program(1.3)
[buildInfo = dict<string, string>({
    {"coremlc-component-MIL", "3402.3.2"}, 
    {"coremlc-version", "3402.5.1"}, 
    {"coremltools-component-torch", "2.4.1"}, 
    {"coremltools-source-dialect", "TorchScript"}, 
    {"coremltools-version", "8.2.2"}, 
    {"model-version", "7.0.127-6bit"}, 
    {"model-iteration", "63000"}, 
    {"model-task-id", "qnqcdytztw"}, 
    {"mldb_token", "mldb-k34yedogb9"}
})] {
    func main<ios18>(pixel_buffer<FMT_32BGRA, shape=[384, 512]> image)[
         E5_FlagsAne = dict<tensor<string, []>, tensor<string, []>>({
             {"KernelRewind", "true"},
             {"SpatialSplitMode", "auto"}
         }),
         E5_FlagsEir = dict<tensor<string, []>, tensor<string, []>>({
             {"experimental.ane.early_arch_transposes", "1"},
             {"experimental.ane.reduce_mean_spatial", "1"}
         })] {
            tensor<uint8, [4, 384, 512]> bgra_tensor = pixel_buffer_to_tensor(input = image);

            tensor<fp16, [3, 384, 512]> bgra_tensor_fp16 = cast(dtype = string("fp16"), x = bgra_tensor);
            tensor<fp16, [1, 384, 512]> b_tensor = slice_by_index(
                begin = tensor<int32, [3]>([0, 0, 0]),
                end = tensor<int32, [3]>([1, 384, 512]),
                end_mask = tensor<bool, [3]>([false, true, true]),
                x = bgra_tensor_fp16);
            tensor<fp16, [1, 384, 512]> g_tensor = slice_by_index(
                begin = tensor<int32, [3]>([1, 0, 0]),
                end = tensor<int32, [3]>([2, 384, 512]),
                end_mask = tensor<bool, [3]>([false, true, true]),
                x = bgra_tensor_fp16);
            tensor<fp16, [1, 384, 512]> r_tensor = slice_by_index(
                begin = tensor<int32, [3]>([2, 0, 0]),
                end = tensor<int32, [3]>([3, 384, 512]),
                end_mask = tensor<bool, [3]>([false, true, true]),
                x = bgra_tensor_fp16);

            tensor<fp16, [3, 384, 512]> rgb_tensor_fp16 = concat(axis = int32(0), interleave = bool(false), values = (r_tensor, g_tensor, b_tensor));
            tensor<fp16, [1, 3, 384, 512]> rgb_tensor_batch_fp16 = expand_dims(axes = tensor<int32, [1]>([0]), x = rgb_tensor_fp16);
            tensor<fp16, [1, 3, 384, 512]> image_to_fp16 = mul(x = rgb_tensor_batch_fp16, y = tensor<fp16, []>(0x1.010102p-8))[name = tensor<string, []>("image_to_fp16")];
            
            tensor<fp16, [64, 1, 7, 7]> model_encoder_stages_0_0_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(64))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(2496))))[name = string("model_encoder_stages_0_0_depthwise_weight_cast_fp16")];
            tensor<fp16, [256, 64, 1, 1]> model_encoder_stages_0_0_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [256, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(2816))), lut = tensor<fp16, [8, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(15168))))[name = string("model_encoder_stages_0_0_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [64, 256, 1, 1]> model_encoder_stages_0_0_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(16256))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(28608))))[name = string("model_encoder_stages_0_0_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [64, 1, 7, 7]> model_encoder_stages_0_1_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(28928))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(31360))))[name = string("model_encoder_stages_0_1_depthwise_weight_cast_fp16")];
            tensor<fp16, [256, 64, 1, 1]> model_encoder_stages_0_1_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [256, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(31680))), lut = tensor<fp16, [8, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(44032))))[name = string("model_encoder_stages_0_1_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [64, 256, 1, 1]> model_encoder_stages_0_1_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(45120))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(57472))))[name = string("model_encoder_stages_0_1_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [64, 1, 7, 7]> model_encoder_stages_0_2_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(57792))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(60224))))[name = string("model_encoder_stages_0_2_depthwise_weight_cast_fp16")];
            tensor<fp16, [256, 64, 1, 1]> model_encoder_stages_0_2_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [256, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(60544))), lut = tensor<fp16, [8, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(72896))))[name = string("model_encoder_stages_0_2_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [64, 256, 1, 1]> model_encoder_stages_0_2_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(73984))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(86336))))[name = string("model_encoder_stages_0_2_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [96, 64, 2, 2]> model_encoder_downsample_layers_1_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [96, 64, 2, 2]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(86656))), lut = tensor<fp16, [3, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(105152))))[name = string("model_encoder_downsample_layers_1_1_weight_cast_fp16")];
            tensor<fp16, [96, 1, 7, 7]> model_encoder_stages_1_0_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [96, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(105600))), lut = tensor<fp16, [3, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(109248))))[name = string("model_encoder_stages_1_0_depthwise_weight_cast_fp16")];
            tensor<fp16, [384, 96, 1, 1]> model_encoder_stages_1_0_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [384, 96, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(109696))), lut = tensor<fp16, [12, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(137408))))[name = string("model_encoder_stages_1_0_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [96, 384, 1, 1]> model_encoder_stages_1_0_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [96, 384, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(139008))), lut = tensor<fp16, [3, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(166720))))[name = string("model_encoder_stages_1_0_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [96, 1, 7, 7]> model_encoder_stages_1_1_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [96, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(167168))), lut = tensor<fp16, [3, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(170816))))[name = string("model_encoder_stages_1_1_depthwise_weight_cast_fp16")];
            tensor<fp16, [384, 96, 1, 1]> model_encoder_stages_1_1_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [384, 96, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(171264))), lut = tensor<fp16, [12, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(198976))))[name = string("model_encoder_stages_1_1_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [96, 384, 1, 1]> model_encoder_stages_1_1_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [96, 384, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(200576))), lut = tensor<fp16, [3, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(228288))))[name = string("model_encoder_stages_1_1_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [96, 1, 7, 7]> model_encoder_stages_1_2_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [96, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(228736))), lut = tensor<fp16, [3, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(232384))))[name = string("model_encoder_stages_1_2_depthwise_weight_cast_fp16")];
            tensor<fp16, [384, 96, 1, 1]> model_encoder_stages_1_2_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [384, 96, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(232832))), lut = tensor<fp16, [12, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(260544))))[name = string("model_encoder_stages_1_2_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [96, 384, 1, 1]> model_encoder_stages_1_2_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [96, 384, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(262144))), lut = tensor<fp16, [3, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(289856))))[name = string("model_encoder_stages_1_2_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [192, 96, 2, 2]> model_encoder_downsample_layers_2_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [192, 96, 2, 2]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(290304))), lut = tensor<fp16, [6, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(345664))))[name = string("model_encoder_downsample_layers_2_1_weight_cast_fp16")];
            tensor<fp16, [192, 1, 7, 7]> model_encoder_stages_2_0_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [192, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(346496))), lut = tensor<fp16, [6, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(353664))))[name = string("model_encoder_stages_2_0_depthwise_weight_cast_fp16")];
            tensor<fp16, [768, 192, 1, 1]> model_encoder_stages_2_0_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [768, 192, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(354496))), lut = tensor<fp16, [24, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(465152))))[name = string("model_encoder_stages_2_0_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [192, 768, 1, 1]> model_encoder_stages_2_0_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [192, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(468288))), lut = tensor<fp16, [6, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(578944))))[name = string("model_encoder_stages_2_0_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [192, 1, 7, 7]> model_encoder_stages_2_1_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [192, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(579776))), lut = tensor<fp16, [6, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(586944))))[name = string("model_encoder_stages_2_1_depthwise_weight_cast_fp16")];
            tensor<fp16, [768, 192, 1, 1]> model_encoder_stages_2_1_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [768, 192, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(587776))), lut = tensor<fp16, [24, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(698432))))[name = string("model_encoder_stages_2_1_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [192, 768, 1, 1]> model_encoder_stages_2_1_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [192, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(701568))), lut = tensor<fp16, [6, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(812224))))[name = string("model_encoder_stages_2_1_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [192, 1, 7, 7]> model_encoder_stages_2_2_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [192, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(813056))), lut = tensor<fp16, [6, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(820224))))[name = string("model_encoder_stages_2_2_depthwise_weight_cast_fp16")];
            tensor<fp16, [768, 192, 1, 1]> model_encoder_stages_2_2_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [768, 192, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(821056))), lut = tensor<fp16, [24, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(931712))))[name = string("model_encoder_stages_2_2_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [192, 768, 1, 1]> model_encoder_stages_2_2_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [192, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(934848))), lut = tensor<fp16, [6, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1045504))))[name = string("model_encoder_stages_2_2_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [192, 1, 7, 7]> model_encoder_stages_2_3_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [192, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1046336))), lut = tensor<fp16, [6, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1053504))))[name = string("model_encoder_stages_2_3_depthwise_weight_cast_fp16")];
            tensor<fp16, [768, 192, 1, 1]> model_encoder_stages_2_3_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [768, 192, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1054336))), lut = tensor<fp16, [24, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1164992))))[name = string("model_encoder_stages_2_3_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [192, 768, 1, 1]> model_encoder_stages_2_3_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [192, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1168128))), lut = tensor<fp16, [6, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1278784))))[name = string("model_encoder_stages_2_3_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [192, 1, 7, 7]> model_encoder_stages_2_4_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [192, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1279616))), lut = tensor<fp16, [6, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1286784))))[name = string("model_encoder_stages_2_4_depthwise_weight_cast_fp16")];
            tensor<fp16, [768, 192, 1, 1]> model_encoder_stages_2_4_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [768, 192, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1287616))), lut = tensor<fp16, [24, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1398272))))[name = string("model_encoder_stages_2_4_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [192, 768, 1, 1]> model_encoder_stages_2_4_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [192, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1401408))), lut = tensor<fp16, [6, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1512064))))[name = string("model_encoder_stages_2_4_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [192, 1, 7, 7]> model_encoder_stages_2_5_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [192, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1512896))), lut = tensor<fp16, [6, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1520064))))[name = string("model_encoder_stages_2_5_depthwise_weight_cast_fp16")];
            tensor<fp16, [768, 192, 1, 1]> model_encoder_stages_2_5_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [768, 192, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1520896))), lut = tensor<fp16, [24, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1631552))))[name = string("model_encoder_stages_2_5_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [192, 768, 1, 1]> model_encoder_stages_2_5_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [192, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1634688))), lut = tensor<fp16, [6, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1745344))))[name = string("model_encoder_stages_2_5_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [384, 192, 2, 2]> model_encoder_downsample_layers_3_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [384, 192, 2, 2]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1746176))), lut = tensor<fp16, [12, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1967424))))[name = string("model_encoder_downsample_layers_3_1_weight_cast_fp16")];
            tensor<fp16, [384, 1, 7, 7]> model_encoder_stages_3_0_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [384, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1969024))), lut = tensor<fp16, [12, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1983232))))[name = string("model_encoder_stages_3_0_depthwise_weight_cast_fp16")];
            tensor<fp16, [1536, 384, 1, 1]> model_encoder_stages_3_0_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [1536, 384, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(1984832))), lut = tensor<fp16, [48, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(2427264))))[name = string("model_encoder_stages_3_0_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [384, 1536, 1, 1]> model_encoder_stages_3_0_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [384, 1536, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(2433472))), lut = tensor<fp16, [12, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(2875904))))[name = string("model_encoder_stages_3_0_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [384, 1, 7, 7]> model_encoder_stages_3_1_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [384, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(2877504))), lut = tensor<fp16, [12, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(2891712))))[name = string("model_encoder_stages_3_1_depthwise_weight_cast_fp16")];
            tensor<fp16, [1536, 384, 1, 1]> model_encoder_stages_3_1_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [1536, 384, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(2893312))), lut = tensor<fp16, [48, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(3335744))))[name = string("model_encoder_stages_3_1_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [384, 1536, 1, 1]> model_encoder_stages_3_1_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [384, 1536, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(3341952))), lut = tensor<fp16, [12, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(3784384))))[name = string("model_encoder_stages_3_1_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [384, 1, 7, 7]> model_encoder_stages_3_2_depthwise_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [384, 1, 7, 7]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(3785984))), lut = tensor<fp16, [12, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(3800192))))[name = string("model_encoder_stages_3_2_depthwise_weight_cast_fp16")];
            tensor<fp16, [1536, 384, 1, 1]> model_encoder_stages_3_2_pointwise_1_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [1536, 384, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(3801792))), lut = tensor<fp16, [48, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4244224))))[name = string("model_encoder_stages_3_2_pointwise_1_weight_cast_fp16")];
            tensor<fp16, [384, 1536, 1, 1]> model_encoder_stages_3_2_pointwise_2_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [384, 1536, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4250432))), lut = tensor<fp16, [12, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4692864))))[name = string("model_encoder_stages_3_2_pointwise_2_weight_cast_fp16")];
            tensor<fp16, [128, 384, 1, 1]> model_decoder_p5_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [128, 384, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4694464))), lut = tensor<fp16, [4, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4731392))))[name = string("model_decoder_p5_conv_weight_cast_fp16")];
            tensor<fp16, [128, 192, 1, 1]> model_decoder_p4_skip_conv_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [128, 192, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4731968))), lut = tensor<fp16, [4, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4750464))))[name = string("model_decoder_p4_skip_conv_conv_weight_cast_fp16")];
            tensor<fp16, [128, 96, 1, 1]> model_decoder_p3_skip_conv_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [128, 96, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4751040))), lut = tensor<fp16, [4, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4760320))))[name = string("model_decoder_p3_skip_conv_conv_weight_cast_fp16")];
            tensor<fp16, [128, 64, 1, 1]> model_decoder_p2_skip_conv_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [128, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4760896))), lut = tensor<fp16, [4, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4767104))))[name = string("model_decoder_p2_skip_conv_conv_weight_cast_fp16")];
            tensor<fp16, [64, 128, 3, 3]> model_decoder_s5_block_0_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 128, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4767680))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4823040))))[name = string("model_decoder_s5_block_0_conv_weight_cast_fp16")];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_s5_block_1_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4823360))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4851072))))[name = string("model_decoder_s5_block_1_conv_weight_cast_fp16")];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_s5_block_3_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4851392))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4879104))))[name = string("model_decoder_s5_block_3_conv_weight_cast_fp16")];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_s5_block_5_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4879424))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4907136))))[name = string("model_decoder_s5_block_5_conv_weight_cast_fp16")];
            tensor<fp16, [64, 128, 3, 3]> model_decoder_s4_block_0_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 128, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4907456))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4962816))))[name = string("model_decoder_s4_block_0_conv_weight_cast_fp16")];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_s4_block_1_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4963136))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4990848))))[name = string("model_decoder_s4_block_1_conv_weight_cast_fp16")];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_s4_block_3_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(4991168))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5018880))))[name = string("model_decoder_s4_block_3_conv_weight_cast_fp16")];
            tensor<fp16, [64, 128, 3, 3]> model_decoder_s3_block_0_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 128, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5019200))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5074560))))[name = string("model_decoder_s3_block_0_conv_weight_cast_fp16")];
            tensor<fp16, [64, 64, 3, 3]> model_decoder_s3_block_1_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 64, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5074880))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5102592))))[name = string("model_decoder_s3_block_1_conv_weight_cast_fp16")];
            tensor<fp16, [64, 128, 3, 3]> model_decoder_s2_block_0_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 128, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5102912))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5158272))))[name = string("model_decoder_s2_block_0_conv_weight_cast_fp16")];
            tensor<fp16, [64, 256, 1, 1]> model_decoder_fpn_combine_fusion_block_0_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [64, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5158592))), lut = tensor<fp16, [2, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5170944))))[name = string("model_decoder_fpn_combine_fusion_block_0_conv_weight_cast_fp16")];
            tensor<fp16, [12, 3, 3, 3]> model_decoder_detail_head_blocks_0_0_conv1_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [12, 3, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5171264))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5171584))))[name = string("model_decoder_detail_head_blocks_0_0_conv1_conv_weight_cast_fp16")];
            tensor<fp16, [12, 12, 3, 3]> model_decoder_detail_head_blocks_0_0_conv2_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [12, 12, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5171776))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5172864))))[name = string("model_decoder_detail_head_blocks_0_0_conv2_conv_weight_cast_fp16")];
            tensor<fp16, [12, 3, 1, 1]> model_decoder_detail_head_blocks_0_0_downsample_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [12, 3, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5173056))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5173184))))[name = string("model_decoder_detail_head_blocks_0_0_downsample_conv_weight_cast_fp16")];
            tensor<fp16, [24, 12, 3, 3]> model_decoder_detail_head_blocks_1_1_conv1_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [24, 12, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5173376))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5175424))))[name = string("model_decoder_detail_head_blocks_1_1_conv1_conv_weight_cast_fp16")];
            tensor<fp16, [24, 24, 3, 3]> model_decoder_detail_head_blocks_1_1_conv2_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [24, 24, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5175616))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5179584))))[name = string("model_decoder_detail_head_blocks_1_1_conv2_conv_weight_cast_fp16")];
            tensor<fp16, [24, 12, 1, 1]> model_decoder_detail_head_blocks_1_1_downsample_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [24, 12, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5179776))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5180096))))[name = string("model_decoder_detail_head_blocks_1_1_downsample_conv_weight_cast_fp16")];
            tensor<fp16, [24, 64, 1, 1]> model_decoder_heads_0_blocks_0_conv1_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [24, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5180288))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5181504))))[name = string("model_decoder_heads_0_blocks_0_conv1_conv_weight_cast_fp16")];
            tensor<fp16, [24, 48, 3, 3]> model_decoder_heads_0_blocks_0_conv2_conv1_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [24, 48, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5181696))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5189568))))[name = string("model_decoder_heads_0_blocks_0_conv2_conv1_conv_weight_cast_fp16")];
            tensor<fp16, [24, 24, 3, 3]> model_decoder_heads_0_blocks_0_conv2_conv2_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [24, 24, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5189760))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5193728))))[name = string("model_decoder_heads_0_blocks_0_conv2_conv2_conv_weight_cast_fp16")];
            tensor<fp16, [24, 48, 1, 1]> model_decoder_heads_0_blocks_0_conv2_downsample_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [24, 48, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5193920))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5194880))))[name = string("model_decoder_heads_0_blocks_0_conv2_downsample_conv_weight_cast_fp16")];
            tensor<fp16, [12, 24, 1, 1]> model_decoder_heads_0_blocks_1_conv1_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [12, 24, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5195072))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5195392))))[name = string("model_decoder_heads_0_blocks_1_conv1_conv_weight_cast_fp16")];
            tensor<fp16, [12, 24, 3, 3]> model_decoder_heads_0_blocks_1_conv2_conv1_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [12, 24, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5195584))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5197632))))[name = string("model_decoder_heads_0_blocks_1_conv2_conv1_conv_weight_cast_fp16")];
            tensor<fp16, [12, 12, 3, 3]> model_decoder_heads_0_blocks_1_conv2_conv2_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [12, 12, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5197824))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5198912))))[name = string("model_decoder_heads_0_blocks_1_conv2_conv2_conv_weight_cast_fp16")];
            tensor<fp16, [12, 24, 1, 1]> model_decoder_heads_0_blocks_1_conv2_downsample_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [12, 24, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5199104))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5199424))))[name = string("model_decoder_heads_0_blocks_1_conv2_downsample_conv_weight_cast_fp16")];
            tensor<fp16, [6, 12, 1, 1]> model_decoder_heads_0_final_layer_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [6, 12, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5199616))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5199744))))[name = string("model_decoder_heads_0_final_layer_weight_cast_fp16")];
            tensor<fp16, [24, 64, 1, 1]> model_decoder_heads_1_blocks_0_conv1_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [24, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5199936))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5201152))))[name = string("model_decoder_heads_1_blocks_0_conv1_conv_weight_cast_fp16")];
            tensor<fp16, [24, 48, 3, 3]> model_decoder_heads_1_blocks_0_conv2_conv1_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [24, 48, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5201344))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5209216))))[name = string("model_decoder_heads_1_blocks_0_conv2_conv1_conv_weight_cast_fp16")];
            tensor<fp16, [24, 24, 3, 3]> model_decoder_heads_1_blocks_0_conv2_conv2_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [24, 24, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5209408))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5213376))))[name = string("model_decoder_heads_1_blocks_0_conv2_conv2_conv_weight_cast_fp16")];
            tensor<fp16, [24, 48, 1, 1]> model_decoder_heads_1_blocks_0_conv2_downsample_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [24, 48, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5213568))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5214528))))[name = string("model_decoder_heads_1_blocks_0_conv2_downsample_conv_weight_cast_fp16")];
