %81 = numpy.copy_to_tensor %74 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %82 = numpy.tensor_static_info_cast %81 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %83 = "aten.relu"(%82) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %84 = numpy.tensor_static_info_cast %83 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %84 overwrites %74 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %85 = basicpy.singleton : !basicpy.NoneType
  %86 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %87 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %88 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %89 = numpy.copy_to_tensor %74 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %90 = numpy.tensor_static_info_cast %89 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %91 = "aten.conv2d"(%90, %cst_2, %85, %86, %87, %88, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<64x64x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %92 = numpy.tensor_static_info_cast %91 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %93 = numpy.tensor_static_info_cast %92 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %94 = numpy.tensor_static_info_cast %93 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %95 = numpy.create_array_from_tensor %94 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %96 = numpy.copy_to_tensor %95 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %97 = numpy.copy_to_tensor %95 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %98 = numpy.tensor_static_info_cast %97 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %99 = "aten.batch_norm"(%98, %cst_3, %cst_4, %cst_4, %cst_3, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %100 = numpy.tensor_static_info_cast %99 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %101 = numpy.tensor_static_info_cast %100 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %102 = numpy.tensor_static_info_cast %101 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %103 = numpy.create_array_from_tensor %102 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %104 = numpy.copy_to_tensor %103 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %105 = numpy.tensor_static_info_cast %104 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %106 = "aten.relu"(%105) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %107 = numpy.tensor_static_info_cast %106 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %107 overwrites %103 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %108 = basicpy.singleton : !basicpy.NoneType
  %109 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %110 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %111 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %112 = numpy.copy_to_tensor %103 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %113 = numpy.tensor_static_info_cast %112 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %114 = "aten.conv2d"(%113, %cst_2, %108, %109, %110, %111, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<64x64x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %115 = numpy.tensor_static_info_cast %114 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %116 = numpy.tensor_static_info_cast %115 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %117 = numpy.tensor_static_info_cast %116 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %118 = numpy.create_array_from_tensor %117 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %119 = numpy.copy_to_tensor %118 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %120 = numpy.copy_to_tensor %118 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %121 = numpy.tensor_static_info_cast %120 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %122 = "aten.batch_norm"(%121, %cst_3, %cst_4, %cst_4, %cst_3, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %123 = numpy.tensor_static_info_cast %122 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %124 = numpy.tensor_static_info_cast %123 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %125 = numpy.tensor_static_info_cast %124 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %126 = numpy.create_array_from_tensor %125 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %127 = numpy.copy_to_tensor %126 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %128 = numpy.tensor_static_info_cast %127 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %129 = numpy.copy_to_tensor %74 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %130 = numpy.tensor_static_info_cast %129 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %131 = "aten.add"(%128, %130, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>, i64) -> tensor<?x?x?x?xf32>
  %132 = numpy.tensor_static_info_cast %131 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %132 overwrites %126 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %133 = numpy.copy_to_tensor %126 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %134 = numpy.tensor_static_info_cast %133 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %135 = "aten.relu"(%134) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %136 = numpy.tensor_static_info_cast %135 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %136 overwrites %126 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %137 = basicpy.singleton : !basicpy.NoneType
  %138 = basicpy.build_list %c2_i64, %c2_i64 : (i64, i64) -> !basicpy.ListType
  %139 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %140 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %141 = numpy.copy_to_tensor %126 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %142 = numpy.tensor_static_info_cast %141 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %143 = "aten.conv2d"(%142, %cst_5, %137, %138, %139, %140, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<128x64x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %144 = numpy.tensor_static_info_cast %143 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %145 = numpy.tensor_static_info_cast %144 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %146 = numpy.tensor_static_info_cast %145 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %147 = numpy.create_array_from_tensor %146 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %148 = numpy.copy_to_tensor %147 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %149 = numpy.copy_to_tensor %147 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %150 = numpy.tensor_static_info_cast %149 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %151 = "aten.batch_norm"(%150, %cst_8, %cst_9, %cst_9, %cst_8, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %152 = numpy.tensor_static_info_cast %151 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %153 = numpy.tensor_static_info_cast %152 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %154 = numpy.tensor_static_info_cast %153 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %155 = numpy.create_array_from_tensor %154 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %156 = numpy.copy_to_tensor %155 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %157 = numpy.tensor_static_info_cast %156 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %158 = "aten.relu"(%157) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %159 = numpy.tensor_static_info_cast %158 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %159 overwrites %155 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %160 = basicpy.singleton : !basicpy.NoneType
