CoreMLModels/ImageEncoder_mobileCLIP_s2.mlmodelc/model.mil

program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "1.13.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})]
{
    func main<ios16>(tensor<fp32, [1, 3, 256, 256]> colorImage) {
            tensor<fp32, []> colorImage__scaled___y_0 = const()[name = tensor<string, []>("colorImage__scaled___y_0"), val = tensor<fp32, []>(0x1.010102p-8)];
            tensor<fp32, [1, 3, 256, 256]> colorImage__scaled__ = mul(x = colorImage, y = colorImage__scaled___y_0)[name = tensor<string, []>("colorImage__scaled__")];
            tensor<int32, []> var_4 = const()[name = tensor<string, []>("op_4"), val = tensor<int32, []>(80)];
            tensor<bool, []> var_5 = const()[name = tensor<string, []>("op_5"), val = tensor<bool, []>(true)];
            tensor<bool, []> var_7 = const()[name = tensor<string, []>("op_7"), val = tensor<bool, []>(false)];
            tensor<int32, []> var_8 = const()[name = tensor<string, []>("op_8"), val = tensor<int32, []>(1)];
            tensor<int32, []> var_16 = const()[name = tensor<string, []>("op_16"), val = tensor<int32, []>(160)];
            tensor<int32, []> var_17 = const()[name = tensor<string, []>("op_17"), val = tensor<int32, []>(320)];
            tensor<int32, []> var_18 = const()[name = tensor<string, []>("op_18"), val = tensor<int32, []>(640)];
            tensor<int32, []> var_23 = const()[name = tensor<string, []>("op_23"), val = tensor<int32, []>(-1)];
            tensor<int32, [2]> var_50 = const()[name = tensor<string, []>("op_50"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_52 = const()[name = tensor<string, []>("op_52"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_1_pad_type_0 = const()[name = tensor<string, []>("input_1_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_1_pad_0 = const()[name = tensor<string, []>("input_1_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<string, []> colorImage_to_fp16_dtype_0 = const()[name = tensor<string, []>("colorImage_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, [80, 3, 3, 3]> original_model_image_encoder_model_patch_embed_0_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_patch_embed_0_reparam_conv_weight_to_fp16"), val = tensor<fp16, [80, 3, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
            tensor<fp16, [80]> original_model_image_encoder_model_patch_embed_0_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_patch_embed_0_reparam_conv_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4480)))];
            tensor<fp16, [1, 3, 256, 256]> cast_18 = cast(dtype = colorImage_to_fp16_dtype_0, x = colorImage__scaled__)[name = tensor<string, []>("cast_18")];
            tensor<fp16, [1, 80, 128, 128]> input_1_cast_fp16 = conv(bias = original_model_image_encoder_model_patch_embed_0_reparam_conv_bias_to_fp16, dilations = var_52, groups = var_8, pad = input_1_pad_0, pad_type = input_1_pad_type_0, strides = var_50, weight = original_model_image_encoder_model_patch_embed_0_reparam_conv_weight_to_fp16, x = cast_18)[name = tensor<string, []>("input_1_cast_fp16")];
            tensor<string, []> input_3_mode_0 = const()[name = tensor<string, []>("input_3_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 80, 128, 128]> input_3_cast_fp16 = gelu(mode = input_3_mode_0, x = input_1_cast_fp16)[name = tensor<string, []>("input_3_cast_fp16")];
            tensor<int32, [2]> var_59 = const()[name = tensor<string, []>("op_59"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_61 = const()[name = tensor<string, []>("op_61"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_5_pad_type_0 = const()[name = tensor<string, []>("input_5_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_5_pad_0 = const()[name = tensor<string, []>("input_5_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [80, 1, 3, 3]> original_model_image_encoder_model_patch_embed_1_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_patch_embed_1_reparam_conv_weight_to_fp16"), val = tensor<fp16, [80, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4736)))];
            tensor<fp16, [80]> original_model_image_encoder_model_patch_embed_1_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_patch_embed_1_reparam_conv_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6272)))];
            tensor<fp16, [1, 80, 64, 64]> input_5_cast_fp16 = conv(bias = original_model_image_encoder_model_patch_embed_1_reparam_conv_bias_to_fp16, dilations = var_61, groups = var_4, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = var_59, weight = original_model_image_encoder_model_patch_embed_1_reparam_conv_weight_to_fp16, x = input_3_cast_fp16)[name = tensor<string, []>("input_5_cast_fp16")];
            tensor<string, []> input_7_mode_0 = const()[name = tensor<string, []>("input_7_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 80, 64, 64]> input_7_cast_fp16 = gelu(mode = input_7_mode_0, x = input_5_cast_fp16)[name = tensor<string, []>("input_7_cast_fp16")];
            tensor<int32, [2]> var_68 = const()[name = tensor<string, []>("op_68"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_70 = const()[name = tensor<string, []>("op_70"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_9_pad_type_0 = const()[name = tensor<string, []>("input_9_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_9_pad_0 = const()[name = tensor<string, []>("input_9_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [80, 80, 1, 1]> original_model_image_encoder_model_patch_embed_2_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_patch_embed_2_reparam_conv_weight_to_fp16"), val = tensor<fp16, [80, 80, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6528)))];
            tensor<fp16, [80]> original_model_image_encoder_model_patch_embed_2_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_patch_embed_2_reparam_conv_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19392)))];
            tensor<fp16, [1, 80, 64, 64]> input_9_cast_fp16 = conv(bias = original_model_image_encoder_model_patch_embed_2_reparam_conv_bias_to_fp16, dilations = var_70, groups = var_8, pad = input_9_pad_0, pad_type = input_9_pad_type_0, strides = var_68, weight = original_model_image_encoder_model_patch_embed_2_reparam_conv_weight_to_fp16, x = input_7_cast_fp16)[name = tensor<string, []>("input_9_cast_fp16")];
            tensor<string, []> input_11_mode_0 = const()[name = tensor<string, []>("input_11_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 80, 64, 64]> input_11_cast_fp16 = gelu(mode = input_11_mode_0, x = input_9_cast_fp16)[name = tensor<string, []>("input_11_cast_fp16")];
            tensor<int32, [2]> var_84 = const()[name = tensor<string, []>("op_84"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_86 = const()[name = tensor<string, []>("op_86"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_13_pad_type_0 = const()[name = tensor<string, []>("input_13_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_13_pad_0 = const()[name = tensor<string, []>("input_13_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [80, 1, 3, 3]> original_model_image_encoder_model_network_0_0_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_0_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [80, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19648)))];
            tensor<fp16, [80]> original_model_image_encoder_model_network_0_0_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_0_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21184)))];
            tensor<fp16, [1, 80, 64, 64]> input_13_cast_fp16 = conv(bias = original_model_image_encoder_model_network_0_0_token_mixer_reparam_conv_bias_to_fp16, dilations = var_86, groups = var_4, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = var_84, weight = original_model_image_encoder_model_network_0_0_token_mixer_reparam_conv_weight_to_fp16, x = input_11_cast_fp16)[name = tensor<string, []>("input_13_cast_fp16")];
            tensor<int32, [2]> var_95 = const()[name = tensor<string, []>("op_95"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_97 = const()[name = tensor<string, []>("op_97"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_15_pad_type_0 = const()[name = tensor<string, []>("input_15_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_15_pad_0 = const()[name = tensor<string, []>("input_15_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [80, 1, 7, 7]> input_17_weight_0_to_fp16 = const()[name = tensor<string, []>("input_17_weight_0_to_fp16"), val = tensor<fp16, [80, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21440)))];
            tensor<fp16, [80]> input_17_bias_0_to_fp16 = const()[name = tensor<string, []>("input_17_bias_0_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29376)))];
            tensor<fp16, [1, 80, 64, 64]> input_17_cast_fp16 = conv(bias = input_17_bias_0_to_fp16, dilations = var_97, groups = var_4, pad = input_15_pad_0, pad_type = input_15_pad_type_0, strides = var_95, weight = input_17_weight_0_to_fp16, x = input_13_cast_fp16)[name = tensor<string, []>("input_17_cast_fp16")];
            tensor<int32, [2]> var_107 = const()[name = tensor<string, []>("op_107"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_109 = const()[name = tensor<string, []>("op_109"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_19_pad_type_0 = const()[name = tensor<string, []>("input_19_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_19_pad_0 = const()[name = tensor<string, []>("input_19_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [240, 80, 1, 1]> original_model_image_encoder_model_network_0_0_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_0_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [240, 80, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29632)))];
            tensor<fp16, [240]> original_model_image_encoder_model_network_0_0_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_0_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [240]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(68096)))];
            tensor<fp16, [1, 240, 64, 64]> input_19_cast_fp16 = conv(bias = original_model_image_encoder_model_network_0_0_convffn_fc1_bias_to_fp16, dilations = var_109, groups = var_8, pad = input_19_pad_0, pad_type = input_19_pad_type_0, strides = var_107, weight = original_model_image_encoder_model_network_0_0_convffn_fc1_weight_to_fp16, x = input_17_cast_fp16)[name = tensor<string, []>("input_19_cast_fp16")];
            tensor<string, []> input_21_mode_0 = const()[name = tensor<string, []>("input_21_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 240, 64, 64]> input_21_cast_fp16 = gelu(mode = input_21_mode_0, x = input_19_cast_fp16)[name = tensor<string, []>("input_21_cast_fp16")];
            tensor<int32, [2]> var_116 = const()[name = tensor<string, []>("op_116"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_118 = const()[name = tensor<string, []>("op_118"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_25_pad_type_0 = const()[name = tensor<string, []>("input_25_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_25_pad_0 = const()[name = tensor<string, []>("input_25_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [80, 240, 1, 1]> var_122_weight_0_to_fp16 = const()[name = tensor<string, []>("op_122_weight_0_to_fp16"), val = tensor<fp16, [80, 240, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(68672)))];
            tensor<fp16, [80]> var_122_bias_0_to_fp16 = const()[name = tensor<string, []>("op_122_bias_0_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107136)))];
            tensor<fp16, [1, 80, 64, 64]> var_122_cast_fp16 = conv(bias = var_122_bias_0_to_fp16, dilations = var_118, groups = var_8, pad = input_25_pad_0, pad_type = input_25_pad_type_0, strides = var_116, weight = var_122_weight_0_to_fp16, x = input_21_cast_fp16)[name = tensor<string, []>("op_122_cast_fp16")];
            tensor<fp16, [1, 80, 64, 64]> input_27_cast_fp16 = add(x = input_13_cast_fp16, y = var_122_cast_fp16)[name = tensor<string, []>("input_27_cast_fp16")];
            tensor<int32, [2]> var_130 = const()[name = tensor<string, []>("op_130"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_132 = const()[name = tensor<string, []>("op_132"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_29_pad_type_0 = const()[name = tensor<string, []>("input_29_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_29_pad_0 = const()[name = tensor<string, []>("input_29_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [80, 1, 3, 3]> original_model_image_encoder_model_network_0_1_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_1_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [80, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107392)))];
            tensor<fp16, [80]> original_model_image_encoder_model_network_0_1_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_1_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(108928)))];
            tensor<fp16, [1, 80, 64, 64]> input_29_cast_fp16 = conv(bias = original_model_image_encoder_model_network_0_1_token_mixer_reparam_conv_bias_to_fp16, dilations = var_132, groups = var_4, pad = input_29_pad_0, pad_type = input_29_pad_type_0, strides = var_130, weight = original_model_image_encoder_model_network_0_1_token_mixer_reparam_conv_weight_to_fp16, x = input_27_cast_fp16)[name = tensor<string, []>("input_29_cast_fp16")];
            tensor<int32, [2]> var_141 = const()[name = tensor<string, []>("op_141"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_143 = const()[name = tensor<string, []>("op_143"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_31_pad_type_0 = const()[name = tensor<string, []>("input_31_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_31_pad_0 = const()[name = tensor<string, []>("input_31_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [80, 1, 7, 7]> input_33_weight_0_to_fp16 = const()[name = tensor<string, []>("input_33_weight_0_to_fp16"), val = tensor<fp16, [80, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(109184)))];
            tensor<fp16, [80]> input_33_bias_0_to_fp16 = const()[name = tensor<string, []>("input_33_bias_0_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(117120)))];
            tensor<fp16, [1, 80, 64, 64]> input_33_cast_fp16 = conv(bias = input_33_bias_0_to_fp16, dilations = var_143, groups = var_4, pad = input_31_pad_0, pad_type = input_31_pad_type_0, strides = var_141, weight = input_33_weight_0_to_fp16, x = input_29_cast_fp16)[name = tensor<string, []>("input_33_cast_fp16")];
            tensor<int32, [2]> var_153 = const()[name = tensor<string, []>("op_153"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_155 = const()[name = tensor<string, []>("op_155"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_35_pad_type_0 = const()[name = tensor<string, []>("input_35_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_35_pad_0 = const()[name = tensor<string, []>("input_35_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [240, 80, 1, 1]> original_model_image_encoder_model_network_0_1_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_1_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [240, 80, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(117376)))];
            tensor<fp16, [240]> original_model_image_encoder_model_network_0_1_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_1_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [240]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155840)))];
            tensor<fp16, [1, 240, 64, 64]> input_35_cast_fp16 = conv(bias = original_model_image_encoder_model_network_0_1_convffn_fc1_bias_to_fp16, dilations = var_155, groups = var_8, pad = input_35_pad_0, pad_type = input_35_pad_type_0, strides = var_153, weight = original_model_image_encoder_model_network_0_1_convffn_fc1_weight_to_fp16, x = input_33_cast_fp16)[name = tensor<string, []>("input_35_cast_fp16")];
            tensor<string, []> input_37_mode_0 = const()[name = tensor<string, []>("input_37_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 240, 64, 64]> input_37_cast_fp16 = gelu(mode = input_37_mode_0, x = input_35_cast_fp16)[name = tensor<string, []>("input_37_cast_fp16")];
            tensor<int32, [2]> var_162 = const()[name = tensor<string, []>("op_162"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_164 = const()[name = tensor<string, []>("op_164"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_41_pad_type_0 = const()[name = tensor<string, []>("input_41_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_41_pad_0 = const()[name = tensor<string, []>("input_41_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [80, 240, 1, 1]> var_168_weight_0_to_fp16 = const()[name = tensor<string, []>("op_168_weight_0_to_fp16"), val = tensor<fp16, [80, 240, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(156416)))];
            tensor<fp16, [80]> var_168_bias_0_to_fp16 = const()[name = tensor<string, []>("op_168_bias_0_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(194880)))];
            tensor<fp16, [1, 80, 64, 64]> var_168_cast_fp16 = conv(bias = var_168_bias_0_to_fp16, dilations = var_164, groups = var_8, pad = input_41_pad_0, pad_type = input_41_pad_type_0, strides = var_162, weight = var_168_weight_0_to_fp16, x = input_37_cast_fp16)[name = tensor<string, []>("op_168_cast_fp16")];
            tensor<fp16, [1, 80, 64, 64]> input_43_cast_fp16 = add(x = input_29_cast_fp16, y = var_168_cast_fp16)[name = tensor<string, []>("input_43_cast_fp16")];
            tensor<int32, [2]> var_176 = const()[name = tensor<string, []>("op_176"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_178 = const()[name = tensor<string, []>("op_178"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_45_pad_type_0 = const()[name = tensor<string, []>("input_45_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_45_pad_0 = const()[name = tensor<string, []>("input_45_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [80, 1, 3, 3]> original_model_image_encoder_model_network_0_2_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_2_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [80, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195136)))];
            tensor<fp16, [80]> original_model_image_encoder_model_network_0_2_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_2_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196672)))];
            tensor<fp16, [1, 80, 64, 64]> input_45_cast_fp16 = conv(bias = original_model_image_encoder_model_network_0_2_token_mixer_reparam_conv_bias_to_fp16, dilations = var_178, groups = var_4, pad = input_45_pad_0, pad_type = input_45_pad_type_0, strides = var_176, weight = original_model_image_encoder_model_network_0_2_token_mixer_reparam_conv_weight_to_fp16, x = input_43_cast_fp16)[name = tensor<string, []>("input_45_cast_fp16")];
            tensor<int32, [2]> var_187 = const()[name = tensor<string, []>("op_187"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_189 = const()[name = tensor<string, []>("op_189"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_47_pad_type_0 = const()[name = tensor<string, []>("input_47_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_47_pad_0 = const()[name = tensor<string, []>("input_47_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [80, 1, 7, 7]> input_49_weight_0_to_fp16 = const()[name = tensor<string, []>("input_49_weight_0_to_fp16"), val = tensor<fp16, [80, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196928)))];
            tensor<fp16, [80]> input_49_bias_0_to_fp16 = const()[name = tensor<string, []>("input_49_bias_0_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(204864)))];
            tensor<fp16, [1, 80, 64, 64]> input_49_cast_fp16 = conv(bias = input_49_bias_0_to_fp16, dilations = var_189, groups = var_4, pad = input_47_pad_0, pad_type = input_47_pad_type_0, strides = var_187, weight = input_49_weight_0_to_fp16, x = input_45_cast_fp16)[name = tensor<string, []>("input_49_cast_fp16")];
            tensor<int32, [2]> var_199 = const()[name = tensor<string, []>("op_199"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_201 = const()[name = tensor<string, []>("op_201"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_51_pad_type_0 = const()[name = tensor<string, []>("input_51_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_51_pad_0 = const()[name = tensor<string, []>("input_51_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [240, 80, 1, 1]> original_model_image_encoder_model_network_0_2_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_2_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [240, 80, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205120)))];
            tensor<fp16, [240]> original_model_image_encoder_model_network_0_2_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_2_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [240]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(243584)))];
            tensor<fp16, [1, 240, 64, 64]> input_51_cast_fp16 = conv(bias = original_model_image_encoder_model_network_0_2_convffn_fc1_bias_to_fp16, dilations = var_201, groups = var_8, pad = input_51_pad_0, pad_type = input_51_pad_type_0, strides = var_199, weight = original_model_image_encoder_model_network_0_2_convffn_fc1_weight_to_fp16, x = input_49_cast_fp16)[name = tensor<string, []>("input_51_cast_fp16")];
            tensor<string, []> input_53_mode_0 = const()[name = tensor<string, []>("input_53_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 240, 64, 64]> input_53_cast_fp16 = gelu(mode = input_53_mode_0, x = input_51_cast_fp16)[name = tensor<string, []>("input_53_cast_fp16")];
            tensor<int32, [2]> var_208 = const()[name = tensor<string, []>("op_208"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_210 = const()[name = tensor<string, []>("op_210"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_57_pad_type_0 = const()[name = tensor<string, []>("input_57_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_57_pad_0 = const()[name = tensor<string, []>("input_57_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [80, 240, 1, 1]> var_214_weight_0_to_fp16 = const()[name = tensor<string, []>("op_214_weight_0_to_fp16"), val = tensor<fp16, [80, 240, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244160)))];
            tensor<fp16, [80]> var_214_bias_0_to_fp16 = const()[name = tensor<string, []>("op_214_bias_0_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(282624)))];
            tensor<fp16, [1, 80, 64, 64]> var_214_cast_fp16 = conv(bias = var_214_bias_0_to_fp16, dilations = var_210, groups = var_8, pad = input_57_pad_0, pad_type = input_57_pad_type_0, strides = var_208, weight = var_214_weight_0_to_fp16, x = input_53_cast_fp16)[name = tensor<string, []>("op_214_cast_fp16")];
            tensor<fp16, [1, 80, 64, 64]> input_59_cast_fp16 = add(x = input_45_cast_fp16, y = var_214_cast_fp16)[name = tensor<string, []>("input_59_cast_fp16")];
            tensor<int32, [2]> var_222 = const()[name = tensor<string, []>("op_222"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_224 = const()[name = tensor<string, []>("op_224"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_61_pad_type_0 = const()[name = tensor<string, []>("input_61_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_61_pad_0 = const()[name = tensor<string, []>("input_61_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [80, 1, 3, 3]> original_model_image_encoder_model_network_0_3_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_3_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [80, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(282880)))];
            tensor<fp16, [80]> original_model_image_encoder_model_network_0_3_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_3_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284416)))];
            tensor<fp16, [1, 80, 64, 64]> input_61_cast_fp16 = conv(bias = original_model_image_encoder_model_network_0_3_token_mixer_reparam_conv_bias_to_fp16, dilations = var_224, groups = var_4, pad = input_61_pad_0, pad_type = input_61_pad_type_0, strides = var_222, weight = original_model_image_encoder_model_network_0_3_token_mixer_reparam_conv_weight_to_fp16, x = input_59_cast_fp16)[name = tensor<string, []>("input_61_cast_fp16")];
            tensor<int32, [2]> var_233 = const()[name = tensor<string, []>("op_233"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_235 = const()[name = tensor<string, []>("op_235"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_63_pad_type_0 = const()[name = tensor<string, []>("input_63_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_63_pad_0 = const()[name = tensor<string, []>("input_63_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [80, 1, 7, 7]> input_65_weight_0_to_fp16 = const()[name = tensor<string, []>("input_65_weight_0_to_fp16"), val = tensor<fp16, [80, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284672)))];
            tensor<fp16, [80]> input_65_bias_0_to_fp16 = const()[name = tensor<string, []>("input_65_bias_0_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(292608)))];
            tensor<fp16, [1, 80, 64, 64]> input_65_cast_fp16 = conv(bias = input_65_bias_0_to_fp16, dilations = var_235, groups = var_4, pad = input_63_pad_0, pad_type = input_63_pad_type_0, strides = var_233, weight = input_65_weight_0_to_fp16, x = input_61_cast_fp16)[name = tensor<string, []>("input_65_cast_fp16")];
            tensor<int32, [2]> var_245 = const()[name = tensor<string, []>("op_245"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_247 = const()[name = tensor<string, []>("op_247"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_67_pad_type_0 = const()[name = tensor<string, []>("input_67_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_67_pad_0 = const()[name = tensor<string, []>("input_67_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [240, 80, 1, 1]> original_model_image_encoder_model_network_0_3_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_3_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [240, 80, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(292864)))];
            tensor<fp16, [240]> original_model_image_encoder_model_network_0_3_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_0_3_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [240]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(331328)))];
            tensor<fp16, [1, 240, 64, 64]> input_67_cast_fp16 = conv(bias = original_model_image_encoder_model_network_0_3_convffn_fc1_bias_to_fp16, dilations = var_247, groups = var_8, pad = input_67_pad_0, pad_type = input_67_pad_type_0, strides = var_245, weight = original_model_image_encoder_model_network_0_3_convffn_fc1_weight_to_fp16, x = input_65_cast_fp16)[name = tensor<string, []>("input_67_cast_fp16")];
            tensor<string, []> input_69_mode_0 = const()[name = tensor<string, []>("input_69_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 240, 64, 64]> input_69_cast_fp16 = gelu(mode = input_69_mode_0, x = input_67_cast_fp16)[name = tensor<string, []>("input_69_cast_fp16")];
            tensor<int32, [2]> var_254 = const()[name = tensor<string, []>("op_254"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_256 = const()[name = tensor<string, []>("op_256"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_73_pad_type_0 = const()[name = tensor<string, []>("input_73_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_73_pad_0 = const()[name = tensor<string, []>("input_73_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [80, 240, 1, 1]> var_260_weight_0_to_fp16 = const()[name = tensor<string, []>("op_260_weight_0_to_fp16"), val = tensor<fp16, [80, 240, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(331904)))];
            tensor<fp16, [80]> var_260_bias_0_to_fp16 = const()[name = tensor<string, []>("op_260_bias_0_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(370368)))];
            tensor<fp16, [1, 80, 64, 64]> var_260_cast_fp16 = conv(bias = var_260_bias_0_to_fp16, dilations = var_256, groups = var_8, pad = input_73_pad_0, pad_type = input_73_pad_type_0, strides = var_254, weight = var_260_weight_0_to_fp16, x = input_69_cast_fp16)[name = tensor<string, []>("op_260_cast_fp16")];
            tensor<fp16, [1, 80, 64, 64]> input_75_cast_fp16 = add(x = input_61_cast_fp16, y = var_260_cast_fp16)[name = tensor<string, []>("input_75_cast_fp16")];
            tensor<int32, [2]> var_268 = const()[name = tensor<string, []>("op_268"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_270 = const()[name = tensor<string, []>("op_270"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_77_pad_type_0 = const()[name = tensor<string, []>("input_77_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_77_pad_0 = const()[name = tensor<string, []>("input_77_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [160, 1, 7, 7]> original_model_image_encoder_model_network_1_proj_0_lkb_reparam_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_1_proj_0_lkb_reparam_weight_to_fp16"), val = tensor<fp16, [160, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(370624)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_1_proj_0_lkb_reparam_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_1_proj_0_lkb_reparam_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(386368)))];
            tensor<fp16, [1, 160, 32, 32]> input_77_cast_fp16 = conv(bias = original_model_image_encoder_model_network_1_proj_0_lkb_reparam_bias_to_fp16, dilations = var_270, groups = var_4, pad = input_77_pad_0, pad_type = input_77_pad_type_0, strides = var_268, weight = original_model_image_encoder_model_network_1_proj_0_lkb_reparam_weight_to_fp16, x = input_75_cast_fp16)[name = tensor<string, []>("input_77_cast_fp16")];
            tensor<string, []> input_79_mode_0 = const()[name = tensor<string, []>("input_79_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 160, 32, 32]> input_79_cast_fp16 = gelu(mode = input_79_mode_0, x = input_77_cast_fp16)[name = tensor<string, []>("input_79_cast_fp16")];