            tensor<fp16, [12, 24, 1, 1]> model_decoder_heads_1_blocks_1_conv1_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [12, 24, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5214720))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5215040))))[name = string("model_decoder_heads_1_blocks_1_conv1_conv_weight_cast_fp16")];
            tensor<fp16, [12, 24, 3, 3]> model_decoder_heads_1_blocks_1_conv2_conv1_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [12, 24, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5215232))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5217280))))[name = string("model_decoder_heads_1_blocks_1_conv2_conv1_conv_weight_cast_fp16")];
            tensor<fp16, [12, 12, 3, 3]> model_decoder_heads_1_blocks_1_conv2_conv2_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [12, 12, 3, 3]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5217472))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5218560))))[name = string("model_decoder_heads_1_blocks_1_conv2_conv2_conv_weight_cast_fp16")];
            tensor<fp16, [12, 24, 1, 1]> model_decoder_heads_1_blocks_1_conv2_downsample_conv_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [12, 24, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5218752))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5219072))))[name = string("model_decoder_heads_1_blocks_1_conv2_downsample_conv_weight_cast_fp16")];
            tensor<fp16, [5, 12, 1, 1]> model_decoder_heads_1_final_layer_weight_cast_fp16 = constexpr_lut_to_dense(indices = tensor<uint6, [5, 12, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5219264))), lut = tensor<fp16, [1, 1, 1, 1, 64, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5219392))))[name = string("model_decoder_heads_1_final_layer_weight_cast_fp16")];
            int32 var_9 = const()[name = string("op_9"), val = int32(1)];
            string input_3_pad_type_0 = const()[name = string("input_3_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_3_strides_0 = const()[name = string("input_3_strides_0"), val = tensor<int32, [2]>([4, 4])];
            tensor<int32, [4]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_3_dilations_0 = const()[name = string("input_3_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3_groups_0 = const()[name = string("input_3_groups_0"), val = int32(1)];
            tensor<fp16, [64, 3, 4, 4]> const_3_to_fp16 = const()[name = string("const_3_to_fp16"), val = tensor<fp16, [64, 3, 4, 4]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5219584)))];
            tensor<fp16, [64]> const_4_to_fp16 = const()[name = string("const_4_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5225792)))];
            tensor<fp16, [1, 64, 96, 128]> input_5_cast_fp16 = conv(bias = const_4_to_fp16, dilations = input_3_dilations_0, groups = input_3_groups_0, pad = input_3_pad_0, pad_type = input_3_pad_type_0, strides = input_3_strides_0, weight = const_3_to_fp16, x = image_to_fp16)[name = string("input_5_cast_fp16")];
            string input_7_pad_type_0 = const()[name = string("input_7_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_7_pad_0 = const()[name = string("input_7_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_7_groups_0 = const()[name = string("input_7_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_7_strides_0 = const()[name = string("input_7_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_7_dilations_0 = const()[name = string("input_7_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> model_encoder_stages_0_0_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_0_0_depthwise_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5225984)))];
            tensor<fp16, [1, 64, 96, 128]> input_7_cast_fp16 = conv(bias = model_encoder_stages_0_0_depthwise_bias_to_fp16, dilations = input_7_dilations_0, groups = input_7_groups_0, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = input_7_strides_0, weight = model_encoder_stages_0_0_depthwise_weight_cast_fp16, x = input_5_cast_fp16)[name = string("input_7_cast_fp16")];
            tensor<fp16, [64]> model_encoder_stages_0_0_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_0_0_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5226176)))];
            tensor<fp16, [64]> model_encoder_stages_0_0_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_0_0_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5226368)))];
            tensor<fp16, [64]> model_encoder_stages_0_0_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_0_0_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5226560)))];
            tensor<fp16, [64]> model_encoder_stages_0_0_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_0_0_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5226752)))];
            fp16 var_6_to_fp16 = const()[name = string("op_6_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 64, 96, 128]> input_9_cast_fp16 = batch_norm(beta = model_encoder_stages_0_0_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_0_0_norm_weight_to_fp16, mean = model_encoder_stages_0_0_norm_running_mean_to_fp16, variance = model_encoder_stages_0_0_norm_running_var_to_fp16, x = input_7_cast_fp16)[name = string("input_9_cast_fp16")];
            string input_11_pad_type_0 = const()[name = string("input_11_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_11_strides_0 = const()[name = string("input_11_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_11_pad_0 = const()[name = string("input_11_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_11_dilations_0 = const()[name = string("input_11_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_11_groups_0 = const()[name = string("input_11_groups_0"), val = int32(1)];
            tensor<fp16, [256]> model_encoder_stages_0_0_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_0_0_pointwise_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5226944)))];
            tensor<fp16, [1, 256, 96, 128]> input_11_cast_fp16 = conv(bias = model_encoder_stages_0_0_pointwise_1_bias_to_fp16, dilations = input_11_dilations_0, groups = input_11_groups_0, pad = input_11_pad_0, pad_type = input_11_pad_type_0, strides = input_11_strides_0, weight = model_encoder_stages_0_0_pointwise_1_weight_cast_fp16, x = input_9_cast_fp16)[name = string("input_11_cast_fp16")];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 256, 96, 128]> input_13_cast_fp16 = gelu(mode = input_13_mode_0, x = input_11_cast_fp16)[name = string("input_13_cast_fp16")];
            string x_1_pad_type_0 = const()[name = string("x_1_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_1_strides_0 = const()[name = string("x_1_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_1_pad_0 = const()[name = string("x_1_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_1_dilations_0 = const()[name = string("x_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_1_groups_0 = const()[name = string("x_1_groups_0"), val = int32(1)];
            tensor<fp16, [64]> model_encoder_stages_0_0_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_0_0_pointwise_2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5227520)))];
            tensor<fp16, [1, 64, 96, 128]> x_1_cast_fp16 = conv(bias = model_encoder_stages_0_0_pointwise_2_bias_to_fp16, dilations = x_1_dilations_0, groups = x_1_groups_0, pad = x_1_pad_0, pad_type = x_1_pad_type_0, strides = x_1_strides_0, weight = model_encoder_stages_0_0_pointwise_2_weight_cast_fp16, x = input_13_cast_fp16)[name = string("x_1_cast_fp16")];
            tensor<fp16, [1, 64, 1, 1]> model_encoder_stages_0_0_gamma_to_fp16 = const()[name = string("model_encoder_stages_0_0_gamma_to_fp16"), val = tensor<fp16, [1, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5227712)))];
            tensor<fp16, [1, 64, 96, 128]> x_3_cast_fp16 = mul(x = model_encoder_stages_0_0_gamma_to_fp16, y = x_1_cast_fp16)[name = string("x_3_cast_fp16")];
            tensor<fp16, [1, 64, 96, 128]> input_15_cast_fp16 = add(x = input_5_cast_fp16, y = x_3_cast_fp16)[name = string("input_15_cast_fp16")];
            string input_17_pad_type_0 = const()[name = string("input_17_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_17_pad_0 = const()[name = string("input_17_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_17_groups_0 = const()[name = string("input_17_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_17_strides_0 = const()[name = string("input_17_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_17_dilations_0 = const()[name = string("input_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> model_encoder_stages_0_1_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_0_1_depthwise_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5227904)))];
            tensor<fp16, [1, 64, 96, 128]> input_17_cast_fp16 = conv(bias = model_encoder_stages_0_1_depthwise_bias_to_fp16, dilations = input_17_dilations_0, groups = input_17_groups_0, pad = input_17_pad_0, pad_type = input_17_pad_type_0, strides = input_17_strides_0, weight = model_encoder_stages_0_1_depthwise_weight_cast_fp16, x = input_15_cast_fp16)[name = string("input_17_cast_fp16")];
            tensor<fp16, [64]> model_encoder_stages_0_1_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_0_1_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5228096)))];
            tensor<fp16, [64]> model_encoder_stages_0_1_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_0_1_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5228288)))];
            tensor<fp16, [64]> model_encoder_stages_0_1_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_0_1_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5228480)))];
            tensor<fp16, [64]> model_encoder_stages_0_1_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_0_1_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5228672)))];
            tensor<fp16, [1, 64, 96, 128]> input_19_cast_fp16 = batch_norm(beta = model_encoder_stages_0_1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_0_1_norm_weight_to_fp16, mean = model_encoder_stages_0_1_norm_running_mean_to_fp16, variance = model_encoder_stages_0_1_norm_running_var_to_fp16, x = input_17_cast_fp16)[name = string("input_19_cast_fp16")];
            string input_21_pad_type_0 = const()[name = string("input_21_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_21_strides_0 = const()[name = string("input_21_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_21_pad_0 = const()[name = string("input_21_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_21_dilations_0 = const()[name = string("input_21_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_21_groups_0 = const()[name = string("input_21_groups_0"), val = int32(1)];
            tensor<fp16, [256]> model_encoder_stages_0_1_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_0_1_pointwise_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5228864)))];
            tensor<fp16, [1, 256, 96, 128]> input_21_cast_fp16 = conv(bias = model_encoder_stages_0_1_pointwise_1_bias_to_fp16, dilations = input_21_dilations_0, groups = input_21_groups_0, pad = input_21_pad_0, pad_type = input_21_pad_type_0, strides = input_21_strides_0, weight = model_encoder_stages_0_1_pointwise_1_weight_cast_fp16, x = input_19_cast_fp16)[name = string("input_21_cast_fp16")];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 256, 96, 128]> input_23_cast_fp16 = gelu(mode = input_23_mode_0, x = input_21_cast_fp16)[name = string("input_23_cast_fp16")];
            string x_5_pad_type_0 = const()[name = string("x_5_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_5_strides_0 = const()[name = string("x_5_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_5_pad_0 = const()[name = string("x_5_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_5_dilations_0 = const()[name = string("x_5_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_5_groups_0 = const()[name = string("x_5_groups_0"), val = int32(1)];
            tensor<fp16, [64]> model_encoder_stages_0_1_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_0_1_pointwise_2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5229440)))];
            tensor<fp16, [1, 64, 96, 128]> x_5_cast_fp16 = conv(bias = model_encoder_stages_0_1_pointwise_2_bias_to_fp16, dilations = x_5_dilations_0, groups = x_5_groups_0, pad = x_5_pad_0, pad_type = x_5_pad_type_0, strides = x_5_strides_0, weight = model_encoder_stages_0_1_pointwise_2_weight_cast_fp16, x = input_23_cast_fp16)[name = string("x_5_cast_fp16")];
            tensor<fp16, [1, 64, 1, 1]> model_encoder_stages_0_1_gamma_to_fp16 = const()[name = string("model_encoder_stages_0_1_gamma_to_fp16"), val = tensor<fp16, [1, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5229632)))];
            tensor<fp16, [1, 64, 96, 128]> x_7_cast_fp16 = mul(x = model_encoder_stages_0_1_gamma_to_fp16, y = x_5_cast_fp16)[name = string("x_7_cast_fp16")];
            tensor<fp16, [1, 64, 96, 128]> input_25_cast_fp16 = add(x = input_15_cast_fp16, y = x_7_cast_fp16)[name = string("input_25_cast_fp16")];
            string input_27_pad_type_0 = const()[name = string("input_27_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_27_pad_0 = const()[name = string("input_27_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_27_groups_0 = const()[name = string("input_27_groups_0"), val = int32(64)];
            tensor<int32, [2]> input_27_strides_0 = const()[name = string("input_27_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_27_dilations_0 = const()[name = string("input_27_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [64]> model_encoder_stages_0_2_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_0_2_depthwise_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5229824)))];
            tensor<fp16, [1, 64, 96, 128]> input_27_cast_fp16 = conv(bias = model_encoder_stages_0_2_depthwise_bias_to_fp16, dilations = input_27_dilations_0, groups = input_27_groups_0, pad = input_27_pad_0, pad_type = input_27_pad_type_0, strides = input_27_strides_0, weight = model_encoder_stages_0_2_depthwise_weight_cast_fp16, x = input_25_cast_fp16)[name = string("input_27_cast_fp16")];
            tensor<fp16, [64]> model_encoder_stages_0_2_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_0_2_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5230016)))];
            tensor<fp16, [64]> model_encoder_stages_0_2_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_0_2_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5230208)))];
            tensor<fp16, [64]> model_encoder_stages_0_2_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_0_2_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5230400)))];
            tensor<fp16, [64]> model_encoder_stages_0_2_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_0_2_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5230592)))];
            tensor<fp16, [1, 64, 96, 128]> input_29_cast_fp16 = batch_norm(beta = model_encoder_stages_0_2_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_0_2_norm_weight_to_fp16, mean = model_encoder_stages_0_2_norm_running_mean_to_fp16, variance = model_encoder_stages_0_2_norm_running_var_to_fp16, x = input_27_cast_fp16)[name = string("input_29_cast_fp16")];
            string input_31_pad_type_0 = const()[name = string("input_31_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_31_strides_0 = const()[name = string("input_31_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_31_pad_0 = const()[name = string("input_31_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_31_dilations_0 = const()[name = string("input_31_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_31_groups_0 = const()[name = string("input_31_groups_0"), val = int32(1)];
            tensor<fp16, [256]> model_encoder_stages_0_2_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_0_2_pointwise_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5230784)))];
            tensor<fp16, [1, 256, 96, 128]> input_31_cast_fp16 = conv(bias = model_encoder_stages_0_2_pointwise_1_bias_to_fp16, dilations = input_31_dilations_0, groups = input_31_groups_0, pad = input_31_pad_0, pad_type = input_31_pad_type_0, strides = input_31_strides_0, weight = model_encoder_stages_0_2_pointwise_1_weight_cast_fp16, x = input_29_cast_fp16)[name = string("input_31_cast_fp16")];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 256, 96, 128]> input_33_cast_fp16 = gelu(mode = input_33_mode_0, x = input_31_cast_fp16)[name = string("input_33_cast_fp16")];
            string x_9_pad_type_0 = const()[name = string("x_9_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_9_strides_0 = const()[name = string("x_9_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_9_pad_0 = const()[name = string("x_9_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_9_dilations_0 = const()[name = string("x_9_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_9_groups_0 = const()[name = string("x_9_groups_0"), val = int32(1)];
            tensor<fp16, [64]> model_encoder_stages_0_2_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_0_2_pointwise_2_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5231360)))];
            tensor<fp16, [1, 64, 96, 128]> x_9_cast_fp16 = conv(bias = model_encoder_stages_0_2_pointwise_2_bias_to_fp16, dilations = x_9_dilations_0, groups = x_9_groups_0, pad = x_9_pad_0, pad_type = x_9_pad_type_0, strides = x_9_strides_0, weight = model_encoder_stages_0_2_pointwise_2_weight_cast_fp16, x = input_33_cast_fp16)[name = string("x_9_cast_fp16")];
            tensor<fp16, [1, 64, 1, 1]> model_encoder_stages_0_2_gamma_to_fp16 = const()[name = string("model_encoder_stages_0_2_gamma_to_fp16"), val = tensor<fp16, [1, 64, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5231552)))];
            tensor<fp16, [1, 64, 96, 128]> x_11_cast_fp16 = mul(x = model_encoder_stages_0_2_gamma_to_fp16, y = x_9_cast_fp16)[name = string("x_11_cast_fp16")];
            tensor<fp16, [1, 64, 96, 128]> input_35_cast_fp16 = add(x = input_25_cast_fp16, y = x_11_cast_fp16)[name = string("input_35_cast_fp16")];
            tensor<fp16, [64]> model_encoder_norm0_running_mean_to_fp16 = const()[name = string("model_encoder_norm0_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5231744)))];
            tensor<fp16, [64]> model_encoder_norm0_running_var_to_fp16 = const()[name = string("model_encoder_norm0_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5231936)))];
            tensor<fp16, [64]> model_encoder_norm0_weight_to_fp16 = const()[name = string("model_encoder_norm0_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5232128)))];
            tensor<fp16, [64]> model_encoder_norm0_bias_to_fp16 = const()[name = string("model_encoder_norm0_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5232320)))];
            tensor<fp16, [1, 64, 96, 128]> input_191_cast_fp16 = batch_norm(beta = model_encoder_norm0_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_norm0_weight_to_fp16, mean = model_encoder_norm0_running_mean_to_fp16, variance = model_encoder_norm0_running_var_to_fp16, x = input_35_cast_fp16)[name = string("input_191_cast_fp16")];
            tensor<fp16, [64]> model_encoder_downsample_layers_1_0_running_mean_to_fp16 = const()[name = string("model_encoder_downsample_layers_1_0_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5232512)))];
            tensor<fp16, [64]> model_encoder_downsample_layers_1_0_running_var_to_fp16 = const()[name = string("model_encoder_downsample_layers_1_0_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5232704)))];
            tensor<fp16, [64]> model_encoder_downsample_layers_1_0_weight_to_fp16 = const()[name = string("model_encoder_downsample_layers_1_0_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5232896)))];
            tensor<fp16, [64]> model_encoder_downsample_layers_1_0_bias_to_fp16 = const()[name = string("model_encoder_downsample_layers_1_0_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5233088)))];
            tensor<fp16, [1, 64, 96, 128]> input_37_cast_fp16 = batch_norm(beta = model_encoder_downsample_layers_1_0_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_downsample_layers_1_0_weight_to_fp16, mean = model_encoder_downsample_layers_1_0_running_mean_to_fp16, variance = model_encoder_downsample_layers_1_0_running_var_to_fp16, x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
            string input_39_pad_type_0 = const()[name = string("input_39_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_39_strides_0 = const()[name = string("input_39_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> input_39_pad_0 = const()[name = string("input_39_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_39_dilations_0 = const()[name = string("input_39_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_39_groups_0 = const()[name = string("input_39_groups_0"), val = int32(1)];
            tensor<fp16, [96]> model_encoder_downsample_layers_1_1_bias_to_fp16 = const()[name = string("model_encoder_downsample_layers_1_1_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5233280)))];
            tensor<fp16, [1, 96, 48, 64]> input_39_cast_fp16 = conv(bias = model_encoder_downsample_layers_1_1_bias_to_fp16, dilations = input_39_dilations_0, groups = input_39_groups_0, pad = input_39_pad_0, pad_type = input_39_pad_type_0, strides = input_39_strides_0, weight = model_encoder_downsample_layers_1_1_weight_cast_fp16, x = input_37_cast_fp16)[name = string("input_39_cast_fp16")];
            string input_41_pad_type_0 = const()[name = string("input_41_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_41_pad_0 = const()[name = string("input_41_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_41_groups_0 = const()[name = string("input_41_groups_0"), val = int32(96)];
            tensor<int32, [2]> input_41_strides_0 = const()[name = string("input_41_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_41_dilations_0 = const()[name = string("input_41_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [96]> model_encoder_stages_1_0_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_1_0_depthwise_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5233536)))];
            tensor<fp16, [1, 96, 48, 64]> input_41_cast_fp16 = conv(bias = model_encoder_stages_1_0_depthwise_bias_to_fp16, dilations = input_41_dilations_0, groups = input_41_groups_0, pad = input_41_pad_0, pad_type = input_41_pad_type_0, strides = input_41_strides_0, weight = model_encoder_stages_1_0_depthwise_weight_cast_fp16, x = input_39_cast_fp16)[name = string("input_41_cast_fp16")];
            tensor<fp16, [96]> model_encoder_stages_1_0_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_1_0_norm_running_mean_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5233792)))];
            tensor<fp16, [96]> model_encoder_stages_1_0_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_1_0_norm_running_var_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5234048)))];
            tensor<fp16, [96]> model_encoder_stages_1_0_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_1_0_norm_weight_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5234304)))];
            tensor<fp16, [96]> model_encoder_stages_1_0_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_1_0_norm_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5234560)))];
            tensor<fp16, [1, 96, 48, 64]> input_43_cast_fp16 = batch_norm(beta = model_encoder_stages_1_0_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_1_0_norm_weight_to_fp16, mean = model_encoder_stages_1_0_norm_running_mean_to_fp16, variance = model_encoder_stages_1_0_norm_running_var_to_fp16, x = input_41_cast_fp16)[name = string("input_43_cast_fp16")];
            string input_45_pad_type_0 = const()[name = string("input_45_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_45_strides_0 = const()[name = string("input_45_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_45_pad_0 = const()[name = string("input_45_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_45_dilations_0 = const()[name = string("input_45_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_45_groups_0 = const()[name = string("input_45_groups_0"), val = int32(1)];
            tensor<fp16, [384]> model_encoder_stages_1_0_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_1_0_pointwise_1_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5234816)))];
            tensor<fp16, [1, 384, 48, 64]> input_45_cast_fp16 = conv(bias = model_encoder_stages_1_0_pointwise_1_bias_to_fp16, dilations = input_45_dilations_0, groups = input_45_groups_0, pad = input_45_pad_0, pad_type = input_45_pad_type_0, strides = input_45_strides_0, weight = model_encoder_stages_1_0_pointwise_1_weight_cast_fp16, x = input_43_cast_fp16)[name = string("input_45_cast_fp16")];
            string input_47_mode_0 = const()[name = string("input_47_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 384, 48, 64]> input_47_cast_fp16 = gelu(mode = input_47_mode_0, x = input_45_cast_fp16)[name = string("input_47_cast_fp16")];
            string x_13_pad_type_0 = const()[name = string("x_13_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_13_strides_0 = const()[name = string("x_13_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_13_pad_0 = const()[name = string("x_13_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_13_dilations_0 = const()[name = string("x_13_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_13_groups_0 = const()[name = string("x_13_groups_0"), val = int32(1)];
            tensor<fp16, [96]> model_encoder_stages_1_0_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_1_0_pointwise_2_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5235648)))];
            tensor<fp16, [1, 96, 48, 64]> x_13_cast_fp16 = conv(bias = model_encoder_stages_1_0_pointwise_2_bias_to_fp16, dilations = x_13_dilations_0, groups = x_13_groups_0, pad = x_13_pad_0, pad_type = x_13_pad_type_0, strides = x_13_strides_0, weight = model_encoder_stages_1_0_pointwise_2_weight_cast_fp16, x = input_47_cast_fp16)[name = string("x_13_cast_fp16")];
            tensor<fp16, [1, 96, 1, 1]> model_encoder_stages_1_0_gamma_to_fp16 = const()[name = string("model_encoder_stages_1_0_gamma_to_fp16"), val = tensor<fp16, [1, 96, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5235904)))];
            tensor<fp16, [1, 96, 48, 64]> x_15_cast_fp16 = mul(x = model_encoder_stages_1_0_gamma_to_fp16, y = x_13_cast_fp16)[name = string("x_15_cast_fp16")];
            tensor<fp16, [1, 96, 48, 64]> input_49_cast_fp16 = add(x = input_39_cast_fp16, y = x_15_cast_fp16)[name = string("input_49_cast_fp16")];
            string input_51_pad_type_0 = const()[name = string("input_51_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_51_pad_0 = const()[name = string("input_51_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_51_groups_0 = const()[name = string("input_51_groups_0"), val = int32(96)];
            tensor<int32, [2]> input_51_strides_0 = const()[name = string("input_51_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_51_dilations_0 = const()[name = string("input_51_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [96]> model_encoder_stages_1_1_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_1_1_depthwise_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5236160)))];
            tensor<fp16, [1, 96, 48, 64]> input_51_cast_fp16 = conv(bias = model_encoder_stages_1_1_depthwise_bias_to_fp16, dilations = input_51_dilations_0, groups = input_51_groups_0, pad = input_51_pad_0, pad_type = input_51_pad_type_0, strides = input_51_strides_0, weight = model_encoder_stages_1_1_depthwise_weight_cast_fp16, x = input_49_cast_fp16)[name = string("input_51_cast_fp16")];
            tensor<fp16, [96]> model_encoder_stages_1_1_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_1_1_norm_running_mean_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5236416)))];
            tensor<fp16, [96]> model_encoder_stages_1_1_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_1_1_norm_running_var_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5236672)))];
            tensor<fp16, [96]> model_encoder_stages_1_1_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_1_1_norm_weight_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5236928)))];
            tensor<fp16, [96]> model_encoder_stages_1_1_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_1_1_norm_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5237184)))];
            tensor<fp16, [1, 96, 48, 64]> input_53_cast_fp16 = batch_norm(beta = model_encoder_stages_1_1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_1_1_norm_weight_to_fp16, mean = model_encoder_stages_1_1_norm_running_mean_to_fp16, variance = model_encoder_stages_1_1_norm_running_var_to_fp16, x = input_51_cast_fp16)[name = string("input_53_cast_fp16")];
            string input_55_pad_type_0 = const()[name = string("input_55_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_55_strides_0 = const()[name = string("input_55_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_55_pad_0 = const()[name = string("input_55_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_55_dilations_0 = const()[name = string("input_55_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_55_groups_0 = const()[name = string("input_55_groups_0"), val = int32(1)];
            tensor<fp16, [384]> model_encoder_stages_1_1_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_1_1_pointwise_1_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5237440)))];
            tensor<fp16, [1, 384, 48, 64]> input_55_cast_fp16 = conv(bias = model_encoder_stages_1_1_pointwise_1_bias_to_fp16, dilations = input_55_dilations_0, groups = input_55_groups_0, pad = input_55_pad_0, pad_type = input_55_pad_type_0, strides = input_55_strides_0, weight = model_encoder_stages_1_1_pointwise_1_weight_cast_fp16, x = input_53_cast_fp16)[name = string("input_55_cast_fp16")];