  %161 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %162 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %163 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %164 = numpy.copy_to_tensor %155 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %165 = numpy.tensor_static_info_cast %164 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %166 = "aten.conv2d"(%165, %cst_7, %160, %161, %162, %163, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<128x128x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %167 = numpy.tensor_static_info_cast %166 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %168 = numpy.tensor_static_info_cast %167 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %169 = numpy.tensor_static_info_cast %168 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %170 = numpy.create_array_from_tensor %169 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %171 = numpy.copy_to_tensor %170 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %172 = numpy.copy_to_tensor %170 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %173 = numpy.tensor_static_info_cast %172 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %174 = "aten.batch_norm"(%173, %cst_8, %cst_9, %cst_9, %cst_8, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %175 = numpy.tensor_static_info_cast %174 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %176 = numpy.tensor_static_info_cast %175 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %177 = numpy.tensor_static_info_cast %176 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %178 = numpy.create_array_from_tensor %177 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %179 = basicpy.singleton : !basicpy.NoneType
  %180 = basicpy.build_list %c2_i64, %c2_i64 : (i64, i64) -> !basicpy.ListType
  %181 = basicpy.build_list %c0_i64, %c0_i64 : (i64, i64) -> !basicpy.ListType
  %182 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %183 = numpy.copy_to_tensor %126 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %184 = numpy.tensor_static_info_cast %183 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %185 = "aten.conv2d"(%184, %cst_6, %179, %180, %181, %182, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<128x64x1x1xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %186 = numpy.tensor_static_info_cast %185 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %187 = numpy.tensor_static_info_cast %186 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %188 = numpy.tensor_static_info_cast %187 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %189 = numpy.create_array_from_tensor %188 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %190 = numpy.copy_to_tensor %189 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %191 = numpy.copy_to_tensor %189 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %192 = numpy.tensor_static_info_cast %191 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %193 = "aten.batch_norm"(%192, %cst_8, %cst_9, %cst_9, %cst_8, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %194 = numpy.copy_to_tensor %178 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %195 = numpy.tensor_static_info_cast %194 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %196 = "aten.add"(%195, %193, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>, i64) -> tensor<?x?x?x?xf32>
  %197 = numpy.tensor_static_info_cast %196 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %197 overwrites %178 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %198 = numpy.copy_to_tensor %178 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %199 = numpy.tensor_static_info_cast %198 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %200 = "aten.relu"(%199) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %201 = numpy.tensor_static_info_cast %200 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %201 overwrites %178 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %202 = basicpy.singleton : !basicpy.NoneType
  %203 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %204 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %205 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %206 = numpy.copy_to_tensor %178 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %207 = numpy.tensor_static_info_cast %206 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %208 = "aten.conv2d"(%207, %cst_7, %202, %203, %204, %205, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<128x128x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %209 = numpy.tensor_static_info_cast %208 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %210 = numpy.tensor_static_info_cast %209 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %211 = numpy.tensor_static_info_cast %210 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %212 = numpy.create_array_from_tensor %211 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %213 = numpy.copy_to_tensor %212 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %214 = numpy.copy_to_tensor %212 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %215 = numpy.tensor_static_info_cast %214 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %216 = "aten.batch_norm"(%215, %cst_8, %cst_9, %cst_9, %cst_8, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %217 = numpy.tensor_static_info_cast %216 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %218 = numpy.tensor_static_info_cast %217 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %219 = numpy.tensor_static_info_cast %218 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %220 = numpy.create_array_from_tensor %219 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %221 = numpy.copy_to_tensor %220 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %222 = numpy.tensor_static_info_cast %221 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %223 = "aten.relu"(%222) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %224 = numpy.tensor_static_info_cast %223 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %224 overwrites %220 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %225 = basicpy.singleton : !basicpy.NoneType