            tensor<int32, [2]> var_277 = const()[name = tensor<string, []>("op_277"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_279 = const()[name = tensor<string, []>("op_279"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_81_pad_type_0 = const()[name = tensor<string, []>("input_81_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_81_pad_0 = const()[name = tensor<string, []>("input_81_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 160, 1, 1]> original_model_image_encoder_model_network_1_proj_1_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_1_proj_1_reparam_conv_weight_to_fp16"), val = tensor<fp16, [160, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(386752)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_1_proj_1_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_1_proj_1_reparam_conv_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(438016)))];
            tensor<fp16, [1, 160, 32, 32]> input_81_cast_fp16 = conv(bias = original_model_image_encoder_model_network_1_proj_1_reparam_conv_bias_to_fp16, dilations = var_279, groups = var_8, pad = input_81_pad_0, pad_type = input_81_pad_type_0, strides = var_277, weight = original_model_image_encoder_model_network_1_proj_1_reparam_conv_weight_to_fp16, x = input_79_cast_fp16)[name = tensor<string, []>("input_81_cast_fp16")];
            tensor<string, []> input_83_mode_0 = const()[name = tensor<string, []>("input_83_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 160, 32, 32]> input_83_cast_fp16 = gelu(mode = input_83_mode_0, x = input_81_cast_fp16)[name = tensor<string, []>("input_83_cast_fp16")];
            tensor<int32, [2]> var_301 = const()[name = tensor<string, []>("op_301"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_303 = const()[name = tensor<string, []>("op_303"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_85_pad_type_0 = const()[name = tensor<string, []>("input_85_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_85_pad_0 = const()[name = tensor<string, []>("input_85_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [160, 1, 3, 3]> original_model_image_encoder_model_network_2_0_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_0_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [160, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(438400)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_2_0_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_0_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441344)))];
            tensor<fp16, [1, 160, 32, 32]> input_85_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_0_token_mixer_reparam_conv_bias_to_fp16, dilations = var_303, groups = var_16, pad = input_85_pad_0, pad_type = input_85_pad_type_0, strides = var_301, weight = original_model_image_encoder_model_network_2_0_token_mixer_reparam_conv_weight_to_fp16, x = input_83_cast_fp16)[name = tensor<string, []>("input_85_cast_fp16")];
            tensor<int32, [2]> var_312 = const()[name = tensor<string, []>("op_312"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_314 = const()[name = tensor<string, []>("op_314"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_87_pad_type_0 = const()[name = tensor<string, []>("input_87_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_87_pad_0 = const()[name = tensor<string, []>("input_87_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [160, 1, 7, 7]> input_89_weight_0_to_fp16 = const()[name = tensor<string, []>("input_89_weight_0_to_fp16"), val = tensor<fp16, [160, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441728)))];
            tensor<fp16, [160]> input_89_bias_0_to_fp16 = const()[name = tensor<string, []>("input_89_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(457472)))];
            tensor<fp16, [1, 160, 32, 32]> input_89_cast_fp16 = conv(bias = input_89_bias_0_to_fp16, dilations = var_314, groups = var_16, pad = input_87_pad_0, pad_type = input_87_pad_type_0, strides = var_312, weight = input_89_weight_0_to_fp16, x = input_85_cast_fp16)[name = tensor<string, []>("input_89_cast_fp16")];
            tensor<int32, [2]> var_324 = const()[name = tensor<string, []>("op_324"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_326 = const()[name = tensor<string, []>("op_326"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_91_pad_type_0 = const()[name = tensor<string, []>("input_91_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_91_pad_0 = const()[name = tensor<string, []>("input_91_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [480, 160, 1, 1]> original_model_image_encoder_model_network_2_0_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_0_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [480, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(457856)))];
            tensor<fp16, [480]> original_model_image_encoder_model_network_2_0_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_0_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(611520)))];
            tensor<fp16, [1, 480, 32, 32]> input_91_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_0_convffn_fc1_bias_to_fp16, dilations = var_326, groups = var_8, pad = input_91_pad_0, pad_type = input_91_pad_type_0, strides = var_324, weight = original_model_image_encoder_model_network_2_0_convffn_fc1_weight_to_fp16, x = input_89_cast_fp16)[name = tensor<string, []>("input_91_cast_fp16")];
            tensor<string, []> input_93_mode_0 = const()[name = tensor<string, []>("input_93_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 480, 32, 32]> input_93_cast_fp16 = gelu(mode = input_93_mode_0, x = input_91_cast_fp16)[name = tensor<string, []>("input_93_cast_fp16")];
            tensor<int32, [2]> var_333 = const()[name = tensor<string, []>("op_333"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_335 = const()[name = tensor<string, []>("op_335"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_97_pad_type_0 = const()[name = tensor<string, []>("input_97_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_97_pad_0 = const()[name = tensor<string, []>("input_97_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 480, 1, 1]> var_339_weight_0_to_fp16 = const()[name = tensor<string, []>("op_339_weight_0_to_fp16"), val = tensor<fp16, [160, 480, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(612544)))];
            tensor<fp16, [160]> var_339_bias_0_to_fp16 = const()[name = tensor<string, []>("op_339_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(766208)))];
            tensor<fp16, [1, 160, 32, 32]> var_339_cast_fp16 = conv(bias = var_339_bias_0_to_fp16, dilations = var_335, groups = var_8, pad = input_97_pad_0, pad_type = input_97_pad_type_0, strides = var_333, weight = var_339_weight_0_to_fp16, x = input_93_cast_fp16)[name = tensor<string, []>("op_339_cast_fp16")];
            tensor<fp16, [1, 160, 32, 32]> input_99_cast_fp16 = add(x = input_85_cast_fp16, y = var_339_cast_fp16)[name = tensor<string, []>("input_99_cast_fp16")];
            tensor<int32, [2]> var_347 = const()[name = tensor<string, []>("op_347"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_349 = const()[name = tensor<string, []>("op_349"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_101_pad_type_0 = const()[name = tensor<string, []>("input_101_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_101_pad_0 = const()[name = tensor<string, []>("input_101_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [160, 1, 3, 3]> original_model_image_encoder_model_network_2_1_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_1_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [160, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(766592)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_2_1_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_1_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(769536)))];
            tensor<fp16, [1, 160, 32, 32]> input_101_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_1_token_mixer_reparam_conv_bias_to_fp16, dilations = var_349, groups = var_16, pad = input_101_pad_0, pad_type = input_101_pad_type_0, strides = var_347, weight = original_model_image_encoder_model_network_2_1_token_mixer_reparam_conv_weight_to_fp16, x = input_99_cast_fp16)[name = tensor<string, []>("input_101_cast_fp16")];
            tensor<int32, [2]> var_358 = const()[name = tensor<string, []>("op_358"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_360 = const()[name = tensor<string, []>("op_360"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_103_pad_type_0 = const()[name = tensor<string, []>("input_103_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_103_pad_0 = const()[name = tensor<string, []>("input_103_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [160, 1, 7, 7]> input_105_weight_0_to_fp16 = const()[name = tensor<string, []>("input_105_weight_0_to_fp16"), val = tensor<fp16, [160, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(769920)))];
            tensor<fp16, [160]> input_105_bias_0_to_fp16 = const()[name = tensor<string, []>("input_105_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(785664)))];
            tensor<fp16, [1, 160, 32, 32]> input_105_cast_fp16 = conv(bias = input_105_bias_0_to_fp16, dilations = var_360, groups = var_16, pad = input_103_pad_0, pad_type = input_103_pad_type_0, strides = var_358, weight = input_105_weight_0_to_fp16, x = input_101_cast_fp16)[name = tensor<string, []>("input_105_cast_fp16")];
            tensor<int32, [2]> var_370 = const()[name = tensor<string, []>("op_370"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_372 = const()[name = tensor<string, []>("op_372"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_107_pad_type_0 = const()[name = tensor<string, []>("input_107_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_107_pad_0 = const()[name = tensor<string, []>("input_107_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [480, 160, 1, 1]> original_model_image_encoder_model_network_2_1_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_1_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [480, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(786048)))];
            tensor<fp16, [480]> original_model_image_encoder_model_network_2_1_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_1_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(939712)))];
            tensor<fp16, [1, 480, 32, 32]> input_107_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_1_convffn_fc1_bias_to_fp16, dilations = var_372, groups = var_8, pad = input_107_pad_0, pad_type = input_107_pad_type_0, strides = var_370, weight = original_model_image_encoder_model_network_2_1_convffn_fc1_weight_to_fp16, x = input_105_cast_fp16)[name = tensor<string, []>("input_107_cast_fp16")];
            tensor<string, []> input_109_mode_0 = const()[name = tensor<string, []>("input_109_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 480, 32, 32]> input_109_cast_fp16 = gelu(mode = input_109_mode_0, x = input_107_cast_fp16)[name = tensor<string, []>("input_109_cast_fp16")];
            tensor<int32, [2]> var_379 = const()[name = tensor<string, []>("op_379"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_381 = const()[name = tensor<string, []>("op_381"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_113_pad_type_0 = const()[name = tensor<string, []>("input_113_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_113_pad_0 = const()[name = tensor<string, []>("input_113_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 480, 1, 1]> var_385_weight_0_to_fp16 = const()[name = tensor<string, []>("op_385_weight_0_to_fp16"), val = tensor<fp16, [160, 480, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(940736)))];
            tensor<fp16, [160]> var_385_bias_0_to_fp16 = const()[name = tensor<string, []>("op_385_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1094400)))];
            tensor<fp16, [1, 160, 32, 32]> var_385_cast_fp16 = conv(bias = var_385_bias_0_to_fp16, dilations = var_381, groups = var_8, pad = input_113_pad_0, pad_type = input_113_pad_type_0, strides = var_379, weight = var_385_weight_0_to_fp16, x = input_109_cast_fp16)[name = tensor<string, []>("op_385_cast_fp16")];
            tensor<fp16, [1, 160, 32, 32]> input_115_cast_fp16 = add(x = input_101_cast_fp16, y = var_385_cast_fp16)[name = tensor<string, []>("input_115_cast_fp16")];
            tensor<int32, [2]> var_393 = const()[name = tensor<string, []>("op_393"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_395 = const()[name = tensor<string, []>("op_395"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_117_pad_type_0 = const()[name = tensor<string, []>("input_117_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_117_pad_0 = const()[name = tensor<string, []>("input_117_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [160, 1, 3, 3]> original_model_image_encoder_model_network_2_2_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_2_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [160, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1094784)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_2_2_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_2_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1097728)))];
            tensor<fp16, [1, 160, 32, 32]> input_117_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_2_token_mixer_reparam_conv_bias_to_fp16, dilations = var_395, groups = var_16, pad = input_117_pad_0, pad_type = input_117_pad_type_0, strides = var_393, weight = original_model_image_encoder_model_network_2_2_token_mixer_reparam_conv_weight_to_fp16, x = input_115_cast_fp16)[name = tensor<string, []>("input_117_cast_fp16")];
            tensor<int32, [2]> var_404 = const()[name = tensor<string, []>("op_404"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_406 = const()[name = tensor<string, []>("op_406"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_119_pad_type_0 = const()[name = tensor<string, []>("input_119_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_119_pad_0 = const()[name = tensor<string, []>("input_119_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [160, 1, 7, 7]> input_121_weight_0_to_fp16 = const()[name = tensor<string, []>("input_121_weight_0_to_fp16"), val = tensor<fp16, [160, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1098112)))];
            tensor<fp16, [160]> input_121_bias_0_to_fp16 = const()[name = tensor<string, []>("input_121_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1113856)))];
            tensor<fp16, [1, 160, 32, 32]> input_121_cast_fp16 = conv(bias = input_121_bias_0_to_fp16, dilations = var_406, groups = var_16, pad = input_119_pad_0, pad_type = input_119_pad_type_0, strides = var_404, weight = input_121_weight_0_to_fp16, x = input_117_cast_fp16)[name = tensor<string, []>("input_121_cast_fp16")];
            tensor<int32, [2]> var_416 = const()[name = tensor<string, []>("op_416"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_418 = const()[name = tensor<string, []>("op_418"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_123_pad_type_0 = const()[name = tensor<string, []>("input_123_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_123_pad_0 = const()[name = tensor<string, []>("input_123_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [480, 160, 1, 1]> original_model_image_encoder_model_network_2_2_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_2_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [480, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1114240)))];
            tensor<fp16, [480]> original_model_image_encoder_model_network_2_2_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_2_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1267904)))];
            tensor<fp16, [1, 480, 32, 32]> input_123_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_2_convffn_fc1_bias_to_fp16, dilations = var_418, groups = var_8, pad = input_123_pad_0, pad_type = input_123_pad_type_0, strides = var_416, weight = original_model_image_encoder_model_network_2_2_convffn_fc1_weight_to_fp16, x = input_121_cast_fp16)[name = tensor<string, []>("input_123_cast_fp16")];
            tensor<string, []> input_125_mode_0 = const()[name = tensor<string, []>("input_125_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 480, 32, 32]> input_125_cast_fp16 = gelu(mode = input_125_mode_0, x = input_123_cast_fp16)[name = tensor<string, []>("input_125_cast_fp16")];
            tensor<int32, [2]> var_425 = const()[name = tensor<string, []>("op_425"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_427 = const()[name = tensor<string, []>("op_427"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_129_pad_type_0 = const()[name = tensor<string, []>("input_129_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_129_pad_0 = const()[name = tensor<string, []>("input_129_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 480, 1, 1]> var_431_weight_0_to_fp16 = const()[name = tensor<string, []>("op_431_weight_0_to_fp16"), val = tensor<fp16, [160, 480, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268928)))];
            tensor<fp16, [160]> var_431_bias_0_to_fp16 = const()[name = tensor<string, []>("op_431_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1422592)))];
            tensor<fp16, [1, 160, 32, 32]> var_431_cast_fp16 = conv(bias = var_431_bias_0_to_fp16, dilations = var_427, groups = var_8, pad = input_129_pad_0, pad_type = input_129_pad_type_0, strides = var_425, weight = var_431_weight_0_to_fp16, x = input_125_cast_fp16)[name = tensor<string, []>("op_431_cast_fp16")];
            tensor<fp16, [1, 160, 32, 32]> input_131_cast_fp16 = add(x = input_117_cast_fp16, y = var_431_cast_fp16)[name = tensor<string, []>("input_131_cast_fp16")];
            tensor<int32, [2]> var_439 = const()[name = tensor<string, []>("op_439"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_441 = const()[name = tensor<string, []>("op_441"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_133_pad_type_0 = const()[name = tensor<string, []>("input_133_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_133_pad_0 = const()[name = tensor<string, []>("input_133_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [160, 1, 3, 3]> original_model_image_encoder_model_network_2_3_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_3_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [160, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1422976)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_2_3_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_3_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1425920)))];
            tensor<fp16, [1, 160, 32, 32]> input_133_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_3_token_mixer_reparam_conv_bias_to_fp16, dilations = var_441, groups = var_16, pad = input_133_pad_0, pad_type = input_133_pad_type_0, strides = var_439, weight = original_model_image_encoder_model_network_2_3_token_mixer_reparam_conv_weight_to_fp16, x = input_131_cast_fp16)[name = tensor<string, []>("input_133_cast_fp16")];
            tensor<int32, [2]> var_450 = const()[name = tensor<string, []>("op_450"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_452 = const()[name = tensor<string, []>("op_452"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_135_pad_type_0 = const()[name = tensor<string, []>("input_135_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_135_pad_0 = const()[name = tensor<string, []>("input_135_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [160, 1, 7, 7]> input_137_weight_0_to_fp16 = const()[name = tensor<string, []>("input_137_weight_0_to_fp16"), val = tensor<fp16, [160, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1426304)))];
            tensor<fp16, [160]> input_137_bias_0_to_fp16 = const()[name = tensor<string, []>("input_137_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1442048)))];
            tensor<fp16, [1, 160, 32, 32]> input_137_cast_fp16 = conv(bias = input_137_bias_0_to_fp16, dilations = var_452, groups = var_16, pad = input_135_pad_0, pad_type = input_135_pad_type_0, strides = var_450, weight = input_137_weight_0_to_fp16, x = input_133_cast_fp16)[name = tensor<string, []>("input_137_cast_fp16")];
            tensor<int32, [2]> var_462 = const()[name = tensor<string, []>("op_462"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_464 = const()[name = tensor<string, []>("op_464"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_139_pad_type_0 = const()[name = tensor<string, []>("input_139_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_139_pad_0 = const()[name = tensor<string, []>("input_139_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [480, 160, 1, 1]> original_model_image_encoder_model_network_2_3_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_3_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [480, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1442432)))];
            tensor<fp16, [480]> original_model_image_encoder_model_network_2_3_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_3_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1596096)))];
            tensor<fp16, [1, 480, 32, 32]> input_139_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_3_convffn_fc1_bias_to_fp16, dilations = var_464, groups = var_8, pad = input_139_pad_0, pad_type = input_139_pad_type_0, strides = var_462, weight = original_model_image_encoder_model_network_2_3_convffn_fc1_weight_to_fp16, x = input_137_cast_fp16)[name = tensor<string, []>("input_139_cast_fp16")];
            tensor<string, []> input_141_mode_0 = const()[name = tensor<string, []>("input_141_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 480, 32, 32]> input_141_cast_fp16 = gelu(mode = input_141_mode_0, x = input_139_cast_fp16)[name = tensor<string, []>("input_141_cast_fp16")];
            tensor<int32, [2]> var_471 = const()[name = tensor<string, []>("op_471"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_473 = const()[name = tensor<string, []>("op_473"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_145_pad_type_0 = const()[name = tensor<string, []>("input_145_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_145_pad_0 = const()[name = tensor<string, []>("input_145_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 480, 1, 1]> var_477_weight_0_to_fp16 = const()[name = tensor<string, []>("op_477_weight_0_to_fp16"), val = tensor<fp16, [160, 480, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1597120)))];
            tensor<fp16, [160]> var_477_bias_0_to_fp16 = const()[name = tensor<string, []>("op_477_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1750784)))];
            tensor<fp16, [1, 160, 32, 32]> var_477_cast_fp16 = conv(bias = var_477_bias_0_to_fp16, dilations = var_473, groups = var_8, pad = input_145_pad_0, pad_type = input_145_pad_type_0, strides = var_471, weight = var_477_weight_0_to_fp16, x = input_141_cast_fp16)[name = tensor<string, []>("op_477_cast_fp16")];
            tensor<fp16, [1, 160, 32, 32]> input_147_cast_fp16 = add(x = input_133_cast_fp16, y = var_477_cast_fp16)[name = tensor<string, []>("input_147_cast_fp16")];
            tensor<int32, [2]> var_485 = const()[name = tensor<string, []>("op_485"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_487 = const()[name = tensor<string, []>("op_487"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_149_pad_type_0 = const()[name = tensor<string, []>("input_149_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_149_pad_0 = const()[name = tensor<string, []>("input_149_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [160, 1, 3, 3]> original_model_image_encoder_model_network_2_4_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_4_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [160, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1751168)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_2_4_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_4_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1754112)))];
            tensor<fp16, [1, 160, 32, 32]> input_149_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_4_token_mixer_reparam_conv_bias_to_fp16, dilations = var_487, groups = var_16, pad = input_149_pad_0, pad_type = input_149_pad_type_0, strides = var_485, weight = original_model_image_encoder_model_network_2_4_token_mixer_reparam_conv_weight_to_fp16, x = input_147_cast_fp16)[name = tensor<string, []>("input_149_cast_fp16")];
            tensor<int32, [2]> var_496 = const()[name = tensor<string, []>("op_496"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_498 = const()[name = tensor<string, []>("op_498"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_151_pad_type_0 = const()[name = tensor<string, []>("input_151_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_151_pad_0 = const()[name = tensor<string, []>("input_151_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [160, 1, 7, 7]> input_153_weight_0_to_fp16 = const()[name = tensor<string, []>("input_153_weight_0_to_fp16"), val = tensor<fp16, [160, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1754496)))];
            tensor<fp16, [160]> input_153_bias_0_to_fp16 = const()[name = tensor<string, []>("input_153_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1770240)))];
            tensor<fp16, [1, 160, 32, 32]> input_153_cast_fp16 = conv(bias = input_153_bias_0_to_fp16, dilations = var_498, groups = var_16, pad = input_151_pad_0, pad_type = input_151_pad_type_0, strides = var_496, weight = input_153_weight_0_to_fp16, x = input_149_cast_fp16)[name = tensor<string, []>("input_153_cast_fp16")];
            tensor<int32, [2]> var_508 = const()[name = tensor<string, []>("op_508"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_510 = const()[name = tensor<string, []>("op_510"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_155_pad_type_0 = const()[name = tensor<string, []>("input_155_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_155_pad_0 = const()[name = tensor<string, []>("input_155_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [480, 160, 1, 1]> original_model_image_encoder_model_network_2_4_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_4_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [480, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1770624)))];
            tensor<fp16, [480]> original_model_image_encoder_model_network_2_4_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_4_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1924288)))];
            tensor<fp16, [1, 480, 32, 32]> input_155_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_4_convffn_fc1_bias_to_fp16, dilations = var_510, groups = var_8, pad = input_155_pad_0, pad_type = input_155_pad_type_0, strides = var_508, weight = original_model_image_encoder_model_network_2_4_convffn_fc1_weight_to_fp16, x = input_153_cast_fp16)[name = tensor<string, []>("input_155_cast_fp16")];
            tensor<string, []> input_157_mode_0 = const()[name = tensor<string, []>("input_157_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 480, 32, 32]> input_157_cast_fp16 = gelu(mode = input_157_mode_0, x = input_155_cast_fp16)[name = tensor<string, []>("input_157_cast_fp16")];
            tensor<int32, [2]> var_517 = const()[name = tensor<string, []>("op_517"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_519 = const()[name = tensor<string, []>("op_519"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_161_pad_type_0 = const()[name = tensor<string, []>("input_161_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_161_pad_0 = const()[name = tensor<string, []>("input_161_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 480, 1, 1]> var_523_weight_0_to_fp16 = const()[name = tensor<string, []>("op_523_weight_0_to_fp16"), val = tensor<fp16, [160, 480, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1925312)))];
            tensor<fp16, [160]> var_523_bias_0_to_fp16 = const()[name = tensor<string, []>("op_523_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2078976)))];
            tensor<fp16, [1, 160, 32, 32]> var_523_cast_fp16 = conv(bias = var_523_bias_0_to_fp16, dilations = var_519, groups = var_8, pad = input_161_pad_0, pad_type = input_161_pad_type_0, strides = var_517, weight = var_523_weight_0_to_fp16, x = input_157_cast_fp16)[name = tensor<string, []>("op_523_cast_fp16")];
            tensor<fp16, [1, 160, 32, 32]> input_163_cast_fp16 = add(x = input_149_cast_fp16, y = var_523_cast_fp16)[name = tensor<string, []>("input_163_cast_fp16")];
            tensor<int32, [2]> var_531 = const()[name = tensor<string, []>("op_531"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_533 = const()[name = tensor<string, []>("op_533"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_165_pad_type_0 = const()[name = tensor<string, []>("input_165_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_165_pad_0 = const()[name = tensor<string, []>("input_165_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [160, 1, 3, 3]> original_model_image_encoder_model_network_2_5_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_5_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [160, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2079360)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_2_5_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_5_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2082304)))];
            tensor<fp16, [1, 160, 32, 32]> input_165_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_5_token_mixer_reparam_conv_bias_to_fp16, dilations = var_533, groups = var_16, pad = input_165_pad_0, pad_type = input_165_pad_type_0, strides = var_531, weight = original_model_image_encoder_model_network_2_5_token_mixer_reparam_conv_weight_to_fp16, x = input_163_cast_fp16)[name = tensor<string, []>("input_165_cast_fp16")];