            string input_57_mode_0 = const()[name = string("input_57_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 384, 48, 64]> input_57_cast_fp16 = gelu(mode = input_57_mode_0, x = input_55_cast_fp16)[name = string("input_57_cast_fp16")];
            string x_17_pad_type_0 = const()[name = string("x_17_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_17_strides_0 = const()[name = string("x_17_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_17_pad_0 = const()[name = string("x_17_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_17_dilations_0 = const()[name = string("x_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_17_groups_0 = const()[name = string("x_17_groups_0"), val = int32(1)];
            tensor<fp16, [96]> model_encoder_stages_1_1_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_1_1_pointwise_2_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5238272)))];
            tensor<fp16, [1, 96, 48, 64]> x_17_cast_fp16 = conv(bias = model_encoder_stages_1_1_pointwise_2_bias_to_fp16, dilations = x_17_dilations_0, groups = x_17_groups_0, pad = x_17_pad_0, pad_type = x_17_pad_type_0, strides = x_17_strides_0, weight = model_encoder_stages_1_1_pointwise_2_weight_cast_fp16, x = input_57_cast_fp16)[name = string("x_17_cast_fp16")];
            tensor<fp16, [1, 96, 1, 1]> model_encoder_stages_1_1_gamma_to_fp16 = const()[name = string("model_encoder_stages_1_1_gamma_to_fp16"), val = tensor<fp16, [1, 96, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5238528)))];
            tensor<fp16, [1, 96, 48, 64]> x_19_cast_fp16 = mul(x = model_encoder_stages_1_1_gamma_to_fp16, y = x_17_cast_fp16)[name = string("x_19_cast_fp16")];
            tensor<fp16, [1, 96, 48, 64]> input_59_cast_fp16 = add(x = input_49_cast_fp16, y = x_19_cast_fp16)[name = string("input_59_cast_fp16")];
            string input_61_pad_type_0 = const()[name = string("input_61_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_61_pad_0 = const()[name = string("input_61_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_61_groups_0 = const()[name = string("input_61_groups_0"), val = int32(96)];
            tensor<int32, [2]> input_61_strides_0 = const()[name = string("input_61_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_61_dilations_0 = const()[name = string("input_61_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [96]> model_encoder_stages_1_2_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_1_2_depthwise_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5238784)))];
            tensor<fp16, [1, 96, 48, 64]> input_61_cast_fp16 = conv(bias = model_encoder_stages_1_2_depthwise_bias_to_fp16, dilations = input_61_dilations_0, groups = input_61_groups_0, pad = input_61_pad_0, pad_type = input_61_pad_type_0, strides = input_61_strides_0, weight = model_encoder_stages_1_2_depthwise_weight_cast_fp16, x = input_59_cast_fp16)[name = string("input_61_cast_fp16")];
            tensor<fp16, [96]> model_encoder_stages_1_2_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_1_2_norm_running_mean_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5239040)))];
            tensor<fp16, [96]> model_encoder_stages_1_2_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_1_2_norm_running_var_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5239296)))];
            tensor<fp16, [96]> model_encoder_stages_1_2_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_1_2_norm_weight_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5239552)))];
            tensor<fp16, [96]> model_encoder_stages_1_2_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_1_2_norm_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5239808)))];
            tensor<fp16, [1, 96, 48, 64]> input_63_cast_fp16 = batch_norm(beta = model_encoder_stages_1_2_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_1_2_norm_weight_to_fp16, mean = model_encoder_stages_1_2_norm_running_mean_to_fp16, variance = model_encoder_stages_1_2_norm_running_var_to_fp16, x = input_61_cast_fp16)[name = string("input_63_cast_fp16")];
            string input_65_pad_type_0 = const()[name = string("input_65_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_65_strides_0 = const()[name = string("input_65_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_65_pad_0 = const()[name = string("input_65_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_65_dilations_0 = const()[name = string("input_65_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_65_groups_0 = const()[name = string("input_65_groups_0"), val = int32(1)];
            tensor<fp16, [384]> model_encoder_stages_1_2_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_1_2_pointwise_1_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5240064)))];
            tensor<fp16, [1, 384, 48, 64]> input_65_cast_fp16 = conv(bias = model_encoder_stages_1_2_pointwise_1_bias_to_fp16, dilations = input_65_dilations_0, groups = input_65_groups_0, pad = input_65_pad_0, pad_type = input_65_pad_type_0, strides = input_65_strides_0, weight = model_encoder_stages_1_2_pointwise_1_weight_cast_fp16, x = input_63_cast_fp16)[name = string("input_65_cast_fp16")];
            string input_67_mode_0 = const()[name = string("input_67_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 384, 48, 64]> input_67_cast_fp16 = gelu(mode = input_67_mode_0, x = input_65_cast_fp16)[name = string("input_67_cast_fp16")];
            string x_21_pad_type_0 = const()[name = string("x_21_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_21_strides_0 = const()[name = string("x_21_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_21_pad_0 = const()[name = string("x_21_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_21_dilations_0 = const()[name = string("x_21_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_21_groups_0 = const()[name = string("x_21_groups_0"), val = int32(1)];
            tensor<fp16, [96]> model_encoder_stages_1_2_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_1_2_pointwise_2_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5240896)))];
            tensor<fp16, [1, 96, 48, 64]> x_21_cast_fp16 = conv(bias = model_encoder_stages_1_2_pointwise_2_bias_to_fp16, dilations = x_21_dilations_0, groups = x_21_groups_0, pad = x_21_pad_0, pad_type = x_21_pad_type_0, strides = x_21_strides_0, weight = model_encoder_stages_1_2_pointwise_2_weight_cast_fp16, x = input_67_cast_fp16)[name = string("x_21_cast_fp16")];
            tensor<fp16, [1, 96, 1, 1]> model_encoder_stages_1_2_gamma_to_fp16 = const()[name = string("model_encoder_stages_1_2_gamma_to_fp16"), val = tensor<fp16, [1, 96, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5241152)))];
            tensor<fp16, [1, 96, 48, 64]> x_23_cast_fp16 = mul(x = model_encoder_stages_1_2_gamma_to_fp16, y = x_21_cast_fp16)[name = string("x_23_cast_fp16")];
            tensor<fp16, [1, 96, 48, 64]> input_69_cast_fp16 = add(x = input_59_cast_fp16, y = x_23_cast_fp16)[name = string("input_69_cast_fp16")];
            tensor<fp16, [96]> model_encoder_norm1_running_mean_to_fp16 = const()[name = string("model_encoder_norm1_running_mean_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5241408)))];
            tensor<fp16, [96]> model_encoder_norm1_running_var_to_fp16 = const()[name = string("model_encoder_norm1_running_var_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5241664)))];
            tensor<fp16, [96]> model_encoder_norm1_weight_to_fp16 = const()[name = string("model_encoder_norm1_weight_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5241920)))];
            tensor<fp16, [96]> model_encoder_norm1_bias_to_fp16 = const()[name = string("model_encoder_norm1_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5242176)))];
            tensor<fp16, [1, 96, 48, 64]> input_183_cast_fp16 = batch_norm(beta = model_encoder_norm1_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_norm1_weight_to_fp16, mean = model_encoder_norm1_running_mean_to_fp16, variance = model_encoder_norm1_running_var_to_fp16, x = input_69_cast_fp16)[name = string("input_183_cast_fp16")];
            tensor<fp16, [96]> model_encoder_downsample_layers_2_0_running_mean_to_fp16 = const()[name = string("model_encoder_downsample_layers_2_0_running_mean_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5242432)))];
            tensor<fp16, [96]> model_encoder_downsample_layers_2_0_running_var_to_fp16 = const()[name = string("model_encoder_downsample_layers_2_0_running_var_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5242688)))];
            tensor<fp16, [96]> model_encoder_downsample_layers_2_0_weight_to_fp16 = const()[name = string("model_encoder_downsample_layers_2_0_weight_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5242944)))];
            tensor<fp16, [96]> model_encoder_downsample_layers_2_0_bias_to_fp16 = const()[name = string("model_encoder_downsample_layers_2_0_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5243200)))];
            tensor<fp16, [1, 96, 48, 64]> input_71_cast_fp16 = batch_norm(beta = model_encoder_downsample_layers_2_0_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_downsample_layers_2_0_weight_to_fp16, mean = model_encoder_downsample_layers_2_0_running_mean_to_fp16, variance = model_encoder_downsample_layers_2_0_running_var_to_fp16, x = input_69_cast_fp16)[name = string("input_71_cast_fp16")];
            string input_73_pad_type_0 = const()[name = string("input_73_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_73_strides_0 = const()[name = string("input_73_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> input_73_pad_0 = const()[name = string("input_73_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_73_dilations_0 = const()[name = string("input_73_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_73_groups_0 = const()[name = string("input_73_groups_0"), val = int32(1)];
            tensor<fp16, [192]> model_encoder_downsample_layers_2_1_bias_to_fp16 = const()[name = string("model_encoder_downsample_layers_2_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5243456)))];
            tensor<fp16, [1, 192, 24, 32]> input_73_cast_fp16 = conv(bias = model_encoder_downsample_layers_2_1_bias_to_fp16, dilations = input_73_dilations_0, groups = input_73_groups_0, pad = input_73_pad_0, pad_type = input_73_pad_type_0, strides = input_73_strides_0, weight = model_encoder_downsample_layers_2_1_weight_cast_fp16, x = input_71_cast_fp16)[name = string("input_73_cast_fp16")];
            string input_75_pad_type_0 = const()[name = string("input_75_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_75_pad_0 = const()[name = string("input_75_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_75_groups_0 = const()[name = string("input_75_groups_0"), val = int32(192)];
            tensor<int32, [2]> input_75_strides_0 = const()[name = string("input_75_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_75_dilations_0 = const()[name = string("input_75_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [192]> model_encoder_stages_2_0_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_2_0_depthwise_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5243904)))];
            tensor<fp16, [1, 192, 24, 32]> input_75_cast_fp16 = conv(bias = model_encoder_stages_2_0_depthwise_bias_to_fp16, dilations = input_75_dilations_0, groups = input_75_groups_0, pad = input_75_pad_0, pad_type = input_75_pad_type_0, strides = input_75_strides_0, weight = model_encoder_stages_2_0_depthwise_weight_cast_fp16, x = input_73_cast_fp16)[name = string("input_75_cast_fp16")];
            tensor<fp16, [192]> model_encoder_stages_2_0_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_2_0_norm_running_mean_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5244352)))];
            tensor<fp16, [192]> model_encoder_stages_2_0_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_2_0_norm_running_var_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5244800)))];
            tensor<fp16, [192]> model_encoder_stages_2_0_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_2_0_norm_weight_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5245248)))];
            tensor<fp16, [192]> model_encoder_stages_2_0_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_2_0_norm_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5245696)))];
            tensor<fp16, [1, 192, 24, 32]> input_77_cast_fp16 = batch_norm(beta = model_encoder_stages_2_0_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_2_0_norm_weight_to_fp16, mean = model_encoder_stages_2_0_norm_running_mean_to_fp16, variance = model_encoder_stages_2_0_norm_running_var_to_fp16, x = input_75_cast_fp16)[name = string("input_77_cast_fp16")];
            string input_79_pad_type_0 = const()[name = string("input_79_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_79_strides_0 = const()[name = string("input_79_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_79_pad_0 = const()[name = string("input_79_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_79_dilations_0 = const()[name = string("input_79_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_79_groups_0 = const()[name = string("input_79_groups_0"), val = int32(1)];
            tensor<fp16, [768]> model_encoder_stages_2_0_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_2_0_pointwise_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5246144)))];
            tensor<fp16, [1, 768, 24, 32]> input_79_cast_fp16 = conv(bias = model_encoder_stages_2_0_pointwise_1_bias_to_fp16, dilations = input_79_dilations_0, groups = input_79_groups_0, pad = input_79_pad_0, pad_type = input_79_pad_type_0, strides = input_79_strides_0, weight = model_encoder_stages_2_0_pointwise_1_weight_cast_fp16, x = input_77_cast_fp16)[name = string("input_79_cast_fp16")];
            string input_81_mode_0 = const()[name = string("input_81_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 768, 24, 32]> input_81_cast_fp16 = gelu(mode = input_81_mode_0, x = input_79_cast_fp16)[name = string("input_81_cast_fp16")];
            string x_25_pad_type_0 = const()[name = string("x_25_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_25_strides_0 = const()[name = string("x_25_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_25_pad_0 = const()[name = string("x_25_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_25_dilations_0 = const()[name = string("x_25_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_25_groups_0 = const()[name = string("x_25_groups_0"), val = int32(1)];
            tensor<fp16, [192]> model_encoder_stages_2_0_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_2_0_pointwise_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5247744)))];
            tensor<fp16, [1, 192, 24, 32]> x_25_cast_fp16 = conv(bias = model_encoder_stages_2_0_pointwise_2_bias_to_fp16, dilations = x_25_dilations_0, groups = x_25_groups_0, pad = x_25_pad_0, pad_type = x_25_pad_type_0, strides = x_25_strides_0, weight = model_encoder_stages_2_0_pointwise_2_weight_cast_fp16, x = input_81_cast_fp16)[name = string("x_25_cast_fp16")];
            tensor<fp16, [1, 192, 1, 1]> model_encoder_stages_2_0_gamma_to_fp16 = const()[name = string("model_encoder_stages_2_0_gamma_to_fp16"), val = tensor<fp16, [1, 192, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5248192)))];
            tensor<fp16, [1, 192, 24, 32]> x_27_cast_fp16 = mul(x = model_encoder_stages_2_0_gamma_to_fp16, y = x_25_cast_fp16)[name = string("x_27_cast_fp16")];
            tensor<fp16, [1, 192, 24, 32]> input_83_cast_fp16 = add(x = input_73_cast_fp16, y = x_27_cast_fp16)[name = string("input_83_cast_fp16")];
            string input_85_pad_type_0 = const()[name = string("input_85_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_85_pad_0 = const()[name = string("input_85_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_85_groups_0 = const()[name = string("input_85_groups_0"), val = int32(192)];
            tensor<int32, [2]> input_85_strides_0 = const()[name = string("input_85_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_85_dilations_0 = const()[name = string("input_85_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [192]> model_encoder_stages_2_1_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_2_1_depthwise_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5248640)))];
            tensor<fp16, [1, 192, 24, 32]> input_85_cast_fp16 = conv(bias = model_encoder_stages_2_1_depthwise_bias_to_fp16, dilations = input_85_dilations_0, groups = input_85_groups_0, pad = input_85_pad_0, pad_type = input_85_pad_type_0, strides = input_85_strides_0, weight = model_encoder_stages_2_1_depthwise_weight_cast_fp16, x = input_83_cast_fp16)[name = string("input_85_cast_fp16")];
            tensor<fp16, [192]> model_encoder_stages_2_1_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_2_1_norm_running_mean_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5249088)))];
            tensor<fp16, [192]> model_encoder_stages_2_1_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_2_1_norm_running_var_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5249536)))];
            tensor<fp16, [192]> model_encoder_stages_2_1_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_2_1_norm_weight_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5249984)))];
            tensor<fp16, [192]> model_encoder_stages_2_1_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_2_1_norm_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5250432)))];
            tensor<fp16, [1, 192, 24, 32]> input_87_cast_fp16 = batch_norm(beta = model_encoder_stages_2_1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_2_1_norm_weight_to_fp16, mean = model_encoder_stages_2_1_norm_running_mean_to_fp16, variance = model_encoder_stages_2_1_norm_running_var_to_fp16, x = input_85_cast_fp16)[name = string("input_87_cast_fp16")];
            string input_89_pad_type_0 = const()[name = string("input_89_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_89_strides_0 = const()[name = string("input_89_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_89_pad_0 = const()[name = string("input_89_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_89_dilations_0 = const()[name = string("input_89_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_89_groups_0 = const()[name = string("input_89_groups_0"), val = int32(1)];
            tensor<fp16, [768]> model_encoder_stages_2_1_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_2_1_pointwise_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5250880)))];
            tensor<fp16, [1, 768, 24, 32]> input_89_cast_fp16 = conv(bias = model_encoder_stages_2_1_pointwise_1_bias_to_fp16, dilations = input_89_dilations_0, groups = input_89_groups_0, pad = input_89_pad_0, pad_type = input_89_pad_type_0, strides = input_89_strides_0, weight = model_encoder_stages_2_1_pointwise_1_weight_cast_fp16, x = input_87_cast_fp16)[name = string("input_89_cast_fp16")];
            string input_91_mode_0 = const()[name = string("input_91_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 768, 24, 32]> input_91_cast_fp16 = gelu(mode = input_91_mode_0, x = input_89_cast_fp16)[name = string("input_91_cast_fp16")];
            string x_29_pad_type_0 = const()[name = string("x_29_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_29_strides_0 = const()[name = string("x_29_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_29_pad_0 = const()[name = string("x_29_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_29_dilations_0 = const()[name = string("x_29_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_29_groups_0 = const()[name = string("x_29_groups_0"), val = int32(1)];
            tensor<fp16, [192]> model_encoder_stages_2_1_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_2_1_pointwise_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5252480)))];
            tensor<fp16, [1, 192, 24, 32]> x_29_cast_fp16 = conv(bias = model_encoder_stages_2_1_pointwise_2_bias_to_fp16, dilations = x_29_dilations_0, groups = x_29_groups_0, pad = x_29_pad_0, pad_type = x_29_pad_type_0, strides = x_29_strides_0, weight = model_encoder_stages_2_1_pointwise_2_weight_cast_fp16, x = input_91_cast_fp16)[name = string("x_29_cast_fp16")];
            tensor<fp16, [1, 192, 1, 1]> model_encoder_stages_2_1_gamma_to_fp16 = const()[name = string("model_encoder_stages_2_1_gamma_to_fp16"), val = tensor<fp16, [1, 192, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5252928)))];
            tensor<fp16, [1, 192, 24, 32]> x_31_cast_fp16 = mul(x = model_encoder_stages_2_1_gamma_to_fp16, y = x_29_cast_fp16)[name = string("x_31_cast_fp16")];
            tensor<fp16, [1, 192, 24, 32]> input_93_cast_fp16 = add(x = input_83_cast_fp16, y = x_31_cast_fp16)[name = string("input_93_cast_fp16")];
            string input_95_pad_type_0 = const()[name = string("input_95_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_95_pad_0 = const()[name = string("input_95_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_95_groups_0 = const()[name = string("input_95_groups_0"), val = int32(192)];
            tensor<int32, [2]> input_95_strides_0 = const()[name = string("input_95_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_95_dilations_0 = const()[name = string("input_95_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [192]> model_encoder_stages_2_2_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_2_2_depthwise_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5253376)))];
            tensor<fp16, [1, 192, 24, 32]> input_95_cast_fp16 = conv(bias = model_encoder_stages_2_2_depthwise_bias_to_fp16, dilations = input_95_dilations_0, groups = input_95_groups_0, pad = input_95_pad_0, pad_type = input_95_pad_type_0, strides = input_95_strides_0, weight = model_encoder_stages_2_2_depthwise_weight_cast_fp16, x = input_93_cast_fp16)[name = string("input_95_cast_fp16")];
            tensor<fp16, [192]> model_encoder_stages_2_2_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_2_2_norm_running_mean_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5253824)))];
            tensor<fp16, [192]> model_encoder_stages_2_2_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_2_2_norm_running_var_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5254272)))];
            tensor<fp16, [192]> model_encoder_stages_2_2_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_2_2_norm_weight_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5254720)))];
            tensor<fp16, [192]> model_encoder_stages_2_2_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_2_2_norm_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5255168)))];
            tensor<fp16, [1, 192, 24, 32]> input_97_cast_fp16 = batch_norm(beta = model_encoder_stages_2_2_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_2_2_norm_weight_to_fp16, mean = model_encoder_stages_2_2_norm_running_mean_to_fp16, variance = model_encoder_stages_2_2_norm_running_var_to_fp16, x = input_95_cast_fp16)[name = string("input_97_cast_fp16")];
            string input_99_pad_type_0 = const()[name = string("input_99_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_99_strides_0 = const()[name = string("input_99_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_99_pad_0 = const()[name = string("input_99_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_99_dilations_0 = const()[name = string("input_99_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_99_groups_0 = const()[name = string("input_99_groups_0"), val = int32(1)];
            tensor<fp16, [768]> model_encoder_stages_2_2_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_2_2_pointwise_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5255616)))];
            tensor<fp16, [1, 768, 24, 32]> input_99_cast_fp16 = conv(bias = model_encoder_stages_2_2_pointwise_1_bias_to_fp16, dilations = input_99_dilations_0, groups = input_99_groups_0, pad = input_99_pad_0, pad_type = input_99_pad_type_0, strides = input_99_strides_0, weight = model_encoder_stages_2_2_pointwise_1_weight_cast_fp16, x = input_97_cast_fp16)[name = string("input_99_cast_fp16")];
            string input_101_mode_0 = const()[name = string("input_101_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 768, 24, 32]> input_101_cast_fp16 = gelu(mode = input_101_mode_0, x = input_99_cast_fp16)[name = string("input_101_cast_fp16")];
            string x_33_pad_type_0 = const()[name = string("x_33_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_33_strides_0 = const()[name = string("x_33_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_33_pad_0 = const()[name = string("x_33_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_33_dilations_0 = const()[name = string("x_33_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_33_groups_0 = const()[name = string("x_33_groups_0"), val = int32(1)];
            tensor<fp16, [192]> model_encoder_stages_2_2_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_2_2_pointwise_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5257216)))];
            tensor<fp16, [1, 192, 24, 32]> x_33_cast_fp16 = conv(bias = model_encoder_stages_2_2_pointwise_2_bias_to_fp16, dilations = x_33_dilations_0, groups = x_33_groups_0, pad = x_33_pad_0, pad_type = x_33_pad_type_0, strides = x_33_strides_0, weight = model_encoder_stages_2_2_pointwise_2_weight_cast_fp16, x = input_101_cast_fp16)[name = string("x_33_cast_fp16")];
            tensor<fp16, [1, 192, 1, 1]> model_encoder_stages_2_2_gamma_to_fp16 = const()[name = string("model_encoder_stages_2_2_gamma_to_fp16"), val = tensor<fp16, [1, 192, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5257664)))];
            tensor<fp16, [1, 192, 24, 32]> x_35_cast_fp16 = mul(x = model_encoder_stages_2_2_gamma_to_fp16, y = x_33_cast_fp16)[name = string("x_35_cast_fp16")];
            tensor<fp16, [1, 192, 24, 32]> input_103_cast_fp16 = add(x = input_93_cast_fp16, y = x_35_cast_fp16)[name = string("input_103_cast_fp16")];
            string input_105_pad_type_0 = const()[name = string("input_105_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_105_pad_0 = const()[name = string("input_105_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_105_groups_0 = const()[name = string("input_105_groups_0"), val = int32(192)];
            tensor<int32, [2]> input_105_strides_0 = const()[name = string("input_105_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_105_dilations_0 = const()[name = string("input_105_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [192]> model_encoder_stages_2_3_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_2_3_depthwise_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5258112)))];
            tensor<fp16, [1, 192, 24, 32]> input_105_cast_fp16 = conv(bias = model_encoder_stages_2_3_depthwise_bias_to_fp16, dilations = input_105_dilations_0, groups = input_105_groups_0, pad = input_105_pad_0, pad_type = input_105_pad_type_0, strides = input_105_strides_0, weight = model_encoder_stages_2_3_depthwise_weight_cast_fp16, x = input_103_cast_fp16)[name = string("input_105_cast_fp16")];
            tensor<fp16, [192]> model_encoder_stages_2_3_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_2_3_norm_running_mean_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5258560)))];
            tensor<fp16, [192]> model_encoder_stages_2_3_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_2_3_norm_running_var_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5259008)))];
            tensor<fp16, [192]> model_encoder_stages_2_3_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_2_3_norm_weight_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5259456)))];
            tensor<fp16, [192]> model_encoder_stages_2_3_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_2_3_norm_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5259904)))];
            tensor<fp16, [1, 192, 24, 32]> input_107_cast_fp16 = batch_norm(beta = model_encoder_stages_2_3_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_2_3_norm_weight_to_fp16, mean = model_encoder_stages_2_3_norm_running_mean_to_fp16, variance = model_encoder_stages_2_3_norm_running_var_to_fp16, x = input_105_cast_fp16)[name = string("input_107_cast_fp16")];
            string input_109_pad_type_0 = const()[name = string("input_109_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_109_strides_0 = const()[name = string("input_109_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_109_pad_0 = const()[name = string("input_109_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_109_dilations_0 = const()[name = string("input_109_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_109_groups_0 = const()[name = string("input_109_groups_0"), val = int32(1)];
            tensor<fp16, [768]> model_encoder_stages_2_3_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_2_3_pointwise_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5260352)))];
            tensor<fp16, [1, 768, 24, 32]> input_109_cast_fp16 = conv(bias = model_encoder_stages_2_3_pointwise_1_bias_to_fp16, dilations = input_109_dilations_0, groups = input_109_groups_0, pad = input_109_pad_0, pad_type = input_109_pad_type_0, strides = input_109_strides_0, weight = model_encoder_stages_2_3_pointwise_1_weight_cast_fp16, x = input_107_cast_fp16)[name = string("input_109_cast_fp16")];
            string input_111_mode_0 = const()[name = string("input_111_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 768, 24, 32]> input_111_cast_fp16 = gelu(mode = input_111_mode_0, x = input_109_cast_fp16)[name = string("input_111_cast_fp16")];