  %226 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %227 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %228 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %229 = numpy.copy_to_tensor %220 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %230 = numpy.tensor_static_info_cast %229 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %231 = "aten.conv2d"(%230, %cst_7, %225, %226, %227, %228, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<128x128x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %232 = numpy.tensor_static_info_cast %231 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %233 = numpy.tensor_static_info_cast %232 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %234 = numpy.tensor_static_info_cast %233 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %235 = numpy.create_array_from_tensor %234 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %236 = numpy.copy_to_tensor %235 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %237 = numpy.copy_to_tensor %235 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %238 = numpy.tensor_static_info_cast %237 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %239 = "aten.batch_norm"(%238, %cst_8, %cst_9, %cst_9, %cst_8, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %240 = numpy.tensor_static_info_cast %239 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %241 = numpy.tensor_static_info_cast %240 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %242 = numpy.tensor_static_info_cast %241 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %243 = numpy.create_array_from_tensor %242 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %244 = numpy.copy_to_tensor %243 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %245 = numpy.tensor_static_info_cast %244 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %246 = numpy.copy_to_tensor %178 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %247 = numpy.tensor_static_info_cast %246 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %248 = "aten.add"(%245, %247, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>, i64) -> tensor<?x?x?x?xf32>
  %249 = numpy.tensor_static_info_cast %248 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %249 overwrites %243 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %250 = numpy.copy_to_tensor %243 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %251 = numpy.tensor_static_info_cast %250 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %252 = "aten.relu"(%251) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %253 = numpy.tensor_static_info_cast %252 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %253 overwrites %243 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %254 = basicpy.singleton : !basicpy.NoneType
  %255 = basicpy.build_list %c2_i64, %c2_i64 : (i64, i64) -> !basicpy.ListType
  %256 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %257 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %258 = numpy.copy_to_tensor %243 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %259 = numpy.tensor_static_info_cast %258 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %260 = "aten.conv2d"(%259, %cst_10, %254, %255, %256, %257, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<256x128x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %261 = numpy.tensor_static_info_cast %260 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %262 = numpy.tensor_static_info_cast %261 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %263 = numpy.tensor_static_info_cast %262 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %264 = numpy.create_array_from_tensor %263 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %265 = numpy.copy_to_tensor %264 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %266 = numpy.copy_to_tensor %264 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %267 = numpy.tensor_static_info_cast %266 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %268 = "aten.batch_norm"(%267, %cst_13, %cst_14, %cst_14, %cst_13, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %269 = numpy.tensor_static_info_cast %268 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %270 = numpy.tensor_static_info_cast %269 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %271 = numpy.tensor_static_info_cast %270 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %272 = numpy.create_array_from_tensor %271 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %273 = numpy.copy_to_tensor %272 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %274 = numpy.tensor_static_info_cast %273 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %275 = "aten.relu"(%274) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %276 = numpy.tensor_static_info_cast %275 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %276 overwrites %272 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %277 = basicpy.singleton : !basicpy.NoneType
  %278 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %279 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %280 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %281 = numpy.copy_to_tensor %272 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %282 = numpy.tensor_static_info_cast %281 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %283 = "aten.conv2d"(%282, %cst_12, %277, %278, %279, %280, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<256x256x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %284 = numpy.tensor_static_info_cast %283 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %285 = numpy.tensor_static_info_cast %284 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %286 = numpy.tensor_static_info_cast %285 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %287 = numpy.create_array_from_tensor %286 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %288 = numpy.copy_to_tensor %287 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %289 = numpy.copy_to_tensor %287 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %290 = numpy.tensor_static_info_cast %289 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %291 = "aten.batch_norm"(%290, %cst_13, %cst_14, %cst_14, %cst_13, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %292 = numpy.tensor_static_info_cast %291 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %293 = numpy.tensor_static_info_cast %292 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %294 = numpy.tensor_static_info_cast %293 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %295 = numpy.create_array_from_tensor %294 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %296 = basicpy.singleton : !basicpy.NoneType