            tensor<int32, [2]> var_542 = const()[name = tensor<string, []>("op_542"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_544 = const()[name = tensor<string, []>("op_544"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_167_pad_type_0 = const()[name = tensor<string, []>("input_167_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_167_pad_0 = const()[name = tensor<string, []>("input_167_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [160, 1, 7, 7]> input_169_weight_0_to_fp16 = const()[name = tensor<string, []>("input_169_weight_0_to_fp16"), val = tensor<fp16, [160, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2082688)))];
            tensor<fp16, [160]> input_169_bias_0_to_fp16 = const()[name = tensor<string, []>("input_169_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2098432)))];
            tensor<fp16, [1, 160, 32, 32]> input_169_cast_fp16 = conv(bias = input_169_bias_0_to_fp16, dilations = var_544, groups = var_16, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = var_542, weight = input_169_weight_0_to_fp16, x = input_165_cast_fp16)[name = tensor<string, []>("input_169_cast_fp16")];
            tensor<int32, [2]> var_554 = const()[name = tensor<string, []>("op_554"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_556 = const()[name = tensor<string, []>("op_556"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_171_pad_type_0 = const()[name = tensor<string, []>("input_171_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_171_pad_0 = const()[name = tensor<string, []>("input_171_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [480, 160, 1, 1]> original_model_image_encoder_model_network_2_5_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_5_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [480, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2098816)))];
            tensor<fp16, [480]> original_model_image_encoder_model_network_2_5_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_5_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2252480)))];
            tensor<fp16, [1, 480, 32, 32]> input_171_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_5_convffn_fc1_bias_to_fp16, dilations = var_556, groups = var_8, pad = input_171_pad_0, pad_type = input_171_pad_type_0, strides = var_554, weight = original_model_image_encoder_model_network_2_5_convffn_fc1_weight_to_fp16, x = input_169_cast_fp16)[name = tensor<string, []>("input_171_cast_fp16")];
            tensor<string, []> input_173_mode_0 = const()[name = tensor<string, []>("input_173_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 480, 32, 32]> input_173_cast_fp16 = gelu(mode = input_173_mode_0, x = input_171_cast_fp16)[name = tensor<string, []>("input_173_cast_fp16")];
            tensor<int32, [2]> var_563 = const()[name = tensor<string, []>("op_563"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_565 = const()[name = tensor<string, []>("op_565"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_177_pad_type_0 = const()[name = tensor<string, []>("input_177_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_177_pad_0 = const()[name = tensor<string, []>("input_177_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 480, 1, 1]> var_569_weight_0_to_fp16 = const()[name = tensor<string, []>("op_569_weight_0_to_fp16"), val = tensor<fp16, [160, 480, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2253504)))];
            tensor<fp16, [160]> var_569_bias_0_to_fp16 = const()[name = tensor<string, []>("op_569_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2407168)))];
            tensor<fp16, [1, 160, 32, 32]> var_569_cast_fp16 = conv(bias = var_569_bias_0_to_fp16, dilations = var_565, groups = var_8, pad = input_177_pad_0, pad_type = input_177_pad_type_0, strides = var_563, weight = var_569_weight_0_to_fp16, x = input_173_cast_fp16)[name = tensor<string, []>("op_569_cast_fp16")];
            tensor<fp16, [1, 160, 32, 32]> input_179_cast_fp16 = add(x = input_165_cast_fp16, y = var_569_cast_fp16)[name = tensor<string, []>("input_179_cast_fp16")];
            tensor<int32, [2]> var_577 = const()[name = tensor<string, []>("op_577"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_579 = const()[name = tensor<string, []>("op_579"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_181_pad_type_0 = const()[name = tensor<string, []>("input_181_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_181_pad_0 = const()[name = tensor<string, []>("input_181_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [160, 1, 3, 3]> original_model_image_encoder_model_network_2_6_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_6_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [160, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2407552)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_2_6_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_6_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2410496)))];
            tensor<fp16, [1, 160, 32, 32]> input_181_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_6_token_mixer_reparam_conv_bias_to_fp16, dilations = var_579, groups = var_16, pad = input_181_pad_0, pad_type = input_181_pad_type_0, strides = var_577, weight = original_model_image_encoder_model_network_2_6_token_mixer_reparam_conv_weight_to_fp16, x = input_179_cast_fp16)[name = tensor<string, []>("input_181_cast_fp16")];
            tensor<int32, [2]> var_588 = const()[name = tensor<string, []>("op_588"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_590 = const()[name = tensor<string, []>("op_590"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_183_pad_type_0 = const()[name = tensor<string, []>("input_183_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_183_pad_0 = const()[name = tensor<string, []>("input_183_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [160, 1, 7, 7]> input_185_weight_0_to_fp16 = const()[name = tensor<string, []>("input_185_weight_0_to_fp16"), val = tensor<fp16, [160, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2410880)))];
            tensor<fp16, [160]> input_185_bias_0_to_fp16 = const()[name = tensor<string, []>("input_185_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2426624)))];
            tensor<fp16, [1, 160, 32, 32]> input_185_cast_fp16 = conv(bias = input_185_bias_0_to_fp16, dilations = var_590, groups = var_16, pad = input_183_pad_0, pad_type = input_183_pad_type_0, strides = var_588, weight = input_185_weight_0_to_fp16, x = input_181_cast_fp16)[name = tensor<string, []>("input_185_cast_fp16")];
            tensor<int32, [2]> var_600 = const()[name = tensor<string, []>("op_600"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_602 = const()[name = tensor<string, []>("op_602"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_187_pad_type_0 = const()[name = tensor<string, []>("input_187_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_187_pad_0 = const()[name = tensor<string, []>("input_187_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [480, 160, 1, 1]> original_model_image_encoder_model_network_2_6_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_6_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [480, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2427008)))];
            tensor<fp16, [480]> original_model_image_encoder_model_network_2_6_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_6_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2580672)))];
            tensor<fp16, [1, 480, 32, 32]> input_187_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_6_convffn_fc1_bias_to_fp16, dilations = var_602, groups = var_8, pad = input_187_pad_0, pad_type = input_187_pad_type_0, strides = var_600, weight = original_model_image_encoder_model_network_2_6_convffn_fc1_weight_to_fp16, x = input_185_cast_fp16)[name = tensor<string, []>("input_187_cast_fp16")];
            tensor<string, []> input_189_mode_0 = const()[name = tensor<string, []>("input_189_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 480, 32, 32]> input_189_cast_fp16 = gelu(mode = input_189_mode_0, x = input_187_cast_fp16)[name = tensor<string, []>("input_189_cast_fp16")];
            tensor<int32, [2]> var_609 = const()[name = tensor<string, []>("op_609"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_611 = const()[name = tensor<string, []>("op_611"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_193_pad_type_0 = const()[name = tensor<string, []>("input_193_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_193_pad_0 = const()[name = tensor<string, []>("input_193_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 480, 1, 1]> var_615_weight_0_to_fp16 = const()[name = tensor<string, []>("op_615_weight_0_to_fp16"), val = tensor<fp16, [160, 480, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2581696)))];
            tensor<fp16, [160]> var_615_bias_0_to_fp16 = const()[name = tensor<string, []>("op_615_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2735360)))];
            tensor<fp16, [1, 160, 32, 32]> var_615_cast_fp16 = conv(bias = var_615_bias_0_to_fp16, dilations = var_611, groups = var_8, pad = input_193_pad_0, pad_type = input_193_pad_type_0, strides = var_609, weight = var_615_weight_0_to_fp16, x = input_189_cast_fp16)[name = tensor<string, []>("op_615_cast_fp16")];
            tensor<fp16, [1, 160, 32, 32]> input_195_cast_fp16 = add(x = input_181_cast_fp16, y = var_615_cast_fp16)[name = tensor<string, []>("input_195_cast_fp16")];
            tensor<int32, [2]> var_623 = const()[name = tensor<string, []>("op_623"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_625 = const()[name = tensor<string, []>("op_625"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_197_pad_type_0 = const()[name = tensor<string, []>("input_197_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_197_pad_0 = const()[name = tensor<string, []>("input_197_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [160, 1, 3, 3]> original_model_image_encoder_model_network_2_7_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_7_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [160, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2735744)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_2_7_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_7_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2738688)))];
            tensor<fp16, [1, 160, 32, 32]> input_197_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_7_token_mixer_reparam_conv_bias_to_fp16, dilations = var_625, groups = var_16, pad = input_197_pad_0, pad_type = input_197_pad_type_0, strides = var_623, weight = original_model_image_encoder_model_network_2_7_token_mixer_reparam_conv_weight_to_fp16, x = input_195_cast_fp16)[name = tensor<string, []>("input_197_cast_fp16")];
            tensor<int32, [2]> var_634 = const()[name = tensor<string, []>("op_634"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_636 = const()[name = tensor<string, []>("op_636"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_199_pad_type_0 = const()[name = tensor<string, []>("input_199_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_199_pad_0 = const()[name = tensor<string, []>("input_199_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [160, 1, 7, 7]> input_201_weight_0_to_fp16 = const()[name = tensor<string, []>("input_201_weight_0_to_fp16"), val = tensor<fp16, [160, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2739072)))];
            tensor<fp16, [160]> input_201_bias_0_to_fp16 = const()[name = tensor<string, []>("input_201_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2754816)))];
            tensor<fp16, [1, 160, 32, 32]> input_201_cast_fp16 = conv(bias = input_201_bias_0_to_fp16, dilations = var_636, groups = var_16, pad = input_199_pad_0, pad_type = input_199_pad_type_0, strides = var_634, weight = input_201_weight_0_to_fp16, x = input_197_cast_fp16)[name = tensor<string, []>("input_201_cast_fp16")];
            tensor<int32, [2]> var_646 = const()[name = tensor<string, []>("op_646"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_648 = const()[name = tensor<string, []>("op_648"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_203_pad_type_0 = const()[name = tensor<string, []>("input_203_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_203_pad_0 = const()[name = tensor<string, []>("input_203_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [480, 160, 1, 1]> original_model_image_encoder_model_network_2_7_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_7_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [480, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2755200)))];
            tensor<fp16, [480]> original_model_image_encoder_model_network_2_7_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_7_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2908864)))];
            tensor<fp16, [1, 480, 32, 32]> input_203_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_7_convffn_fc1_bias_to_fp16, dilations = var_648, groups = var_8, pad = input_203_pad_0, pad_type = input_203_pad_type_0, strides = var_646, weight = original_model_image_encoder_model_network_2_7_convffn_fc1_weight_to_fp16, x = input_201_cast_fp16)[name = tensor<string, []>("input_203_cast_fp16")];
            tensor<string, []> input_205_mode_0 = const()[name = tensor<string, []>("input_205_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 480, 32, 32]> input_205_cast_fp16 = gelu(mode = input_205_mode_0, x = input_203_cast_fp16)[name = tensor<string, []>("input_205_cast_fp16")];
            tensor<int32, [2]> var_655 = const()[name = tensor<string, []>("op_655"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_657 = const()[name = tensor<string, []>("op_657"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_209_pad_type_0 = const()[name = tensor<string, []>("input_209_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_209_pad_0 = const()[name = tensor<string, []>("input_209_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 480, 1, 1]> var_661_weight_0_to_fp16 = const()[name = tensor<string, []>("op_661_weight_0_to_fp16"), val = tensor<fp16, [160, 480, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2909888)))];
            tensor<fp16, [160]> var_661_bias_0_to_fp16 = const()[name = tensor<string, []>("op_661_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3063552)))];
            tensor<fp16, [1, 160, 32, 32]> var_661_cast_fp16 = conv(bias = var_661_bias_0_to_fp16, dilations = var_657, groups = var_8, pad = input_209_pad_0, pad_type = input_209_pad_type_0, strides = var_655, weight = var_661_weight_0_to_fp16, x = input_205_cast_fp16)[name = tensor<string, []>("op_661_cast_fp16")];
            tensor<fp16, [1, 160, 32, 32]> input_211_cast_fp16 = add(x = input_197_cast_fp16, y = var_661_cast_fp16)[name = tensor<string, []>("input_211_cast_fp16")];
            tensor<int32, [2]> var_669 = const()[name = tensor<string, []>("op_669"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_671 = const()[name = tensor<string, []>("op_671"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_213_pad_type_0 = const()[name = tensor<string, []>("input_213_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_213_pad_0 = const()[name = tensor<string, []>("input_213_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [160, 1, 3, 3]> original_model_image_encoder_model_network_2_8_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_8_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [160, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3063936)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_2_8_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_8_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3066880)))];
            tensor<fp16, [1, 160, 32, 32]> input_213_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_8_token_mixer_reparam_conv_bias_to_fp16, dilations = var_671, groups = var_16, pad = input_213_pad_0, pad_type = input_213_pad_type_0, strides = var_669, weight = original_model_image_encoder_model_network_2_8_token_mixer_reparam_conv_weight_to_fp16, x = input_211_cast_fp16)[name = tensor<string, []>("input_213_cast_fp16")];
            tensor<int32, [2]> var_680 = const()[name = tensor<string, []>("op_680"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_682 = const()[name = tensor<string, []>("op_682"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_215_pad_type_0 = const()[name = tensor<string, []>("input_215_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_215_pad_0 = const()[name = tensor<string, []>("input_215_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [160, 1, 7, 7]> input_217_weight_0_to_fp16 = const()[name = tensor<string, []>("input_217_weight_0_to_fp16"), val = tensor<fp16, [160, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3067264)))];
            tensor<fp16, [160]> input_217_bias_0_to_fp16 = const()[name = tensor<string, []>("input_217_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3083008)))];
            tensor<fp16, [1, 160, 32, 32]> input_217_cast_fp16 = conv(bias = input_217_bias_0_to_fp16, dilations = var_682, groups = var_16, pad = input_215_pad_0, pad_type = input_215_pad_type_0, strides = var_680, weight = input_217_weight_0_to_fp16, x = input_213_cast_fp16)[name = tensor<string, []>("input_217_cast_fp16")];
            tensor<int32, [2]> var_692 = const()[name = tensor<string, []>("op_692"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_694 = const()[name = tensor<string, []>("op_694"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_219_pad_type_0 = const()[name = tensor<string, []>("input_219_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_219_pad_0 = const()[name = tensor<string, []>("input_219_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [480, 160, 1, 1]> original_model_image_encoder_model_network_2_8_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_8_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [480, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3083392)))];
            tensor<fp16, [480]> original_model_image_encoder_model_network_2_8_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_8_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3237056)))];
            tensor<fp16, [1, 480, 32, 32]> input_219_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_8_convffn_fc1_bias_to_fp16, dilations = var_694, groups = var_8, pad = input_219_pad_0, pad_type = input_219_pad_type_0, strides = var_692, weight = original_model_image_encoder_model_network_2_8_convffn_fc1_weight_to_fp16, x = input_217_cast_fp16)[name = tensor<string, []>("input_219_cast_fp16")];
            tensor<string, []> input_221_mode_0 = const()[name = tensor<string, []>("input_221_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 480, 32, 32]> input_221_cast_fp16 = gelu(mode = input_221_mode_0, x = input_219_cast_fp16)[name = tensor<string, []>("input_221_cast_fp16")];
            tensor<int32, [2]> var_701 = const()[name = tensor<string, []>("op_701"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_703 = const()[name = tensor<string, []>("op_703"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_225_pad_type_0 = const()[name = tensor<string, []>("input_225_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_225_pad_0 = const()[name = tensor<string, []>("input_225_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 480, 1, 1]> var_707_weight_0_to_fp16 = const()[name = tensor<string, []>("op_707_weight_0_to_fp16"), val = tensor<fp16, [160, 480, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3238080)))];
            tensor<fp16, [160]> var_707_bias_0_to_fp16 = const()[name = tensor<string, []>("op_707_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3391744)))];
            tensor<fp16, [1, 160, 32, 32]> var_707_cast_fp16 = conv(bias = var_707_bias_0_to_fp16, dilations = var_703, groups = var_8, pad = input_225_pad_0, pad_type = input_225_pad_type_0, strides = var_701, weight = var_707_weight_0_to_fp16, x = input_221_cast_fp16)[name = tensor<string, []>("op_707_cast_fp16")];
            tensor<fp16, [1, 160, 32, 32]> input_227_cast_fp16 = add(x = input_213_cast_fp16, y = var_707_cast_fp16)[name = tensor<string, []>("input_227_cast_fp16")];
            tensor<int32, [2]> var_715 = const()[name = tensor<string, []>("op_715"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_717 = const()[name = tensor<string, []>("op_717"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_229_pad_type_0 = const()[name = tensor<string, []>("input_229_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_229_pad_0 = const()[name = tensor<string, []>("input_229_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [160, 1, 3, 3]> original_model_image_encoder_model_network_2_9_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_9_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [160, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3392128)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_2_9_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_9_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3395072)))];
            tensor<fp16, [1, 160, 32, 32]> input_229_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_9_token_mixer_reparam_conv_bias_to_fp16, dilations = var_717, groups = var_16, pad = input_229_pad_0, pad_type = input_229_pad_type_0, strides = var_715, weight = original_model_image_encoder_model_network_2_9_token_mixer_reparam_conv_weight_to_fp16, x = input_227_cast_fp16)[name = tensor<string, []>("input_229_cast_fp16")];
            tensor<int32, [2]> var_726 = const()[name = tensor<string, []>("op_726"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_728 = const()[name = tensor<string, []>("op_728"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_231_pad_type_0 = const()[name = tensor<string, []>("input_231_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_231_pad_0 = const()[name = tensor<string, []>("input_231_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [160, 1, 7, 7]> input_233_weight_0_to_fp16 = const()[name = tensor<string, []>("input_233_weight_0_to_fp16"), val = tensor<fp16, [160, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3395456)))];
            tensor<fp16, [160]> input_233_bias_0_to_fp16 = const()[name = tensor<string, []>("input_233_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3411200)))];
            tensor<fp16, [1, 160, 32, 32]> input_233_cast_fp16 = conv(bias = input_233_bias_0_to_fp16, dilations = var_728, groups = var_16, pad = input_231_pad_0, pad_type = input_231_pad_type_0, strides = var_726, weight = input_233_weight_0_to_fp16, x = input_229_cast_fp16)[name = tensor<string, []>("input_233_cast_fp16")];
            tensor<int32, [2]> var_738 = const()[name = tensor<string, []>("op_738"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_740 = const()[name = tensor<string, []>("op_740"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_235_pad_type_0 = const()[name = tensor<string, []>("input_235_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_235_pad_0 = const()[name = tensor<string, []>("input_235_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [480, 160, 1, 1]> original_model_image_encoder_model_network_2_9_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_9_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [480, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3411584)))];
            tensor<fp16, [480]> original_model_image_encoder_model_network_2_9_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_9_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3565248)))];
            tensor<fp16, [1, 480, 32, 32]> input_235_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_9_convffn_fc1_bias_to_fp16, dilations = var_740, groups = var_8, pad = input_235_pad_0, pad_type = input_235_pad_type_0, strides = var_738, weight = original_model_image_encoder_model_network_2_9_convffn_fc1_weight_to_fp16, x = input_233_cast_fp16)[name = tensor<string, []>("input_235_cast_fp16")];
            tensor<string, []> input_237_mode_0 = const()[name = tensor<string, []>("input_237_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 480, 32, 32]> input_237_cast_fp16 = gelu(mode = input_237_mode_0, x = input_235_cast_fp16)[name = tensor<string, []>("input_237_cast_fp16")];
            tensor<int32, [2]> var_747 = const()[name = tensor<string, []>("op_747"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_749 = const()[name = tensor<string, []>("op_749"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_241_pad_type_0 = const()[name = tensor<string, []>("input_241_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_241_pad_0 = const()[name = tensor<string, []>("input_241_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 480, 1, 1]> var_753_weight_0_to_fp16 = const()[name = tensor<string, []>("op_753_weight_0_to_fp16"), val = tensor<fp16, [160, 480, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3566272)))];
            tensor<fp16, [160]> var_753_bias_0_to_fp16 = const()[name = tensor<string, []>("op_753_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3719936)))];
            tensor<fp16, [1, 160, 32, 32]> var_753_cast_fp16 = conv(bias = var_753_bias_0_to_fp16, dilations = var_749, groups = var_8, pad = input_241_pad_0, pad_type = input_241_pad_type_0, strides = var_747, weight = var_753_weight_0_to_fp16, x = input_237_cast_fp16)[name = tensor<string, []>("op_753_cast_fp16")];
            tensor<fp16, [1, 160, 32, 32]> input_243_cast_fp16 = add(x = input_229_cast_fp16, y = var_753_cast_fp16)[name = tensor<string, []>("input_243_cast_fp16")];
            tensor<int32, [2]> var_761 = const()[name = tensor<string, []>("op_761"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_763 = const()[name = tensor<string, []>("op_763"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_245_pad_type_0 = const()[name = tensor<string, []>("input_245_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_245_pad_0 = const()[name = tensor<string, []>("input_245_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [160, 1, 3, 3]> original_model_image_encoder_model_network_2_10_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_10_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [160, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3720320)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_2_10_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_10_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3723264)))];
            tensor<fp16, [1, 160, 32, 32]> input_245_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_10_token_mixer_reparam_conv_bias_to_fp16, dilations = var_763, groups = var_16, pad = input_245_pad_0, pad_type = input_245_pad_type_0, strides = var_761, weight = original_model_image_encoder_model_network_2_10_token_mixer_reparam_conv_weight_to_fp16, x = input_243_cast_fp16)[name = tensor<string, []>("input_245_cast_fp16")];
            tensor<int32, [2]> var_772 = const()[name = tensor<string, []>("op_772"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_774 = const()[name = tensor<string, []>("op_774"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_247_pad_type_0 = const()[name = tensor<string, []>("input_247_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_247_pad_0 = const()[name = tensor<string, []>("input_247_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [160, 1, 7, 7]> input_249_weight_0_to_fp16 = const()[name = tensor<string, []>("input_249_weight_0_to_fp16"), val = tensor<fp16, [160, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3723648)))];
            tensor<fp16, [160]> input_249_bias_0_to_fp16 = const()[name = tensor<string, []>("input_249_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3739392)))];
            tensor<fp16, [1, 160, 32, 32]> input_249_cast_fp16 = conv(bias = input_249_bias_0_to_fp16, dilations = var_774, groups = var_16, pad = input_247_pad_0, pad_type = input_247_pad_type_0, strides = var_772, weight = input_249_weight_0_to_fp16, x = input_245_cast_fp16)[name = tensor<string, []>("input_249_cast_fp16")];
            tensor<int32, [2]> var_784 = const()[name = tensor<string, []>("op_784"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_786 = const()[name = tensor<string, []>("op_786"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_251_pad_type_0 = const()[name = tensor<string, []>("input_251_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_251_pad_0 = const()[name = tensor<string, []>("input_251_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [480, 160, 1, 1]> original_model_image_encoder_model_network_2_10_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_10_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [480, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3739776)))];
            tensor<fp16, [480]> original_model_image_encoder_model_network_2_10_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_10_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3893440)))];
            tensor<fp16, [1, 480, 32, 32]> input_251_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_10_convffn_fc1_bias_to_fp16, dilations = var_786, groups = var_8, pad = input_251_pad_0, pad_type = input_251_pad_type_0, strides = var_784, weight = original_model_image_encoder_model_network_2_10_convffn_fc1_weight_to_fp16, x = input_249_cast_fp16)[name = tensor<string, []>("input_251_cast_fp16")];
            tensor<string, []> input_253_mode_0 = const()[name = tensor<string, []>("input_253_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 480, 32, 32]> input_253_cast_fp16 = gelu(mode = input_253_mode_0, x = input_251_cast_fp16)[name = tensor<string, []>("input_253_cast_fp16")];
            tensor<int32, [2]> var_793 = const()[name = tensor<string, []>("op_793"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_795 = const()[name = tensor<string, []>("op_795"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_257_pad_type_0 = const()[name = tensor<string, []>("input_257_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_257_pad_0 = const()[name = tensor<string, []>("input_257_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 480, 1, 1]> var_799_weight_0_to_fp16 = const()[name = tensor<string, []>("op_799_weight_0_to_fp16"), val = tensor<fp16, [160, 480, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3894464)))];