            string x_37_pad_type_0 = const()[name = string("x_37_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_37_strides_0 = const()[name = string("x_37_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_37_pad_0 = const()[name = string("x_37_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_37_dilations_0 = const()[name = string("x_37_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_37_groups_0 = const()[name = string("x_37_groups_0"), val = int32(1)];
            tensor<fp16, [192]> model_encoder_stages_2_3_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_2_3_pointwise_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5261952)))];
            tensor<fp16, [1, 192, 24, 32]> x_37_cast_fp16 = conv(bias = model_encoder_stages_2_3_pointwise_2_bias_to_fp16, dilations = x_37_dilations_0, groups = x_37_groups_0, pad = x_37_pad_0, pad_type = x_37_pad_type_0, strides = x_37_strides_0, weight = model_encoder_stages_2_3_pointwise_2_weight_cast_fp16, x = input_111_cast_fp16)[name = string("x_37_cast_fp16")];
            tensor<fp16, [1, 192, 1, 1]> model_encoder_stages_2_3_gamma_to_fp16 = const()[name = string("model_encoder_stages_2_3_gamma_to_fp16"), val = tensor<fp16, [1, 192, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5262400)))];
            tensor<fp16, [1, 192, 24, 32]> x_39_cast_fp16 = mul(x = model_encoder_stages_2_3_gamma_to_fp16, y = x_37_cast_fp16)[name = string("x_39_cast_fp16")];
            tensor<fp16, [1, 192, 24, 32]> input_113_cast_fp16 = add(x = input_103_cast_fp16, y = x_39_cast_fp16)[name = string("input_113_cast_fp16")];
            string input_115_pad_type_0 = const()[name = string("input_115_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_115_pad_0 = const()[name = string("input_115_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_115_groups_0 = const()[name = string("input_115_groups_0"), val = int32(192)];
            tensor<int32, [2]> input_115_strides_0 = const()[name = string("input_115_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_115_dilations_0 = const()[name = string("input_115_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [192]> model_encoder_stages_2_4_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_2_4_depthwise_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5262848)))];
            tensor<fp16, [1, 192, 24, 32]> input_115_cast_fp16 = conv(bias = model_encoder_stages_2_4_depthwise_bias_to_fp16, dilations = input_115_dilations_0, groups = input_115_groups_0, pad = input_115_pad_0, pad_type = input_115_pad_type_0, strides = input_115_strides_0, weight = model_encoder_stages_2_4_depthwise_weight_cast_fp16, x = input_113_cast_fp16)[name = string("input_115_cast_fp16")];
            tensor<fp16, [192]> model_encoder_stages_2_4_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_2_4_norm_running_mean_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5263296)))];
            tensor<fp16, [192]> model_encoder_stages_2_4_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_2_4_norm_running_var_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5263744)))];
            tensor<fp16, [192]> model_encoder_stages_2_4_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_2_4_norm_weight_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5264192)))];
            tensor<fp16, [192]> model_encoder_stages_2_4_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_2_4_norm_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5264640)))];
            tensor<fp16, [1, 192, 24, 32]> input_117_cast_fp16 = batch_norm(beta = model_encoder_stages_2_4_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_2_4_norm_weight_to_fp16, mean = model_encoder_stages_2_4_norm_running_mean_to_fp16, variance = model_encoder_stages_2_4_norm_running_var_to_fp16, x = input_115_cast_fp16)[name = string("input_117_cast_fp16")];
            string input_119_pad_type_0 = const()[name = string("input_119_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_119_strides_0 = const()[name = string("input_119_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_119_pad_0 = const()[name = string("input_119_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_119_dilations_0 = const()[name = string("input_119_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_119_groups_0 = const()[name = string("input_119_groups_0"), val = int32(1)];
            tensor<fp16, [768]> model_encoder_stages_2_4_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_2_4_pointwise_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5265088)))];
            tensor<fp16, [1, 768, 24, 32]> input_119_cast_fp16 = conv(bias = model_encoder_stages_2_4_pointwise_1_bias_to_fp16, dilations = input_119_dilations_0, groups = input_119_groups_0, pad = input_119_pad_0, pad_type = input_119_pad_type_0, strides = input_119_strides_0, weight = model_encoder_stages_2_4_pointwise_1_weight_cast_fp16, x = input_117_cast_fp16)[name = string("input_119_cast_fp16")];
            string input_121_mode_0 = const()[name = string("input_121_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 768, 24, 32]> input_121_cast_fp16 = gelu(mode = input_121_mode_0, x = input_119_cast_fp16)[name = string("input_121_cast_fp16")];
            string x_41_pad_type_0 = const()[name = string("x_41_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_41_strides_0 = const()[name = string("x_41_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_41_pad_0 = const()[name = string("x_41_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_41_dilations_0 = const()[name = string("x_41_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_41_groups_0 = const()[name = string("x_41_groups_0"), val = int32(1)];
            tensor<fp16, [192]> model_encoder_stages_2_4_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_2_4_pointwise_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5266688)))];
            tensor<fp16, [1, 192, 24, 32]> x_41_cast_fp16 = conv(bias = model_encoder_stages_2_4_pointwise_2_bias_to_fp16, dilations = x_41_dilations_0, groups = x_41_groups_0, pad = x_41_pad_0, pad_type = x_41_pad_type_0, strides = x_41_strides_0, weight = model_encoder_stages_2_4_pointwise_2_weight_cast_fp16, x = input_121_cast_fp16)[name = string("x_41_cast_fp16")];
            tensor<fp16, [1, 192, 1, 1]> model_encoder_stages_2_4_gamma_to_fp16 = const()[name = string("model_encoder_stages_2_4_gamma_to_fp16"), val = tensor<fp16, [1, 192, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5267136)))];
            tensor<fp16, [1, 192, 24, 32]> x_43_cast_fp16 = mul(x = model_encoder_stages_2_4_gamma_to_fp16, y = x_41_cast_fp16)[name = string("x_43_cast_fp16")];
            tensor<fp16, [1, 192, 24, 32]> input_123_cast_fp16 = add(x = input_113_cast_fp16, y = x_43_cast_fp16)[name = string("input_123_cast_fp16")];
            string input_125_pad_type_0 = const()[name = string("input_125_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_125_pad_0 = const()[name = string("input_125_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_125_groups_0 = const()[name = string("input_125_groups_0"), val = int32(192)];
            tensor<int32, [2]> input_125_strides_0 = const()[name = string("input_125_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_125_dilations_0 = const()[name = string("input_125_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [192]> model_encoder_stages_2_5_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_2_5_depthwise_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5267584)))];
            tensor<fp16, [1, 192, 24, 32]> input_125_cast_fp16 = conv(bias = model_encoder_stages_2_5_depthwise_bias_to_fp16, dilations = input_125_dilations_0, groups = input_125_groups_0, pad = input_125_pad_0, pad_type = input_125_pad_type_0, strides = input_125_strides_0, weight = model_encoder_stages_2_5_depthwise_weight_cast_fp16, x = input_123_cast_fp16)[name = string("input_125_cast_fp16")];
            tensor<fp16, [192]> model_encoder_stages_2_5_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_2_5_norm_running_mean_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5268032)))];
            tensor<fp16, [192]> model_encoder_stages_2_5_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_2_5_norm_running_var_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5268480)))];
            tensor<fp16, [192]> model_encoder_stages_2_5_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_2_5_norm_weight_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5268928)))];
            tensor<fp16, [192]> model_encoder_stages_2_5_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_2_5_norm_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5269376)))];
            tensor<fp16, [1, 192, 24, 32]> input_127_cast_fp16 = batch_norm(beta = model_encoder_stages_2_5_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_2_5_norm_weight_to_fp16, mean = model_encoder_stages_2_5_norm_running_mean_to_fp16, variance = model_encoder_stages_2_5_norm_running_var_to_fp16, x = input_125_cast_fp16)[name = string("input_127_cast_fp16")];
            string input_129_pad_type_0 = const()[name = string("input_129_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_129_strides_0 = const()[name = string("input_129_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_129_pad_0 = const()[name = string("input_129_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_129_dilations_0 = const()[name = string("input_129_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_129_groups_0 = const()[name = string("input_129_groups_0"), val = int32(1)];
            tensor<fp16, [768]> model_encoder_stages_2_5_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_2_5_pointwise_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5269824)))];
            tensor<fp16, [1, 768, 24, 32]> input_129_cast_fp16 = conv(bias = model_encoder_stages_2_5_pointwise_1_bias_to_fp16, dilations = input_129_dilations_0, groups = input_129_groups_0, pad = input_129_pad_0, pad_type = input_129_pad_type_0, strides = input_129_strides_0, weight = model_encoder_stages_2_5_pointwise_1_weight_cast_fp16, x = input_127_cast_fp16)[name = string("input_129_cast_fp16")];
            string input_131_mode_0 = const()[name = string("input_131_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 768, 24, 32]> input_131_cast_fp16 = gelu(mode = input_131_mode_0, x = input_129_cast_fp16)[name = string("input_131_cast_fp16")];
            string x_45_pad_type_0 = const()[name = string("x_45_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_45_strides_0 = const()[name = string("x_45_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_45_pad_0 = const()[name = string("x_45_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_45_dilations_0 = const()[name = string("x_45_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_45_groups_0 = const()[name = string("x_45_groups_0"), val = int32(1)];
            tensor<fp16, [192]> model_encoder_stages_2_5_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_2_5_pointwise_2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5271424)))];
            tensor<fp16, [1, 192, 24, 32]> x_45_cast_fp16 = conv(bias = model_encoder_stages_2_5_pointwise_2_bias_to_fp16, dilations = x_45_dilations_0, groups = x_45_groups_0, pad = x_45_pad_0, pad_type = x_45_pad_type_0, strides = x_45_strides_0, weight = model_encoder_stages_2_5_pointwise_2_weight_cast_fp16, x = input_131_cast_fp16)[name = string("x_45_cast_fp16")];
            tensor<fp16, [1, 192, 1, 1]> model_encoder_stages_2_5_gamma_to_fp16 = const()[name = string("model_encoder_stages_2_5_gamma_to_fp16"), val = tensor<fp16, [1, 192, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5271872)))];
            tensor<fp16, [1, 192, 24, 32]> x_47_cast_fp16 = mul(x = model_encoder_stages_2_5_gamma_to_fp16, y = x_45_cast_fp16)[name = string("x_47_cast_fp16")];
            tensor<fp16, [1, 192, 24, 32]> input_133_cast_fp16 = add(x = input_123_cast_fp16, y = x_47_cast_fp16)[name = string("input_133_cast_fp16")];
            tensor<fp16, [192]> model_encoder_norm2_running_mean_to_fp16 = const()[name = string("model_encoder_norm2_running_mean_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5272320)))];
            tensor<fp16, [192]> model_encoder_norm2_running_var_to_fp16 = const()[name = string("model_encoder_norm2_running_var_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5272768)))];
            tensor<fp16, [192]> model_encoder_norm2_weight_to_fp16 = const()[name = string("model_encoder_norm2_weight_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5273216)))];
            tensor<fp16, [192]> model_encoder_norm2_bias_to_fp16 = const()[name = string("model_encoder_norm2_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5273664)))];
            tensor<fp16, [1, 192, 24, 32]> input_175_cast_fp16 = batch_norm(beta = model_encoder_norm2_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_norm2_weight_to_fp16, mean = model_encoder_norm2_running_mean_to_fp16, variance = model_encoder_norm2_running_var_to_fp16, x = input_133_cast_fp16)[name = string("input_175_cast_fp16")];
            tensor<fp16, [192]> model_encoder_downsample_layers_3_0_weight_to_fp16 = const()[name = string("model_encoder_downsample_layers_3_0_weight_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5274112)))];
            tensor<fp16, [192]> model_encoder_downsample_layers_3_0_bias_to_fp16 = const()[name = string("model_encoder_downsample_layers_3_0_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5274560)))];
            tensor<fp16, [1, 192, 24, 32]> input_135_cast_fp16 = batch_norm(beta = model_encoder_downsample_layers_3_0_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_downsample_layers_3_0_weight_to_fp16, mean = model_encoder_norm2_running_mean_to_fp16, variance = model_encoder_norm2_running_var_to_fp16, x = input_133_cast_fp16)[name = string("input_135_cast_fp16")];
            string input_137_pad_type_0 = const()[name = string("input_137_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_137_strides_0 = const()[name = string("input_137_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> input_137_pad_0 = const()[name = string("input_137_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_137_dilations_0 = const()[name = string("input_137_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_137_groups_0 = const()[name = string("input_137_groups_0"), val = int32(1)];
            tensor<fp16, [384]> model_encoder_downsample_layers_3_1_bias_to_fp16 = const()[name = string("model_encoder_downsample_layers_3_1_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5275008)))];
            tensor<fp16, [1, 384, 12, 16]> input_137_cast_fp16 = conv(bias = model_encoder_downsample_layers_3_1_bias_to_fp16, dilations = input_137_dilations_0, groups = input_137_groups_0, pad = input_137_pad_0, pad_type = input_137_pad_type_0, strides = input_137_strides_0, weight = model_encoder_downsample_layers_3_1_weight_cast_fp16, x = input_135_cast_fp16)[name = string("input_137_cast_fp16")];
            string input_139_pad_type_0 = const()[name = string("input_139_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_139_pad_0 = const()[name = string("input_139_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_139_groups_0 = const()[name = string("input_139_groups_0"), val = int32(384)];
            tensor<int32, [2]> input_139_strides_0 = const()[name = string("input_139_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_139_dilations_0 = const()[name = string("input_139_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [384]> model_encoder_stages_3_0_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_3_0_depthwise_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5275840)))];
            tensor<fp16, [1, 384, 12, 16]> input_139_cast_fp16 = conv(bias = model_encoder_stages_3_0_depthwise_bias_to_fp16, dilations = input_139_dilations_0, groups = input_139_groups_0, pad = input_139_pad_0, pad_type = input_139_pad_type_0, strides = input_139_strides_0, weight = model_encoder_stages_3_0_depthwise_weight_cast_fp16, x = input_137_cast_fp16)[name = string("input_139_cast_fp16")];
            tensor<fp16, [384]> model_encoder_stages_3_0_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_3_0_norm_running_mean_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5276672)))];
            tensor<fp16, [384]> model_encoder_stages_3_0_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_3_0_norm_running_var_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5277504)))];
            tensor<fp16, [384]> model_encoder_stages_3_0_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_3_0_norm_weight_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5278336)))];
            tensor<fp16, [384]> model_encoder_stages_3_0_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_3_0_norm_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5279168)))];
            tensor<fp16, [1, 384, 12, 16]> input_141_cast_fp16 = batch_norm(beta = model_encoder_stages_3_0_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_3_0_norm_weight_to_fp16, mean = model_encoder_stages_3_0_norm_running_mean_to_fp16, variance = model_encoder_stages_3_0_norm_running_var_to_fp16, x = input_139_cast_fp16)[name = string("input_141_cast_fp16")];
            string input_143_pad_type_0 = const()[name = string("input_143_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_143_strides_0 = const()[name = string("input_143_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_143_pad_0 = const()[name = string("input_143_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_143_dilations_0 = const()[name = string("input_143_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_143_groups_0 = const()[name = string("input_143_groups_0"), val = int32(1)];
            tensor<fp16, [1536]> model_encoder_stages_3_0_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_3_0_pointwise_1_bias_to_fp16"), val = tensor<fp16, [1536]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5280000)))];
            tensor<fp16, [1, 1536, 12, 16]> input_143_cast_fp16 = conv(bias = model_encoder_stages_3_0_pointwise_1_bias_to_fp16, dilations = input_143_dilations_0, groups = input_143_groups_0, pad = input_143_pad_0, pad_type = input_143_pad_type_0, strides = input_143_strides_0, weight = model_encoder_stages_3_0_pointwise_1_weight_cast_fp16, x = input_141_cast_fp16)[name = string("input_143_cast_fp16")];
            string input_145_mode_0 = const()[name = string("input_145_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1536, 12, 16]> input_145_cast_fp16 = gelu(mode = input_145_mode_0, x = input_143_cast_fp16)[name = string("input_145_cast_fp16")];
            string x_49_pad_type_0 = const()[name = string("x_49_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_49_strides_0 = const()[name = string("x_49_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_49_pad_0 = const()[name = string("x_49_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_49_dilations_0 = const()[name = string("x_49_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_49_groups_0 = const()[name = string("x_49_groups_0"), val = int32(1)];
            tensor<fp16, [384]> model_encoder_stages_3_0_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_3_0_pointwise_2_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5283136)))];
            tensor<fp16, [1, 384, 12, 16]> x_49_cast_fp16 = conv(bias = model_encoder_stages_3_0_pointwise_2_bias_to_fp16, dilations = x_49_dilations_0, groups = x_49_groups_0, pad = x_49_pad_0, pad_type = x_49_pad_type_0, strides = x_49_strides_0, weight = model_encoder_stages_3_0_pointwise_2_weight_cast_fp16, x = input_145_cast_fp16)[name = string("x_49_cast_fp16")];
            tensor<fp16, [1, 384, 1, 1]> model_encoder_stages_3_0_gamma_to_fp16 = const()[name = string("model_encoder_stages_3_0_gamma_to_fp16"), val = tensor<fp16, [1, 384, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5283968)))];
            tensor<fp16, [1, 384, 12, 16]> x_51_cast_fp16 = mul(x = model_encoder_stages_3_0_gamma_to_fp16, y = x_49_cast_fp16)[name = string("x_51_cast_fp16")];
            tensor<fp16, [1, 384, 12, 16]> input_147_cast_fp16 = add(x = input_137_cast_fp16, y = x_51_cast_fp16)[name = string("input_147_cast_fp16")];
            string input_149_pad_type_0 = const()[name = string("input_149_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_149_pad_0 = const()[name = string("input_149_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_149_groups_0 = const()[name = string("input_149_groups_0"), val = int32(384)];
            tensor<int32, [2]> input_149_strides_0 = const()[name = string("input_149_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_149_dilations_0 = const()[name = string("input_149_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [384]> model_encoder_stages_3_1_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_3_1_depthwise_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5284800)))];
            tensor<fp16, [1, 384, 12, 16]> input_149_cast_fp16 = conv(bias = model_encoder_stages_3_1_depthwise_bias_to_fp16, dilations = input_149_dilations_0, groups = input_149_groups_0, pad = input_149_pad_0, pad_type = input_149_pad_type_0, strides = input_149_strides_0, weight = model_encoder_stages_3_1_depthwise_weight_cast_fp16, x = input_147_cast_fp16)[name = string("input_149_cast_fp16")];
            tensor<fp16, [384]> model_encoder_stages_3_1_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_3_1_norm_running_mean_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5285632)))];
            tensor<fp16, [384]> model_encoder_stages_3_1_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_3_1_norm_running_var_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5286464)))];
            tensor<fp16, [384]> model_encoder_stages_3_1_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_3_1_norm_weight_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5287296)))];
            tensor<fp16, [384]> model_encoder_stages_3_1_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_3_1_norm_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5288128)))];
            tensor<fp16, [1, 384, 12, 16]> input_151_cast_fp16 = batch_norm(beta = model_encoder_stages_3_1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_3_1_norm_weight_to_fp16, mean = model_encoder_stages_3_1_norm_running_mean_to_fp16, variance = model_encoder_stages_3_1_norm_running_var_to_fp16, x = input_149_cast_fp16)[name = string("input_151_cast_fp16")];
            string input_153_pad_type_0 = const()[name = string("input_153_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_153_strides_0 = const()[name = string("input_153_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_153_pad_0 = const()[name = string("input_153_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_153_dilations_0 = const()[name = string("input_153_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_153_groups_0 = const()[name = string("input_153_groups_0"), val = int32(1)];
            tensor<fp16, [1536]> model_encoder_stages_3_1_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_3_1_pointwise_1_bias_to_fp16"), val = tensor<fp16, [1536]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5288960)))];
            tensor<fp16, [1, 1536, 12, 16]> input_153_cast_fp16 = conv(bias = model_encoder_stages_3_1_pointwise_1_bias_to_fp16, dilations = input_153_dilations_0, groups = input_153_groups_0, pad = input_153_pad_0, pad_type = input_153_pad_type_0, strides = input_153_strides_0, weight = model_encoder_stages_3_1_pointwise_1_weight_cast_fp16, x = input_151_cast_fp16)[name = string("input_153_cast_fp16")];
            string input_155_mode_0 = const()[name = string("input_155_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1536, 12, 16]> input_155_cast_fp16 = gelu(mode = input_155_mode_0, x = input_153_cast_fp16)[name = string("input_155_cast_fp16")];
            string x_53_pad_type_0 = const()[name = string("x_53_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_53_strides_0 = const()[name = string("x_53_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_53_pad_0 = const()[name = string("x_53_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_53_dilations_0 = const()[name = string("x_53_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_53_groups_0 = const()[name = string("x_53_groups_0"), val = int32(1)];
            tensor<fp16, [384]> model_encoder_stages_3_1_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_3_1_pointwise_2_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5292096)))];
            tensor<fp16, [1, 384, 12, 16]> x_53_cast_fp16 = conv(bias = model_encoder_stages_3_1_pointwise_2_bias_to_fp16, dilations = x_53_dilations_0, groups = x_53_groups_0, pad = x_53_pad_0, pad_type = x_53_pad_type_0, strides = x_53_strides_0, weight = model_encoder_stages_3_1_pointwise_2_weight_cast_fp16, x = input_155_cast_fp16)[name = string("x_53_cast_fp16")];
            tensor<fp16, [1, 384, 1, 1]> model_encoder_stages_3_1_gamma_to_fp16 = const()[name = string("model_encoder_stages_3_1_gamma_to_fp16"), val = tensor<fp16, [1, 384, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5292928)))];
            tensor<fp16, [1, 384, 12, 16]> x_55_cast_fp16 = mul(x = model_encoder_stages_3_1_gamma_to_fp16, y = x_53_cast_fp16)[name = string("x_55_cast_fp16")];
            tensor<fp16, [1, 384, 12, 16]> input_157_cast_fp16 = add(x = input_147_cast_fp16, y = x_55_cast_fp16)[name = string("input_157_cast_fp16")];
            string input_159_pad_type_0 = const()[name = string("input_159_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_159_pad_0 = const()[name = string("input_159_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            int32 input_159_groups_0 = const()[name = string("input_159_groups_0"), val = int32(384)];
            tensor<int32, [2]> input_159_strides_0 = const()[name = string("input_159_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_159_dilations_0 = const()[name = string("input_159_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [384]> model_encoder_stages_3_2_depthwise_bias_to_fp16 = const()[name = string("model_encoder_stages_3_2_depthwise_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5293760)))];
            tensor<fp16, [1, 384, 12, 16]> input_159_cast_fp16 = conv(bias = model_encoder_stages_3_2_depthwise_bias_to_fp16, dilations = input_159_dilations_0, groups = input_159_groups_0, pad = input_159_pad_0, pad_type = input_159_pad_type_0, strides = input_159_strides_0, weight = model_encoder_stages_3_2_depthwise_weight_cast_fp16, x = input_157_cast_fp16)[name = string("input_159_cast_fp16")];
            tensor<fp16, [384]> model_encoder_stages_3_2_norm_running_mean_to_fp16 = const()[name = string("model_encoder_stages_3_2_norm_running_mean_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5294592)))];
            tensor<fp16, [384]> model_encoder_stages_3_2_norm_running_var_to_fp16 = const()[name = string("model_encoder_stages_3_2_norm_running_var_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5295424)))];
            tensor<fp16, [384]> model_encoder_stages_3_2_norm_weight_to_fp16 = const()[name = string("model_encoder_stages_3_2_norm_weight_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5296256)))];
            tensor<fp16, [384]> model_encoder_stages_3_2_norm_bias_to_fp16 = const()[name = string("model_encoder_stages_3_2_norm_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5297088)))];
            tensor<fp16, [1, 384, 12, 16]> input_161_cast_fp16 = batch_norm(beta = model_encoder_stages_3_2_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_stages_3_2_norm_weight_to_fp16, mean = model_encoder_stages_3_2_norm_running_mean_to_fp16, variance = model_encoder_stages_3_2_norm_running_var_to_fp16, x = input_159_cast_fp16)[name = string("input_161_cast_fp16")];
            string input_163_pad_type_0 = const()[name = string("input_163_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_163_strides_0 = const()[name = string("input_163_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_163_pad_0 = const()[name = string("input_163_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_163_dilations_0 = const()[name = string("input_163_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_163_groups_0 = const()[name = string("input_163_groups_0"), val = int32(1)];
            tensor<fp16, [1536]> model_encoder_stages_3_2_pointwise_1_bias_to_fp16 = const()[name = string("model_encoder_stages_3_2_pointwise_1_bias_to_fp16"), val = tensor<fp16, [1536]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5297920)))];
            tensor<fp16, [1, 1536, 12, 16]> input_163_cast_fp16 = conv(bias = model_encoder_stages_3_2_pointwise_1_bias_to_fp16, dilations = input_163_dilations_0, groups = input_163_groups_0, pad = input_163_pad_0, pad_type = input_163_pad_type_0, strides = input_163_strides_0, weight = model_encoder_stages_3_2_pointwise_1_weight_cast_fp16, x = input_161_cast_fp16)[name = string("input_163_cast_fp16")];
            string input_165_mode_0 = const()[name = string("input_165_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1536, 12, 16]> input_165_cast_fp16 = gelu(mode = input_165_mode_0, x = input_163_cast_fp16)[name = string("input_165_cast_fp16")];
            string x_57_pad_type_0 = const()[name = string("x_57_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_57_strides_0 = const()[name = string("x_57_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_57_pad_0 = const()[name = string("x_57_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_57_dilations_0 = const()[name = string("x_57_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_57_groups_0 = const()[name = string("x_57_groups_0"), val = int32(1)];
            tensor<fp16, [384]> model_encoder_stages_3_2_pointwise_2_bias_to_fp16 = const()[name = string("model_encoder_stages_3_2_pointwise_2_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5301056)))];