  %297 = basicpy.build_list %c2_i64, %c2_i64 : (i64, i64) -> !basicpy.ListType
  %298 = basicpy.build_list %c0_i64, %c0_i64 : (i64, i64) -> !basicpy.ListType
  %299 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %300 = numpy.copy_to_tensor %243 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %301 = numpy.tensor_static_info_cast %300 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %302 = "aten.conv2d"(%301, %cst_11, %296, %297, %298, %299, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<256x128x1x1xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %303 = numpy.tensor_static_info_cast %302 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %304 = numpy.tensor_static_info_cast %303 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %305 = numpy.tensor_static_info_cast %304 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %306 = numpy.create_array_from_tensor %305 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %307 = numpy.copy_to_tensor %306 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %308 = numpy.copy_to_tensor %306 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %309 = numpy.tensor_static_info_cast %308 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %310 = "aten.batch_norm"(%309, %cst_13, %cst_14, %cst_14, %cst_13, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %311 = numpy.copy_to_tensor %295 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %312 = numpy.tensor_static_info_cast %311 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %313 = "aten.add"(%312, %310, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>, i64) -> tensor<?x?x?x?xf32>
  %314 = numpy.tensor_static_info_cast %313 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %314 overwrites %295 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %315 = numpy.copy_to_tensor %295 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %316 = numpy.tensor_static_info_cast %315 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %317 = "aten.relu"(%316) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %318 = numpy.tensor_static_info_cast %317 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %318 overwrites %295 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %319 = basicpy.singleton : !basicpy.NoneType
  %320 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %321 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %322 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %323 = numpy.copy_to_tensor %295 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %324 = numpy.tensor_static_info_cast %323 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %325 = "aten.conv2d"(%324, %cst_12, %319, %320, %321, %322, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<256x256x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %326 = numpy.tensor_static_info_cast %325 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %327 = numpy.tensor_static_info_cast %326 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %328 = numpy.tensor_static_info_cast %327 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %329 = numpy.create_array_from_tensor %328 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %330 = numpy.copy_to_tensor %329 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %331 = numpy.copy_to_tensor %329 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %332 = numpy.tensor_static_info_cast %331 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %333 = "aten.batch_norm"(%332, %cst_13, %cst_14, %cst_14, %cst_13, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %334 = numpy.tensor_static_info_cast %333 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %335 = numpy.tensor_static_info_cast %334 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %336 = numpy.tensor_static_info_cast %335 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %337 = numpy.create_array_from_tensor %336 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %338 = numpy.copy_to_tensor %337 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %339 = numpy.tensor_static_info_cast %338 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %340 = "aten.relu"(%339) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %341 = numpy.tensor_static_info_cast %340 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %341 overwrites %337 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %342 = basicpy.singleton : !basicpy.NoneType
  %343 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %344 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %345 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %346 = numpy.copy_to_tensor %337 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %347 = numpy.tensor_static_info_cast %346 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %348 = "aten.conv2d"(%347, %cst_12, %342, %343, %344, %345, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<256x256x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %349 = numpy.tensor_static_info_cast %348 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %350 = numpy.tensor_static_info_cast %349 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %351 = numpy.tensor_static_info_cast %350 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %352 = numpy.create_array_from_tensor %351 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %353 = numpy.copy_to_tensor %352 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %354 = numpy.copy_to_tensor %352 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %355 = numpy.tensor_static_info_cast %354 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %356 = "aten.batch_norm"(%355, %cst_13, %cst_14, %cst_14, %cst_13, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %357 = numpy.tensor_static_info_cast %356 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %358 = numpy.tensor_static_info_cast %357 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %359 = numpy.tensor_static_info_cast %358 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %360 = numpy.create_array_from_tensor %359 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %361 = numpy.copy_to_tensor %360 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %362 = numpy.tensor_static_info_cast %361 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %363 = numpy.copy_to_tensor %295 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %364 = numpy.tensor_static_info_cast %363 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %365 = "aten.add"(%362, %364, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>, i64) -> tensor<?x?x?x?xf32>