            tensor<fp16, [160]> var_799_bias_0_to_fp16 = const()[name = tensor<string, []>("op_799_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4048128)))];
            tensor<fp16, [1, 160, 32, 32]> var_799_cast_fp16 = conv(bias = var_799_bias_0_to_fp16, dilations = var_795, groups = var_8, pad = input_257_pad_0, pad_type = input_257_pad_type_0, strides = var_793, weight = var_799_weight_0_to_fp16, x = input_253_cast_fp16)[name = tensor<string, []>("op_799_cast_fp16")];
            tensor<fp16, [1, 160, 32, 32]> input_259_cast_fp16 = add(x = input_245_cast_fp16, y = var_799_cast_fp16)[name = tensor<string, []>("input_259_cast_fp16")];
            tensor<int32, [2]> var_807 = const()[name = tensor<string, []>("op_807"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_809 = const()[name = tensor<string, []>("op_809"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_261_pad_type_0 = const()[name = tensor<string, []>("input_261_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_261_pad_0 = const()[name = tensor<string, []>("input_261_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [160, 1, 3, 3]> original_model_image_encoder_model_network_2_11_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_11_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [160, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4048512)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_2_11_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_11_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4051456)))];
            tensor<fp16, [1, 160, 32, 32]> input_261_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_11_token_mixer_reparam_conv_bias_to_fp16, dilations = var_809, groups = var_16, pad = input_261_pad_0, pad_type = input_261_pad_type_0, strides = var_807, weight = original_model_image_encoder_model_network_2_11_token_mixer_reparam_conv_weight_to_fp16, x = input_259_cast_fp16)[name = tensor<string, []>("input_261_cast_fp16")];
            tensor<int32, [2]> var_818 = const()[name = tensor<string, []>("op_818"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_820 = const()[name = tensor<string, []>("op_820"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_263_pad_type_0 = const()[name = tensor<string, []>("input_263_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_263_pad_0 = const()[name = tensor<string, []>("input_263_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [160, 1, 7, 7]> input_265_weight_0_to_fp16 = const()[name = tensor<string, []>("input_265_weight_0_to_fp16"), val = tensor<fp16, [160, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4051840)))];
            tensor<fp16, [160]> input_265_bias_0_to_fp16 = const()[name = tensor<string, []>("input_265_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4067584)))];
            tensor<fp16, [1, 160, 32, 32]> input_265_cast_fp16 = conv(bias = input_265_bias_0_to_fp16, dilations = var_820, groups = var_16, pad = input_263_pad_0, pad_type = input_263_pad_type_0, strides = var_818, weight = input_265_weight_0_to_fp16, x = input_261_cast_fp16)[name = tensor<string, []>("input_265_cast_fp16")];
            tensor<int32, [2]> var_830 = const()[name = tensor<string, []>("op_830"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_832 = const()[name = tensor<string, []>("op_832"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_267_pad_type_0 = const()[name = tensor<string, []>("input_267_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_267_pad_0 = const()[name = tensor<string, []>("input_267_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [480, 160, 1, 1]> original_model_image_encoder_model_network_2_11_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_11_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [480, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4067968)))];
            tensor<fp16, [480]> original_model_image_encoder_model_network_2_11_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_2_11_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4221632)))];
            tensor<fp16, [1, 480, 32, 32]> input_267_cast_fp16 = conv(bias = original_model_image_encoder_model_network_2_11_convffn_fc1_bias_to_fp16, dilations = var_832, groups = var_8, pad = input_267_pad_0, pad_type = input_267_pad_type_0, strides = var_830, weight = original_model_image_encoder_model_network_2_11_convffn_fc1_weight_to_fp16, x = input_265_cast_fp16)[name = tensor<string, []>("input_267_cast_fp16")];
            tensor<string, []> input_269_mode_0 = const()[name = tensor<string, []>("input_269_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 480, 32, 32]> input_269_cast_fp16 = gelu(mode = input_269_mode_0, x = input_267_cast_fp16)[name = tensor<string, []>("input_269_cast_fp16")];
            tensor<int32, [2]> var_839 = const()[name = tensor<string, []>("op_839"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_841 = const()[name = tensor<string, []>("op_841"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_273_pad_type_0 = const()[name = tensor<string, []>("input_273_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_273_pad_0 = const()[name = tensor<string, []>("input_273_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 480, 1, 1]> var_845_weight_0_to_fp16 = const()[name = tensor<string, []>("op_845_weight_0_to_fp16"), val = tensor<fp16, [160, 480, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4222656)))];
            tensor<fp16, [160]> var_845_bias_0_to_fp16 = const()[name = tensor<string, []>("op_845_bias_0_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4376320)))];
            tensor<fp16, [1, 160, 32, 32]> var_845_cast_fp16 = conv(bias = var_845_bias_0_to_fp16, dilations = var_841, groups = var_8, pad = input_273_pad_0, pad_type = input_273_pad_type_0, strides = var_839, weight = var_845_weight_0_to_fp16, x = input_269_cast_fp16)[name = tensor<string, []>("op_845_cast_fp16")];
            tensor<fp16, [1, 160, 32, 32]> input_275_cast_fp16 = add(x = input_261_cast_fp16, y = var_845_cast_fp16)[name = tensor<string, []>("input_275_cast_fp16")];
            tensor<int32, [2]> var_854 = const()[name = tensor<string, []>("op_854"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_856 = const()[name = tensor<string, []>("op_856"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> x_1_pad_type_0 = const()[name = tensor<string, []>("x_1_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> x_1_pad_0 = const()[name = tensor<string, []>("x_1_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> original_model_image_encoder_model_network_3_proj_0_lkb_reparam_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_3_proj_0_lkb_reparam_weight_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4376704)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_3_proj_0_lkb_reparam_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_3_proj_0_lkb_reparam_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4408128)))];
            tensor<fp16, [1, 320, 16, 16]> x_1_cast_fp16 = conv(bias = original_model_image_encoder_model_network_3_proj_0_lkb_reparam_bias_to_fp16, dilations = var_856, groups = var_16, pad = x_1_pad_0, pad_type = x_1_pad_type_0, strides = var_854, weight = original_model_image_encoder_model_network_3_proj_0_lkb_reparam_weight_to_fp16, x = input_275_cast_fp16)[name = tensor<string, []>("x_1_cast_fp16")];
            tensor<int32, [2]> var_861 = const()[name = tensor<string, []>("op_861"), val = tensor<int32, [2]>([2, 3])];
            tensor<fp16, [1, 320, 1, 1]> input_277_cast_fp16 = reduce_mean(axes = var_861, keep_dims = var_5, x = x_1_cast_fp16)[name = tensor<string, []>("input_277_cast_fp16")];
            tensor<int32, [2]> var_865 = const()[name = tensor<string, []>("op_865"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_867 = const()[name = tensor<string, []>("op_867"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_279_pad_type_0 = const()[name = tensor<string, []>("input_279_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_279_pad_0 = const()[name = tensor<string, []>("input_279_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [80, 320, 1, 1]> original_model_image_encoder_model_network_3_proj_0_se_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_3_proj_0_se_fc1_weight_to_fp16"), val = tensor<fp16, [80, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4408832)))];
            tensor<fp16, [80]> original_model_image_encoder_model_network_3_proj_0_se_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_3_proj_0_se_fc1_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4460096)))];
            tensor<fp16, [1, 80, 1, 1]> input_279_cast_fp16 = conv(bias = original_model_image_encoder_model_network_3_proj_0_se_fc1_bias_to_fp16, dilations = var_867, groups = var_8, pad = input_279_pad_0, pad_type = input_279_pad_type_0, strides = var_865, weight = original_model_image_encoder_model_network_3_proj_0_se_fc1_weight_to_fp16, x = input_277_cast_fp16)[name = tensor<string, []>("input_279_cast_fp16")];
            tensor<fp16, [1, 80, 1, 1]> input_281_cast_fp16 = relu(x = input_279_cast_fp16)[name = tensor<string, []>("input_281_cast_fp16")];
            tensor<int32, [2]> var_873 = const()[name = tensor<string, []>("op_873"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_875 = const()[name = tensor<string, []>("op_875"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> x_3_pad_type_0 = const()[name = tensor<string, []>("x_3_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> x_3_pad_0 = const()[name = tensor<string, []>("x_3_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 80, 1, 1]> original_model_image_encoder_model_network_3_proj_0_se_fc2_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_3_proj_0_se_fc2_weight_to_fp16"), val = tensor<fp16, [320, 80, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4460352)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_3_proj_0_se_fc2_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_3_proj_0_se_fc2_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4511616)))];
            tensor<fp16, [1, 320, 1, 1]> x_3_cast_fp16 = conv(bias = original_model_image_encoder_model_network_3_proj_0_se_fc2_bias_to_fp16, dilations = var_875, groups = var_8, pad = x_3_pad_0, pad_type = x_3_pad_type_0, strides = var_873, weight = original_model_image_encoder_model_network_3_proj_0_se_fc2_weight_to_fp16, x = input_281_cast_fp16)[name = tensor<string, []>("x_3_cast_fp16")];
            tensor<fp16, [1, 320, 1, 1]> var_878_cast_fp16 = sigmoid(x = x_3_cast_fp16)[name = tensor<string, []>("op_878_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_283_cast_fp16 = mul(x = x_1_cast_fp16, y = var_878_cast_fp16)[name = tensor<string, []>("input_283_cast_fp16")];
            tensor<string, []> input_285_mode_0 = const()[name = tensor<string, []>("input_285_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 320, 16, 16]> input_285_cast_fp16 = gelu(mode = input_285_mode_0, x = input_283_cast_fp16)[name = tensor<string, []>("input_285_cast_fp16")];
            tensor<int32, [2]> var_884 = const()[name = tensor<string, []>("op_884"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_886 = const()[name = tensor<string, []>("op_886"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_287_pad_type_0 = const()[name = tensor<string, []>("input_287_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_287_pad_0 = const()[name = tensor<string, []>("input_287_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 320, 1, 1]> original_model_image_encoder_model_network_3_proj_1_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_3_proj_1_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4512320)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_3_proj_1_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_3_proj_1_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4717184)))];
            tensor<fp16, [1, 320, 16, 16]> input_287_cast_fp16 = conv(bias = original_model_image_encoder_model_network_3_proj_1_reparam_conv_bias_to_fp16, dilations = var_886, groups = var_8, pad = input_287_pad_0, pad_type = input_287_pad_type_0, strides = var_884, weight = original_model_image_encoder_model_network_3_proj_1_reparam_conv_weight_to_fp16, x = input_285_cast_fp16)[name = tensor<string, []>("input_287_cast_fp16")];
            tensor<string, []> input_289_mode_0 = const()[name = tensor<string, []>("input_289_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 320, 16, 16]> input_289_cast_fp16 = gelu(mode = input_289_mode_0, x = input_287_cast_fp16)[name = tensor<string, []>("input_289_cast_fp16")];
            tensor<int32, [2]> var_920 = const()[name = tensor<string, []>("op_920"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_922 = const()[name = tensor<string, []>("op_922"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_291_pad_type_0 = const()[name = tensor<string, []>("input_291_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_291_pad_0 = const()[name = tensor<string, []>("input_291_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_0_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_0_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4717888)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_0_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_0_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4723712)))];
            tensor<fp16, [1, 320, 16, 16]> input_291_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_0_token_mixer_reparam_conv_bias_to_fp16, dilations = var_922, groups = var_17, pad = input_291_pad_0, pad_type = input_291_pad_type_0, strides = var_920, weight = original_model_image_encoder_model_network_4_0_token_mixer_reparam_conv_weight_to_fp16, x = input_289_cast_fp16)[name = tensor<string, []>("input_291_cast_fp16")];
            tensor<int32, [2]> var_931 = const()[name = tensor<string, []>("op_931"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_933 = const()[name = tensor<string, []>("op_933"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_293_pad_type_0 = const()[name = tensor<string, []>("input_293_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_293_pad_0 = const()[name = tensor<string, []>("input_293_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_295_weight_0_to_fp16 = const()[name = tensor<string, []>("input_295_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4724416)))];
            tensor<fp16, [320]> input_295_bias_0_to_fp16 = const()[name = tensor<string, []>("input_295_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4755840)))];
            tensor<fp16, [1, 320, 16, 16]> input_295_cast_fp16 = conv(bias = input_295_bias_0_to_fp16, dilations = var_933, groups = var_17, pad = input_293_pad_0, pad_type = input_293_pad_type_0, strides = var_931, weight = input_295_weight_0_to_fp16, x = input_291_cast_fp16)[name = tensor<string, []>("input_295_cast_fp16")];
            tensor<int32, [2]> var_943 = const()[name = tensor<string, []>("op_943"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_945 = const()[name = tensor<string, []>("op_945"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_297_pad_type_0 = const()[name = tensor<string, []>("input_297_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_297_pad_0 = const()[name = tensor<string, []>("input_297_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_0_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_0_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4756544)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_0_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_0_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5371008)))];
            tensor<fp16, [1, 960, 16, 16]> input_297_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_0_convffn_fc1_bias_to_fp16, dilations = var_945, groups = var_8, pad = input_297_pad_0, pad_type = input_297_pad_type_0, strides = var_943, weight = original_model_image_encoder_model_network_4_0_convffn_fc1_weight_to_fp16, x = input_295_cast_fp16)[name = tensor<string, []>("input_297_cast_fp16")];
            tensor<string, []> input_299_mode_0 = const()[name = tensor<string, []>("input_299_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_299_cast_fp16 = gelu(mode = input_299_mode_0, x = input_297_cast_fp16)[name = tensor<string, []>("input_299_cast_fp16")];
            tensor<int32, [2]> var_952 = const()[name = tensor<string, []>("op_952"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_954 = const()[name = tensor<string, []>("op_954"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_303_pad_type_0 = const()[name = tensor<string, []>("input_303_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_303_pad_0 = const()[name = tensor<string, []>("input_303_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_958_weight_0_to_fp16 = const()[name = tensor<string, []>("op_958_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5372992)))];
            tensor<fp16, [320]> var_958_bias_0_to_fp16 = const()[name = tensor<string, []>("op_958_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5987456)))];
            tensor<fp16, [1, 320, 16, 16]> var_958_cast_fp16 = conv(bias = var_958_bias_0_to_fp16, dilations = var_954, groups = var_8, pad = input_303_pad_0, pad_type = input_303_pad_type_0, strides = var_952, weight = var_958_weight_0_to_fp16, x = input_299_cast_fp16)[name = tensor<string, []>("op_958_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_305_cast_fp16 = add(x = input_291_cast_fp16, y = var_958_cast_fp16)[name = tensor<string, []>("input_305_cast_fp16")];
            tensor<int32, [2]> var_966 = const()[name = tensor<string, []>("op_966"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_968 = const()[name = tensor<string, []>("op_968"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_307_pad_type_0 = const()[name = tensor<string, []>("input_307_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_307_pad_0 = const()[name = tensor<string, []>("input_307_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_1_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_1_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5988160)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_1_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_1_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5993984)))];
            tensor<fp16, [1, 320, 16, 16]> input_307_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_1_token_mixer_reparam_conv_bias_to_fp16, dilations = var_968, groups = var_17, pad = input_307_pad_0, pad_type = input_307_pad_type_0, strides = var_966, weight = original_model_image_encoder_model_network_4_1_token_mixer_reparam_conv_weight_to_fp16, x = input_305_cast_fp16)[name = tensor<string, []>("input_307_cast_fp16")];
            tensor<int32, [2]> var_977 = const()[name = tensor<string, []>("op_977"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_979 = const()[name = tensor<string, []>("op_979"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_309_pad_type_0 = const()[name = tensor<string, []>("input_309_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_309_pad_0 = const()[name = tensor<string, []>("input_309_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_311_weight_0_to_fp16 = const()[name = tensor<string, []>("input_311_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5994688)))];
            tensor<fp16, [320]> input_311_bias_0_to_fp16 = const()[name = tensor<string, []>("input_311_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6026112)))];
            tensor<fp16, [1, 320, 16, 16]> input_311_cast_fp16 = conv(bias = input_311_bias_0_to_fp16, dilations = var_979, groups = var_17, pad = input_309_pad_0, pad_type = input_309_pad_type_0, strides = var_977, weight = input_311_weight_0_to_fp16, x = input_307_cast_fp16)[name = tensor<string, []>("input_311_cast_fp16")];
            tensor<int32, [2]> var_989 = const()[name = tensor<string, []>("op_989"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_991 = const()[name = tensor<string, []>("op_991"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_313_pad_type_0 = const()[name = tensor<string, []>("input_313_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_313_pad_0 = const()[name = tensor<string, []>("input_313_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_1_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_1_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6026816)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_1_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_1_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6641280)))];
            tensor<fp16, [1, 960, 16, 16]> input_313_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_1_convffn_fc1_bias_to_fp16, dilations = var_991, groups = var_8, pad = input_313_pad_0, pad_type = input_313_pad_type_0, strides = var_989, weight = original_model_image_encoder_model_network_4_1_convffn_fc1_weight_to_fp16, x = input_311_cast_fp16)[name = tensor<string, []>("input_313_cast_fp16")];
            tensor<string, []> input_315_mode_0 = const()[name = tensor<string, []>("input_315_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_315_cast_fp16 = gelu(mode = input_315_mode_0, x = input_313_cast_fp16)[name = tensor<string, []>("input_315_cast_fp16")];
            tensor<int32, [2]> var_998 = const()[name = tensor<string, []>("op_998"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1000 = const()[name = tensor<string, []>("op_1000"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_319_pad_type_0 = const()[name = tensor<string, []>("input_319_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_319_pad_0 = const()[name = tensor<string, []>("input_319_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1004_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1004_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6643264)))];
            tensor<fp16, [320]> var_1004_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1004_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7257728)))];
            tensor<fp16, [1, 320, 16, 16]> var_1004_cast_fp16 = conv(bias = var_1004_bias_0_to_fp16, dilations = var_1000, groups = var_8, pad = input_319_pad_0, pad_type = input_319_pad_type_0, strides = var_998, weight = var_1004_weight_0_to_fp16, x = input_315_cast_fp16)[name = tensor<string, []>("op_1004_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_321_cast_fp16 = add(x = input_307_cast_fp16, y = var_1004_cast_fp16)[name = tensor<string, []>("input_321_cast_fp16")];
            tensor<int32, [2]> var_1012 = const()[name = tensor<string, []>("op_1012"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1014 = const()[name = tensor<string, []>("op_1014"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_323_pad_type_0 = const()[name = tensor<string, []>("input_323_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_323_pad_0 = const()[name = tensor<string, []>("input_323_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_2_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_2_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7258432)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_2_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_2_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7264256)))];
            tensor<fp16, [1, 320, 16, 16]> input_323_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_2_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1014, groups = var_17, pad = input_323_pad_0, pad_type = input_323_pad_type_0, strides = var_1012, weight = original_model_image_encoder_model_network_4_2_token_mixer_reparam_conv_weight_to_fp16, x = input_321_cast_fp16)[name = tensor<string, []>("input_323_cast_fp16")];
            tensor<int32, [2]> var_1023 = const()[name = tensor<string, []>("op_1023"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1025 = const()[name = tensor<string, []>("op_1025"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_325_pad_type_0 = const()[name = tensor<string, []>("input_325_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_325_pad_0 = const()[name = tensor<string, []>("input_325_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_327_weight_0_to_fp16 = const()[name = tensor<string, []>("input_327_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7264960)))];
            tensor<fp16, [320]> input_327_bias_0_to_fp16 = const()[name = tensor<string, []>("input_327_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7296384)))];
            tensor<fp16, [1, 320, 16, 16]> input_327_cast_fp16 = conv(bias = input_327_bias_0_to_fp16, dilations = var_1025, groups = var_17, pad = input_325_pad_0, pad_type = input_325_pad_type_0, strides = var_1023, weight = input_327_weight_0_to_fp16, x = input_323_cast_fp16)[name = tensor<string, []>("input_327_cast_fp16")];
            tensor<int32, [2]> var_1035 = const()[name = tensor<string, []>("op_1035"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1037 = const()[name = tensor<string, []>("op_1037"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_329_pad_type_0 = const()[name = tensor<string, []>("input_329_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_329_pad_0 = const()[name = tensor<string, []>("input_329_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_2_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_2_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7297088)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_2_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_2_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7911552)))];
            tensor<fp16, [1, 960, 16, 16]> input_329_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_2_convffn_fc1_bias_to_fp16, dilations = var_1037, groups = var_8, pad = input_329_pad_0, pad_type = input_329_pad_type_0, strides = var_1035, weight = original_model_image_encoder_model_network_4_2_convffn_fc1_weight_to_fp16, x = input_327_cast_fp16)[name = tensor<string, []>("input_329_cast_fp16")];
            tensor<string, []> input_331_mode_0 = const()[name = tensor<string, []>("input_331_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_331_cast_fp16 = gelu(mode = input_331_mode_0, x = input_329_cast_fp16)[name = tensor<string, []>("input_331_cast_fp16")];
            tensor<int32, [2]> var_1044 = const()[name = tensor<string, []>("op_1044"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1046 = const()[name = tensor<string, []>("op_1046"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_335_pad_type_0 = const()[name = tensor<string, []>("input_335_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_335_pad_0 = const()[name = tensor<string, []>("input_335_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1050_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1050_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7913536)))];
            tensor<fp16, [320]> var_1050_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1050_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8528000)))];
            tensor<fp16, [1, 320, 16, 16]> var_1050_cast_fp16 = conv(bias = var_1050_bias_0_to_fp16, dilations = var_1046, groups = var_8, pad = input_335_pad_0, pad_type = input_335_pad_type_0, strides = var_1044, weight = var_1050_weight_0_to_fp16, x = input_331_cast_fp16)[name = tensor<string, []>("op_1050_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_337_cast_fp16 = add(x = input_323_cast_fp16, y = var_1050_cast_fp16)[name = tensor<string, []>("input_337_cast_fp16")];
            tensor<int32, [2]> var_1058 = const()[name = tensor<string, []>("op_1058"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1060 = const()[name = tensor<string, []>("op_1060"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_339_pad_type_0 = const()[name = tensor<string, []>("input_339_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_339_pad_0 = const()[name = tensor<string, []>("input_339_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_3_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_3_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8528704)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_3_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_3_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8534528)))];
            tensor<fp16, [1, 320, 16, 16]> input_339_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_3_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1060, groups = var_17, pad = input_339_pad_0, pad_type = input_339_pad_type_0, strides = var_1058, weight = original_model_image_encoder_model_network_4_3_token_mixer_reparam_conv_weight_to_fp16, x = input_337_cast_fp16)[name = tensor<string, []>("input_339_cast_fp16")];
            tensor<int32, [2]> var_1069 = const()[name = tensor<string, []>("op_1069"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1071 = const()[name = tensor<string, []>("op_1071"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_341_pad_type_0 = const()[name = tensor<string, []>("input_341_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_341_pad_0 = const()[name = tensor<string, []>("input_341_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_343_weight_0_to_fp16 = const()[name = tensor<string, []>("input_343_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8535232)))];
            tensor<fp16, [320]> input_343_bias_0_to_fp16 = const()[name = tensor<string, []>("input_343_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8566656)))];
            tensor<fp16, [1, 320, 16, 16]> input_343_cast_fp16 = conv(bias = input_343_bias_0_to_fp16, dilations = var_1071, groups = var_17, pad = input_341_pad_0, pad_type = input_341_pad_type_0, strides = var_1069, weight = input_343_weight_0_to_fp16, x = input_339_cast_fp16)[name = tensor<string, []>("input_343_cast_fp16")];