            tensor<fp16, [1, 384, 12, 16]> x_57_cast_fp16 = conv(bias = model_encoder_stages_3_2_pointwise_2_bias_to_fp16, dilations = x_57_dilations_0, groups = x_57_groups_0, pad = x_57_pad_0, pad_type = x_57_pad_type_0, strides = x_57_strides_0, weight = model_encoder_stages_3_2_pointwise_2_weight_cast_fp16, x = input_165_cast_fp16)[name = string("x_57_cast_fp16")];
            tensor<fp16, [1, 384, 1, 1]> model_encoder_stages_3_2_gamma_to_fp16 = const()[name = string("model_encoder_stages_3_2_gamma_to_fp16"), val = tensor<fp16, [1, 384, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5301888)))];
            tensor<fp16, [1, 384, 12, 16]> x_59_cast_fp16 = mul(x = model_encoder_stages_3_2_gamma_to_fp16, y = x_57_cast_fp16)[name = string("x_59_cast_fp16")];
            tensor<fp16, [1, 384, 12, 16]> input_167_cast_fp16 = add(x = input_157_cast_fp16, y = x_59_cast_fp16)[name = string("input_167_cast_fp16")];
            tensor<fp16, [384]> model_encoder_norm3_running_mean_to_fp16 = const()[name = string("model_encoder_norm3_running_mean_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5302720)))];
            tensor<fp16, [384]> model_encoder_norm3_running_var_to_fp16 = const()[name = string("model_encoder_norm3_running_var_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5303552)))];
            tensor<fp16, [384]> model_encoder_norm3_weight_to_fp16 = const()[name = string("model_encoder_norm3_weight_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5304384)))];
            tensor<fp16, [384]> model_encoder_norm3_bias_to_fp16 = const()[name = string("model_encoder_norm3_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5305216)))];
            tensor<fp16, [1, 384, 12, 16]> input_169_cast_fp16 = batch_norm(beta = model_encoder_norm3_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_encoder_norm3_weight_to_fp16, mean = model_encoder_norm3_running_mean_to_fp16, variance = model_encoder_norm3_running_var_to_fp16, x = input_167_cast_fp16)[name = string("input_169_cast_fp16")];
            string input_171_pad_type_0 = const()[name = string("input_171_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_171_strides_0 = const()[name = string("input_171_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_171_pad_0 = const()[name = string("input_171_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_171_dilations_0 = const()[name = string("input_171_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_171_groups_0 = const()[name = string("input_171_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 12, 16]> input_171_cast_fp16 = conv(dilations = input_171_dilations_0, groups = input_171_groups_0, pad = input_171_pad_0, pad_type = input_171_pad_type_0, strides = input_171_strides_0, weight = model_decoder_p5_conv_weight_cast_fp16, x = input_169_cast_fp16)[name = string("input_171_cast_fp16")];
            tensor<fp16, [128]> model_decoder_p5_norm_running_mean_to_fp16 = const()[name = string("model_decoder_p5_norm_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5306048)))];
            tensor<fp16, [128]> model_decoder_p5_norm_running_var_to_fp16 = const()[name = string("model_decoder_p5_norm_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5306368)))];
            tensor<fp16, [128]> model_decoder_p5_norm_weight_to_fp16 = const()[name = string("model_decoder_p5_norm_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5306688)))];
            tensor<fp16, [128]> model_decoder_p5_norm_bias_to_fp16 = const()[name = string("model_decoder_p5_norm_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5307008)))];
            tensor<fp16, [1, 128, 12, 16]> input_173_cast_fp16 = batch_norm(beta = model_decoder_p5_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_p5_norm_weight_to_fp16, mean = model_decoder_p5_norm_running_mean_to_fp16, variance = model_decoder_p5_norm_running_var_to_fp16, x = input_171_cast_fp16)[name = string("input_173_cast_fp16")];
            string input_181_mode_0 = const()[name = string("input_181_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 128, 12, 16]> input_181_cast_fp16 = gelu(mode = input_181_mode_0, x = input_173_cast_fp16)[name = string("input_181_cast_fp16")];
            string input_177_pad_type_0 = const()[name = string("input_177_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_177_strides_0 = const()[name = string("input_177_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_177_pad_0 = const()[name = string("input_177_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_177_dilations_0 = const()[name = string("input_177_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_177_groups_0 = const()[name = string("input_177_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 24, 32]> input_177_cast_fp16 = conv(dilations = input_177_dilations_0, groups = input_177_groups_0, pad = input_177_pad_0, pad_type = input_177_pad_type_0, strides = input_177_strides_0, weight = model_decoder_p4_skip_conv_conv_weight_cast_fp16, x = input_175_cast_fp16)[name = string("input_177_cast_fp16")];
            tensor<fp16, [128]> model_decoder_p4_skip_conv_norm_running_mean_to_fp16 = const()[name = string("model_decoder_p4_skip_conv_norm_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5307328)))];
            tensor<fp16, [128]> model_decoder_p4_skip_conv_norm_running_var_to_fp16 = const()[name = string("model_decoder_p4_skip_conv_norm_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5307648)))];
            tensor<fp16, [128]> model_decoder_p4_skip_conv_norm_weight_to_fp16 = const()[name = string("model_decoder_p4_skip_conv_norm_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5307968)))];
            tensor<fp16, [128]> model_decoder_p4_skip_conv_norm_bias_to_fp16 = const()[name = string("model_decoder_p4_skip_conv_norm_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5308288)))];
            tensor<fp16, [1, 128, 24, 32]> input_179_cast_fp16 = batch_norm(beta = model_decoder_p4_skip_conv_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_p4_skip_conv_norm_weight_to_fp16, mean = model_decoder_p4_skip_conv_norm_running_mean_to_fp16, variance = model_decoder_p4_skip_conv_norm_running_var_to_fp16, x = input_177_cast_fp16)[name = string("input_179_cast_fp16")];
            string skip_1_mode_0 = const()[name = string("skip_1_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 128, 24, 32]> skip_1_cast_fp16 = gelu(mode = skip_1_mode_0, x = input_179_cast_fp16)[name = string("skip_1_cast_fp16")];
            fp32 x_61_scale_factor_height_0 = const()[name = string("x_61_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 x_61_scale_factor_width_0 = const()[name = string("x_61_scale_factor_width_0"), val = fp32(0x1p+1)];
            tensor<fp16, [1, 128, 24, 32]> x_61_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = x_61_scale_factor_height_0, scale_factor_width = x_61_scale_factor_width_0, x = input_181_cast_fp16)[name = string("x_61_cast_fp16")];
            tensor<fp16, [1, 128, 24, 32]> input_189_cast_fp16 = add(x = x_61_cast_fp16, y = skip_1_cast_fp16)[name = string("input_189_cast_fp16")];
            string input_185_pad_type_0 = const()[name = string("input_185_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_185_strides_0 = const()[name = string("input_185_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_185_pad_0 = const()[name = string("input_185_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_185_dilations_0 = const()[name = string("input_185_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_185_groups_0 = const()[name = string("input_185_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 48, 64]> input_185_cast_fp16 = conv(dilations = input_185_dilations_0, groups = input_185_groups_0, pad = input_185_pad_0, pad_type = input_185_pad_type_0, strides = input_185_strides_0, weight = model_decoder_p3_skip_conv_conv_weight_cast_fp16, x = input_183_cast_fp16)[name = string("input_185_cast_fp16")];
            tensor<fp16, [128]> model_decoder_p3_skip_conv_norm_running_mean_to_fp16 = const()[name = string("model_decoder_p3_skip_conv_norm_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5308608)))];
            tensor<fp16, [128]> model_decoder_p3_skip_conv_norm_running_var_to_fp16 = const()[name = string("model_decoder_p3_skip_conv_norm_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5308928)))];
            tensor<fp16, [128]> model_decoder_p3_skip_conv_norm_weight_to_fp16 = const()[name = string("model_decoder_p3_skip_conv_norm_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5309248)))];
            tensor<fp16, [128]> model_decoder_p3_skip_conv_norm_bias_to_fp16 = const()[name = string("model_decoder_p3_skip_conv_norm_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5309568)))];
            tensor<fp16, [1, 128, 48, 64]> input_187_cast_fp16 = batch_norm(beta = model_decoder_p3_skip_conv_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_p3_skip_conv_norm_weight_to_fp16, mean = model_decoder_p3_skip_conv_norm_running_mean_to_fp16, variance = model_decoder_p3_skip_conv_norm_running_var_to_fp16, x = input_185_cast_fp16)[name = string("input_187_cast_fp16")];
            string skip_3_mode_0 = const()[name = string("skip_3_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 128, 48, 64]> skip_3_cast_fp16 = gelu(mode = skip_3_mode_0, x = input_187_cast_fp16)[name = string("skip_3_cast_fp16")];
            fp32 x_63_scale_factor_height_0 = const()[name = string("x_63_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 x_63_scale_factor_width_0 = const()[name = string("x_63_scale_factor_width_0"), val = fp32(0x1p+1)];
            tensor<fp16, [1, 128, 48, 64]> x_63_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = x_63_scale_factor_height_0, scale_factor_width = x_63_scale_factor_width_0, x = input_189_cast_fp16)[name = string("x_63_cast_fp16")];
            tensor<fp16, [1, 128, 48, 64]> input_197_cast_fp16 = add(x = x_63_cast_fp16, y = skip_3_cast_fp16)[name = string("input_197_cast_fp16")];
            string input_193_pad_type_0 = const()[name = string("input_193_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_193_strides_0 = const()[name = string("input_193_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_193_pad_0 = const()[name = string("input_193_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_193_dilations_0 = const()[name = string("input_193_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_193_groups_0 = const()[name = string("input_193_groups_0"), val = int32(1)];
            tensor<fp16, [1, 128, 96, 128]> input_193_cast_fp16 = conv(dilations = input_193_dilations_0, groups = input_193_groups_0, pad = input_193_pad_0, pad_type = input_193_pad_type_0, strides = input_193_strides_0, weight = model_decoder_p2_skip_conv_conv_weight_cast_fp16, x = input_191_cast_fp16)[name = string("input_193_cast_fp16")];
            tensor<fp16, [128]> model_decoder_p2_skip_conv_norm_running_mean_to_fp16 = const()[name = string("model_decoder_p2_skip_conv_norm_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5309888)))];
            tensor<fp16, [128]> model_decoder_p2_skip_conv_norm_running_var_to_fp16 = const()[name = string("model_decoder_p2_skip_conv_norm_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5310208)))];
            tensor<fp16, [128]> model_decoder_p2_skip_conv_norm_weight_to_fp16 = const()[name = string("model_decoder_p2_skip_conv_norm_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5310528)))];
            tensor<fp16, [128]> model_decoder_p2_skip_conv_norm_bias_to_fp16 = const()[name = string("model_decoder_p2_skip_conv_norm_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5310848)))];
            tensor<fp16, [1, 128, 96, 128]> input_195_cast_fp16 = batch_norm(beta = model_decoder_p2_skip_conv_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_p2_skip_conv_norm_weight_to_fp16, mean = model_decoder_p2_skip_conv_norm_running_mean_to_fp16, variance = model_decoder_p2_skip_conv_norm_running_var_to_fp16, x = input_193_cast_fp16)[name = string("input_195_cast_fp16")];
            string skip_5_mode_0 = const()[name = string("skip_5_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 128, 96, 128]> skip_5_cast_fp16 = gelu(mode = skip_5_mode_0, x = input_195_cast_fp16)[name = string("skip_5_cast_fp16")];
            fp32 x_65_scale_factor_height_0 = const()[name = string("x_65_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 x_65_scale_factor_width_0 = const()[name = string("x_65_scale_factor_width_0"), val = fp32(0x1p+1)];
            tensor<fp16, [1, 128, 96, 128]> x_65_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = x_65_scale_factor_height_0, scale_factor_width = x_65_scale_factor_width_0, x = input_197_cast_fp16)[name = string("x_65_cast_fp16")];
            tensor<fp16, [1, 128, 96, 128]> input_259_cast_fp16 = add(x = x_65_cast_fp16, y = skip_5_cast_fp16)[name = string("input_259_cast_fp16")];
            string input_199_pad_type_0 = const()[name = string("input_199_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_199_pad_0 = const()[name = string("input_199_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_199_strides_0 = const()[name = string("input_199_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_199_dilations_0 = const()[name = string("input_199_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_199_groups_0 = const()[name = string("input_199_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 12, 16]> input_199_cast_fp16 = conv(dilations = input_199_dilations_0, groups = input_199_groups_0, pad = input_199_pad_0, pad_type = input_199_pad_type_0, strides = input_199_strides_0, weight = model_decoder_s5_block_0_conv_weight_cast_fp16, x = input_181_cast_fp16)[name = string("input_199_cast_fp16")];
            tensor<fp16, [64]> model_decoder_s5_block_0_norm_running_mean_to_fp16 = const()[name = string("model_decoder_s5_block_0_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5311168)))];
            tensor<fp16, [64]> model_decoder_s5_block_0_norm_running_var_to_fp16 = const()[name = string("model_decoder_s5_block_0_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5311360)))];
            tensor<fp16, [64]> model_decoder_s5_block_0_norm_weight_to_fp16 = const()[name = string("model_decoder_s5_block_0_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5311552)))];
            tensor<fp16, [64]> model_decoder_s5_block_0_norm_bias_to_fp16 = const()[name = string("model_decoder_s5_block_0_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5311744)))];
            tensor<fp16, [1, 64, 12, 16]> input_201_cast_fp16 = batch_norm(beta = model_decoder_s5_block_0_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_s5_block_0_norm_weight_to_fp16, mean = model_decoder_s5_block_0_norm_running_mean_to_fp16, variance = model_decoder_s5_block_0_norm_running_var_to_fp16, x = input_199_cast_fp16)[name = string("input_201_cast_fp16")];
            string input_203_mode_0 = const()[name = string("input_203_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 64, 12, 16]> input_203_cast_fp16 = gelu(mode = input_203_mode_0, x = input_201_cast_fp16)[name = string("input_203_cast_fp16")];
            string input_205_pad_type_0 = const()[name = string("input_205_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_205_pad_0 = const()[name = string("input_205_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_205_strides_0 = const()[name = string("input_205_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_205_dilations_0 = const()[name = string("input_205_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_205_groups_0 = const()[name = string("input_205_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 12, 16]> input_205_cast_fp16 = conv(dilations = input_205_dilations_0, groups = input_205_groups_0, pad = input_205_pad_0, pad_type = input_205_pad_type_0, strides = input_205_strides_0, weight = model_decoder_s5_block_1_conv_weight_cast_fp16, x = input_203_cast_fp16)[name = string("input_205_cast_fp16")];
            tensor<fp16, [64]> model_decoder_s5_block_1_norm_running_mean_to_fp16 = const()[name = string("model_decoder_s5_block_1_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5311936)))];
            tensor<fp16, [64]> model_decoder_s5_block_1_norm_running_var_to_fp16 = const()[name = string("model_decoder_s5_block_1_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5312128)))];
            tensor<fp16, [64]> model_decoder_s5_block_1_norm_weight_to_fp16 = const()[name = string("model_decoder_s5_block_1_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5312320)))];
            tensor<fp16, [64]> model_decoder_s5_block_1_norm_bias_to_fp16 = const()[name = string("model_decoder_s5_block_1_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5312512)))];
            tensor<fp16, [1, 64, 12, 16]> input_207_cast_fp16 = batch_norm(beta = model_decoder_s5_block_1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_s5_block_1_norm_weight_to_fp16, mean = model_decoder_s5_block_1_norm_running_mean_to_fp16, variance = model_decoder_s5_block_1_norm_running_var_to_fp16, x = input_205_cast_fp16)[name = string("input_207_cast_fp16")];
            string input_209_mode_0 = const()[name = string("input_209_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 64, 12, 16]> input_209_cast_fp16 = gelu(mode = input_209_mode_0, x = input_207_cast_fp16)[name = string("input_209_cast_fp16")];
            fp32 input_211_scale_factor_height_0 = const()[name = string("input_211_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 input_211_scale_factor_width_0 = const()[name = string("input_211_scale_factor_width_0"), val = fp32(0x1p+1)];
            bool input_211_align_corners_0 = const()[name = string("input_211_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 64, 24, 32]> input_211_cast_fp16 = upsample_bilinear(align_corners = input_211_align_corners_0, scale_factor_height = input_211_scale_factor_height_0, scale_factor_width = input_211_scale_factor_width_0, x = input_209_cast_fp16)[name = string("input_211_cast_fp16")];
            string input_213_pad_type_0 = const()[name = string("input_213_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_213_pad_0 = const()[name = string("input_213_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_213_strides_0 = const()[name = string("input_213_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_213_dilations_0 = const()[name = string("input_213_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_213_groups_0 = const()[name = string("input_213_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 24, 32]> input_213_cast_fp16 = conv(dilations = input_213_dilations_0, groups = input_213_groups_0, pad = input_213_pad_0, pad_type = input_213_pad_type_0, strides = input_213_strides_0, weight = model_decoder_s5_block_3_conv_weight_cast_fp16, x = input_211_cast_fp16)[name = string("input_213_cast_fp16")];
            tensor<fp16, [64]> model_decoder_s5_block_3_norm_running_mean_to_fp16 = const()[name = string("model_decoder_s5_block_3_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5312704)))];
            tensor<fp16, [64]> model_decoder_s5_block_3_norm_running_var_to_fp16 = const()[name = string("model_decoder_s5_block_3_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5312896)))];
            tensor<fp16, [64]> model_decoder_s5_block_3_norm_weight_to_fp16 = const()[name = string("model_decoder_s5_block_3_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5313088)))];
            tensor<fp16, [64]> model_decoder_s5_block_3_norm_bias_to_fp16 = const()[name = string("model_decoder_s5_block_3_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5313280)))];
            tensor<fp16, [1, 64, 24, 32]> input_215_cast_fp16 = batch_norm(beta = model_decoder_s5_block_3_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_s5_block_3_norm_weight_to_fp16, mean = model_decoder_s5_block_3_norm_running_mean_to_fp16, variance = model_decoder_s5_block_3_norm_running_var_to_fp16, x = input_213_cast_fp16)[name = string("input_215_cast_fp16")];
            string input_217_mode_0 = const()[name = string("input_217_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 64, 24, 32]> input_217_cast_fp16 = gelu(mode = input_217_mode_0, x = input_215_cast_fp16)[name = string("input_217_cast_fp16")];
            fp32 input_219_scale_factor_height_0 = const()[name = string("input_219_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 input_219_scale_factor_width_0 = const()[name = string("input_219_scale_factor_width_0"), val = fp32(0x1p+1)];
            bool input_219_align_corners_0 = const()[name = string("input_219_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 64, 48, 64]> input_219_cast_fp16 = upsample_bilinear(align_corners = input_219_align_corners_0, scale_factor_height = input_219_scale_factor_height_0, scale_factor_width = input_219_scale_factor_width_0, x = input_217_cast_fp16)[name = string("input_219_cast_fp16")];
            string input_221_pad_type_0 = const()[name = string("input_221_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_221_pad_0 = const()[name = string("input_221_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_221_strides_0 = const()[name = string("input_221_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_221_dilations_0 = const()[name = string("input_221_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_221_groups_0 = const()[name = string("input_221_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 48, 64]> input_221_cast_fp16 = conv(dilations = input_221_dilations_0, groups = input_221_groups_0, pad = input_221_pad_0, pad_type = input_221_pad_type_0, strides = input_221_strides_0, weight = model_decoder_s5_block_5_conv_weight_cast_fp16, x = input_219_cast_fp16)[name = string("input_221_cast_fp16")];
            tensor<fp16, [64]> model_decoder_s5_block_5_norm_running_mean_to_fp16 = const()[name = string("model_decoder_s5_block_5_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5313472)))];
            tensor<fp16, [64]> model_decoder_s5_block_5_norm_running_var_to_fp16 = const()[name = string("model_decoder_s5_block_5_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5313664)))];
            tensor<fp16, [64]> model_decoder_s5_block_5_norm_weight_to_fp16 = const()[name = string("model_decoder_s5_block_5_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5313856)))];
            tensor<fp16, [64]> model_decoder_s5_block_5_norm_bias_to_fp16 = const()[name = string("model_decoder_s5_block_5_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5314048)))];
            tensor<fp16, [1, 64, 48, 64]> input_223_cast_fp16 = batch_norm(beta = model_decoder_s5_block_5_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_s5_block_5_norm_weight_to_fp16, mean = model_decoder_s5_block_5_norm_running_mean_to_fp16, variance = model_decoder_s5_block_5_norm_running_var_to_fp16, x = input_221_cast_fp16)[name = string("input_223_cast_fp16")];
            string input_225_mode_0 = const()[name = string("input_225_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 64, 48, 64]> input_225_cast_fp16 = gelu(mode = input_225_mode_0, x = input_223_cast_fp16)[name = string("input_225_cast_fp16")];
            fp32 var_796_scale_factor_height_0 = const()[name = string("op_796_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 var_796_scale_factor_width_0 = const()[name = string("op_796_scale_factor_width_0"), val = fp32(0x1p+1)];
            bool var_796_align_corners_0 = const()[name = string("op_796_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 64, 96, 128]> var_796_cast_fp16 = upsample_bilinear(align_corners = var_796_align_corners_0, scale_factor_height = var_796_scale_factor_height_0, scale_factor_width = var_796_scale_factor_width_0, x = input_225_cast_fp16)[name = string("op_796_cast_fp16")];
            string input_227_pad_type_0 = const()[name = string("input_227_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_227_pad_0 = const()[name = string("input_227_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_227_strides_0 = const()[name = string("input_227_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_227_dilations_0 = const()[name = string("input_227_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_227_groups_0 = const()[name = string("input_227_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 24, 32]> input_227_cast_fp16 = conv(dilations = input_227_dilations_0, groups = input_227_groups_0, pad = input_227_pad_0, pad_type = input_227_pad_type_0, strides = input_227_strides_0, weight = model_decoder_s4_block_0_conv_weight_cast_fp16, x = input_189_cast_fp16)[name = string("input_227_cast_fp16")];
            tensor<fp16, [64]> model_decoder_s4_block_0_norm_running_mean_to_fp16 = const()[name = string("model_decoder_s4_block_0_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5314240)))];
            tensor<fp16, [64]> model_decoder_s4_block_0_norm_running_var_to_fp16 = const()[name = string("model_decoder_s4_block_0_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5314432)))];
            tensor<fp16, [64]> model_decoder_s4_block_0_norm_weight_to_fp16 = const()[name = string("model_decoder_s4_block_0_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5314624)))];
            tensor<fp16, [64]> model_decoder_s4_block_0_norm_bias_to_fp16 = const()[name = string("model_decoder_s4_block_0_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5314816)))];
            tensor<fp16, [1, 64, 24, 32]> input_229_cast_fp16 = batch_norm(beta = model_decoder_s4_block_0_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_s4_block_0_norm_weight_to_fp16, mean = model_decoder_s4_block_0_norm_running_mean_to_fp16, variance = model_decoder_s4_block_0_norm_running_var_to_fp16, x = input_227_cast_fp16)[name = string("input_229_cast_fp16")];
            string input_231_mode_0 = const()[name = string("input_231_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 64, 24, 32]> input_231_cast_fp16 = gelu(mode = input_231_mode_0, x = input_229_cast_fp16)[name = string("input_231_cast_fp16")];
            string input_233_pad_type_0 = const()[name = string("input_233_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_233_pad_0 = const()[name = string("input_233_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_233_strides_0 = const()[name = string("input_233_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_233_dilations_0 = const()[name = string("input_233_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_233_groups_0 = const()[name = string("input_233_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 24, 32]> input_233_cast_fp16 = conv(dilations = input_233_dilations_0, groups = input_233_groups_0, pad = input_233_pad_0, pad_type = input_233_pad_type_0, strides = input_233_strides_0, weight = model_decoder_s4_block_1_conv_weight_cast_fp16, x = input_231_cast_fp16)[name = string("input_233_cast_fp16")];
            tensor<fp16, [64]> model_decoder_s4_block_1_norm_running_mean_to_fp16 = const()[name = string("model_decoder_s4_block_1_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5315008)))];
            tensor<fp16, [64]> model_decoder_s4_block_1_norm_running_var_to_fp16 = const()[name = string("model_decoder_s4_block_1_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5315200)))];
            tensor<fp16, [64]> model_decoder_s4_block_1_norm_weight_to_fp16 = const()[name = string("model_decoder_s4_block_1_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5315392)))];
            tensor<fp16, [64]> model_decoder_s4_block_1_norm_bias_to_fp16 = const()[name = string("model_decoder_s4_block_1_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5315584)))];
            tensor<fp16, [1, 64, 24, 32]> input_235_cast_fp16 = batch_norm(beta = model_decoder_s4_block_1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_s4_block_1_norm_weight_to_fp16, mean = model_decoder_s4_block_1_norm_running_mean_to_fp16, variance = model_decoder_s4_block_1_norm_running_var_to_fp16, x = input_233_cast_fp16)[name = string("input_235_cast_fp16")];
            string input_237_mode_0 = const()[name = string("input_237_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 64, 24, 32]> input_237_cast_fp16 = gelu(mode = input_237_mode_0, x = input_235_cast_fp16)[name = string("input_237_cast_fp16")];
            fp32 input_239_scale_factor_height_0 = const()[name = string("input_239_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 input_239_scale_factor_width_0 = const()[name = string("input_239_scale_factor_width_0"), val = fp32(0x1p+1)];
            bool input_239_align_corners_0 = const()[name = string("input_239_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 64, 48, 64]> input_239_cast_fp16 = upsample_bilinear(align_corners = input_239_align_corners_0, scale_factor_height = input_239_scale_factor_height_0, scale_factor_width = input_239_scale_factor_width_0, x = input_237_cast_fp16)[name = string("input_239_cast_fp16")];
            string input_241_pad_type_0 = const()[name = string("input_241_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_241_pad_0 = const()[name = string("input_241_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_241_strides_0 = const()[name = string("input_241_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_241_dilations_0 = const()[name = string("input_241_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_241_groups_0 = const()[name = string("input_241_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 48, 64]> input_241_cast_fp16 = conv(dilations = input_241_dilations_0, groups = input_241_groups_0, pad = input_241_pad_0, pad_type = input_241_pad_type_0, strides = input_241_strides_0, weight = model_decoder_s4_block_3_conv_weight_cast_fp16, x = input_239_cast_fp16)[name = string("input_241_cast_fp16")];
            tensor<fp16, [64]> model_decoder_s4_block_3_norm_running_mean_to_fp16 = const()[name = string("model_decoder_s4_block_3_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5315776)))];