  %366 = numpy.tensor_static_info_cast %365 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %366 overwrites %360 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %367 = numpy.copy_to_tensor %360 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %368 = numpy.tensor_static_info_cast %367 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %369 = "aten.relu"(%368) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %370 = numpy.tensor_static_info_cast %369 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %370 overwrites %360 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %371 = basicpy.singleton : !basicpy.NoneType
  %372 = basicpy.build_list %c2_i64, %c2_i64 : (i64, i64) -> !basicpy.ListType
  %373 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %374 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %375 = numpy.copy_to_tensor %360 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %376 = numpy.tensor_static_info_cast %375 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %377 = "aten.conv2d"(%376, %cst_15, %371, %372, %373, %374, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<512x256x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %378 = numpy.tensor_static_info_cast %377 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %379 = numpy.tensor_static_info_cast %378 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %380 = numpy.tensor_static_info_cast %379 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %381 = numpy.create_array_from_tensor %380 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %382 = numpy.copy_to_tensor %381 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %383 = numpy.copy_to_tensor %381 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %384 = numpy.tensor_static_info_cast %383 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %385 = "aten.batch_norm"(%384, %cst_18, %cst_19, %cst_19, %cst_18, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %386 = numpy.tensor_static_info_cast %385 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %387 = numpy.tensor_static_info_cast %386 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %388 = numpy.tensor_static_info_cast %387 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %389 = numpy.create_array_from_tensor %388 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %390 = numpy.copy_to_tensor %389 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %391 = numpy.tensor_static_info_cast %390 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %392 = "aten.relu"(%391) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %393 = numpy.tensor_static_info_cast %392 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %393 overwrites %389 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %394 = basicpy.singleton : !basicpy.NoneType
  %395 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %396 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %397 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %398 = numpy.copy_to_tensor %389 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %399 = numpy.tensor_static_info_cast %398 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %400 = "aten.conv2d"(%399, %cst_17, %394, %395, %396, %397, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<512x512x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %401 = numpy.tensor_static_info_cast %400 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %402 = numpy.tensor_static_info_cast %401 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %403 = numpy.tensor_static_info_cast %402 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %404 = numpy.create_array_from_tensor %403 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %405 = numpy.copy_to_tensor %404 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %406 = numpy.copy_to_tensor %404 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %407 = numpy.tensor_static_info_cast %406 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %408 = "aten.batch_norm"(%407, %cst_18, %cst_19, %cst_19, %cst_18, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %409 = numpy.tensor_static_info_cast %408 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %410 = numpy.tensor_static_info_cast %409 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %411 = numpy.tensor_static_info_cast %410 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %412 = numpy.create_array_from_tensor %411 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %413 = basicpy.singleton : !basicpy.NoneType
  %414 = basicpy.build_list %c2_i64, %c2_i64 : (i64, i64) -> !basicpy.ListType
  %415 = basicpy.build_list %c0_i64, %c0_i64 : (i64, i64) -> !basicpy.ListType
  %416 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %417 = numpy.copy_to_tensor %360 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %418 = numpy.tensor_static_info_cast %417 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %419 = "aten.conv2d"(%418, %cst_16, %413, %414, %415, %416, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<512x256x1x1xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %420 = numpy.tensor_static_info_cast %419 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %421 = numpy.tensor_static_info_cast %420 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %422 = numpy.tensor_static_info_cast %421 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %423 = numpy.create_array_from_tensor %422 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %424 = numpy.copy_to_tensor %423 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %425 = numpy.copy_to_tensor %423 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %426 = numpy.tensor_static_info_cast %425 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %427 = "aten.batch_norm"(%426, %cst_18, %cst_19, %cst_19, %cst_18, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %428 = numpy.copy_to_tensor %412 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %429 = numpy.tensor_static_info_cast %428 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %430 = "aten.add"(%429, %427, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>, i64) -> tensor<?x?x?x?xf32>
  %431 = numpy.tensor_static_info_cast %430 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %431 overwrites %412 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %432 = numpy.copy_to_tensor %412 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %433 = numpy.tensor_static_info_cast %432 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %434 = "aten.relu"(%433) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %435 = numpy.tensor_static_info_cast %434 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %435 overwrites %412 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %436 = basicpy.singleton : !basicpy.NoneType