            tensor<int32, [2]> var_1081 = const()[name = tensor<string, []>("op_1081"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1083 = const()[name = tensor<string, []>("op_1083"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_345_pad_type_0 = const()[name = tensor<string, []>("input_345_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_345_pad_0 = const()[name = tensor<string, []>("input_345_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_3_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_3_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8567360)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_3_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_3_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9181824)))];
            tensor<fp16, [1, 960, 16, 16]> input_345_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_3_convffn_fc1_bias_to_fp16, dilations = var_1083, groups = var_8, pad = input_345_pad_0, pad_type = input_345_pad_type_0, strides = var_1081, weight = original_model_image_encoder_model_network_4_3_convffn_fc1_weight_to_fp16, x = input_343_cast_fp16)[name = tensor<string, []>("input_345_cast_fp16")];
            tensor<string, []> input_347_mode_0 = const()[name = tensor<string, []>("input_347_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_347_cast_fp16 = gelu(mode = input_347_mode_0, x = input_345_cast_fp16)[name = tensor<string, []>("input_347_cast_fp16")];
            tensor<int32, [2]> var_1090 = const()[name = tensor<string, []>("op_1090"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1092 = const()[name = tensor<string, []>("op_1092"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_351_pad_type_0 = const()[name = tensor<string, []>("input_351_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_351_pad_0 = const()[name = tensor<string, []>("input_351_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1096_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1096_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9183808)))];
            tensor<fp16, [320]> var_1096_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1096_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9798272)))];
            tensor<fp16, [1, 320, 16, 16]> var_1096_cast_fp16 = conv(bias = var_1096_bias_0_to_fp16, dilations = var_1092, groups = var_8, pad = input_351_pad_0, pad_type = input_351_pad_type_0, strides = var_1090, weight = var_1096_weight_0_to_fp16, x = input_347_cast_fp16)[name = tensor<string, []>("op_1096_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_353_cast_fp16 = add(x = input_339_cast_fp16, y = var_1096_cast_fp16)[name = tensor<string, []>("input_353_cast_fp16")];
            tensor<int32, [2]> var_1104 = const()[name = tensor<string, []>("op_1104"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1106 = const()[name = tensor<string, []>("op_1106"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_355_pad_type_0 = const()[name = tensor<string, []>("input_355_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_355_pad_0 = const()[name = tensor<string, []>("input_355_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_4_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_4_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9798976)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_4_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_4_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9804800)))];
            tensor<fp16, [1, 320, 16, 16]> input_355_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_4_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1106, groups = var_17, pad = input_355_pad_0, pad_type = input_355_pad_type_0, strides = var_1104, weight = original_model_image_encoder_model_network_4_4_token_mixer_reparam_conv_weight_to_fp16, x = input_353_cast_fp16)[name = tensor<string, []>("input_355_cast_fp16")];
            tensor<int32, [2]> var_1115 = const()[name = tensor<string, []>("op_1115"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1117 = const()[name = tensor<string, []>("op_1117"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_357_pad_type_0 = const()[name = tensor<string, []>("input_357_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_357_pad_0 = const()[name = tensor<string, []>("input_357_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_359_weight_0_to_fp16 = const()[name = tensor<string, []>("input_359_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9805504)))];
            tensor<fp16, [320]> input_359_bias_0_to_fp16 = const()[name = tensor<string, []>("input_359_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9836928)))];
            tensor<fp16, [1, 320, 16, 16]> input_359_cast_fp16 = conv(bias = input_359_bias_0_to_fp16, dilations = var_1117, groups = var_17, pad = input_357_pad_0, pad_type = input_357_pad_type_0, strides = var_1115, weight = input_359_weight_0_to_fp16, x = input_355_cast_fp16)[name = tensor<string, []>("input_359_cast_fp16")];
            tensor<int32, [2]> var_1127 = const()[name = tensor<string, []>("op_1127"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1129 = const()[name = tensor<string, []>("op_1129"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_361_pad_type_0 = const()[name = tensor<string, []>("input_361_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_361_pad_0 = const()[name = tensor<string, []>("input_361_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_4_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_4_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9837632)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_4_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_4_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10452096)))];
            tensor<fp16, [1, 960, 16, 16]> input_361_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_4_convffn_fc1_bias_to_fp16, dilations = var_1129, groups = var_8, pad = input_361_pad_0, pad_type = input_361_pad_type_0, strides = var_1127, weight = original_model_image_encoder_model_network_4_4_convffn_fc1_weight_to_fp16, x = input_359_cast_fp16)[name = tensor<string, []>("input_361_cast_fp16")];
            tensor<string, []> input_363_mode_0 = const()[name = tensor<string, []>("input_363_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_363_cast_fp16 = gelu(mode = input_363_mode_0, x = input_361_cast_fp16)[name = tensor<string, []>("input_363_cast_fp16")];
            tensor<int32, [2]> var_1136 = const()[name = tensor<string, []>("op_1136"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1138 = const()[name = tensor<string, []>("op_1138"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_367_pad_type_0 = const()[name = tensor<string, []>("input_367_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_367_pad_0 = const()[name = tensor<string, []>("input_367_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1142_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1142_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10454080)))];
            tensor<fp16, [320]> var_1142_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1142_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11068544)))];
            tensor<fp16, [1, 320, 16, 16]> var_1142_cast_fp16 = conv(bias = var_1142_bias_0_to_fp16, dilations = var_1138, groups = var_8, pad = input_367_pad_0, pad_type = input_367_pad_type_0, strides = var_1136, weight = var_1142_weight_0_to_fp16, x = input_363_cast_fp16)[name = tensor<string, []>("op_1142_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_369_cast_fp16 = add(x = input_355_cast_fp16, y = var_1142_cast_fp16)[name = tensor<string, []>("input_369_cast_fp16")];
            tensor<int32, [2]> var_1150 = const()[name = tensor<string, []>("op_1150"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1152 = const()[name = tensor<string, []>("op_1152"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_371_pad_type_0 = const()[name = tensor<string, []>("input_371_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_371_pad_0 = const()[name = tensor<string, []>("input_371_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_5_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_5_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11069248)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_5_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_5_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11075072)))];
            tensor<fp16, [1, 320, 16, 16]> input_371_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_5_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1152, groups = var_17, pad = input_371_pad_0, pad_type = input_371_pad_type_0, strides = var_1150, weight = original_model_image_encoder_model_network_4_5_token_mixer_reparam_conv_weight_to_fp16, x = input_369_cast_fp16)[name = tensor<string, []>("input_371_cast_fp16")];
            tensor<int32, [2]> var_1161 = const()[name = tensor<string, []>("op_1161"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1163 = const()[name = tensor<string, []>("op_1163"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_373_pad_type_0 = const()[name = tensor<string, []>("input_373_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_373_pad_0 = const()[name = tensor<string, []>("input_373_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_375_weight_0_to_fp16 = const()[name = tensor<string, []>("input_375_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11075776)))];
            tensor<fp16, [320]> input_375_bias_0_to_fp16 = const()[name = tensor<string, []>("input_375_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11107200)))];
            tensor<fp16, [1, 320, 16, 16]> input_375_cast_fp16 = conv(bias = input_375_bias_0_to_fp16, dilations = var_1163, groups = var_17, pad = input_373_pad_0, pad_type = input_373_pad_type_0, strides = var_1161, weight = input_375_weight_0_to_fp16, x = input_371_cast_fp16)[name = tensor<string, []>("input_375_cast_fp16")];
            tensor<int32, [2]> var_1173 = const()[name = tensor<string, []>("op_1173"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1175 = const()[name = tensor<string, []>("op_1175"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_377_pad_type_0 = const()[name = tensor<string, []>("input_377_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_377_pad_0 = const()[name = tensor<string, []>("input_377_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_5_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_5_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11107904)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_5_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_5_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11722368)))];
            tensor<fp16, [1, 960, 16, 16]> input_377_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_5_convffn_fc1_bias_to_fp16, dilations = var_1175, groups = var_8, pad = input_377_pad_0, pad_type = input_377_pad_type_0, strides = var_1173, weight = original_model_image_encoder_model_network_4_5_convffn_fc1_weight_to_fp16, x = input_375_cast_fp16)[name = tensor<string, []>("input_377_cast_fp16")];
            tensor<string, []> input_379_mode_0 = const()[name = tensor<string, []>("input_379_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_379_cast_fp16 = gelu(mode = input_379_mode_0, x = input_377_cast_fp16)[name = tensor<string, []>("input_379_cast_fp16")];
            tensor<int32, [2]> var_1182 = const()[name = tensor<string, []>("op_1182"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1184 = const()[name = tensor<string, []>("op_1184"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_383_pad_type_0 = const()[name = tensor<string, []>("input_383_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_383_pad_0 = const()[name = tensor<string, []>("input_383_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1188_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1188_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11724352)))];
            tensor<fp16, [320]> var_1188_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1188_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12338816)))];
            tensor<fp16, [1, 320, 16, 16]> var_1188_cast_fp16 = conv(bias = var_1188_bias_0_to_fp16, dilations = var_1184, groups = var_8, pad = input_383_pad_0, pad_type = input_383_pad_type_0, strides = var_1182, weight = var_1188_weight_0_to_fp16, x = input_379_cast_fp16)[name = tensor<string, []>("op_1188_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_385_cast_fp16 = add(x = input_371_cast_fp16, y = var_1188_cast_fp16)[name = tensor<string, []>("input_385_cast_fp16")];
            tensor<int32, [2]> var_1196 = const()[name = tensor<string, []>("op_1196"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1198 = const()[name = tensor<string, []>("op_1198"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_387_pad_type_0 = const()[name = tensor<string, []>("input_387_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_387_pad_0 = const()[name = tensor<string, []>("input_387_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_6_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_6_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12339520)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_6_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_6_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12345344)))];
            tensor<fp16, [1, 320, 16, 16]> input_387_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_6_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1198, groups = var_17, pad = input_387_pad_0, pad_type = input_387_pad_type_0, strides = var_1196, weight = original_model_image_encoder_model_network_4_6_token_mixer_reparam_conv_weight_to_fp16, x = input_385_cast_fp16)[name = tensor<string, []>("input_387_cast_fp16")];
            tensor<int32, [2]> var_1207 = const()[name = tensor<string, []>("op_1207"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1209 = const()[name = tensor<string, []>("op_1209"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_389_pad_type_0 = const()[name = tensor<string, []>("input_389_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_389_pad_0 = const()[name = tensor<string, []>("input_389_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_391_weight_0_to_fp16 = const()[name = tensor<string, []>("input_391_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12346048)))];
            tensor<fp16, [320]> input_391_bias_0_to_fp16 = const()[name = tensor<string, []>("input_391_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12377472)))];
            tensor<fp16, [1, 320, 16, 16]> input_391_cast_fp16 = conv(bias = input_391_bias_0_to_fp16, dilations = var_1209, groups = var_17, pad = input_389_pad_0, pad_type = input_389_pad_type_0, strides = var_1207, weight = input_391_weight_0_to_fp16, x = input_387_cast_fp16)[name = tensor<string, []>("input_391_cast_fp16")];
            tensor<int32, [2]> var_1219 = const()[name = tensor<string, []>("op_1219"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1221 = const()[name = tensor<string, []>("op_1221"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_393_pad_type_0 = const()[name = tensor<string, []>("input_393_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_393_pad_0 = const()[name = tensor<string, []>("input_393_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_6_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_6_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12378176)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_6_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_6_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12992640)))];
            tensor<fp16, [1, 960, 16, 16]> input_393_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_6_convffn_fc1_bias_to_fp16, dilations = var_1221, groups = var_8, pad = input_393_pad_0, pad_type = input_393_pad_type_0, strides = var_1219, weight = original_model_image_encoder_model_network_4_6_convffn_fc1_weight_to_fp16, x = input_391_cast_fp16)[name = tensor<string, []>("input_393_cast_fp16")];
            tensor<string, []> input_395_mode_0 = const()[name = tensor<string, []>("input_395_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_395_cast_fp16 = gelu(mode = input_395_mode_0, x = input_393_cast_fp16)[name = tensor<string, []>("input_395_cast_fp16")];
            tensor<int32, [2]> var_1228 = const()[name = tensor<string, []>("op_1228"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1230 = const()[name = tensor<string, []>("op_1230"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_399_pad_type_0 = const()[name = tensor<string, []>("input_399_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_399_pad_0 = const()[name = tensor<string, []>("input_399_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1234_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1234_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12994624)))];
            tensor<fp16, [320]> var_1234_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1234_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13609088)))];
            tensor<fp16, [1, 320, 16, 16]> var_1234_cast_fp16 = conv(bias = var_1234_bias_0_to_fp16, dilations = var_1230, groups = var_8, pad = input_399_pad_0, pad_type = input_399_pad_type_0, strides = var_1228, weight = var_1234_weight_0_to_fp16, x = input_395_cast_fp16)[name = tensor<string, []>("op_1234_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_401_cast_fp16 = add(x = input_387_cast_fp16, y = var_1234_cast_fp16)[name = tensor<string, []>("input_401_cast_fp16")];
            tensor<int32, [2]> var_1242 = const()[name = tensor<string, []>("op_1242"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1244 = const()[name = tensor<string, []>("op_1244"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_403_pad_type_0 = const()[name = tensor<string, []>("input_403_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_403_pad_0 = const()[name = tensor<string, []>("input_403_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_7_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_7_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13609792)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_7_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_7_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13615616)))];
            tensor<fp16, [1, 320, 16, 16]> input_403_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_7_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1244, groups = var_17, pad = input_403_pad_0, pad_type = input_403_pad_type_0, strides = var_1242, weight = original_model_image_encoder_model_network_4_7_token_mixer_reparam_conv_weight_to_fp16, x = input_401_cast_fp16)[name = tensor<string, []>("input_403_cast_fp16")];
            tensor<int32, [2]> var_1253 = const()[name = tensor<string, []>("op_1253"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1255 = const()[name = tensor<string, []>("op_1255"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_405_pad_type_0 = const()[name = tensor<string, []>("input_405_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_405_pad_0 = const()[name = tensor<string, []>("input_405_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_407_weight_0_to_fp16 = const()[name = tensor<string, []>("input_407_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13616320)))];
            tensor<fp16, [320]> input_407_bias_0_to_fp16 = const()[name = tensor<string, []>("input_407_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13647744)))];
            tensor<fp16, [1, 320, 16, 16]> input_407_cast_fp16 = conv(bias = input_407_bias_0_to_fp16, dilations = var_1255, groups = var_17, pad = input_405_pad_0, pad_type = input_405_pad_type_0, strides = var_1253, weight = input_407_weight_0_to_fp16, x = input_403_cast_fp16)[name = tensor<string, []>("input_407_cast_fp16")];
            tensor<int32, [2]> var_1265 = const()[name = tensor<string, []>("op_1265"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1267 = const()[name = tensor<string, []>("op_1267"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_409_pad_type_0 = const()[name = tensor<string, []>("input_409_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_409_pad_0 = const()[name = tensor<string, []>("input_409_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_7_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_7_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13648448)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_7_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_7_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14262912)))];
            tensor<fp16, [1, 960, 16, 16]> input_409_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_7_convffn_fc1_bias_to_fp16, dilations = var_1267, groups = var_8, pad = input_409_pad_0, pad_type = input_409_pad_type_0, strides = var_1265, weight = original_model_image_encoder_model_network_4_7_convffn_fc1_weight_to_fp16, x = input_407_cast_fp16)[name = tensor<string, []>("input_409_cast_fp16")];
            tensor<string, []> input_411_mode_0 = const()[name = tensor<string, []>("input_411_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_411_cast_fp16 = gelu(mode = input_411_mode_0, x = input_409_cast_fp16)[name = tensor<string, []>("input_411_cast_fp16")];
            tensor<int32, [2]> var_1274 = const()[name = tensor<string, []>("op_1274"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1276 = const()[name = tensor<string, []>("op_1276"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_415_pad_type_0 = const()[name = tensor<string, []>("input_415_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_415_pad_0 = const()[name = tensor<string, []>("input_415_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1280_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1280_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14264896)))];
            tensor<fp16, [320]> var_1280_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1280_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14879360)))];
            tensor<fp16, [1, 320, 16, 16]> var_1280_cast_fp16 = conv(bias = var_1280_bias_0_to_fp16, dilations = var_1276, groups = var_8, pad = input_415_pad_0, pad_type = input_415_pad_type_0, strides = var_1274, weight = var_1280_weight_0_to_fp16, x = input_411_cast_fp16)[name = tensor<string, []>("op_1280_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_417_cast_fp16 = add(x = input_403_cast_fp16, y = var_1280_cast_fp16)[name = tensor<string, []>("input_417_cast_fp16")];
            tensor<int32, [2]> var_1288 = const()[name = tensor<string, []>("op_1288"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1290 = const()[name = tensor<string, []>("op_1290"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_419_pad_type_0 = const()[name = tensor<string, []>("input_419_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_419_pad_0 = const()[name = tensor<string, []>("input_419_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_8_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_8_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14880064)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_8_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_8_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14885888)))];
            tensor<fp16, [1, 320, 16, 16]> input_419_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_8_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1290, groups = var_17, pad = input_419_pad_0, pad_type = input_419_pad_type_0, strides = var_1288, weight = original_model_image_encoder_model_network_4_8_token_mixer_reparam_conv_weight_to_fp16, x = input_417_cast_fp16)[name = tensor<string, []>("input_419_cast_fp16")];
            tensor<int32, [2]> var_1299 = const()[name = tensor<string, []>("op_1299"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1301 = const()[name = tensor<string, []>("op_1301"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_421_pad_type_0 = const()[name = tensor<string, []>("input_421_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_421_pad_0 = const()[name = tensor<string, []>("input_421_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_423_weight_0_to_fp16 = const()[name = tensor<string, []>("input_423_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14886592)))];
            tensor<fp16, [320]> input_423_bias_0_to_fp16 = const()[name = tensor<string, []>("input_423_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14918016)))];
            tensor<fp16, [1, 320, 16, 16]> input_423_cast_fp16 = conv(bias = input_423_bias_0_to_fp16, dilations = var_1301, groups = var_17, pad = input_421_pad_0, pad_type = input_421_pad_type_0, strides = var_1299, weight = input_423_weight_0_to_fp16, x = input_419_cast_fp16)[name = tensor<string, []>("input_423_cast_fp16")];
            tensor<int32, [2]> var_1311 = const()[name = tensor<string, []>("op_1311"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1313 = const()[name = tensor<string, []>("op_1313"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_425_pad_type_0 = const()[name = tensor<string, []>("input_425_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_425_pad_0 = const()[name = tensor<string, []>("input_425_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_8_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_8_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14918720)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_8_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_8_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15533184)))];
            tensor<fp16, [1, 960, 16, 16]> input_425_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_8_convffn_fc1_bias_to_fp16, dilations = var_1313, groups = var_8, pad = input_425_pad_0, pad_type = input_425_pad_type_0, strides = var_1311, weight = original_model_image_encoder_model_network_4_8_convffn_fc1_weight_to_fp16, x = input_423_cast_fp16)[name = tensor<string, []>("input_425_cast_fp16")];
            tensor<string, []> input_427_mode_0 = const()[name = tensor<string, []>("input_427_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_427_cast_fp16 = gelu(mode = input_427_mode_0, x = input_425_cast_fp16)[name = tensor<string, []>("input_427_cast_fp16")];
            tensor<int32, [2]> var_1320 = const()[name = tensor<string, []>("op_1320"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1322 = const()[name = tensor<string, []>("op_1322"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_431_pad_type_0 = const()[name = tensor<string, []>("input_431_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_431_pad_0 = const()[name = tensor<string, []>("input_431_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1326_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1326_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15535168)))];
            tensor<fp16, [320]> var_1326_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1326_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16149632)))];
            tensor<fp16, [1, 320, 16, 16]> var_1326_cast_fp16 = conv(bias = var_1326_bias_0_to_fp16, dilations = var_1322, groups = var_8, pad = input_431_pad_0, pad_type = input_431_pad_type_0, strides = var_1320, weight = var_1326_weight_0_to_fp16, x = input_427_cast_fp16)[name = tensor<string, []>("op_1326_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_433_cast_fp16 = add(x = input_419_cast_fp16, y = var_1326_cast_fp16)[name = tensor<string, []>("input_433_cast_fp16")];
            tensor<int32, [2]> var_1334 = const()[name = tensor<string, []>("op_1334"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1336 = const()[name = tensor<string, []>("op_1336"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_435_pad_type_0 = const()[name = tensor<string, []>("input_435_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_435_pad_0 = const()[name = tensor<string, []>("input_435_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_9_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_9_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16150336)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_9_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_9_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16156160)))];
            tensor<fp16, [1, 320, 16, 16]> input_435_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_9_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1336, groups = var_17, pad = input_435_pad_0, pad_type = input_435_pad_type_0, strides = var_1334, weight = original_model_image_encoder_model_network_4_9_token_mixer_reparam_conv_weight_to_fp16, x = input_433_cast_fp16)[name = tensor<string, []>("input_435_cast_fp16")];
            tensor<int32, [2]> var_1345 = const()[name = tensor<string, []>("op_1345"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1347 = const()[name = tensor<string, []>("op_1347"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_437_pad_type_0 = const()[name = tensor<string, []>("input_437_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_437_pad_0 = const()[name = tensor<string, []>("input_437_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_439_weight_0_to_fp16 = const()[name = tensor<string, []>("input_439_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16156864)))];
            tensor<fp16, [320]> input_439_bias_0_to_fp16 = const()[name = tensor<string, []>("input_439_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16188288)))];
            tensor<fp16, [1, 320, 16, 16]> input_439_cast_fp16 = conv(bias = input_439_bias_0_to_fp16, dilations = var_1347, groups = var_17, pad = input_437_pad_0, pad_type = input_437_pad_type_0, strides = var_1345, weight = input_439_weight_0_to_fp16, x = input_435_cast_fp16)[name = tensor<string, []>("input_439_cast_fp16")];