            tensor<fp16, [64]> model_decoder_s4_block_3_norm_running_var_to_fp16 = const()[name = string("model_decoder_s4_block_3_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5315968)))];
            tensor<fp16, [64]> model_decoder_s4_block_3_norm_weight_to_fp16 = const()[name = string("model_decoder_s4_block_3_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5316160)))];
            tensor<fp16, [64]> model_decoder_s4_block_3_norm_bias_to_fp16 = const()[name = string("model_decoder_s4_block_3_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5316352)))];
            tensor<fp16, [1, 64, 48, 64]> input_243_cast_fp16 = batch_norm(beta = model_decoder_s4_block_3_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_s4_block_3_norm_weight_to_fp16, mean = model_decoder_s4_block_3_norm_running_mean_to_fp16, variance = model_decoder_s4_block_3_norm_running_var_to_fp16, x = input_241_cast_fp16)[name = string("input_243_cast_fp16")];
            string input_245_mode_0 = const()[name = string("input_245_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 64, 48, 64]> input_245_cast_fp16 = gelu(mode = input_245_mode_0, x = input_243_cast_fp16)[name = string("input_245_cast_fp16")];
            fp32 var_846_scale_factor_height_0 = const()[name = string("op_846_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 var_846_scale_factor_width_0 = const()[name = string("op_846_scale_factor_width_0"), val = fp32(0x1p+1)];
            bool var_846_align_corners_0 = const()[name = string("op_846_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 64, 96, 128]> var_846_cast_fp16 = upsample_bilinear(align_corners = var_846_align_corners_0, scale_factor_height = var_846_scale_factor_height_0, scale_factor_width = var_846_scale_factor_width_0, x = input_245_cast_fp16)[name = string("op_846_cast_fp16")];
            string input_247_pad_type_0 = const()[name = string("input_247_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_247_pad_0 = const()[name = string("input_247_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_247_strides_0 = const()[name = string("input_247_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_247_dilations_0 = const()[name = string("input_247_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_247_groups_0 = const()[name = string("input_247_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 48, 64]> input_247_cast_fp16 = conv(dilations = input_247_dilations_0, groups = input_247_groups_0, pad = input_247_pad_0, pad_type = input_247_pad_type_0, strides = input_247_strides_0, weight = model_decoder_s3_block_0_conv_weight_cast_fp16, x = input_197_cast_fp16)[name = string("input_247_cast_fp16")];
            tensor<fp16, [64]> model_decoder_s3_block_0_norm_running_mean_to_fp16 = const()[name = string("model_decoder_s3_block_0_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5316544)))];
            tensor<fp16, [64]> model_decoder_s3_block_0_norm_running_var_to_fp16 = const()[name = string("model_decoder_s3_block_0_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5316736)))];
            tensor<fp16, [64]> model_decoder_s3_block_0_norm_weight_to_fp16 = const()[name = string("model_decoder_s3_block_0_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5316928)))];
            tensor<fp16, [64]> model_decoder_s3_block_0_norm_bias_to_fp16 = const()[name = string("model_decoder_s3_block_0_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5317120)))];
            tensor<fp16, [1, 64, 48, 64]> input_249_cast_fp16 = batch_norm(beta = model_decoder_s3_block_0_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_s3_block_0_norm_weight_to_fp16, mean = model_decoder_s3_block_0_norm_running_mean_to_fp16, variance = model_decoder_s3_block_0_norm_running_var_to_fp16, x = input_247_cast_fp16)[name = string("input_249_cast_fp16")];
            string input_251_mode_0 = const()[name = string("input_251_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 64, 48, 64]> input_251_cast_fp16 = gelu(mode = input_251_mode_0, x = input_249_cast_fp16)[name = string("input_251_cast_fp16")];
            string input_253_pad_type_0 = const()[name = string("input_253_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_253_pad_0 = const()[name = string("input_253_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_253_strides_0 = const()[name = string("input_253_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_253_dilations_0 = const()[name = string("input_253_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_253_groups_0 = const()[name = string("input_253_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 48, 64]> input_253_cast_fp16 = conv(dilations = input_253_dilations_0, groups = input_253_groups_0, pad = input_253_pad_0, pad_type = input_253_pad_type_0, strides = input_253_strides_0, weight = model_decoder_s3_block_1_conv_weight_cast_fp16, x = input_251_cast_fp16)[name = string("input_253_cast_fp16")];
            tensor<fp16, [64]> model_decoder_s3_block_1_norm_running_mean_to_fp16 = const()[name = string("model_decoder_s3_block_1_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5317312)))];
            tensor<fp16, [64]> model_decoder_s3_block_1_norm_running_var_to_fp16 = const()[name = string("model_decoder_s3_block_1_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5317504)))];
            tensor<fp16, [64]> model_decoder_s3_block_1_norm_weight_to_fp16 = const()[name = string("model_decoder_s3_block_1_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5317696)))];
            tensor<fp16, [64]> model_decoder_s3_block_1_norm_bias_to_fp16 = const()[name = string("model_decoder_s3_block_1_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5317888)))];
            tensor<fp16, [1, 64, 48, 64]> input_255_cast_fp16 = batch_norm(beta = model_decoder_s3_block_1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_s3_block_1_norm_weight_to_fp16, mean = model_decoder_s3_block_1_norm_running_mean_to_fp16, variance = model_decoder_s3_block_1_norm_running_var_to_fp16, x = input_253_cast_fp16)[name = string("input_255_cast_fp16")];
            string input_257_mode_0 = const()[name = string("input_257_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 64, 48, 64]> input_257_cast_fp16 = gelu(mode = input_257_mode_0, x = input_255_cast_fp16)[name = string("input_257_cast_fp16")];
            fp32 var_879_scale_factor_height_0 = const()[name = string("op_879_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 var_879_scale_factor_width_0 = const()[name = string("op_879_scale_factor_width_0"), val = fp32(0x1p+1)];
            bool var_879_align_corners_0 = const()[name = string("op_879_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 64, 96, 128]> var_879_cast_fp16 = upsample_bilinear(align_corners = var_879_align_corners_0, scale_factor_height = var_879_scale_factor_height_0, scale_factor_width = var_879_scale_factor_width_0, x = input_257_cast_fp16)[name = string("op_879_cast_fp16")];
            string input_261_pad_type_0 = const()[name = string("input_261_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_261_pad_0 = const()[name = string("input_261_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_261_strides_0 = const()[name = string("input_261_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_261_dilations_0 = const()[name = string("input_261_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_261_groups_0 = const()[name = string("input_261_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 96, 128]> input_261_cast_fp16 = conv(dilations = input_261_dilations_0, groups = input_261_groups_0, pad = input_261_pad_0, pad_type = input_261_pad_type_0, strides = input_261_strides_0, weight = model_decoder_s2_block_0_conv_weight_cast_fp16, x = input_259_cast_fp16)[name = string("input_261_cast_fp16")];
            tensor<fp16, [64]> model_decoder_s2_block_0_norm_running_mean_to_fp16 = const()[name = string("model_decoder_s2_block_0_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5318080)))];
            tensor<fp16, [64]> model_decoder_s2_block_0_norm_running_var_to_fp16 = const()[name = string("model_decoder_s2_block_0_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5318272)))];
            tensor<fp16, [64]> model_decoder_s2_block_0_norm_weight_to_fp16 = const()[name = string("model_decoder_s2_block_0_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5318464)))];
            tensor<fp16, [64]> model_decoder_s2_block_0_norm_bias_to_fp16 = const()[name = string("model_decoder_s2_block_0_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5318656)))];
            tensor<fp16, [1, 64, 96, 128]> input_263_cast_fp16 = batch_norm(beta = model_decoder_s2_block_0_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_s2_block_0_norm_weight_to_fp16, mean = model_decoder_s2_block_0_norm_running_mean_to_fp16, variance = model_decoder_s2_block_0_norm_running_var_to_fp16, x = input_261_cast_fp16)[name = string("input_263_cast_fp16")];
            string var_895_mode_0 = const()[name = string("op_895_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 64, 96, 128]> var_895_cast_fp16 = gelu(mode = var_895_mode_0, x = input_263_cast_fp16)[name = string("op_895_cast_fp16")];
            bool input_265_interleave_0 = const()[name = string("input_265_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 256, 96, 128]> input_265_cast_fp16 = concat(axis = var_9, interleave = input_265_interleave_0, values = (var_796_cast_fp16, var_846_cast_fp16, var_879_cast_fp16, var_895_cast_fp16))[name = string("input_265_cast_fp16")];
            string input_267_pad_type_0 = const()[name = string("input_267_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_267_strides_0 = const()[name = string("input_267_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_267_pad_0 = const()[name = string("input_267_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_267_dilations_0 = const()[name = string("input_267_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_267_groups_0 = const()[name = string("input_267_groups_0"), val = int32(1)];
            tensor<fp16, [1, 64, 96, 128]> input_267_cast_fp16 = conv(dilations = input_267_dilations_0, groups = input_267_groups_0, pad = input_267_pad_0, pad_type = input_267_pad_type_0, strides = input_267_strides_0, weight = model_decoder_fpn_combine_fusion_block_0_conv_weight_cast_fp16, x = input_265_cast_fp16)[name = string("input_267_cast_fp16")];
            tensor<fp16, [64]> model_decoder_fpn_combine_fusion_block_0_norm_running_mean_to_fp16 = const()[name = string("model_decoder_fpn_combine_fusion_block_0_norm_running_mean_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5318848)))];
            tensor<fp16, [64]> model_decoder_fpn_combine_fusion_block_0_norm_running_var_to_fp16 = const()[name = string("model_decoder_fpn_combine_fusion_block_0_norm_running_var_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5319040)))];
            tensor<fp16, [64]> model_decoder_fpn_combine_fusion_block_0_norm_weight_to_fp16 = const()[name = string("model_decoder_fpn_combine_fusion_block_0_norm_weight_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5319232)))];
            tensor<fp16, [64]> model_decoder_fpn_combine_fusion_block_0_norm_bias_to_fp16 = const()[name = string("model_decoder_fpn_combine_fusion_block_0_norm_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5319424)))];
            tensor<fp16, [1, 64, 96, 128]> input_269_cast_fp16 = batch_norm(beta = model_decoder_fpn_combine_fusion_block_0_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_fpn_combine_fusion_block_0_norm_weight_to_fp16, mean = model_decoder_fpn_combine_fusion_block_0_norm_running_mean_to_fp16, variance = model_decoder_fpn_combine_fusion_block_0_norm_running_var_to_fp16, x = input_267_cast_fp16)[name = string("input_269_cast_fp16")];
            string input_271_mode_0 = const()[name = string("input_271_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 64, 96, 128]> input_271_cast_fp16 = gelu(mode = input_271_mode_0, x = input_269_cast_fp16)[name = string("input_271_cast_fp16")];
            string input_273_pad_type_0 = const()[name = string("input_273_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_273_pad_0 = const()[name = string("input_273_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_273_strides_0 = const()[name = string("input_273_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_273_dilations_0 = const()[name = string("input_273_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_273_groups_0 = const()[name = string("input_273_groups_0"), val = int32(1)];
            tensor<fp16, [1, 12, 384, 512]> input_273_cast_fp16 = conv(dilations = input_273_dilations_0, groups = input_273_groups_0, pad = input_273_pad_0, pad_type = input_273_pad_type_0, strides = input_273_strides_0, weight = model_decoder_detail_head_blocks_0_0_conv1_conv_weight_cast_fp16, x = image_to_fp16)[name = string("input_273_cast_fp16")];
            tensor<fp16, [12]> model_decoder_detail_head_blocks_0_0_conv1_norm_running_mean_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_0_0_conv1_norm_running_mean_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5319616)))];
            tensor<fp16, [12]> model_decoder_detail_head_blocks_0_0_conv1_norm_running_var_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_0_0_conv1_norm_running_var_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5319744)))];
            tensor<fp16, [12]> model_decoder_detail_head_blocks_0_0_conv1_norm_weight_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_0_0_conv1_norm_weight_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5319872)))];
            tensor<fp16, [12]> model_decoder_detail_head_blocks_0_0_conv1_norm_bias_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_0_0_conv1_norm_bias_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5320000)))];
            tensor<fp16, [1, 12, 384, 512]> input_275_cast_fp16 = batch_norm(beta = model_decoder_detail_head_blocks_0_0_conv1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_detail_head_blocks_0_0_conv1_norm_weight_to_fp16, mean = model_decoder_detail_head_blocks_0_0_conv1_norm_running_mean_to_fp16, variance = model_decoder_detail_head_blocks_0_0_conv1_norm_running_var_to_fp16, x = input_273_cast_fp16)[name = string("input_275_cast_fp16")];
            string input_277_mode_0 = const()[name = string("input_277_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 12, 384, 512]> input_277_cast_fp16 = gelu(mode = input_277_mode_0, x = input_275_cast_fp16)[name = string("input_277_cast_fp16")];
            string input_279_pad_type_0 = const()[name = string("input_279_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_279_pad_0 = const()[name = string("input_279_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_279_strides_0 = const()[name = string("input_279_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_279_dilations_0 = const()[name = string("input_279_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_279_groups_0 = const()[name = string("input_279_groups_0"), val = int32(1)];
            tensor<fp16, [1, 12, 384, 512]> input_279_cast_fp16 = conv(dilations = input_279_dilations_0, groups = input_279_groups_0, pad = input_279_pad_0, pad_type = input_279_pad_type_0, strides = input_279_strides_0, weight = model_decoder_detail_head_blocks_0_0_conv2_conv_weight_cast_fp16, x = input_277_cast_fp16)[name = string("input_279_cast_fp16")];
            tensor<fp16, [12]> model_decoder_detail_head_blocks_0_0_conv2_norm_running_mean_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_0_0_conv2_norm_running_mean_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5320128)))];
            tensor<fp16, [12]> model_decoder_detail_head_blocks_0_0_conv2_norm_running_var_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_0_0_conv2_norm_running_var_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5320256)))];
            tensor<fp16, [12]> model_decoder_detail_head_blocks_0_0_conv2_norm_weight_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_0_0_conv2_norm_weight_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5320384)))];
            tensor<fp16, [12]> model_decoder_detail_head_blocks_0_0_conv2_norm_bias_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_0_0_conv2_norm_bias_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5320512)))];
            tensor<fp16, [1, 12, 384, 512]> x_67_cast_fp16 = batch_norm(beta = model_decoder_detail_head_blocks_0_0_conv2_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_detail_head_blocks_0_0_conv2_norm_weight_to_fp16, mean = model_decoder_detail_head_blocks_0_0_conv2_norm_running_mean_to_fp16, variance = model_decoder_detail_head_blocks_0_0_conv2_norm_running_var_to_fp16, x = input_279_cast_fp16)[name = string("x_67_cast_fp16")];
            string input_281_pad_type_0 = const()[name = string("input_281_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_281_strides_0 = const()[name = string("input_281_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_281_pad_0 = const()[name = string("input_281_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_281_dilations_0 = const()[name = string("input_281_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_281_groups_0 = const()[name = string("input_281_groups_0"), val = int32(1)];
            tensor<fp16, [1, 12, 384, 512]> input_281_cast_fp16 = conv(dilations = input_281_dilations_0, groups = input_281_groups_0, pad = input_281_pad_0, pad_type = input_281_pad_type_0, strides = input_281_strides_0, weight = model_decoder_detail_head_blocks_0_0_downsample_conv_weight_cast_fp16, x = image_to_fp16)[name = string("input_281_cast_fp16")];
            tensor<fp16, [12]> model_decoder_detail_head_blocks_0_0_downsample_norm_running_mean_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_0_0_downsample_norm_running_mean_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5320640)))];
            tensor<fp16, [12]> model_decoder_detail_head_blocks_0_0_downsample_norm_running_var_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_0_0_downsample_norm_running_var_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5320768)))];
            tensor<fp16, [12]> model_decoder_detail_head_blocks_0_0_downsample_norm_weight_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_0_0_downsample_norm_weight_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5320896)))];
            tensor<fp16, [12]> model_decoder_detail_head_blocks_0_0_downsample_norm_bias_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_0_0_downsample_norm_bias_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5321024)))];
            tensor<fp16, [1, 12, 384, 512]> x_in_1_cast_fp16 = batch_norm(beta = model_decoder_detail_head_blocks_0_0_downsample_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_detail_head_blocks_0_0_downsample_norm_weight_to_fp16, mean = model_decoder_detail_head_blocks_0_0_downsample_norm_running_mean_to_fp16, variance = model_decoder_detail_head_blocks_0_0_downsample_norm_running_var_to_fp16, x = input_281_cast_fp16)[name = string("x_in_1_cast_fp16")];
            tensor<fp16, [1, 12, 384, 512]> input_283_cast_fp16 = add(x = x_67_cast_fp16, y = x_in_1_cast_fp16)[name = string("input_283_cast_fp16")];
            string input_285_mode_0 = const()[name = string("input_285_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 12, 384, 512]> input_285_cast_fp16 = gelu(mode = input_285_mode_0, x = input_283_cast_fp16)[name = string("input_285_cast_fp16")];
            tensor<int32, [2]> var_966 = const()[name = string("op_966"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_967 = const()[name = string("op_967"), val = tensor<int32, [2]>([2, 2])];
            string input_287_pad_type_0 = const()[name = string("input_287_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_287_pad_0 = const()[name = string("input_287_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            bool input_287_ceil_mode_0 = const()[name = string("input_287_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 12, 192, 256]> input_287_cast_fp16 = max_pool(ceil_mode = input_287_ceil_mode_0, kernel_sizes = var_966, pad = input_287_pad_0, pad_type = input_287_pad_type_0, strides = var_967, x = input_285_cast_fp16)[name = string("input_287_cast_fp16")];
            string input_289_pad_type_0 = const()[name = string("input_289_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_289_pad_0 = const()[name = string("input_289_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_289_strides_0 = const()[name = string("input_289_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_289_dilations_0 = const()[name = string("input_289_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_289_groups_0 = const()[name = string("input_289_groups_0"), val = int32(1)];
            tensor<fp16, [1, 24, 192, 256]> input_289_cast_fp16 = conv(dilations = input_289_dilations_0, groups = input_289_groups_0, pad = input_289_pad_0, pad_type = input_289_pad_type_0, strides = input_289_strides_0, weight = model_decoder_detail_head_blocks_1_1_conv1_conv_weight_cast_fp16, x = input_287_cast_fp16)[name = string("input_289_cast_fp16")];
            tensor<fp16, [24]> model_decoder_detail_head_blocks_1_1_conv1_norm_running_mean_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_1_1_conv1_norm_running_mean_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5321152)))];
            tensor<fp16, [24]> model_decoder_detail_head_blocks_1_1_conv1_norm_running_var_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_1_1_conv1_norm_running_var_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5321280)))];
            tensor<fp16, [24]> model_decoder_detail_head_blocks_1_1_conv1_norm_weight_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_1_1_conv1_norm_weight_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5321408)))];
            tensor<fp16, [24]> model_decoder_detail_head_blocks_1_1_conv1_norm_bias_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_1_1_conv1_norm_bias_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5321536)))];
            tensor<fp16, [1, 24, 192, 256]> input_291_cast_fp16 = batch_norm(beta = model_decoder_detail_head_blocks_1_1_conv1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_detail_head_blocks_1_1_conv1_norm_weight_to_fp16, mean = model_decoder_detail_head_blocks_1_1_conv1_norm_running_mean_to_fp16, variance = model_decoder_detail_head_blocks_1_1_conv1_norm_running_var_to_fp16, x = input_289_cast_fp16)[name = string("input_291_cast_fp16")];
            string input_293_mode_0 = const()[name = string("input_293_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 24, 192, 256]> input_293_cast_fp16 = gelu(mode = input_293_mode_0, x = input_291_cast_fp16)[name = string("input_293_cast_fp16")];
            string input_295_pad_type_0 = const()[name = string("input_295_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_295_pad_0 = const()[name = string("input_295_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_295_strides_0 = const()[name = string("input_295_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_295_dilations_0 = const()[name = string("input_295_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_295_groups_0 = const()[name = string("input_295_groups_0"), val = int32(1)];
            tensor<fp16, [1, 24, 192, 256]> input_295_cast_fp16 = conv(dilations = input_295_dilations_0, groups = input_295_groups_0, pad = input_295_pad_0, pad_type = input_295_pad_type_0, strides = input_295_strides_0, weight = model_decoder_detail_head_blocks_1_1_conv2_conv_weight_cast_fp16, x = input_293_cast_fp16)[name = string("input_295_cast_fp16")];
            tensor<fp16, [24]> model_decoder_detail_head_blocks_1_1_conv2_norm_running_mean_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_1_1_conv2_norm_running_mean_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5321664)))];
            tensor<fp16, [24]> model_decoder_detail_head_blocks_1_1_conv2_norm_running_var_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_1_1_conv2_norm_running_var_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5321792)))];
            tensor<fp16, [24]> model_decoder_detail_head_blocks_1_1_conv2_norm_weight_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_1_1_conv2_norm_weight_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5321920)))];
            tensor<fp16, [24]> model_decoder_detail_head_blocks_1_1_conv2_norm_bias_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_1_1_conv2_norm_bias_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5322048)))];
            tensor<fp16, [1, 24, 192, 256]> x_69_cast_fp16 = batch_norm(beta = model_decoder_detail_head_blocks_1_1_conv2_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_detail_head_blocks_1_1_conv2_norm_weight_to_fp16, mean = model_decoder_detail_head_blocks_1_1_conv2_norm_running_mean_to_fp16, variance = model_decoder_detail_head_blocks_1_1_conv2_norm_running_var_to_fp16, x = input_295_cast_fp16)[name = string("x_69_cast_fp16")];
            string input_297_pad_type_0 = const()[name = string("input_297_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_297_strides_0 = const()[name = string("input_297_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_297_pad_0 = const()[name = string("input_297_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_297_dilations_0 = const()[name = string("input_297_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_297_groups_0 = const()[name = string("input_297_groups_0"), val = int32(1)];
            tensor<fp16, [1, 24, 192, 256]> input_297_cast_fp16 = conv(dilations = input_297_dilations_0, groups = input_297_groups_0, pad = input_297_pad_0, pad_type = input_297_pad_type_0, strides = input_297_strides_0, weight = model_decoder_detail_head_blocks_1_1_downsample_conv_weight_cast_fp16, x = input_287_cast_fp16)[name = string("input_297_cast_fp16")];
            tensor<fp16, [24]> model_decoder_detail_head_blocks_1_1_downsample_norm_running_mean_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_1_1_downsample_norm_running_mean_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5322176)))];
            tensor<fp16, [24]> model_decoder_detail_head_blocks_1_1_downsample_norm_running_var_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_1_1_downsample_norm_running_var_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5322304)))];
            tensor<fp16, [24]> model_decoder_detail_head_blocks_1_1_downsample_norm_weight_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_1_1_downsample_norm_weight_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5322432)))];
            tensor<fp16, [24]> model_decoder_detail_head_blocks_1_1_downsample_norm_bias_to_fp16 = const()[name = string("model_decoder_detail_head_blocks_1_1_downsample_norm_bias_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5322560)))];
            tensor<fp16, [1, 24, 192, 256]> x_in_3_cast_fp16 = batch_norm(beta = model_decoder_detail_head_blocks_1_1_downsample_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_detail_head_blocks_1_1_downsample_norm_weight_to_fp16, mean = model_decoder_detail_head_blocks_1_1_downsample_norm_running_mean_to_fp16, variance = model_decoder_detail_head_blocks_1_1_downsample_norm_running_var_to_fp16, x = input_297_cast_fp16)[name = string("x_in_3_cast_fp16")];
            tensor<fp16, [1, 24, 192, 256]> input_299_cast_fp16 = add(x = x_69_cast_fp16, y = x_in_3_cast_fp16)[name = string("input_299_cast_fp16")];
            string skip_mode_0 = const()[name = string("skip_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 24, 192, 256]> skip_cast_fp16 = gelu(mode = skip_mode_0, x = input_299_cast_fp16)[name = string("skip_cast_fp16")];
            fp32 input_303_scale_factor_height_0 = const()[name = string("input_303_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 input_303_scale_factor_width_0 = const()[name = string("input_303_scale_factor_width_0"), val = fp32(0x1p+1)];
            bool input_303_align_corners_0 = const()[name = string("input_303_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 64, 192, 256]> input_303_cast_fp16 = upsample_bilinear(align_corners = input_303_align_corners_0, scale_factor_height = input_303_scale_factor_height_0, scale_factor_width = input_303_scale_factor_width_0, x = input_271_cast_fp16)[name = string("input_303_cast_fp16")];
            string input_305_pad_type_0 = const()[name = string("input_305_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_305_strides_0 = const()[name = string("input_305_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_305_pad_0 = const()[name = string("input_305_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_305_dilations_0 = const()[name = string("input_305_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_305_groups_0 = const()[name = string("input_305_groups_0"), val = int32(1)];
            tensor<fp16, [1, 24, 192, 256]> input_305_cast_fp16 = conv(dilations = input_305_dilations_0, groups = input_305_groups_0, pad = input_305_pad_0, pad_type = input_305_pad_type_0, strides = input_305_strides_0, weight = model_decoder_heads_0_blocks_0_conv1_conv_weight_cast_fp16, x = input_303_cast_fp16)[name = string("input_305_cast_fp16")];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv1_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv1_norm_running_mean_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5322688)))];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv1_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv1_norm_running_var_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5322816)))];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv1_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv1_norm_weight_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5322944)))];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv1_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv1_norm_bias_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5323072)))];