  %437 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %438 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %439 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %440 = numpy.copy_to_tensor %412 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %441 = numpy.tensor_static_info_cast %440 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %442 = "aten.conv2d"(%441, %cst_17, %436, %437, %438, %439, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<512x512x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %443 = numpy.tensor_static_info_cast %442 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %444 = numpy.tensor_static_info_cast %443 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %445 = numpy.tensor_static_info_cast %444 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %446 = numpy.create_array_from_tensor %445 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %447 = numpy.copy_to_tensor %446 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %448 = numpy.copy_to_tensor %446 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %449 = numpy.tensor_static_info_cast %448 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %450 = "aten.batch_norm"(%449, %cst_18, %cst_19, %cst_19, %cst_18, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %451 = numpy.tensor_static_info_cast %450 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %452 = numpy.tensor_static_info_cast %451 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %453 = numpy.tensor_static_info_cast %452 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %454 = numpy.create_array_from_tensor %453 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %455 = numpy.copy_to_tensor %454 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %456 = numpy.tensor_static_info_cast %455 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %457 = "aten.relu"(%456) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %458 = numpy.tensor_static_info_cast %457 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %458 overwrites %454 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %459 = basicpy.singleton : !basicpy.NoneType
  %460 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %461 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %462 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %463 = numpy.copy_to_tensor %454 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %464 = numpy.tensor_static_info_cast %463 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %465 = "aten.conv2d"(%464, %cst_17, %459, %460, %461, %462, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<512x512x3x3xf32>, !basicpy.NoneType, !basicpy.ListType, !basicpy.ListType, !basicpy.ListType, i64) -> tensor<?x?x?x?xf32>
  %466 = numpy.tensor_static_info_cast %465 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %467 = numpy.tensor_static_info_cast %466 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %468 = numpy.tensor_static_info_cast %467 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %469 = numpy.create_array_from_tensor %468 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %470 = numpy.copy_to_tensor %469 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %471 = numpy.copy_to_tensor %469 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %472 = numpy.tensor_static_info_cast %471 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %473 = "aten.batch_norm"(%472, %cst_18, %cst_19, %cst_19, %cst_18, %bool_false, %cst_0, %cst, %bool_true) : (tensor<?x?x?x?xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, !basicpy.BoolType, f64, f64, !basicpy.BoolType) -> tensor<?x?x?x?xf32>
  %474 = numpy.tensor_static_info_cast %473 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %475 = numpy.tensor_static_info_cast %474 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %476 = numpy.tensor_static_info_cast %475 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %477 = numpy.create_array_from_tensor %476 : (tensor<*x!numpy.any_dtype>) -> !numpy.ndarray<*:!numpy.any_dtype>
  %478 = numpy.copy_to_tensor %477 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %479 = numpy.tensor_static_info_cast %478 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %480 = numpy.copy_to_tensor %412 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %481 = numpy.tensor_static_info_cast %480 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %482 = "aten.add"(%479, %481, %c1_i64) : (tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>, i64) -> tensor<?x?x?x?xf32>
  %483 = numpy.tensor_static_info_cast %482 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %483 overwrites %477 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %484 = numpy.copy_to_tensor %477 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %485 = numpy.tensor_static_info_cast %484 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %486 = "aten.relu"(%485) : (tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
  %487 = numpy.tensor_static_info_cast %486 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  numpy.overwrite_array %487 overwrites %477 : tensor<*x!numpy.any_dtype>, !numpy.ndarray<*:!numpy.any_dtype>
  %488 = basicpy.build_list %c1_i64, %c1_i64 : (i64, i64) -> !basicpy.ListType
  %489 = numpy.copy_to_tensor %477 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %490 = numpy.copy_to_tensor %477 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %491 = numpy.tensor_static_info_cast %490 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %492 = "aten.adaptive_avg_pool2d"(%491, %488) : (tensor<?x?x?x?xf32>, !basicpy.ListType) -> tensor<?x?x?x?xf32>
  %493 = numpy.tensor_static_info_cast %492 : tensor<?x?x?x?xf32> to tensor<*x!numpy.any_dtype>
  %494 = numpy.tensor_static_info_cast %493 : tensor<*x!numpy.any_dtype> to tensor<?x?x?x?xf32>
  %495 = numpy.create_array_from_tensor %494 : (tensor<?x?x?x?xf32>) -> !numpy.ndarray<[?,?,?,?]:f32>
  %496 = "aten.flatten"(%495, %c1_i64, %c-1_i64) : (!numpy.ndarray<[?,?,?,?]:f32>, i64, i64) -> !numpy.ndarray<[?,?]:f32>
  %497 = numpy.static_info_cast %496 : !numpy.ndarray<[?,?]:f32> to !numpy.ndarray<*:!numpy.any_dtype>
  %498 = numpy.copy_to_tensor %497 : (!numpy.ndarray<*:!numpy.any_dtype>) -> tensor<*x!numpy.any_dtype>
  %499 = numpy.tensor_static_info_cast %498 : tensor<*x!numpy.any_dtype> to tensor<?x?xf32>
  %500 = "aten.linear"(%499, %cst_20, %cst_21) : (tensor<?x?xf32>, tensor<1000x512xf32>, tensor<1000xf32>) -> tensor<?x?xf32>
  return %500 : tensor<?x?xf32>
}