            tensor<int32, [2]> var_1357 = const()[name = tensor<string, []>("op_1357"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1359 = const()[name = tensor<string, []>("op_1359"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_441_pad_type_0 = const()[name = tensor<string, []>("input_441_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_441_pad_0 = const()[name = tensor<string, []>("input_441_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_9_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_9_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16188992)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_9_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_9_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16803456)))];
            tensor<fp16, [1, 960, 16, 16]> input_441_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_9_convffn_fc1_bias_to_fp16, dilations = var_1359, groups = var_8, pad = input_441_pad_0, pad_type = input_441_pad_type_0, strides = var_1357, weight = original_model_image_encoder_model_network_4_9_convffn_fc1_weight_to_fp16, x = input_439_cast_fp16)[name = tensor<string, []>("input_441_cast_fp16")];
            tensor<string, []> input_443_mode_0 = const()[name = tensor<string, []>("input_443_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_443_cast_fp16 = gelu(mode = input_443_mode_0, x = input_441_cast_fp16)[name = tensor<string, []>("input_443_cast_fp16")];
            tensor<int32, [2]> var_1366 = const()[name = tensor<string, []>("op_1366"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1368 = const()[name = tensor<string, []>("op_1368"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_447_pad_type_0 = const()[name = tensor<string, []>("input_447_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_447_pad_0 = const()[name = tensor<string, []>("input_447_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1372_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1372_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16805440)))];
            tensor<fp16, [320]> var_1372_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1372_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17419904)))];
            tensor<fp16, [1, 320, 16, 16]> var_1372_cast_fp16 = conv(bias = var_1372_bias_0_to_fp16, dilations = var_1368, groups = var_8, pad = input_447_pad_0, pad_type = input_447_pad_type_0, strides = var_1366, weight = var_1372_weight_0_to_fp16, x = input_443_cast_fp16)[name = tensor<string, []>("op_1372_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_449_cast_fp16 = add(x = input_435_cast_fp16, y = var_1372_cast_fp16)[name = tensor<string, []>("input_449_cast_fp16")];
            tensor<int32, [2]> var_1380 = const()[name = tensor<string, []>("op_1380"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1382 = const()[name = tensor<string, []>("op_1382"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_451_pad_type_0 = const()[name = tensor<string, []>("input_451_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_451_pad_0 = const()[name = tensor<string, []>("input_451_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_10_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_10_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17420608)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_10_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_10_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17426432)))];
            tensor<fp16, [1, 320, 16, 16]> input_451_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_10_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1382, groups = var_17, pad = input_451_pad_0, pad_type = input_451_pad_type_0, strides = var_1380, weight = original_model_image_encoder_model_network_4_10_token_mixer_reparam_conv_weight_to_fp16, x = input_449_cast_fp16)[name = tensor<string, []>("input_451_cast_fp16")];
            tensor<int32, [2]> var_1391 = const()[name = tensor<string, []>("op_1391"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1393 = const()[name = tensor<string, []>("op_1393"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_453_pad_type_0 = const()[name = tensor<string, []>("input_453_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_453_pad_0 = const()[name = tensor<string, []>("input_453_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_455_weight_0_to_fp16 = const()[name = tensor<string, []>("input_455_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17427136)))];
            tensor<fp16, [320]> input_455_bias_0_to_fp16 = const()[name = tensor<string, []>("input_455_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17458560)))];
            tensor<fp16, [1, 320, 16, 16]> input_455_cast_fp16 = conv(bias = input_455_bias_0_to_fp16, dilations = var_1393, groups = var_17, pad = input_453_pad_0, pad_type = input_453_pad_type_0, strides = var_1391, weight = input_455_weight_0_to_fp16, x = input_451_cast_fp16)[name = tensor<string, []>("input_455_cast_fp16")];
            tensor<int32, [2]> var_1403 = const()[name = tensor<string, []>("op_1403"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1405 = const()[name = tensor<string, []>("op_1405"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_457_pad_type_0 = const()[name = tensor<string, []>("input_457_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_457_pad_0 = const()[name = tensor<string, []>("input_457_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_10_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_10_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17459264)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_10_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_10_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18073728)))];
            tensor<fp16, [1, 960, 16, 16]> input_457_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_10_convffn_fc1_bias_to_fp16, dilations = var_1405, groups = var_8, pad = input_457_pad_0, pad_type = input_457_pad_type_0, strides = var_1403, weight = original_model_image_encoder_model_network_4_10_convffn_fc1_weight_to_fp16, x = input_455_cast_fp16)[name = tensor<string, []>("input_457_cast_fp16")];
            tensor<string, []> input_459_mode_0 = const()[name = tensor<string, []>("input_459_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_459_cast_fp16 = gelu(mode = input_459_mode_0, x = input_457_cast_fp16)[name = tensor<string, []>("input_459_cast_fp16")];
            tensor<int32, [2]> var_1412 = const()[name = tensor<string, []>("op_1412"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1414 = const()[name = tensor<string, []>("op_1414"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_463_pad_type_0 = const()[name = tensor<string, []>("input_463_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_463_pad_0 = const()[name = tensor<string, []>("input_463_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1418_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1418_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18075712)))];
            tensor<fp16, [320]> var_1418_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1418_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18690176)))];
            tensor<fp16, [1, 320, 16, 16]> var_1418_cast_fp16 = conv(bias = var_1418_bias_0_to_fp16, dilations = var_1414, groups = var_8, pad = input_463_pad_0, pad_type = input_463_pad_type_0, strides = var_1412, weight = var_1418_weight_0_to_fp16, x = input_459_cast_fp16)[name = tensor<string, []>("op_1418_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_465_cast_fp16 = add(x = input_451_cast_fp16, y = var_1418_cast_fp16)[name = tensor<string, []>("input_465_cast_fp16")];
            tensor<int32, [2]> var_1426 = const()[name = tensor<string, []>("op_1426"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1428 = const()[name = tensor<string, []>("op_1428"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_467_pad_type_0 = const()[name = tensor<string, []>("input_467_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_467_pad_0 = const()[name = tensor<string, []>("input_467_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_11_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_11_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18690880)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_11_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_11_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18696704)))];
            tensor<fp16, [1, 320, 16, 16]> input_467_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_11_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1428, groups = var_17, pad = input_467_pad_0, pad_type = input_467_pad_type_0, strides = var_1426, weight = original_model_image_encoder_model_network_4_11_token_mixer_reparam_conv_weight_to_fp16, x = input_465_cast_fp16)[name = tensor<string, []>("input_467_cast_fp16")];
            tensor<int32, [2]> var_1437 = const()[name = tensor<string, []>("op_1437"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1439 = const()[name = tensor<string, []>("op_1439"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_469_pad_type_0 = const()[name = tensor<string, []>("input_469_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_469_pad_0 = const()[name = tensor<string, []>("input_469_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_471_weight_0_to_fp16 = const()[name = tensor<string, []>("input_471_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18697408)))];
            tensor<fp16, [320]> input_471_bias_0_to_fp16 = const()[name = tensor<string, []>("input_471_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18728832)))];
            tensor<fp16, [1, 320, 16, 16]> input_471_cast_fp16 = conv(bias = input_471_bias_0_to_fp16, dilations = var_1439, groups = var_17, pad = input_469_pad_0, pad_type = input_469_pad_type_0, strides = var_1437, weight = input_471_weight_0_to_fp16, x = input_467_cast_fp16)[name = tensor<string, []>("input_471_cast_fp16")];
            tensor<int32, [2]> var_1449 = const()[name = tensor<string, []>("op_1449"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1451 = const()[name = tensor<string, []>("op_1451"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_473_pad_type_0 = const()[name = tensor<string, []>("input_473_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_473_pad_0 = const()[name = tensor<string, []>("input_473_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_11_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_11_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18729536)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_11_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_11_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19344000)))];
            tensor<fp16, [1, 960, 16, 16]> input_473_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_11_convffn_fc1_bias_to_fp16, dilations = var_1451, groups = var_8, pad = input_473_pad_0, pad_type = input_473_pad_type_0, strides = var_1449, weight = original_model_image_encoder_model_network_4_11_convffn_fc1_weight_to_fp16, x = input_471_cast_fp16)[name = tensor<string, []>("input_473_cast_fp16")];
            tensor<string, []> input_475_mode_0 = const()[name = tensor<string, []>("input_475_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_475_cast_fp16 = gelu(mode = input_475_mode_0, x = input_473_cast_fp16)[name = tensor<string, []>("input_475_cast_fp16")];
            tensor<int32, [2]> var_1458 = const()[name = tensor<string, []>("op_1458"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1460 = const()[name = tensor<string, []>("op_1460"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_479_pad_type_0 = const()[name = tensor<string, []>("input_479_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_479_pad_0 = const()[name = tensor<string, []>("input_479_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1464_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1464_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19345984)))];
            tensor<fp16, [320]> var_1464_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1464_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19960448)))];
            tensor<fp16, [1, 320, 16, 16]> var_1464_cast_fp16 = conv(bias = var_1464_bias_0_to_fp16, dilations = var_1460, groups = var_8, pad = input_479_pad_0, pad_type = input_479_pad_type_0, strides = var_1458, weight = var_1464_weight_0_to_fp16, x = input_475_cast_fp16)[name = tensor<string, []>("op_1464_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_481_cast_fp16 = add(x = input_467_cast_fp16, y = var_1464_cast_fp16)[name = tensor<string, []>("input_481_cast_fp16")];
            tensor<int32, [2]> var_1472 = const()[name = tensor<string, []>("op_1472"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1474 = const()[name = tensor<string, []>("op_1474"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_483_pad_type_0 = const()[name = tensor<string, []>("input_483_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_483_pad_0 = const()[name = tensor<string, []>("input_483_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_12_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_12_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19961152)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_12_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_12_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19966976)))];
            tensor<fp16, [1, 320, 16, 16]> input_483_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_12_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1474, groups = var_17, pad = input_483_pad_0, pad_type = input_483_pad_type_0, strides = var_1472, weight = original_model_image_encoder_model_network_4_12_token_mixer_reparam_conv_weight_to_fp16, x = input_481_cast_fp16)[name = tensor<string, []>("input_483_cast_fp16")];
            tensor<int32, [2]> var_1483 = const()[name = tensor<string, []>("op_1483"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1485 = const()[name = tensor<string, []>("op_1485"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_485_pad_type_0 = const()[name = tensor<string, []>("input_485_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_485_pad_0 = const()[name = tensor<string, []>("input_485_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_487_weight_0_to_fp16 = const()[name = tensor<string, []>("input_487_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19967680)))];
            tensor<fp16, [320]> input_487_bias_0_to_fp16 = const()[name = tensor<string, []>("input_487_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19999104)))];
            tensor<fp16, [1, 320, 16, 16]> input_487_cast_fp16 = conv(bias = input_487_bias_0_to_fp16, dilations = var_1485, groups = var_17, pad = input_485_pad_0, pad_type = input_485_pad_type_0, strides = var_1483, weight = input_487_weight_0_to_fp16, x = input_483_cast_fp16)[name = tensor<string, []>("input_487_cast_fp16")];
            tensor<int32, [2]> var_1495 = const()[name = tensor<string, []>("op_1495"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1497 = const()[name = tensor<string, []>("op_1497"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_489_pad_type_0 = const()[name = tensor<string, []>("input_489_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_489_pad_0 = const()[name = tensor<string, []>("input_489_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_12_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_12_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19999808)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_12_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_12_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20614272)))];
            tensor<fp16, [1, 960, 16, 16]> input_489_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_12_convffn_fc1_bias_to_fp16, dilations = var_1497, groups = var_8, pad = input_489_pad_0, pad_type = input_489_pad_type_0, strides = var_1495, weight = original_model_image_encoder_model_network_4_12_convffn_fc1_weight_to_fp16, x = input_487_cast_fp16)[name = tensor<string, []>("input_489_cast_fp16")];
            tensor<string, []> input_491_mode_0 = const()[name = tensor<string, []>("input_491_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_491_cast_fp16 = gelu(mode = input_491_mode_0, x = input_489_cast_fp16)[name = tensor<string, []>("input_491_cast_fp16")];
            tensor<int32, [2]> var_1504 = const()[name = tensor<string, []>("op_1504"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1506 = const()[name = tensor<string, []>("op_1506"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_495_pad_type_0 = const()[name = tensor<string, []>("input_495_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_495_pad_0 = const()[name = tensor<string, []>("input_495_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1510_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1510_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20616256)))];
            tensor<fp16, [320]> var_1510_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1510_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21230720)))];
            tensor<fp16, [1, 320, 16, 16]> var_1510_cast_fp16 = conv(bias = var_1510_bias_0_to_fp16, dilations = var_1506, groups = var_8, pad = input_495_pad_0, pad_type = input_495_pad_type_0, strides = var_1504, weight = var_1510_weight_0_to_fp16, x = input_491_cast_fp16)[name = tensor<string, []>("op_1510_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_497_cast_fp16 = add(x = input_483_cast_fp16, y = var_1510_cast_fp16)[name = tensor<string, []>("input_497_cast_fp16")];
            tensor<int32, [2]> var_1518 = const()[name = tensor<string, []>("op_1518"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1520 = const()[name = tensor<string, []>("op_1520"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_499_pad_type_0 = const()[name = tensor<string, []>("input_499_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_499_pad_0 = const()[name = tensor<string, []>("input_499_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_13_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_13_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21231424)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_13_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_13_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21237248)))];
            tensor<fp16, [1, 320, 16, 16]> input_499_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_13_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1520, groups = var_17, pad = input_499_pad_0, pad_type = input_499_pad_type_0, strides = var_1518, weight = original_model_image_encoder_model_network_4_13_token_mixer_reparam_conv_weight_to_fp16, x = input_497_cast_fp16)[name = tensor<string, []>("input_499_cast_fp16")];
            tensor<int32, [2]> var_1529 = const()[name = tensor<string, []>("op_1529"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1531 = const()[name = tensor<string, []>("op_1531"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_501_pad_type_0 = const()[name = tensor<string, []>("input_501_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_501_pad_0 = const()[name = tensor<string, []>("input_501_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_503_weight_0_to_fp16 = const()[name = tensor<string, []>("input_503_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21237952)))];
            tensor<fp16, [320]> input_503_bias_0_to_fp16 = const()[name = tensor<string, []>("input_503_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21269376)))];
            tensor<fp16, [1, 320, 16, 16]> input_503_cast_fp16 = conv(bias = input_503_bias_0_to_fp16, dilations = var_1531, groups = var_17, pad = input_501_pad_0, pad_type = input_501_pad_type_0, strides = var_1529, weight = input_503_weight_0_to_fp16, x = input_499_cast_fp16)[name = tensor<string, []>("input_503_cast_fp16")];
            tensor<int32, [2]> var_1541 = const()[name = tensor<string, []>("op_1541"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1543 = const()[name = tensor<string, []>("op_1543"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_505_pad_type_0 = const()[name = tensor<string, []>("input_505_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_505_pad_0 = const()[name = tensor<string, []>("input_505_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_13_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_13_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21270080)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_13_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_13_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21884544)))];
            tensor<fp16, [1, 960, 16, 16]> input_505_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_13_convffn_fc1_bias_to_fp16, dilations = var_1543, groups = var_8, pad = input_505_pad_0, pad_type = input_505_pad_type_0, strides = var_1541, weight = original_model_image_encoder_model_network_4_13_convffn_fc1_weight_to_fp16, x = input_503_cast_fp16)[name = tensor<string, []>("input_505_cast_fp16")];
            tensor<string, []> input_507_mode_0 = const()[name = tensor<string, []>("input_507_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_507_cast_fp16 = gelu(mode = input_507_mode_0, x = input_505_cast_fp16)[name = tensor<string, []>("input_507_cast_fp16")];
            tensor<int32, [2]> var_1550 = const()[name = tensor<string, []>("op_1550"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1552 = const()[name = tensor<string, []>("op_1552"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_511_pad_type_0 = const()[name = tensor<string, []>("input_511_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_511_pad_0 = const()[name = tensor<string, []>("input_511_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1556_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1556_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21886528)))];
            tensor<fp16, [320]> var_1556_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1556_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22500992)))];
            tensor<fp16, [1, 320, 16, 16]> var_1556_cast_fp16 = conv(bias = var_1556_bias_0_to_fp16, dilations = var_1552, groups = var_8, pad = input_511_pad_0, pad_type = input_511_pad_type_0, strides = var_1550, weight = var_1556_weight_0_to_fp16, x = input_507_cast_fp16)[name = tensor<string, []>("op_1556_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_513_cast_fp16 = add(x = input_499_cast_fp16, y = var_1556_cast_fp16)[name = tensor<string, []>("input_513_cast_fp16")];
            tensor<int32, [2]> var_1564 = const()[name = tensor<string, []>("op_1564"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1566 = const()[name = tensor<string, []>("op_1566"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_515_pad_type_0 = const()[name = tensor<string, []>("input_515_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_515_pad_0 = const()[name = tensor<string, []>("input_515_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_14_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_14_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22501696)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_14_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_14_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22507520)))];
            tensor<fp16, [1, 320, 16, 16]> input_515_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_14_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1566, groups = var_17, pad = input_515_pad_0, pad_type = input_515_pad_type_0, strides = var_1564, weight = original_model_image_encoder_model_network_4_14_token_mixer_reparam_conv_weight_to_fp16, x = input_513_cast_fp16)[name = tensor<string, []>("input_515_cast_fp16")];
            tensor<int32, [2]> var_1575 = const()[name = tensor<string, []>("op_1575"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1577 = const()[name = tensor<string, []>("op_1577"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_517_pad_type_0 = const()[name = tensor<string, []>("input_517_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_517_pad_0 = const()[name = tensor<string, []>("input_517_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_519_weight_0_to_fp16 = const()[name = tensor<string, []>("input_519_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22508224)))];
            tensor<fp16, [320]> input_519_bias_0_to_fp16 = const()[name = tensor<string, []>("input_519_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22539648)))];
            tensor<fp16, [1, 320, 16, 16]> input_519_cast_fp16 = conv(bias = input_519_bias_0_to_fp16, dilations = var_1577, groups = var_17, pad = input_517_pad_0, pad_type = input_517_pad_type_0, strides = var_1575, weight = input_519_weight_0_to_fp16, x = input_515_cast_fp16)[name = tensor<string, []>("input_519_cast_fp16")];
            tensor<int32, [2]> var_1587 = const()[name = tensor<string, []>("op_1587"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1589 = const()[name = tensor<string, []>("op_1589"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_521_pad_type_0 = const()[name = tensor<string, []>("input_521_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_521_pad_0 = const()[name = tensor<string, []>("input_521_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_14_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_14_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22540352)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_14_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_14_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23154816)))];
            tensor<fp16, [1, 960, 16, 16]> input_521_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_14_convffn_fc1_bias_to_fp16, dilations = var_1589, groups = var_8, pad = input_521_pad_0, pad_type = input_521_pad_type_0, strides = var_1587, weight = original_model_image_encoder_model_network_4_14_convffn_fc1_weight_to_fp16, x = input_519_cast_fp16)[name = tensor<string, []>("input_521_cast_fp16")];
            tensor<string, []> input_523_mode_0 = const()[name = tensor<string, []>("input_523_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_523_cast_fp16 = gelu(mode = input_523_mode_0, x = input_521_cast_fp16)[name = tensor<string, []>("input_523_cast_fp16")];
            tensor<int32, [2]> var_1596 = const()[name = tensor<string, []>("op_1596"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1598 = const()[name = tensor<string, []>("op_1598"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_527_pad_type_0 = const()[name = tensor<string, []>("input_527_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_527_pad_0 = const()[name = tensor<string, []>("input_527_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1602_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1602_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23156800)))];
            tensor<fp16, [320]> var_1602_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1602_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23771264)))];
            tensor<fp16, [1, 320, 16, 16]> var_1602_cast_fp16 = conv(bias = var_1602_bias_0_to_fp16, dilations = var_1598, groups = var_8, pad = input_527_pad_0, pad_type = input_527_pad_type_0, strides = var_1596, weight = var_1602_weight_0_to_fp16, x = input_523_cast_fp16)[name = tensor<string, []>("op_1602_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_529_cast_fp16 = add(x = input_515_cast_fp16, y = var_1602_cast_fp16)[name = tensor<string, []>("input_529_cast_fp16")];
            tensor<int32, [2]> var_1610 = const()[name = tensor<string, []>("op_1610"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1612 = const()[name = tensor<string, []>("op_1612"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_531_pad_type_0 = const()[name = tensor<string, []>("input_531_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_531_pad_0 = const()[name = tensor<string, []>("input_531_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_15_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_15_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23771968)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_15_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_15_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23777792)))];
            tensor<fp16, [1, 320, 16, 16]> input_531_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_15_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1612, groups = var_17, pad = input_531_pad_0, pad_type = input_531_pad_type_0, strides = var_1610, weight = original_model_image_encoder_model_network_4_15_token_mixer_reparam_conv_weight_to_fp16, x = input_529_cast_fp16)[name = tensor<string, []>("input_531_cast_fp16")];
            tensor<int32, [2]> var_1621 = const()[name = tensor<string, []>("op_1621"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1623 = const()[name = tensor<string, []>("op_1623"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_533_pad_type_0 = const()[name = tensor<string, []>("input_533_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_533_pad_0 = const()[name = tensor<string, []>("input_533_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_535_weight_0_to_fp16 = const()[name = tensor<string, []>("input_535_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23778496)))];
            tensor<fp16, [320]> input_535_bias_0_to_fp16 = const()[name = tensor<string, []>("input_535_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23809920)))];
            tensor<fp16, [1, 320, 16, 16]> input_535_cast_fp16 = conv(bias = input_535_bias_0_to_fp16, dilations = var_1623, groups = var_17, pad = input_533_pad_0, pad_type = input_533_pad_type_0, strides = var_1621, weight = input_535_weight_0_to_fp16, x = input_531_cast_fp16)[name = tensor<string, []>("input_535_cast_fp16")];