            tensor<fp16, [1, 24, 192, 256]> input_307_cast_fp16 = batch_norm(beta = model_decoder_heads_0_blocks_0_conv1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_0_blocks_0_conv1_norm_weight_to_fp16, mean = model_decoder_heads_0_blocks_0_conv1_norm_running_mean_to_fp16, variance = model_decoder_heads_0_blocks_0_conv1_norm_running_var_to_fp16, x = input_305_cast_fp16)[name = string("input_307_cast_fp16")];
            string x_71_mode_0 = const()[name = string("x_71_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 24, 192, 256]> x_71_cast_fp16 = gelu(mode = x_71_mode_0, x = input_307_cast_fp16)[name = string("x_71_cast_fp16")];
            bool input_309_interleave_0 = const()[name = string("input_309_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 48, 192, 256]> input_309_cast_fp16 = concat(axis = var_9, interleave = input_309_interleave_0, values = (x_71_cast_fp16, skip_cast_fp16))[name = string("input_309_cast_fp16")];
            string input_311_pad_type_0 = const()[name = string("input_311_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_311_pad_0 = const()[name = string("input_311_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_311_strides_0 = const()[name = string("input_311_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_311_dilations_0 = const()[name = string("input_311_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_311_groups_0 = const()[name = string("input_311_groups_0"), val = int32(1)];
            tensor<fp16, [1, 24, 192, 256]> input_311_cast_fp16 = conv(dilations = input_311_dilations_0, groups = input_311_groups_0, pad = input_311_pad_0, pad_type = input_311_pad_type_0, strides = input_311_strides_0, weight = model_decoder_heads_0_blocks_0_conv2_conv1_conv_weight_cast_fp16, x = input_309_cast_fp16)[name = string("input_311_cast_fp16")];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv2_conv1_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv2_conv1_norm_running_mean_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5323200)))];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv2_conv1_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv2_conv1_norm_running_var_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5323328)))];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv2_conv1_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv2_conv1_norm_weight_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5323456)))];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv2_conv1_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv2_conv1_norm_bias_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5323584)))];
            tensor<fp16, [1, 24, 192, 256]> input_313_cast_fp16 = batch_norm(beta = model_decoder_heads_0_blocks_0_conv2_conv1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_0_blocks_0_conv2_conv1_norm_weight_to_fp16, mean = model_decoder_heads_0_blocks_0_conv2_conv1_norm_running_mean_to_fp16, variance = model_decoder_heads_0_blocks_0_conv2_conv1_norm_running_var_to_fp16, x = input_311_cast_fp16)[name = string("input_313_cast_fp16")];
            string input_315_mode_0 = const()[name = string("input_315_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 24, 192, 256]> input_315_cast_fp16 = gelu(mode = input_315_mode_0, x = input_313_cast_fp16)[name = string("input_315_cast_fp16")];
            string input_317_pad_type_0 = const()[name = string("input_317_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_317_pad_0 = const()[name = string("input_317_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_317_strides_0 = const()[name = string("input_317_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_317_dilations_0 = const()[name = string("input_317_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_317_groups_0 = const()[name = string("input_317_groups_0"), val = int32(1)];
            tensor<fp16, [1, 24, 192, 256]> input_317_cast_fp16 = conv(dilations = input_317_dilations_0, groups = input_317_groups_0, pad = input_317_pad_0, pad_type = input_317_pad_type_0, strides = input_317_strides_0, weight = model_decoder_heads_0_blocks_0_conv2_conv2_conv_weight_cast_fp16, x = input_315_cast_fp16)[name = string("input_317_cast_fp16")];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv2_conv2_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv2_conv2_norm_running_mean_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5323712)))];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv2_conv2_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv2_conv2_norm_running_var_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5323840)))];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv2_conv2_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv2_conv2_norm_weight_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5323968)))];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv2_conv2_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv2_conv2_norm_bias_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5324096)))];
            tensor<fp16, [1, 24, 192, 256]> x_73_cast_fp16 = batch_norm(beta = model_decoder_heads_0_blocks_0_conv2_conv2_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_0_blocks_0_conv2_conv2_norm_weight_to_fp16, mean = model_decoder_heads_0_blocks_0_conv2_conv2_norm_running_mean_to_fp16, variance = model_decoder_heads_0_blocks_0_conv2_conv2_norm_running_var_to_fp16, x = input_317_cast_fp16)[name = string("x_73_cast_fp16")];
            string input_319_pad_type_0 = const()[name = string("input_319_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_319_strides_0 = const()[name = string("input_319_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_319_pad_0 = const()[name = string("input_319_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_319_dilations_0 = const()[name = string("input_319_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_319_groups_0 = const()[name = string("input_319_groups_0"), val = int32(1)];
            tensor<fp16, [1, 24, 192, 256]> input_319_cast_fp16 = conv(dilations = input_319_dilations_0, groups = input_319_groups_0, pad = input_319_pad_0, pad_type = input_319_pad_type_0, strides = input_319_strides_0, weight = model_decoder_heads_0_blocks_0_conv2_downsample_conv_weight_cast_fp16, x = input_309_cast_fp16)[name = string("input_319_cast_fp16")];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv2_downsample_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv2_downsample_norm_running_mean_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5324224)))];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv2_downsample_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv2_downsample_norm_running_var_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5324352)))];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv2_downsample_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv2_downsample_norm_weight_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5324480)))];
            tensor<fp16, [24]> model_decoder_heads_0_blocks_0_conv2_downsample_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_0_conv2_downsample_norm_bias_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5324608)))];
            tensor<fp16, [1, 24, 192, 256]> x_in_5_cast_fp16 = batch_norm(beta = model_decoder_heads_0_blocks_0_conv2_downsample_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_0_blocks_0_conv2_downsample_norm_weight_to_fp16, mean = model_decoder_heads_0_blocks_0_conv2_downsample_norm_running_mean_to_fp16, variance = model_decoder_heads_0_blocks_0_conv2_downsample_norm_running_var_to_fp16, x = input_319_cast_fp16)[name = string("x_in_5_cast_fp16")];
            tensor<fp16, [1, 24, 192, 256]> input_321_cast_fp16 = add(x = x_73_cast_fp16, y = x_in_5_cast_fp16)[name = string("input_321_cast_fp16")];
            string input_323_mode_0 = const()[name = string("input_323_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 24, 192, 256]> input_323_cast_fp16 = gelu(mode = input_323_mode_0, x = input_321_cast_fp16)[name = string("input_323_cast_fp16")];
            fp32 input_325_scale_factor_height_0 = const()[name = string("input_325_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 input_325_scale_factor_width_0 = const()[name = string("input_325_scale_factor_width_0"), val = fp32(0x1p+1)];
            bool input_325_align_corners_0 = const()[name = string("input_325_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 24, 384, 512]> input_325_cast_fp16 = upsample_bilinear(align_corners = input_325_align_corners_0, scale_factor_height = input_325_scale_factor_height_0, scale_factor_width = input_325_scale_factor_width_0, x = input_323_cast_fp16)[name = string("input_325_cast_fp16")];
            string input_327_pad_type_0 = const()[name = string("input_327_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_327_strides_0 = const()[name = string("input_327_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_327_pad_0 = const()[name = string("input_327_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_327_dilations_0 = const()[name = string("input_327_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_327_groups_0 = const()[name = string("input_327_groups_0"), val = int32(1)];
            tensor<fp16, [1, 12, 384, 512]> input_327_cast_fp16 = conv(dilations = input_327_dilations_0, groups = input_327_groups_0, pad = input_327_pad_0, pad_type = input_327_pad_type_0, strides = input_327_strides_0, weight = model_decoder_heads_0_blocks_1_conv1_conv_weight_cast_fp16, x = input_325_cast_fp16)[name = string("input_327_cast_fp16")];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv1_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv1_norm_running_mean_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5324736)))];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv1_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv1_norm_running_var_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5324864)))];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv1_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv1_norm_weight_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5324992)))];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv1_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv1_norm_bias_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5325120)))];
            tensor<fp16, [1, 12, 384, 512]> input_329_cast_fp16 = batch_norm(beta = model_decoder_heads_0_blocks_1_conv1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_0_blocks_1_conv1_norm_weight_to_fp16, mean = model_decoder_heads_0_blocks_1_conv1_norm_running_mean_to_fp16, variance = model_decoder_heads_0_blocks_1_conv1_norm_running_var_to_fp16, x = input_327_cast_fp16)[name = string("input_329_cast_fp16")];
            string x_75_mode_0 = const()[name = string("x_75_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 12, 384, 512]> x_75_cast_fp16 = gelu(mode = x_75_mode_0, x = input_329_cast_fp16)[name = string("x_75_cast_fp16")];
            bool input_331_interleave_0 = const()[name = string("input_331_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 24, 384, 512]> input_331_cast_fp16 = concat(axis = var_9, interleave = input_331_interleave_0, values = (x_75_cast_fp16, input_285_cast_fp16))[name = string("input_331_cast_fp16")];
            string input_333_pad_type_0 = const()[name = string("input_333_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_333_pad_0 = const()[name = string("input_333_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_333_strides_0 = const()[name = string("input_333_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_333_dilations_0 = const()[name = string("input_333_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_333_groups_0 = const()[name = string("input_333_groups_0"), val = int32(1)];
            tensor<fp16, [1, 12, 384, 512]> input_333_cast_fp16 = conv(dilations = input_333_dilations_0, groups = input_333_groups_0, pad = input_333_pad_0, pad_type = input_333_pad_type_0, strides = input_333_strides_0, weight = model_decoder_heads_0_blocks_1_conv2_conv1_conv_weight_cast_fp16, x = input_331_cast_fp16)[name = string("input_333_cast_fp16")];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv2_conv1_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv2_conv1_norm_running_mean_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5325248)))];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv2_conv1_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv2_conv1_norm_running_var_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5325376)))];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv2_conv1_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv2_conv1_norm_weight_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5325504)))];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv2_conv1_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv2_conv1_norm_bias_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5325632)))];
            tensor<fp16, [1, 12, 384, 512]> input_335_cast_fp16 = batch_norm(beta = model_decoder_heads_0_blocks_1_conv2_conv1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_0_blocks_1_conv2_conv1_norm_weight_to_fp16, mean = model_decoder_heads_0_blocks_1_conv2_conv1_norm_running_mean_to_fp16, variance = model_decoder_heads_0_blocks_1_conv2_conv1_norm_running_var_to_fp16, x = input_333_cast_fp16)[name = string("input_335_cast_fp16")];
            string input_337_mode_0 = const()[name = string("input_337_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 12, 384, 512]> input_337_cast_fp16 = gelu(mode = input_337_mode_0, x = input_335_cast_fp16)[name = string("input_337_cast_fp16")];
            string input_339_pad_type_0 = const()[name = string("input_339_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_339_pad_0 = const()[name = string("input_339_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_339_strides_0 = const()[name = string("input_339_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_339_dilations_0 = const()[name = string("input_339_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_339_groups_0 = const()[name = string("input_339_groups_0"), val = int32(1)];
            tensor<fp16, [1, 12, 384, 512]> input_339_cast_fp16 = conv(dilations = input_339_dilations_0, groups = input_339_groups_0, pad = input_339_pad_0, pad_type = input_339_pad_type_0, strides = input_339_strides_0, weight = model_decoder_heads_0_blocks_1_conv2_conv2_conv_weight_cast_fp16, x = input_337_cast_fp16)[name = string("input_339_cast_fp16")];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv2_conv2_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv2_conv2_norm_running_mean_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5325760)))];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv2_conv2_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv2_conv2_norm_running_var_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5325888)))];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv2_conv2_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv2_conv2_norm_weight_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5326016)))];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv2_conv2_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv2_conv2_norm_bias_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5326144)))];
            tensor<fp16, [1, 12, 384, 512]> x_77_cast_fp16 = batch_norm(beta = model_decoder_heads_0_blocks_1_conv2_conv2_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_0_blocks_1_conv2_conv2_norm_weight_to_fp16, mean = model_decoder_heads_0_blocks_1_conv2_conv2_norm_running_mean_to_fp16, variance = model_decoder_heads_0_blocks_1_conv2_conv2_norm_running_var_to_fp16, x = input_339_cast_fp16)[name = string("x_77_cast_fp16")];
            string input_341_pad_type_0 = const()[name = string("input_341_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_341_strides_0 = const()[name = string("input_341_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_341_pad_0 = const()[name = string("input_341_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_341_dilations_0 = const()[name = string("input_341_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_341_groups_0 = const()[name = string("input_341_groups_0"), val = int32(1)];
            tensor<fp16, [1, 12, 384, 512]> input_341_cast_fp16 = conv(dilations = input_341_dilations_0, groups = input_341_groups_0, pad = input_341_pad_0, pad_type = input_341_pad_type_0, strides = input_341_strides_0, weight = model_decoder_heads_0_blocks_1_conv2_downsample_conv_weight_cast_fp16, x = input_331_cast_fp16)[name = string("input_341_cast_fp16")];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv2_downsample_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv2_downsample_norm_running_mean_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5326272)))];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv2_downsample_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv2_downsample_norm_running_var_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5326400)))];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv2_downsample_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv2_downsample_norm_weight_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5326528)))];
            tensor<fp16, [12]> model_decoder_heads_0_blocks_1_conv2_downsample_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_0_blocks_1_conv2_downsample_norm_bias_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5326656)))];
            tensor<fp16, [1, 12, 384, 512]> x_in_7_cast_fp16 = batch_norm(beta = model_decoder_heads_0_blocks_1_conv2_downsample_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_0_blocks_1_conv2_downsample_norm_weight_to_fp16, mean = model_decoder_heads_0_blocks_1_conv2_downsample_norm_running_mean_to_fp16, variance = model_decoder_heads_0_blocks_1_conv2_downsample_norm_running_var_to_fp16, x = input_341_cast_fp16)[name = string("x_in_7_cast_fp16")];
            tensor<fp16, [1, 12, 384, 512]> input_343_cast_fp16 = add(x = x_77_cast_fp16, y = x_in_7_cast_fp16)[name = string("input_343_cast_fp16")];
            string input_345_mode_0 = const()[name = string("input_345_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 12, 384, 512]> input_345_cast_fp16 = gelu(mode = input_345_mode_0, x = input_343_cast_fp16)[name = string("input_345_cast_fp16")];
            string var_1160_pad_type_0 = const()[name = string("op_1160_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_1160_strides_0 = const()[name = string("op_1160_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_1160_pad_0 = const()[name = string("op_1160_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_1160_dilations_0 = const()[name = string("op_1160_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_1160_groups_0 = const()[name = string("op_1160_groups_0"), val = int32(1)];
            tensor<fp16, [6]> model_decoder_heads_0_final_layer_bias_to_fp16 = const()[name = string("model_decoder_heads_0_final_layer_bias_to_fp16"), val = tensor<fp16, [6]>([-0x1.1ep-2, -0x1.064p-3, -0x1.cc8p-2, -0x1.328p-2, -0x1.54p-2, -0x1.aacp-2])];
            tensor<fp16, [1, 6, 384, 512]> var_1160_cast_fp16 = conv(bias = model_decoder_heads_0_final_layer_bias_to_fp16, dilations = var_1160_dilations_0, groups = var_1160_groups_0, pad = var_1160_pad_0, pad_type = var_1160_pad_type_0, strides = var_1160_strides_0, weight = model_decoder_heads_0_final_layer_weight_cast_fp16, x = input_345_cast_fp16)[name = string("op_1160_cast_fp16")];
            string input_349_pad_type_0 = const()[name = string("input_349_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_349_strides_0 = const()[name = string("input_349_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_349_pad_0 = const()[name = string("input_349_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_349_dilations_0 = const()[name = string("input_349_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_349_groups_0 = const()[name = string("input_349_groups_0"), val = int32(1)];
            tensor<fp16, [1, 24, 192, 256]> input_349_cast_fp16 = conv(dilations = input_349_dilations_0, groups = input_349_groups_0, pad = input_349_pad_0, pad_type = input_349_pad_type_0, strides = input_349_strides_0, weight = model_decoder_heads_1_blocks_0_conv1_conv_weight_cast_fp16, x = input_303_cast_fp16)[name = string("input_349_cast_fp16")];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv1_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv1_norm_running_mean_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5326784)))];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv1_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv1_norm_running_var_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5326912)))];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv1_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv1_norm_weight_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5327040)))];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv1_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv1_norm_bias_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5327168)))];
            tensor<fp16, [1, 24, 192, 256]> input_351_cast_fp16 = batch_norm(beta = model_decoder_heads_1_blocks_0_conv1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_1_blocks_0_conv1_norm_weight_to_fp16, mean = model_decoder_heads_1_blocks_0_conv1_norm_running_mean_to_fp16, variance = model_decoder_heads_1_blocks_0_conv1_norm_running_var_to_fp16, x = input_349_cast_fp16)[name = string("input_351_cast_fp16")];
            string x_79_mode_0 = const()[name = string("x_79_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 24, 192, 256]> x_79_cast_fp16 = gelu(mode = x_79_mode_0, x = input_351_cast_fp16)[name = string("x_79_cast_fp16")];
            bool input_353_interleave_0 = const()[name = string("input_353_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 48, 192, 256]> input_353_cast_fp16 = concat(axis = var_9, interleave = input_353_interleave_0, values = (x_79_cast_fp16, skip_cast_fp16))[name = string("input_353_cast_fp16")];
            string input_355_pad_type_0 = const()[name = string("input_355_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_355_pad_0 = const()[name = string("input_355_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_355_strides_0 = const()[name = string("input_355_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_355_dilations_0 = const()[name = string("input_355_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_355_groups_0 = const()[name = string("input_355_groups_0"), val = int32(1)];
            tensor<fp16, [1, 24, 192, 256]> input_355_cast_fp16 = conv(dilations = input_355_dilations_0, groups = input_355_groups_0, pad = input_355_pad_0, pad_type = input_355_pad_type_0, strides = input_355_strides_0, weight = model_decoder_heads_1_blocks_0_conv2_conv1_conv_weight_cast_fp16, x = input_353_cast_fp16)[name = string("input_355_cast_fp16")];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv2_conv1_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv2_conv1_norm_running_mean_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5327296)))];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv2_conv1_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv2_conv1_norm_running_var_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5327424)))];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv2_conv1_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv2_conv1_norm_weight_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5327552)))];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv2_conv1_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv2_conv1_norm_bias_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5327680)))];
            tensor<fp16, [1, 24, 192, 256]> input_357_cast_fp16 = batch_norm(beta = model_decoder_heads_1_blocks_0_conv2_conv1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_1_blocks_0_conv2_conv1_norm_weight_to_fp16, mean = model_decoder_heads_1_blocks_0_conv2_conv1_norm_running_mean_to_fp16, variance = model_decoder_heads_1_blocks_0_conv2_conv1_norm_running_var_to_fp16, x = input_355_cast_fp16)[name = string("input_357_cast_fp16")];
            string input_359_mode_0 = const()[name = string("input_359_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 24, 192, 256]> input_359_cast_fp16 = gelu(mode = input_359_mode_0, x = input_357_cast_fp16)[name = string("input_359_cast_fp16")];
            string input_361_pad_type_0 = const()[name = string("input_361_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_361_pad_0 = const()[name = string("input_361_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_361_strides_0 = const()[name = string("input_361_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_361_dilations_0 = const()[name = string("input_361_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_361_groups_0 = const()[name = string("input_361_groups_0"), val = int32(1)];
            tensor<fp16, [1, 24, 192, 256]> input_361_cast_fp16 = conv(dilations = input_361_dilations_0, groups = input_361_groups_0, pad = input_361_pad_0, pad_type = input_361_pad_type_0, strides = input_361_strides_0, weight = model_decoder_heads_1_blocks_0_conv2_conv2_conv_weight_cast_fp16, x = input_359_cast_fp16)[name = string("input_361_cast_fp16")];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv2_conv2_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv2_conv2_norm_running_mean_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5327808)))];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv2_conv2_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv2_conv2_norm_running_var_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5327936)))];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv2_conv2_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv2_conv2_norm_weight_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5328064)))];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv2_conv2_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv2_conv2_norm_bias_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5328192)))];
            tensor<fp16, [1, 24, 192, 256]> x_81_cast_fp16 = batch_norm(beta = model_decoder_heads_1_blocks_0_conv2_conv2_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_1_blocks_0_conv2_conv2_norm_weight_to_fp16, mean = model_decoder_heads_1_blocks_0_conv2_conv2_norm_running_mean_to_fp16, variance = model_decoder_heads_1_blocks_0_conv2_conv2_norm_running_var_to_fp16, x = input_361_cast_fp16)[name = string("x_81_cast_fp16")];
            string input_363_pad_type_0 = const()[name = string("input_363_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_363_strides_0 = const()[name = string("input_363_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_363_pad_0 = const()[name = string("input_363_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_363_dilations_0 = const()[name = string("input_363_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_363_groups_0 = const()[name = string("input_363_groups_0"), val = int32(1)];
            tensor<fp16, [1, 24, 192, 256]> input_363_cast_fp16 = conv(dilations = input_363_dilations_0, groups = input_363_groups_0, pad = input_363_pad_0, pad_type = input_363_pad_type_0, strides = input_363_strides_0, weight = model_decoder_heads_1_blocks_0_conv2_downsample_conv_weight_cast_fp16, x = input_353_cast_fp16)[name = string("input_363_cast_fp16")];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv2_downsample_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv2_downsample_norm_running_mean_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5328320)))];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv2_downsample_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv2_downsample_norm_running_var_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5328448)))];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv2_downsample_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv2_downsample_norm_weight_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5328576)))];
            tensor<fp16, [24]> model_decoder_heads_1_blocks_0_conv2_downsample_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_0_conv2_downsample_norm_bias_to_fp16"), val = tensor<fp16, [24]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5328704)))];
            tensor<fp16, [1, 24, 192, 256]> x_in_9_cast_fp16 = batch_norm(beta = model_decoder_heads_1_blocks_0_conv2_downsample_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_1_blocks_0_conv2_downsample_norm_weight_to_fp16, mean = model_decoder_heads_1_blocks_0_conv2_downsample_norm_running_mean_to_fp16, variance = model_decoder_heads_1_blocks_0_conv2_downsample_norm_running_var_to_fp16, x = input_363_cast_fp16)[name = string("x_in_9_cast_fp16")];
            tensor<fp16, [1, 24, 192, 256]> input_365_cast_fp16 = add(x = x_81_cast_fp16, y = x_in_9_cast_fp16)[name = string("input_365_cast_fp16")];
            string input_367_mode_0 = const()[name = string("input_367_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 24, 192, 256]> input_367_cast_fp16 = gelu(mode = input_367_mode_0, x = input_365_cast_fp16)[name = string("input_367_cast_fp16")];
            fp32 input_369_scale_factor_height_0 = const()[name = string("input_369_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 input_369_scale_factor_width_0 = const()[name = string("input_369_scale_factor_width_0"), val = fp32(0x1p+1)];
            bool input_369_align_corners_0 = const()[name = string("input_369_align_corners_0"), val = bool(false)];