            tensor<int32, [2]> var_1633 = const()[name = tensor<string, []>("op_1633"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1635 = const()[name = tensor<string, []>("op_1635"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_537_pad_type_0 = const()[name = tensor<string, []>("input_537_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_537_pad_0 = const()[name = tensor<string, []>("input_537_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_15_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_15_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23810624)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_15_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_15_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(24425088)))];
            tensor<fp16, [1, 960, 16, 16]> input_537_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_15_convffn_fc1_bias_to_fp16, dilations = var_1635, groups = var_8, pad = input_537_pad_0, pad_type = input_537_pad_type_0, strides = var_1633, weight = original_model_image_encoder_model_network_4_15_convffn_fc1_weight_to_fp16, x = input_535_cast_fp16)[name = tensor<string, []>("input_537_cast_fp16")];
            tensor<string, []> input_539_mode_0 = const()[name = tensor<string, []>("input_539_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_539_cast_fp16 = gelu(mode = input_539_mode_0, x = input_537_cast_fp16)[name = tensor<string, []>("input_539_cast_fp16")];
            tensor<int32, [2]> var_1642 = const()[name = tensor<string, []>("op_1642"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1644 = const()[name = tensor<string, []>("op_1644"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_543_pad_type_0 = const()[name = tensor<string, []>("input_543_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_543_pad_0 = const()[name = tensor<string, []>("input_543_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1648_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1648_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(24427072)))];
            tensor<fp16, [320]> var_1648_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1648_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25041536)))];
            tensor<fp16, [1, 320, 16, 16]> var_1648_cast_fp16 = conv(bias = var_1648_bias_0_to_fp16, dilations = var_1644, groups = var_8, pad = input_543_pad_0, pad_type = input_543_pad_type_0, strides = var_1642, weight = var_1648_weight_0_to_fp16, x = input_539_cast_fp16)[name = tensor<string, []>("op_1648_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_545_cast_fp16 = add(x = input_531_cast_fp16, y = var_1648_cast_fp16)[name = tensor<string, []>("input_545_cast_fp16")];
            tensor<int32, [2]> var_1656 = const()[name = tensor<string, []>("op_1656"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1658 = const()[name = tensor<string, []>("op_1658"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_547_pad_type_0 = const()[name = tensor<string, []>("input_547_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_547_pad_0 = const()[name = tensor<string, []>("input_547_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_16_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_16_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25042240)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_16_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_16_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25048064)))];
            tensor<fp16, [1, 320, 16, 16]> input_547_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_16_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1658, groups = var_17, pad = input_547_pad_0, pad_type = input_547_pad_type_0, strides = var_1656, weight = original_model_image_encoder_model_network_4_16_token_mixer_reparam_conv_weight_to_fp16, x = input_545_cast_fp16)[name = tensor<string, []>("input_547_cast_fp16")];
            tensor<int32, [2]> var_1667 = const()[name = tensor<string, []>("op_1667"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1669 = const()[name = tensor<string, []>("op_1669"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_549_pad_type_0 = const()[name = tensor<string, []>("input_549_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_549_pad_0 = const()[name = tensor<string, []>("input_549_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_551_weight_0_to_fp16 = const()[name = tensor<string, []>("input_551_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25048768)))];
            tensor<fp16, [320]> input_551_bias_0_to_fp16 = const()[name = tensor<string, []>("input_551_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25080192)))];
            tensor<fp16, [1, 320, 16, 16]> input_551_cast_fp16 = conv(bias = input_551_bias_0_to_fp16, dilations = var_1669, groups = var_17, pad = input_549_pad_0, pad_type = input_549_pad_type_0, strides = var_1667, weight = input_551_weight_0_to_fp16, x = input_547_cast_fp16)[name = tensor<string, []>("input_551_cast_fp16")];
            tensor<int32, [2]> var_1679 = const()[name = tensor<string, []>("op_1679"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1681 = const()[name = tensor<string, []>("op_1681"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_553_pad_type_0 = const()[name = tensor<string, []>("input_553_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_553_pad_0 = const()[name = tensor<string, []>("input_553_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_16_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_16_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25080896)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_16_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_16_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25695360)))];
            tensor<fp16, [1, 960, 16, 16]> input_553_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_16_convffn_fc1_bias_to_fp16, dilations = var_1681, groups = var_8, pad = input_553_pad_0, pad_type = input_553_pad_type_0, strides = var_1679, weight = original_model_image_encoder_model_network_4_16_convffn_fc1_weight_to_fp16, x = input_551_cast_fp16)[name = tensor<string, []>("input_553_cast_fp16")];
            tensor<string, []> input_555_mode_0 = const()[name = tensor<string, []>("input_555_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_555_cast_fp16 = gelu(mode = input_555_mode_0, x = input_553_cast_fp16)[name = tensor<string, []>("input_555_cast_fp16")];
            tensor<int32, [2]> var_1688 = const()[name = tensor<string, []>("op_1688"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1690 = const()[name = tensor<string, []>("op_1690"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_559_pad_type_0 = const()[name = tensor<string, []>("input_559_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_559_pad_0 = const()[name = tensor<string, []>("input_559_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1694_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1694_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25697344)))];
            tensor<fp16, [320]> var_1694_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1694_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26311808)))];
            tensor<fp16, [1, 320, 16, 16]> var_1694_cast_fp16 = conv(bias = var_1694_bias_0_to_fp16, dilations = var_1690, groups = var_8, pad = input_559_pad_0, pad_type = input_559_pad_type_0, strides = var_1688, weight = var_1694_weight_0_to_fp16, x = input_555_cast_fp16)[name = tensor<string, []>("op_1694_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_561_cast_fp16 = add(x = input_547_cast_fp16, y = var_1694_cast_fp16)[name = tensor<string, []>("input_561_cast_fp16")];
            tensor<int32, [2]> var_1702 = const()[name = tensor<string, []>("op_1702"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1704 = const()[name = tensor<string, []>("op_1704"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_563_pad_type_0 = const()[name = tensor<string, []>("input_563_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_563_pad_0 = const()[name = tensor<string, []>("input_563_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_17_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_17_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26312512)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_17_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_17_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26318336)))];
            tensor<fp16, [1, 320, 16, 16]> input_563_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_17_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1704, groups = var_17, pad = input_563_pad_0, pad_type = input_563_pad_type_0, strides = var_1702, weight = original_model_image_encoder_model_network_4_17_token_mixer_reparam_conv_weight_to_fp16, x = input_561_cast_fp16)[name = tensor<string, []>("input_563_cast_fp16")];
            tensor<int32, [2]> var_1713 = const()[name = tensor<string, []>("op_1713"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1715 = const()[name = tensor<string, []>("op_1715"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_565_pad_type_0 = const()[name = tensor<string, []>("input_565_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_565_pad_0 = const()[name = tensor<string, []>("input_565_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_567_weight_0_to_fp16 = const()[name = tensor<string, []>("input_567_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26319040)))];
            tensor<fp16, [320]> input_567_bias_0_to_fp16 = const()[name = tensor<string, []>("input_567_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26350464)))];
            tensor<fp16, [1, 320, 16, 16]> input_567_cast_fp16 = conv(bias = input_567_bias_0_to_fp16, dilations = var_1715, groups = var_17, pad = input_565_pad_0, pad_type = input_565_pad_type_0, strides = var_1713, weight = input_567_weight_0_to_fp16, x = input_563_cast_fp16)[name = tensor<string, []>("input_567_cast_fp16")];
            tensor<int32, [2]> var_1725 = const()[name = tensor<string, []>("op_1725"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1727 = const()[name = tensor<string, []>("op_1727"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_569_pad_type_0 = const()[name = tensor<string, []>("input_569_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_569_pad_0 = const()[name = tensor<string, []>("input_569_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_17_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_17_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26351168)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_17_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_17_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26965632)))];
            tensor<fp16, [1, 960, 16, 16]> input_569_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_17_convffn_fc1_bias_to_fp16, dilations = var_1727, groups = var_8, pad = input_569_pad_0, pad_type = input_569_pad_type_0, strides = var_1725, weight = original_model_image_encoder_model_network_4_17_convffn_fc1_weight_to_fp16, x = input_567_cast_fp16)[name = tensor<string, []>("input_569_cast_fp16")];
            tensor<string, []> input_571_mode_0 = const()[name = tensor<string, []>("input_571_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_571_cast_fp16 = gelu(mode = input_571_mode_0, x = input_569_cast_fp16)[name = tensor<string, []>("input_571_cast_fp16")];
            tensor<int32, [2]> var_1734 = const()[name = tensor<string, []>("op_1734"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1736 = const()[name = tensor<string, []>("op_1736"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_575_pad_type_0 = const()[name = tensor<string, []>("input_575_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_575_pad_0 = const()[name = tensor<string, []>("input_575_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1740_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1740_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26967616)))];
            tensor<fp16, [320]> var_1740_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1740_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27582080)))];
            tensor<fp16, [1, 320, 16, 16]> var_1740_cast_fp16 = conv(bias = var_1740_bias_0_to_fp16, dilations = var_1736, groups = var_8, pad = input_575_pad_0, pad_type = input_575_pad_type_0, strides = var_1734, weight = var_1740_weight_0_to_fp16, x = input_571_cast_fp16)[name = tensor<string, []>("op_1740_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_577_cast_fp16 = add(x = input_563_cast_fp16, y = var_1740_cast_fp16)[name = tensor<string, []>("input_577_cast_fp16")];
            tensor<int32, [2]> var_1748 = const()[name = tensor<string, []>("op_1748"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1750 = const()[name = tensor<string, []>("op_1750"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_579_pad_type_0 = const()[name = tensor<string, []>("input_579_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_579_pad_0 = const()[name = tensor<string, []>("input_579_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_18_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_18_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27582784)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_18_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_18_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27588608)))];
            tensor<fp16, [1, 320, 16, 16]> input_579_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_18_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1750, groups = var_17, pad = input_579_pad_0, pad_type = input_579_pad_type_0, strides = var_1748, weight = original_model_image_encoder_model_network_4_18_token_mixer_reparam_conv_weight_to_fp16, x = input_577_cast_fp16)[name = tensor<string, []>("input_579_cast_fp16")];
            tensor<int32, [2]> var_1759 = const()[name = tensor<string, []>("op_1759"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1761 = const()[name = tensor<string, []>("op_1761"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_581_pad_type_0 = const()[name = tensor<string, []>("input_581_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_581_pad_0 = const()[name = tensor<string, []>("input_581_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_583_weight_0_to_fp16 = const()[name = tensor<string, []>("input_583_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27589312)))];
            tensor<fp16, [320]> input_583_bias_0_to_fp16 = const()[name = tensor<string, []>("input_583_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27620736)))];
            tensor<fp16, [1, 320, 16, 16]> input_583_cast_fp16 = conv(bias = input_583_bias_0_to_fp16, dilations = var_1761, groups = var_17, pad = input_581_pad_0, pad_type = input_581_pad_type_0, strides = var_1759, weight = input_583_weight_0_to_fp16, x = input_579_cast_fp16)[name = tensor<string, []>("input_583_cast_fp16")];
            tensor<int32, [2]> var_1771 = const()[name = tensor<string, []>("op_1771"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1773 = const()[name = tensor<string, []>("op_1773"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_585_pad_type_0 = const()[name = tensor<string, []>("input_585_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_585_pad_0 = const()[name = tensor<string, []>("input_585_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_18_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_18_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27621440)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_18_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_18_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28235904)))];
            tensor<fp16, [1, 960, 16, 16]> input_585_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_18_convffn_fc1_bias_to_fp16, dilations = var_1773, groups = var_8, pad = input_585_pad_0, pad_type = input_585_pad_type_0, strides = var_1771, weight = original_model_image_encoder_model_network_4_18_convffn_fc1_weight_to_fp16, x = input_583_cast_fp16)[name = tensor<string, []>("input_585_cast_fp16")];
            tensor<string, []> input_587_mode_0 = const()[name = tensor<string, []>("input_587_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_587_cast_fp16 = gelu(mode = input_587_mode_0, x = input_585_cast_fp16)[name = tensor<string, []>("input_587_cast_fp16")];
            tensor<int32, [2]> var_1780 = const()[name = tensor<string, []>("op_1780"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1782 = const()[name = tensor<string, []>("op_1782"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_591_pad_type_0 = const()[name = tensor<string, []>("input_591_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_591_pad_0 = const()[name = tensor<string, []>("input_591_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1786_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1786_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28237888)))];
            tensor<fp16, [320]> var_1786_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1786_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28852352)))];
            tensor<fp16, [1, 320, 16, 16]> var_1786_cast_fp16 = conv(bias = var_1786_bias_0_to_fp16, dilations = var_1782, groups = var_8, pad = input_591_pad_0, pad_type = input_591_pad_type_0, strides = var_1780, weight = var_1786_weight_0_to_fp16, x = input_587_cast_fp16)[name = tensor<string, []>("op_1786_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_593_cast_fp16 = add(x = input_579_cast_fp16, y = var_1786_cast_fp16)[name = tensor<string, []>("input_593_cast_fp16")];
            tensor<int32, [2]> var_1794 = const()[name = tensor<string, []>("op_1794"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1796 = const()[name = tensor<string, []>("op_1796"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_595_pad_type_0 = const()[name = tensor<string, []>("input_595_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_595_pad_0 = const()[name = tensor<string, []>("input_595_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_19_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_19_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28853056)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_19_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_19_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28858880)))];
            tensor<fp16, [1, 320, 16, 16]> input_595_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_19_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1796, groups = var_17, pad = input_595_pad_0, pad_type = input_595_pad_type_0, strides = var_1794, weight = original_model_image_encoder_model_network_4_19_token_mixer_reparam_conv_weight_to_fp16, x = input_593_cast_fp16)[name = tensor<string, []>("input_595_cast_fp16")];
            tensor<int32, [2]> var_1805 = const()[name = tensor<string, []>("op_1805"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1807 = const()[name = tensor<string, []>("op_1807"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_597_pad_type_0 = const()[name = tensor<string, []>("input_597_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_597_pad_0 = const()[name = tensor<string, []>("input_597_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_599_weight_0_to_fp16 = const()[name = tensor<string, []>("input_599_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28859584)))];
            tensor<fp16, [320]> input_599_bias_0_to_fp16 = const()[name = tensor<string, []>("input_599_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28891008)))];
            tensor<fp16, [1, 320, 16, 16]> input_599_cast_fp16 = conv(bias = input_599_bias_0_to_fp16, dilations = var_1807, groups = var_17, pad = input_597_pad_0, pad_type = input_597_pad_type_0, strides = var_1805, weight = input_599_weight_0_to_fp16, x = input_595_cast_fp16)[name = tensor<string, []>("input_599_cast_fp16")];
            tensor<int32, [2]> var_1817 = const()[name = tensor<string, []>("op_1817"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1819 = const()[name = tensor<string, []>("op_1819"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_601_pad_type_0 = const()[name = tensor<string, []>("input_601_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_601_pad_0 = const()[name = tensor<string, []>("input_601_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_19_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_19_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28891712)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_19_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_19_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29506176)))];
            tensor<fp16, [1, 960, 16, 16]> input_601_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_19_convffn_fc1_bias_to_fp16, dilations = var_1819, groups = var_8, pad = input_601_pad_0, pad_type = input_601_pad_type_0, strides = var_1817, weight = original_model_image_encoder_model_network_4_19_convffn_fc1_weight_to_fp16, x = input_599_cast_fp16)[name = tensor<string, []>("input_601_cast_fp16")];
            tensor<string, []> input_603_mode_0 = const()[name = tensor<string, []>("input_603_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_603_cast_fp16 = gelu(mode = input_603_mode_0, x = input_601_cast_fp16)[name = tensor<string, []>("input_603_cast_fp16")];
            tensor<int32, [2]> var_1826 = const()[name = tensor<string, []>("op_1826"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1828 = const()[name = tensor<string, []>("op_1828"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_607_pad_type_0 = const()[name = tensor<string, []>("input_607_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_607_pad_0 = const()[name = tensor<string, []>("input_607_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1832_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1832_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29508160)))];
            tensor<fp16, [320]> var_1832_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1832_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30122624)))];
            tensor<fp16, [1, 320, 16, 16]> var_1832_cast_fp16 = conv(bias = var_1832_bias_0_to_fp16, dilations = var_1828, groups = var_8, pad = input_607_pad_0, pad_type = input_607_pad_type_0, strides = var_1826, weight = var_1832_weight_0_to_fp16, x = input_603_cast_fp16)[name = tensor<string, []>("op_1832_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_609_cast_fp16 = add(x = input_595_cast_fp16, y = var_1832_cast_fp16)[name = tensor<string, []>("input_609_cast_fp16")];
            tensor<int32, [2]> var_1840 = const()[name = tensor<string, []>("op_1840"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1842 = const()[name = tensor<string, []>("op_1842"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_611_pad_type_0 = const()[name = tensor<string, []>("input_611_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_611_pad_0 = const()[name = tensor<string, []>("input_611_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_20_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_20_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30123328)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_20_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_20_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30129152)))];
            tensor<fp16, [1, 320, 16, 16]> input_611_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_20_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1842, groups = var_17, pad = input_611_pad_0, pad_type = input_611_pad_type_0, strides = var_1840, weight = original_model_image_encoder_model_network_4_20_token_mixer_reparam_conv_weight_to_fp16, x = input_609_cast_fp16)[name = tensor<string, []>("input_611_cast_fp16")];
            tensor<int32, [2]> var_1851 = const()[name = tensor<string, []>("op_1851"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1853 = const()[name = tensor<string, []>("op_1853"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_613_pad_type_0 = const()[name = tensor<string, []>("input_613_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_613_pad_0 = const()[name = tensor<string, []>("input_613_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_615_weight_0_to_fp16 = const()[name = tensor<string, []>("input_615_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30129856)))];
            tensor<fp16, [320]> input_615_bias_0_to_fp16 = const()[name = tensor<string, []>("input_615_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30161280)))];
            tensor<fp16, [1, 320, 16, 16]> input_615_cast_fp16 = conv(bias = input_615_bias_0_to_fp16, dilations = var_1853, groups = var_17, pad = input_613_pad_0, pad_type = input_613_pad_type_0, strides = var_1851, weight = input_615_weight_0_to_fp16, x = input_611_cast_fp16)[name = tensor<string, []>("input_615_cast_fp16")];
            tensor<int32, [2]> var_1863 = const()[name = tensor<string, []>("op_1863"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1865 = const()[name = tensor<string, []>("op_1865"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_617_pad_type_0 = const()[name = tensor<string, []>("input_617_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_617_pad_0 = const()[name = tensor<string, []>("input_617_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_20_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_20_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30161984)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_20_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_20_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30776448)))];
            tensor<fp16, [1, 960, 16, 16]> input_617_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_20_convffn_fc1_bias_to_fp16, dilations = var_1865, groups = var_8, pad = input_617_pad_0, pad_type = input_617_pad_type_0, strides = var_1863, weight = original_model_image_encoder_model_network_4_20_convffn_fc1_weight_to_fp16, x = input_615_cast_fp16)[name = tensor<string, []>("input_617_cast_fp16")];
            tensor<string, []> input_619_mode_0 = const()[name = tensor<string, []>("input_619_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_619_cast_fp16 = gelu(mode = input_619_mode_0, x = input_617_cast_fp16)[name = tensor<string, []>("input_619_cast_fp16")];
            tensor<int32, [2]> var_1872 = const()[name = tensor<string, []>("op_1872"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1874 = const()[name = tensor<string, []>("op_1874"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_623_pad_type_0 = const()[name = tensor<string, []>("input_623_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_623_pad_0 = const()[name = tensor<string, []>("input_623_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1878_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1878_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30778432)))];
            tensor<fp16, [320]> var_1878_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1878_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31392896)))];
            tensor<fp16, [1, 320, 16, 16]> var_1878_cast_fp16 = conv(bias = var_1878_bias_0_to_fp16, dilations = var_1874, groups = var_8, pad = input_623_pad_0, pad_type = input_623_pad_type_0, strides = var_1872, weight = var_1878_weight_0_to_fp16, x = input_619_cast_fp16)[name = tensor<string, []>("op_1878_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_625_cast_fp16 = add(x = input_611_cast_fp16, y = var_1878_cast_fp16)[name = tensor<string, []>("input_625_cast_fp16")];
            tensor<int32, [2]> var_1886 = const()[name = tensor<string, []>("op_1886"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1888 = const()[name = tensor<string, []>("op_1888"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_627_pad_type_0 = const()[name = tensor<string, []>("input_627_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_627_pad_0 = const()[name = tensor<string, []>("input_627_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_21_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_21_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31393600)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_21_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_21_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31399424)))];
            tensor<fp16, [1, 320, 16, 16]> input_627_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_21_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1888, groups = var_17, pad = input_627_pad_0, pad_type = input_627_pad_type_0, strides = var_1886, weight = original_model_image_encoder_model_network_4_21_token_mixer_reparam_conv_weight_to_fp16, x = input_625_cast_fp16)[name = tensor<string, []>("input_627_cast_fp16")];
            tensor<int32, [2]> var_1897 = const()[name = tensor<string, []>("op_1897"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1899 = const()[name = tensor<string, []>("op_1899"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_629_pad_type_0 = const()[name = tensor<string, []>("input_629_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_629_pad_0 = const()[name = tensor<string, []>("input_629_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_631_weight_0_to_fp16 = const()[name = tensor<string, []>("input_631_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31400128)))];
            tensor<fp16, [320]> input_631_bias_0_to_fp16 = const()[name = tensor<string, []>("input_631_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31431552)))];
            tensor<fp16, [1, 320, 16, 16]> input_631_cast_fp16 = conv(bias = input_631_bias_0_to_fp16, dilations = var_1899, groups = var_17, pad = input_629_pad_0, pad_type = input_629_pad_type_0, strides = var_1897, weight = input_631_weight_0_to_fp16, x = input_627_cast_fp16)[name = tensor<string, []>("input_631_cast_fp16")];