            tensor<fp16, [1, 24, 384, 512]> input_369_cast_fp16 = upsample_bilinear(align_corners = input_369_align_corners_0, scale_factor_height = input_369_scale_factor_height_0, scale_factor_width = input_369_scale_factor_width_0, x = input_367_cast_fp16)[name = string("input_369_cast_fp16")];
            string input_371_pad_type_0 = const()[name = string("input_371_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_371_strides_0 = const()[name = string("input_371_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_371_pad_0 = const()[name = string("input_371_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_371_dilations_0 = const()[name = string("input_371_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_371_groups_0 = const()[name = string("input_371_groups_0"), val = int32(1)];
            tensor<fp16, [1, 12, 384, 512]> input_371_cast_fp16 = conv(dilations = input_371_dilations_0, groups = input_371_groups_0, pad = input_371_pad_0, pad_type = input_371_pad_type_0, strides = input_371_strides_0, weight = model_decoder_heads_1_blocks_1_conv1_conv_weight_cast_fp16, x = input_369_cast_fp16)[name = string("input_371_cast_fp16")];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv1_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv1_norm_running_mean_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5328832)))];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv1_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv1_norm_running_var_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5328960)))];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv1_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv1_norm_weight_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5329088)))];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv1_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv1_norm_bias_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5329216)))];
            tensor<fp16, [1, 12, 384, 512]> input_373_cast_fp16 = batch_norm(beta = model_decoder_heads_1_blocks_1_conv1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_1_blocks_1_conv1_norm_weight_to_fp16, mean = model_decoder_heads_1_blocks_1_conv1_norm_running_mean_to_fp16, variance = model_decoder_heads_1_blocks_1_conv1_norm_running_var_to_fp16, x = input_371_cast_fp16)[name = string("input_373_cast_fp16")];
            string x_83_mode_0 = const()[name = string("x_83_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 12, 384, 512]> x_83_cast_fp16 = gelu(mode = x_83_mode_0, x = input_373_cast_fp16)[name = string("x_83_cast_fp16")];
            bool input_375_interleave_0 = const()[name = string("input_375_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 24, 384, 512]> input_375_cast_fp16 = concat(axis = var_9, interleave = input_375_interleave_0, values = (x_83_cast_fp16, input_285_cast_fp16))[name = string("input_375_cast_fp16")];
            string input_377_pad_type_0 = const()[name = string("input_377_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_377_pad_0 = const()[name = string("input_377_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_377_strides_0 = const()[name = string("input_377_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_377_dilations_0 = const()[name = string("input_377_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_377_groups_0 = const()[name = string("input_377_groups_0"), val = int32(1)];
            tensor<fp16, [1, 12, 384, 512]> input_377_cast_fp16 = conv(dilations = input_377_dilations_0, groups = input_377_groups_0, pad = input_377_pad_0, pad_type = input_377_pad_type_0, strides = input_377_strides_0, weight = model_decoder_heads_1_blocks_1_conv2_conv1_conv_weight_cast_fp16, x = input_375_cast_fp16)[name = string("input_377_cast_fp16")];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv2_conv1_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv2_conv1_norm_running_mean_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5329344)))];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv2_conv1_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv2_conv1_norm_running_var_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5329472)))];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv2_conv1_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv2_conv1_norm_weight_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5329600)))];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv2_conv1_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv2_conv1_norm_bias_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5329728)))];
            tensor<fp16, [1, 12, 384, 512]> input_379_cast_fp16 = batch_norm(beta = model_decoder_heads_1_blocks_1_conv2_conv1_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_1_blocks_1_conv2_conv1_norm_weight_to_fp16, mean = model_decoder_heads_1_blocks_1_conv2_conv1_norm_running_mean_to_fp16, variance = model_decoder_heads_1_blocks_1_conv2_conv1_norm_running_var_to_fp16, x = input_377_cast_fp16)[name = string("input_379_cast_fp16")];
            string input_381_mode_0 = const()[name = string("input_381_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 12, 384, 512]> input_381_cast_fp16 = gelu(mode = input_381_mode_0, x = input_379_cast_fp16)[name = string("input_381_cast_fp16")];
            string input_383_pad_type_0 = const()[name = string("input_383_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_383_pad_0 = const()[name = string("input_383_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_383_strides_0 = const()[name = string("input_383_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_383_dilations_0 = const()[name = string("input_383_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_383_groups_0 = const()[name = string("input_383_groups_0"), val = int32(1)];
            tensor<fp16, [1, 12, 384, 512]> input_383_cast_fp16 = conv(dilations = input_383_dilations_0, groups = input_383_groups_0, pad = input_383_pad_0, pad_type = input_383_pad_type_0, strides = input_383_strides_0, weight = model_decoder_heads_1_blocks_1_conv2_conv2_conv_weight_cast_fp16, x = input_381_cast_fp16)[name = string("input_383_cast_fp16")];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv2_conv2_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv2_conv2_norm_running_mean_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5329856)))];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv2_conv2_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv2_conv2_norm_running_var_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5329984)))];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv2_conv2_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv2_conv2_norm_weight_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5330112)))];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv2_conv2_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv2_conv2_norm_bias_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5330240)))];
            tensor<fp16, [1, 12, 384, 512]> x_85_cast_fp16 = batch_norm(beta = model_decoder_heads_1_blocks_1_conv2_conv2_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_1_blocks_1_conv2_conv2_norm_weight_to_fp16, mean = model_decoder_heads_1_blocks_1_conv2_conv2_norm_running_mean_to_fp16, variance = model_decoder_heads_1_blocks_1_conv2_conv2_norm_running_var_to_fp16, x = input_383_cast_fp16)[name = string("x_85_cast_fp16")];
            string input_385_pad_type_0 = const()[name = string("input_385_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_385_strides_0 = const()[name = string("input_385_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_385_pad_0 = const()[name = string("input_385_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_385_dilations_0 = const()[name = string("input_385_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_385_groups_0 = const()[name = string("input_385_groups_0"), val = int32(1)];
            tensor<fp16, [1, 12, 384, 512]> input_385_cast_fp16 = conv(dilations = input_385_dilations_0, groups = input_385_groups_0, pad = input_385_pad_0, pad_type = input_385_pad_type_0, strides = input_385_strides_0, weight = model_decoder_heads_1_blocks_1_conv2_downsample_conv_weight_cast_fp16, x = input_375_cast_fp16)[name = string("input_385_cast_fp16")];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv2_downsample_norm_running_mean_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv2_downsample_norm_running_mean_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5330368)))];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv2_downsample_norm_running_var_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv2_downsample_norm_running_var_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5330496)))];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv2_downsample_norm_weight_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv2_downsample_norm_weight_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5330624)))];
            tensor<fp16, [12]> model_decoder_heads_1_blocks_1_conv2_downsample_norm_bias_to_fp16 = const()[name = string("model_decoder_heads_1_blocks_1_conv2_downsample_norm_bias_to_fp16"), val = tensor<fp16, [12]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5330752)))];
            tensor<fp16, [1, 12, 384, 512]> x_in_cast_fp16 = batch_norm(beta = model_decoder_heads_1_blocks_1_conv2_downsample_norm_bias_to_fp16, epsilon = var_6_to_fp16, gamma = model_decoder_heads_1_blocks_1_conv2_downsample_norm_weight_to_fp16, mean = model_decoder_heads_1_blocks_1_conv2_downsample_norm_running_mean_to_fp16, variance = model_decoder_heads_1_blocks_1_conv2_downsample_norm_running_var_to_fp16, x = input_385_cast_fp16)[name = string("x_in_cast_fp16")];
            tensor<fp16, [1, 12, 384, 512]> input_387_cast_fp16 = add(x = x_85_cast_fp16, y = x_in_cast_fp16)[name = string("input_387_cast_fp16")];
            string input_mode_0 = const()[name = string("input_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 12, 384, 512]> input_cast_fp16 = gelu(mode = input_mode_0, x = input_387_cast_fp16)[name = string("input_cast_fp16")];
            string var_1302_pad_type_0 = const()[name = string("op_1302_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_1302_strides_0 = const()[name = string("op_1302_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_1302_pad_0 = const()[name = string("op_1302_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_1302_dilations_0 = const()[name = string("op_1302_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_1302_groups_0 = const()[name = string("op_1302_groups_0"), val = int32(1)];
            tensor<fp16, [5]> model_decoder_heads_1_final_layer_bias_to_fp16 = const()[name = string("model_decoder_heads_1_final_layer_bias_to_fp16"), val = tensor<fp16, [5]>([-0x1.038p-1, -0x1.3ep-2, -0x1.bfcp-2, -0x1.608p-2, -0x1.41p-1])];
            tensor<fp16, [1, 5, 384, 512]> var_1302_cast_fp16 = conv(bias = model_decoder_heads_1_final_layer_bias_to_fp16, dilations = var_1302_dilations_0, groups = var_1302_groups_0, pad = var_1302_pad_0, pad_type = var_1302_pad_type_0, strides = var_1302_strides_0, weight = model_decoder_heads_1_final_layer_weight_cast_fp16, x = input_cast_fp16)[name = string("op_1302_cast_fp16")];
            bool var_1304_interleave_0 = const()[name = string("op_1304_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 11, 384, 512]> var_1304_cast_fp16 = concat(axis = var_9, interleave = var_1304_interleave_0, values = (var_1160_cast_fp16, var_1302_cast_fp16))[name = string("op_1304_cast_fp16")];
            tensor<fp16, [1, 11, 384, 512]> x_87_cast_fp16 = sigmoid(x = var_1304_cast_fp16)[name = string("x_87_cast_fp16")];
            tensor<int32, [2]> var_1347 = const()[name = string("op_1347"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1351 = const()[name = string("op_1351"), val = tensor<int32, [2]>([1, 1])];
            int32 var_1352 = const()[name = string("op_1352"), val = int32(1)];
            string var_1353_pad_type_0 = const()[name = string("op_1353_pad_type_0"), val = string("same")];
            tensor<int32, [4]> var_1353_pad_0 = const()[name = string("op_1353_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1, 11, 1, 1]> kernel_1_internal_tensor_assign_1_to_fp16 = const()[name = string("kernel_1_internal_tensor_assign_1_to_fp16"), val = tensor<fp16, [1, 11, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5330880)))];
            tensor<fp16, [1, 1, 384, 512]> person = conv(dilations = var_1351, groups = var_1352, pad = var_1353_pad_0, pad_type = var_1353_pad_type_0, strides = var_1347, weight = kernel_1_internal_tensor_assign_1_to_fp16, x = x_87_cast_fp16)[name = string("op_1353_cast_fp16")];
            tensor<int32, [2]> var_1381 = const()[name = string("op_1381"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1385 = const()[name = string("op_1385"), val = tensor<int32, [2]>([1, 1])];
            int32 var_1386 = const()[name = string("op_1386"), val = int32(1)];
            string var_1387_pad_type_0 = const()[name = string("op_1387_pad_type_0"), val = string("same")];
            tensor<int32, [4]> var_1387_pad_0 = const()[name = string("op_1387_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1, 11, 1, 1]> kernel_3_internal_tensor_assign_1_to_fp16 = const()[name = string("kernel_3_internal_tensor_assign_1_to_fp16"), val = tensor<fp16, [1, 11, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5331008)))];
            tensor<fp16, [1, 1, 384, 512]> sky = conv(dilations = var_1385, groups = var_1386, pad = var_1387_pad_0, pad_type = var_1387_pad_type_0, strides = var_1381, weight = kernel_3_internal_tensor_assign_1_to_fp16, x = x_87_cast_fp16)[name = string("op_1387_cast_fp16")];
            tensor<int32, [2]> var_1415 = const()[name = string("op_1415"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1419 = const()[name = string("op_1419"), val = tensor<int32, [2]>([1, 1])];
            int32 var_1420 = const()[name = string("op_1420"), val = int32(1)];
            string var_1421_pad_type_0 = const()[name = string("op_1421_pad_type_0"), val = string("same")];
            tensor<int32, [4]> var_1421_pad_0 = const()[name = string("op_1421_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1, 11, 1, 1]> kernel_5_internal_tensor_assign_1_to_fp16 = const()[name = string("kernel_5_internal_tensor_assign_1_to_fp16"), val = tensor<fp16, [1, 11, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5331136)))];
            tensor<fp16, [1, 1, 384, 512]> foliage = conv(dilations = var_1419, groups = var_1420, pad = var_1421_pad_0, pad_type = var_1421_pad_type_0, strides = var_1415, weight = kernel_5_internal_tensor_assign_1_to_fp16, x = x_87_cast_fp16)[name = string("op_1421_cast_fp16")];
            tensor<int32, [2]> var_1449 = const()[name = string("op_1449"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1453 = const()[name = string("op_1453"), val = tensor<int32, [2]>([1, 1])];
            int32 var_1454 = const()[name = string("op_1454"), val = int32(1)];
            string var_1455_pad_type_0 = const()[name = string("op_1455_pad_type_0"), val = string("same")];
            tensor<int32, [4]> var_1455_pad_0 = const()[name = string("op_1455_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1, 11, 1, 1]> kernel_7_internal_tensor_assign_1_to_fp16 = const()[name = string("kernel_7_internal_tensor_assign_1_to_fp16"), val = tensor<fp16, [1, 11, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5331264)))];
            tensor<fp16, [1, 1, 384, 512]> water = conv(dilations = var_1453, groups = var_1454, pad = var_1455_pad_0, pad_type = var_1455_pad_type_0, strides = var_1449, weight = kernel_7_internal_tensor_assign_1_to_fp16, x = x_87_cast_fp16)[name = string("op_1455_cast_fp16")];
            tensor<int32, [2]> var_1483 = const()[name = string("op_1483"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1487 = const()[name = string("op_1487"), val = tensor<int32, [2]>([1, 1])];
            int32 var_1488 = const()[name = string("op_1488"), val = int32(1)];
            string var_1489_pad_type_0 = const()[name = string("op_1489_pad_type_0"), val = string("same")];
            tensor<int32, [4]> var_1489_pad_0 = const()[name = string("op_1489_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1, 11, 1, 1]> kernel_9_internal_tensor_assign_1_to_fp16 = const()[name = string("kernel_9_internal_tensor_assign_1_to_fp16"), val = tensor<fp16, [1, 11, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5331392)))];
            tensor<fp16, [1, 1, 384, 512]> cat = conv(dilations = var_1487, groups = var_1488, pad = var_1489_pad_0, pad_type = var_1489_pad_type_0, strides = var_1483, weight = kernel_9_internal_tensor_assign_1_to_fp16, x = x_87_cast_fp16)[name = string("op_1489_cast_fp16")];
            tensor<int32, [2]> var_1517 = const()[name = string("op_1517"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1521 = const()[name = string("op_1521"), val = tensor<int32, [2]>([1, 1])];
            int32 var_1522 = const()[name = string("op_1522"), val = int32(1)];
            string var_1523_pad_type_0 = const()[name = string("op_1523_pad_type_0"), val = string("same")];
            tensor<int32, [4]> var_1523_pad_0 = const()[name = string("op_1523_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1, 11, 1, 1]> kernel_11_internal_tensor_assign_1_to_fp16 = const()[name = string("kernel_11_internal_tensor_assign_1_to_fp16"), val = tensor<fp16, [1, 11, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5331520)))];
            tensor<fp16, [1, 1, 384, 512]> dog = conv(dilations = var_1521, groups = var_1522, pad = var_1523_pad_0, pad_type = var_1523_pad_type_0, strides = var_1517, weight = kernel_11_internal_tensor_assign_1_to_fp16, x = x_87_cast_fp16)[name = string("op_1523_cast_fp16")];
            tensor<int32, [2]> var_1551 = const()[name = string("op_1551"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1555 = const()[name = string("op_1555"), val = tensor<int32, [2]>([1, 1])];
            int32 var_1556 = const()[name = string("op_1556"), val = int32(1)];
            string var_1557_pad_type_0 = const()[name = string("op_1557_pad_type_0"), val = string("same")];
            tensor<int32, [4]> var_1557_pad_0 = const()[name = string("op_1557_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1, 11, 1, 1]> kernel_13_internal_tensor_assign_1_to_fp16 = const()[name = string("kernel_13_internal_tensor_assign_1_to_fp16"), val = tensor<fp16, [1, 11, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5331648)))];
            tensor<fp16, [1, 1, 384, 512]> hair = conv(dilations = var_1555, groups = var_1556, pad = var_1557_pad_0, pad_type = var_1557_pad_type_0, strides = var_1551, weight = kernel_13_internal_tensor_assign_1_to_fp16, x = x_87_cast_fp16)[name = string("op_1557_cast_fp16")];
            tensor<int32, [2]> var_1585 = const()[name = string("op_1585"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1589 = const()[name = string("op_1589"), val = tensor<int32, [2]>([1, 1])];
            int32 var_1590 = const()[name = string("op_1590"), val = int32(1)];
            string var_1591_pad_type_0 = const()[name = string("op_1591_pad_type_0"), val = string("same")];
            tensor<int32, [4]> var_1591_pad_0 = const()[name = string("op_1591_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1, 11, 1, 1]> kernel_15_internal_tensor_assign_1_to_fp16 = const()[name = string("kernel_15_internal_tensor_assign_1_to_fp16"), val = tensor<fp16, [1, 11, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5331776)))];
            tensor<fp16, [1, 1, 384, 512]> beard = conv(dilations = var_1589, groups = var_1590, pad = var_1591_pad_0, pad_type = var_1591_pad_type_0, strides = var_1585, weight = kernel_15_internal_tensor_assign_1_to_fp16, x = x_87_cast_fp16)[name = string("op_1591_cast_fp16")];
            tensor<int32, [2]> var_1619 = const()[name = string("op_1619"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1623 = const()[name = string("op_1623"), val = tensor<int32, [2]>([1, 1])];
            int32 var_1624 = const()[name = string("op_1624"), val = int32(1)];
            string var_1625_pad_type_0 = const()[name = string("op_1625_pad_type_0"), val = string("same")];
            tensor<int32, [4]> var_1625_pad_0 = const()[name = string("op_1625_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1, 11, 1, 1]> kernel_17_internal_tensor_assign_1_to_fp16 = const()[name = string("kernel_17_internal_tensor_assign_1_to_fp16"), val = tensor<fp16, [1, 11, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5331904)))];
            tensor<fp16, [1, 1, 384, 512]> skin = conv(dilations = var_1623, groups = var_1624, pad = var_1625_pad_0, pad_type = var_1625_pad_type_0, strides = var_1619, weight = kernel_17_internal_tensor_assign_1_to_fp16, x = x_87_cast_fp16)[name = string("op_1625_cast_fp16")];
            tensor<int32, [2]> var_1653 = const()[name = string("op_1653"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1657 = const()[name = string("op_1657"), val = tensor<int32, [2]>([1, 1])];
            int32 var_1658 = const()[name = string("op_1658"), val = int32(1)];
            string var_1659_pad_type_0 = const()[name = string("op_1659_pad_type_0"), val = string("same")];
            tensor<int32, [4]> var_1659_pad_0 = const()[name = string("op_1659_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1, 11, 1, 1]> kernel_19_internal_tensor_assign_1_to_fp16 = const()[name = string("kernel_19_internal_tensor_assign_1_to_fp16"), val = tensor<fp16, [1, 11, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5332032)))];
            tensor<fp16, [1, 1, 384, 512]> teeth = conv(dilations = var_1657, groups = var_1658, pad = var_1659_pad_0, pad_type = var_1659_pad_type_0, strides = var_1653, weight = kernel_19_internal_tensor_assign_1_to_fp16, x = x_87_cast_fp16)[name = string("op_1659_cast_fp16")];
            tensor<int32, [2]> var_1687 = const()[name = string("op_1687"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1691 = const()[name = string("op_1691"), val = tensor<int32, [2]>([1, 1])];
            int32 var_1692 = const()[name = string("op_1692"), val = int32(1)];
            string var_1693_pad_type_0 = const()[name = string("op_1693_pad_type_0"), val = string("same")];
            tensor<int32, [4]> var_1693_pad_0 = const()[name = string("op_1693_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1, 11, 1, 1]> kernel_internal_tensor_assign_1_to_fp16 = const()[name = string("kernel_internal_tensor_assign_1_to_fp16"), val = tensor<fp16, [1, 11, 1, 1]>(BLOBFILE(path = string("@model_path/weights/personsemantics-v7.H11_H12.weights_nonane"), offset = uint64(5332160)))];
            tensor<fp16, [1, 1, 384, 512]> glasses = conv(dilations = var_1691, groups = var_1692, pad = var_1693_pad_0, pad_type = var_1693_pad_type_0, strides = var_1687, weight = kernel_internal_tensor_assign_1_to_fp16, x = x_87_cast_fp16)[name = string("op_1693_cast_fp16")];
            fp16 var_1695_to_fp16 = const()[name = string("op_1695_to_fp16"), val = fp16(0x1p-1)];
            tensor<bool, [1, 11, 384, 512]> var_1696_cast_fp16 = greater(x = x_87_cast_fp16, y = var_1695_to_fp16)[name = string("op_1696_cast_fp16")];
            tensor<int32, [2]> var_1704 = const()[name = string("op_1704"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_1707 = const()[name = string("op_1707"), val = tensor<int32, [2]>([2, 2])];
            string x_93_pad_type_0 = const()[name = string("x_93_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_93_pad_0 = const()[name = string("x_93_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            bool x_93_exclude_padding_from_average_0 = const()[name = string("x_93_exclude_padding_from_average_0"), val = bool(false)];
            bool x_93_ceil_mode_0 = const()[name = string("x_93_ceil_mode_0"), val = bool(false)];
            string cast_1_to_fp16_dtype_0 = const()[name = string("cast_1_to_fp16_dtype_0"), val = string("fp16")];
            tensor<fp16, [1, 11, 384, 512]> var_1696_cast_fp16_to_fp16 = cast(dtype = cast_1_to_fp16_dtype_0, x = var_1696_cast_fp16)[name = string("cast_16")];
            tensor<fp16, [1, 11, 192, 256]> x_93_cast_fp16 = avg_pool(ceil_mode = x_93_ceil_mode_0, exclude_padding_from_average = x_93_exclude_padding_from_average_0, kernel_sizes = var_1704, pad = x_93_pad_0, pad_type = x_93_pad_type_0, strides = var_1707, x = var_1696_cast_fp16_to_fp16)[name = string("x_93_cast_fp16")];
            tensor<int32, [2]> var_1717 = const()[name = string("op_1717"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_1720 = const()[name = string("op_1720"), val = tensor<int32, [2]>([2, 2])];
            string x_95_pad_type_0 = const()[name = string("x_95_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_95_pad_0 = const()[name = string("x_95_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            bool x_95_exclude_padding_from_average_0 = const()[name = string("x_95_exclude_padding_from_average_0"), val = bool(false)];
            bool x_95_ceil_mode_0 = const()[name = string("x_95_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 11, 96, 128]> x_95_cast_fp16 = avg_pool(ceil_mode = x_95_ceil_mode_0, exclude_padding_from_average = x_95_exclude_padding_from_average_0, kernel_sizes = var_1717, pad = x_95_pad_0, pad_type = x_95_pad_type_0, strides = var_1720, x = x_93_cast_fp16)[name = string("x_95_cast_fp16")];
            tensor<int32, [2]> var_1730 = const()[name = string("op_1730"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_1733 = const()[name = string("op_1733"), val = tensor<int32, [2]>([2, 2])];
            string x_97_pad_type_0 = const()[name = string("x_97_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_97_pad_0 = const()[name = string("x_97_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            bool x_97_exclude_padding_from_average_0 = const()[name = string("x_97_exclude_padding_from_average_0"), val = bool(false)];
            bool x_97_ceil_mode_0 = const()[name = string("x_97_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 11, 48, 64]> x_97_cast_fp16 = avg_pool(ceil_mode = x_97_ceil_mode_0, exclude_padding_from_average = x_97_exclude_padding_from_average_0, kernel_sizes = var_1730, pad = x_97_pad_0, pad_type = x_97_pad_type_0, strides = var_1733, x = x_95_cast_fp16)[name = string("x_97_cast_fp16")];
            tensor<int32, [2]> var_1743 = const()[name = string("op_1743"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_1746 = const()[name = string("op_1746"), val = tensor<int32, [2]>([2, 2])];
            string x_99_pad_type_0 = const()[name = string("x_99_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_99_pad_0 = const()[name = string("x_99_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            bool x_99_exclude_padding_from_average_0 = const()[name = string("x_99_exclude_padding_from_average_0"), val = bool(false)];
            bool x_99_ceil_mode_0 = const()[name = string("x_99_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 11, 24, 32]> x_99_cast_fp16 = avg_pool(ceil_mode = x_99_ceil_mode_0, exclude_padding_from_average = x_99_exclude_padding_from_average_0, kernel_sizes = var_1743, pad = x_99_pad_0, pad_type = x_99_pad_type_0, strides = var_1746, x = x_97_cast_fp16)[name = string("x_99_cast_fp16")];
            tensor<int32, [2]> var_1756 = const()[name = string("op_1756"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_1759 = const()[name = string("op_1759"), val = tensor<int32, [2]>([2, 2])];
            string x_101_pad_type_0 = const()[name = string("x_101_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_101_pad_0 = const()[name = string("x_101_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            bool x_101_exclude_padding_from_average_0 = const()[name = string("x_101_exclude_padding_from_average_0"), val = bool(false)];
            bool x_101_ceil_mode_0 = const()[name = string("x_101_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 11, 12, 16]> x_101_cast_fp16 = avg_pool(ceil_mode = x_101_ceil_mode_0, exclude_padding_from_average = x_101_exclude_padding_from_average_0, kernel_sizes = var_1756, pad = x_101_pad_0, pad_type = x_101_pad_type_0, strides = var_1759, x = x_99_cast_fp16)[name = string("x_101_cast_fp16")];
            tensor<int32, [2]> var_1769 = const()[name = string("op_1769"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_1772 = const()[name = string("op_1772"), val = tensor<int32, [2]>([2, 2])];
            string x_pad_type_0 = const()[name = string("x_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> x_pad_0 = const()[name = string("x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            bool x_exclude_padding_from_average_0 = const()[name = string("x_exclude_padding_from_average_0"), val = bool(false)];
            bool x_ceil_mode_0 = const()[name = string("x_ceil_mode_0"), val = bool(false)];
            tensor<fp16, [1, 11, 6, 8]> x_cast_fp16 = avg_pool(ceil_mode = x_ceil_mode_0, exclude_padding_from_average = x_exclude_padding_from_average_0, kernel_sizes = var_1769, pad = x_pad_0, pad_type = x_pad_type_0, strides = var_1772, x = x_101_cast_fp16)[name = string("x_cast_fp16")];
            tensor<int32, [2]> _inversed_1793_axes_0 = const()[name = string("_inversed_1793_axes_0"), val = tensor<int32, [2]>([2, 3])];
            bool _inversed_1793_keep_dims_0 = const()[name = string("_inversed_1793_keep_dims_0"), val = bool(false)];
            
            tensor<fp16, [1, 11]> class_area_tensor = reduce_mean(axes = _inversed_1793_axes_0, keep_dims = _inversed_1793_keep_dims_0, x = x_cast_fp16)[name = string("_inversed_1793_cast_fp16")];
            tensor_buffer<fp16, shape=[1, 11], strides=[32, 1], interleave_factors=[1, 1]> class_area = tensor_to_tensor_buffer(input = class_area_tensor, interleave_factors = tensor<uint8, [2]>([1, 1]), strides = tensor<int64, [2]>([32, 1]));
        } -> (beard, cat, class_area, dog, foliage, glasses, hair, person, skin, sky, teeth, water);
}