            tensor<int32, [2]> var_1909 = const()[name = tensor<string, []>("op_1909"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1911 = const()[name = tensor<string, []>("op_1911"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_633_pad_type_0 = const()[name = tensor<string, []>("input_633_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_633_pad_0 = const()[name = tensor<string, []>("input_633_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_21_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_21_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31432256)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_21_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_21_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32046720)))];
            tensor<fp16, [1, 960, 16, 16]> input_633_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_21_convffn_fc1_bias_to_fp16, dilations = var_1911, groups = var_8, pad = input_633_pad_0, pad_type = input_633_pad_type_0, strides = var_1909, weight = original_model_image_encoder_model_network_4_21_convffn_fc1_weight_to_fp16, x = input_631_cast_fp16)[name = tensor<string, []>("input_633_cast_fp16")];
            tensor<string, []> input_635_mode_0 = const()[name = tensor<string, []>("input_635_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_635_cast_fp16 = gelu(mode = input_635_mode_0, x = input_633_cast_fp16)[name = tensor<string, []>("input_635_cast_fp16")];
            tensor<int32, [2]> var_1918 = const()[name = tensor<string, []>("op_1918"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1920 = const()[name = tensor<string, []>("op_1920"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_639_pad_type_0 = const()[name = tensor<string, []>("input_639_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_639_pad_0 = const()[name = tensor<string, []>("input_639_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1924_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1924_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32048704)))];
            tensor<fp16, [320]> var_1924_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1924_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32663168)))];
            tensor<fp16, [1, 320, 16, 16]> var_1924_cast_fp16 = conv(bias = var_1924_bias_0_to_fp16, dilations = var_1920, groups = var_8, pad = input_639_pad_0, pad_type = input_639_pad_type_0, strides = var_1918, weight = var_1924_weight_0_to_fp16, x = input_635_cast_fp16)[name = tensor<string, []>("op_1924_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_641_cast_fp16 = add(x = input_627_cast_fp16, y = var_1924_cast_fp16)[name = tensor<string, []>("input_641_cast_fp16")];
            tensor<int32, [2]> var_1932 = const()[name = tensor<string, []>("op_1932"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1934 = const()[name = tensor<string, []>("op_1934"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_643_pad_type_0 = const()[name = tensor<string, []>("input_643_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_643_pad_0 = const()[name = tensor<string, []>("input_643_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_22_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_22_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32663872)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_22_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_22_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32669696)))];
            tensor<fp16, [1, 320, 16, 16]> input_643_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_22_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1934, groups = var_17, pad = input_643_pad_0, pad_type = input_643_pad_type_0, strides = var_1932, weight = original_model_image_encoder_model_network_4_22_token_mixer_reparam_conv_weight_to_fp16, x = input_641_cast_fp16)[name = tensor<string, []>("input_643_cast_fp16")];
            tensor<int32, [2]> var_1943 = const()[name = tensor<string, []>("op_1943"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1945 = const()[name = tensor<string, []>("op_1945"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_645_pad_type_0 = const()[name = tensor<string, []>("input_645_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_645_pad_0 = const()[name = tensor<string, []>("input_645_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_647_weight_0_to_fp16 = const()[name = tensor<string, []>("input_647_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32670400)))];
            tensor<fp16, [320]> input_647_bias_0_to_fp16 = const()[name = tensor<string, []>("input_647_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32701824)))];
            tensor<fp16, [1, 320, 16, 16]> input_647_cast_fp16 = conv(bias = input_647_bias_0_to_fp16, dilations = var_1945, groups = var_17, pad = input_645_pad_0, pad_type = input_645_pad_type_0, strides = var_1943, weight = input_647_weight_0_to_fp16, x = input_643_cast_fp16)[name = tensor<string, []>("input_647_cast_fp16")];
            tensor<int32, [2]> var_1955 = const()[name = tensor<string, []>("op_1955"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1957 = const()[name = tensor<string, []>("op_1957"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_649_pad_type_0 = const()[name = tensor<string, []>("input_649_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_649_pad_0 = const()[name = tensor<string, []>("input_649_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_22_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_22_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32702528)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_22_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_22_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33316992)))];
            tensor<fp16, [1, 960, 16, 16]> input_649_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_22_convffn_fc1_bias_to_fp16, dilations = var_1957, groups = var_8, pad = input_649_pad_0, pad_type = input_649_pad_type_0, strides = var_1955, weight = original_model_image_encoder_model_network_4_22_convffn_fc1_weight_to_fp16, x = input_647_cast_fp16)[name = tensor<string, []>("input_649_cast_fp16")];
            tensor<string, []> input_651_mode_0 = const()[name = tensor<string, []>("input_651_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_651_cast_fp16 = gelu(mode = input_651_mode_0, x = input_649_cast_fp16)[name = tensor<string, []>("input_651_cast_fp16")];
            tensor<int32, [2]> var_1964 = const()[name = tensor<string, []>("op_1964"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1966 = const()[name = tensor<string, []>("op_1966"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_655_pad_type_0 = const()[name = tensor<string, []>("input_655_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_655_pad_0 = const()[name = tensor<string, []>("input_655_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_1970_weight_0_to_fp16 = const()[name = tensor<string, []>("op_1970_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33318976)))];
            tensor<fp16, [320]> var_1970_bias_0_to_fp16 = const()[name = tensor<string, []>("op_1970_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33933440)))];
            tensor<fp16, [1, 320, 16, 16]> var_1970_cast_fp16 = conv(bias = var_1970_bias_0_to_fp16, dilations = var_1966, groups = var_8, pad = input_655_pad_0, pad_type = input_655_pad_type_0, strides = var_1964, weight = var_1970_weight_0_to_fp16, x = input_651_cast_fp16)[name = tensor<string, []>("op_1970_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_657_cast_fp16 = add(x = input_643_cast_fp16, y = var_1970_cast_fp16)[name = tensor<string, []>("input_657_cast_fp16")];
            tensor<int32, [2]> var_1978 = const()[name = tensor<string, []>("op_1978"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1980 = const()[name = tensor<string, []>("op_1980"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_659_pad_type_0 = const()[name = tensor<string, []>("input_659_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_659_pad_0 = const()[name = tensor<string, []>("input_659_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [320, 1, 3, 3]> original_model_image_encoder_model_network_4_23_token_mixer_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_23_token_mixer_reparam_conv_weight_to_fp16"), val = tensor<fp16, [320, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33934144)))];
            tensor<fp16, [320]> original_model_image_encoder_model_network_4_23_token_mixer_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_23_token_mixer_reparam_conv_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33939968)))];
            tensor<fp16, [1, 320, 16, 16]> input_659_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_23_token_mixer_reparam_conv_bias_to_fp16, dilations = var_1980, groups = var_17, pad = input_659_pad_0, pad_type = input_659_pad_type_0, strides = var_1978, weight = original_model_image_encoder_model_network_4_23_token_mixer_reparam_conv_weight_to_fp16, x = input_657_cast_fp16)[name = tensor<string, []>("input_659_cast_fp16")];
            tensor<int32, [2]> var_1989 = const()[name = tensor<string, []>("op_1989"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_1991 = const()[name = tensor<string, []>("op_1991"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_661_pad_type_0 = const()[name = tensor<string, []>("input_661_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_661_pad_0 = const()[name = tensor<string, []>("input_661_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [320, 1, 7, 7]> input_663_weight_0_to_fp16 = const()[name = tensor<string, []>("input_663_weight_0_to_fp16"), val = tensor<fp16, [320, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33940672)))];
            tensor<fp16, [320]> input_663_bias_0_to_fp16 = const()[name = tensor<string, []>("input_663_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33972096)))];
            tensor<fp16, [1, 320, 16, 16]> input_663_cast_fp16 = conv(bias = input_663_bias_0_to_fp16, dilations = var_1991, groups = var_17, pad = input_661_pad_0, pad_type = input_661_pad_type_0, strides = var_1989, weight = input_663_weight_0_to_fp16, x = input_659_cast_fp16)[name = tensor<string, []>("input_663_cast_fp16")];
            tensor<int32, [2]> var_2001 = const()[name = tensor<string, []>("op_2001"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2003 = const()[name = tensor<string, []>("op_2003"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_665_pad_type_0 = const()[name = tensor<string, []>("input_665_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_665_pad_0 = const()[name = tensor<string, []>("input_665_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [960, 320, 1, 1]> original_model_image_encoder_model_network_4_23_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_23_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [960, 320, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33972800)))];
            tensor<fp16, [960]> original_model_image_encoder_model_network_4_23_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_4_23_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34587264)))];
            tensor<fp16, [1, 960, 16, 16]> input_665_cast_fp16 = conv(bias = original_model_image_encoder_model_network_4_23_convffn_fc1_bias_to_fp16, dilations = var_2003, groups = var_8, pad = input_665_pad_0, pad_type = input_665_pad_type_0, strides = var_2001, weight = original_model_image_encoder_model_network_4_23_convffn_fc1_weight_to_fp16, x = input_663_cast_fp16)[name = tensor<string, []>("input_665_cast_fp16")];
            tensor<string, []> input_667_mode_0 = const()[name = tensor<string, []>("input_667_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 960, 16, 16]> input_667_cast_fp16 = gelu(mode = input_667_mode_0, x = input_665_cast_fp16)[name = tensor<string, []>("input_667_cast_fp16")];
            tensor<int32, [2]> var_2010 = const()[name = tensor<string, []>("op_2010"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2012 = const()[name = tensor<string, []>("op_2012"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_671_pad_type_0 = const()[name = tensor<string, []>("input_671_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_671_pad_0 = const()[name = tensor<string, []>("input_671_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [320, 960, 1, 1]> var_2016_weight_0_to_fp16 = const()[name = tensor<string, []>("op_2016_weight_0_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34589248)))];
            tensor<fp16, [320]> var_2016_bias_0_to_fp16 = const()[name = tensor<string, []>("op_2016_bias_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35203712)))];
            tensor<fp16, [1, 320, 16, 16]> var_2016_cast_fp16 = conv(bias = var_2016_bias_0_to_fp16, dilations = var_2012, groups = var_8, pad = input_671_pad_0, pad_type = input_671_pad_type_0, strides = var_2010, weight = var_2016_weight_0_to_fp16, x = input_667_cast_fp16)[name = tensor<string, []>("op_2016_cast_fp16")];
            tensor<fp16, [1, 320, 16, 16]> input_673_cast_fp16 = add(x = input_659_cast_fp16, y = var_2016_cast_fp16)[name = tensor<string, []>("input_673_cast_fp16")];
            tensor<int32, [2]> var_2025 = const()[name = tensor<string, []>("op_2025"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> var_2027 = const()[name = tensor<string, []>("op_2027"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> x_5_pad_type_0 = const()[name = tensor<string, []>("x_5_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> x_5_pad_0 = const()[name = tensor<string, []>("x_5_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [640, 1, 7, 7]> original_model_image_encoder_model_network_5_proj_0_lkb_reparam_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_5_proj_0_lkb_reparam_weight_to_fp16"), val = tensor<fp16, [640, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35204416)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_5_proj_0_lkb_reparam_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_5_proj_0_lkb_reparam_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35267200)))];
            tensor<fp16, [1, 640, 8, 8]> x_5_cast_fp16 = conv(bias = original_model_image_encoder_model_network_5_proj_0_lkb_reparam_bias_to_fp16, dilations = var_2027, groups = var_17, pad = x_5_pad_0, pad_type = x_5_pad_type_0, strides = var_2025, weight = original_model_image_encoder_model_network_5_proj_0_lkb_reparam_weight_to_fp16, x = input_673_cast_fp16)[name = tensor<string, []>("x_5_cast_fp16")];
            tensor<int32, [2]> var_2032 = const()[name = tensor<string, []>("op_2032"), val = tensor<int32, [2]>([2, 3])];
            tensor<fp16, [1, 640, 1, 1]> input_675_cast_fp16 = reduce_mean(axes = var_2032, keep_dims = var_5, x = x_5_cast_fp16)[name = tensor<string, []>("input_675_cast_fp16")];
            tensor<int32, [2]> var_2036 = const()[name = tensor<string, []>("op_2036"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2038 = const()[name = tensor<string, []>("op_2038"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_677_pad_type_0 = const()[name = tensor<string, []>("input_677_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_677_pad_0 = const()[name = tensor<string, []>("input_677_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [160, 640, 1, 1]> original_model_image_encoder_model_network_5_proj_0_se_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_5_proj_0_se_fc1_weight_to_fp16"), val = tensor<fp16, [160, 640, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35268544)))];
            tensor<fp16, [160]> original_model_image_encoder_model_network_5_proj_0_se_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_5_proj_0_se_fc1_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35473408)))];
            tensor<fp16, [1, 160, 1, 1]> input_677_cast_fp16 = conv(bias = original_model_image_encoder_model_network_5_proj_0_se_fc1_bias_to_fp16, dilations = var_2038, groups = var_8, pad = input_677_pad_0, pad_type = input_677_pad_type_0, strides = var_2036, weight = original_model_image_encoder_model_network_5_proj_0_se_fc1_weight_to_fp16, x = input_675_cast_fp16)[name = tensor<string, []>("input_677_cast_fp16")];
            tensor<fp16, [1, 160, 1, 1]> input_679_cast_fp16 = relu(x = input_677_cast_fp16)[name = tensor<string, []>("input_679_cast_fp16")];
            tensor<int32, [2]> var_2044 = const()[name = tensor<string, []>("op_2044"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2046 = const()[name = tensor<string, []>("op_2046"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> x_7_pad_type_0 = const()[name = tensor<string, []>("x_7_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> x_7_pad_0 = const()[name = tensor<string, []>("x_7_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [640, 160, 1, 1]> original_model_image_encoder_model_network_5_proj_0_se_fc2_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_5_proj_0_se_fc2_weight_to_fp16"), val = tensor<fp16, [640, 160, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35473792)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_5_proj_0_se_fc2_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_5_proj_0_se_fc2_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35678656)))];
            tensor<fp16, [1, 640, 1, 1]> x_7_cast_fp16 = conv(bias = original_model_image_encoder_model_network_5_proj_0_se_fc2_bias_to_fp16, dilations = var_2046, groups = var_8, pad = x_7_pad_0, pad_type = x_7_pad_type_0, strides = var_2044, weight = original_model_image_encoder_model_network_5_proj_0_se_fc2_weight_to_fp16, x = input_679_cast_fp16)[name = tensor<string, []>("x_7_cast_fp16")];
            tensor<fp16, [1, 640, 1, 1]> var_2049_cast_fp16 = sigmoid(x = x_7_cast_fp16)[name = tensor<string, []>("op_2049_cast_fp16")];
            tensor<fp16, [1, 640, 8, 8]> input_681_cast_fp16 = mul(x = x_5_cast_fp16, y = var_2049_cast_fp16)[name = tensor<string, []>("input_681_cast_fp16")];
            tensor<string, []> input_683_mode_0 = const()[name = tensor<string, []>("input_683_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 640, 8, 8]> input_683_cast_fp16 = gelu(mode = input_683_mode_0, x = input_681_cast_fp16)[name = tensor<string, []>("input_683_cast_fp16")];
            tensor<int32, [2]> var_2055 = const()[name = tensor<string, []>("op_2055"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2057 = const()[name = tensor<string, []>("op_2057"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_685_pad_type_0 = const()[name = tensor<string, []>("input_685_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_685_pad_0 = const()[name = tensor<string, []>("input_685_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [640, 640, 1, 1]> original_model_image_encoder_model_network_5_proj_1_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_5_proj_1_reparam_conv_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35680000)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_5_proj_1_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_5_proj_1_reparam_conv_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36499264)))];
            tensor<fp16, [1, 640, 8, 8]> input_685_cast_fp16 = conv(bias = original_model_image_encoder_model_network_5_proj_1_reparam_conv_bias_to_fp16, dilations = var_2057, groups = var_8, pad = input_685_pad_0, pad_type = input_685_pad_type_0, strides = var_2055, weight = original_model_image_encoder_model_network_5_proj_1_reparam_conv_weight_to_fp16, x = input_683_cast_fp16)[name = tensor<string, []>("input_685_cast_fp16")];
            tensor<string, []> input_687_mode_0 = const()[name = tensor<string, []>("input_687_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 640, 8, 8]> input_687_cast_fp16 = gelu(mode = input_687_mode_0, x = input_685_cast_fp16)[name = tensor<string, []>("input_687_cast_fp16")];
            tensor<int32, [2]> var_2064 = const()[name = tensor<string, []>("op_2064"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2066 = const()[name = tensor<string, []>("op_2066"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_689_pad_type_0 = const()[name = tensor<string, []>("input_689_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_689_pad_0 = const()[name = tensor<string, []>("input_689_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [640, 1, 7, 7]> original_model_image_encoder_model_network_6_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_6_reparam_conv_weight_to_fp16"), val = tensor<fp16, [640, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36500608)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_6_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_6_reparam_conv_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36563392)))];
            tensor<fp16, [1, 640, 8, 8]> input_689_cast_fp16 = conv(bias = original_model_image_encoder_model_network_6_reparam_conv_bias_to_fp16, dilations = var_2066, groups = var_18, pad = input_689_pad_0, pad_type = input_689_pad_type_0, strides = var_2064, weight = original_model_image_encoder_model_network_6_reparam_conv_weight_to_fp16, x = input_687_cast_fp16)[name = tensor<string, []>("input_689_cast_fp16")];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_0_norm_running_mean_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_0_norm_running_mean_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36564736)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_0_norm_running_var_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_0_norm_running_var_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36566080)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_0_norm_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_0_norm_weight_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36567424)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_0_norm_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_0_norm_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36568768)))];
            tensor<fp16, []> var_14_to_fp16 = const()[name = tensor<string, []>("op_14_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 640, 8, 8]> x_9_cast_fp16 = batch_norm(beta = original_model_image_encoder_model_network_7_0_norm_bias_to_fp16, epsilon = var_14_to_fp16, gamma = original_model_image_encoder_model_network_7_0_norm_weight_to_fp16, mean = original_model_image_encoder_model_network_7_0_norm_running_mean_to_fp16, variance = original_model_image_encoder_model_network_7_0_norm_running_var_to_fp16, x = input_689_cast_fp16)[name = tensor<string, []>("x_9_cast_fp16")];
            tensor<int32, [3]> concat_0 = const()[name = tensor<string, []>("concat_0"), val = tensor<int32, [3]>([1, 640, 64])];
            tensor<fp16, [1, 640, 64]> var_2094_cast_fp16 = reshape(shape = concat_0, x = x_9_cast_fp16)[name = tensor<string, []>("op_2094_cast_fp16")];
            tensor<int32, [3]> input_691_perm_0 = const()[name = tensor<string, []>("input_691_perm_0"), val = tensor<int32, [3]>([0, -1, -2])];
            tensor<fp16, [1920, 640]> original_model_image_encoder_model_network_7_0_token_mixer_qkv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_0_token_mixer_qkv_weight_to_fp16"), val = tensor<fp16, [1920, 640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36570112)))];
            tensor<fp16, [1920]> linear_0_bias_0_to_fp16 = const()[name = tensor<string, []>("linear_0_bias_0_to_fp16"), val = tensor<fp16, [1920]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39027776)))];
            tensor<fp16, [1, 64, 640]> transpose_19 = transpose(perm = input_691_perm_0, x = var_2094_cast_fp16)[name = tensor<string, []>("transpose_19")];
            tensor<fp16, [1, 64, 1920]> linear_0_cast_fp16 = linear(bias = linear_0_bias_0_to_fp16, weight = original_model_image_encoder_model_network_7_0_token_mixer_qkv_weight_to_fp16, x = transpose_19)[name = tensor<string, []>("linear_0_cast_fp16")];
            tensor<int32, [5]> var_2098 = const()[name = tensor<string, []>("op_2098"), val = tensor<int32, [5]>([1, 64, 3, 20, 32])];
            tensor<fp16, [1, 64, 3, 20, 32]> var_2099_cast_fp16 = reshape(shape = var_2098, x = linear_0_cast_fp16)[name = tensor<string, []>("op_2099_cast_fp16")];
            tensor<int32, [5]> var_2100 = const()[name = tensor<string, []>("op_2100"), val = tensor<int32, [5]>([2, 0, 3, 1, 4])];
            tensor<int32, [3]> var_2102_split_sizes_0 = const()[name = tensor<string, []>("op_2102_split_sizes_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<int32, []> var_2102_axis_0 = const()[name = tensor<string, []>("op_2102_axis_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [3, 1, 20, 64, 32]> transpose_18 = transpose(perm = var_2100, x = var_2099_cast_fp16)[name = tensor<string, []>("transpose_18")];
            tensor<fp16, [1, 1, 20, 64, 32]> var_2102_cast_fp16_0, tensor<fp16, [1, 1, 20, 64, 32]> var_2102_cast_fp16_1, tensor<fp16, [1, 1, 20, 64, 32]> var_2102_cast_fp16_2 = split(axis = var_2102_axis_0, split_sizes = var_2102_split_sizes_0, x = transpose_18)[name = tensor<string, []>("op_2102_cast_fp16")];
            tensor<int32, [1]> squeeze_0_axes_0 = const()[name = tensor<string, []>("squeeze_0_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 20, 64, 32]> squeeze_0_cast_fp16 = squeeze(axes = squeeze_0_axes_0, x = var_2102_cast_fp16_0)[name = tensor<string, []>("squeeze_0_cast_fp16")];
            tensor<int32, [1]> squeeze_1_axes_0 = const()[name = tensor<string, []>("squeeze_1_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 20, 64, 32]> squeeze_1_cast_fp16 = squeeze(axes = squeeze_1_axes_0, x = var_2102_cast_fp16_1)[name = tensor<string, []>("squeeze_1_cast_fp16")];
            tensor<int32, [1]> squeeze_2_axes_0 = const()[name = tensor<string, []>("squeeze_2_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 20, 64, 32]> squeeze_2_cast_fp16 = squeeze(axes = squeeze_2_axes_0, x = var_2102_cast_fp16_2)[name = tensor<string, []>("squeeze_2_cast_fp16")];
            tensor<fp16, []> var_2106_to_fp16 = const()[name = tensor<string, []>("op_2106_to_fp16"), val = tensor<fp16, []>(0x1.6ap-3)];
            tensor<fp16, [1, 20, 64, 32]> var_2107_cast_fp16 = mul(x = squeeze_0_cast_fp16, y = var_2106_to_fp16)[name = tensor<string, []>("op_2107_cast_fp16")];
            tensor<int32, [4]> var_2108_perm_0 = const()[name = tensor<string, []>("op_2108_perm_0"), val = tensor<int32, [4]>([0, 1, -1, -2])];
            tensor<bool, []> attn_1_transpose_x_0 = const()[name = tensor<string, []>("attn_1_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_1_transpose_y_0 = const()[name = tensor<string, []>("attn_1_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 20, 32, 64]> transpose_17 = transpose(perm = var_2108_perm_0, x = squeeze_1_cast_fp16)[name = tensor<string, []>("transpose_17")];
            tensor<fp16, [1, 20, 64, 64]> attn_1_cast_fp16 = matmul(transpose_x = attn_1_transpose_x_0, transpose_y = attn_1_transpose_y_0, x = var_2107_cast_fp16, y = transpose_17)[name = tensor<string, []>("attn_1_cast_fp16")];
            tensor<fp16, [1, 20, 64, 64]> input_693_cast_fp16 = softmax(axis = var_23, x = attn_1_cast_fp16)[name = tensor<string, []>("input_693_cast_fp16")];
            tensor<bool, []> var_2112_transpose_x_0 = const()[name = tensor<string, []>("op_2112_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> var_2112_transpose_y_0 = const()[name = tensor<string, []>("op_2112_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 20, 64, 32]> var_2112_cast_fp16 = matmul(transpose_x = var_2112_transpose_x_0, transpose_y = var_2112_transpose_y_0, x = input_693_cast_fp16, y = squeeze_2_cast_fp16)[name = tensor<string, []>("op_2112_cast_fp16")];
            tensor<int32, [4]> var_2113_perm_0 = const()[name = tensor<string, []>("op_2113_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2114 = const()[name = tensor<string, []>("op_2114"), val = tensor<int32, [3]>([1, 64, 640])];
            tensor<fp16, [1, 64, 20, 32]> transpose_16 = transpose(perm = var_2113_perm_0, x = var_2112_cast_fp16)[name = tensor<string, []>("transpose_16")];
            tensor<fp16, [1, 64, 640]> input_695_cast_fp16 = reshape(shape = var_2114, x = transpose_16)[name = tensor<string, []>("input_695_cast_fp16")];
            tensor<fp16, [640, 640]> original_model_image_encoder_model_network_7_0_token_mixer_proj_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_0_token_mixer_proj_weight_to_fp16"), val = tensor<fp16, [640, 640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39031680)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_0_token_mixer_proj_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_0_token_mixer_proj_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39850944)))];
            tensor<fp16, [1, 64, 640]> linear_1_cast_fp16 = linear(bias = original_model_image_encoder_model_network_7_0_token_mixer_proj_bias_to_fp16, weight = original_model_image_encoder_model_network_7_0_token_mixer_proj_weight_to_fp16, x = input_695_cast_fp16)[name = tensor<string, []>("linear_1_cast_fp16")];
            tensor<int32, [3]> var_2120_perm_0 = const()[name = tensor<string, []>("op_2120_perm_0"), val = tensor<int32, [3]>([0, -1, -2])];
            tensor<int32, [4]> var_2121 = const()[name = tensor<string, []>("op_2121"), val = tensor<int32, [4]>([1, 640, 8, 8])];
            tensor<fp16, [1, 640, 64]> transpose_15 = transpose(perm = var_2120_perm_0, x = linear_1_cast_fp16)[name = tensor<string, []>("transpose_15")];
            tensor<fp16, [1, 640, 8, 8]> var_2122_cast_fp16 = reshape(shape = var_2121, x = transpose_15)[name = tensor<string, []>("op_2122_cast_fp16")];
            tensor<fp16, [640, 1, 1]> original_model_image_encoder_model_network_7_0_layer_scale_1_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_0_layer_scale_1_to_fp16"), val = tensor<fp16, [640, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39852288)))];
            tensor<fp16, [1, 640, 8, 8]> var_2123_cast_fp16 = mul(x = original_model_image_encoder_model_network_7_0_layer_scale_1_to_fp16, y = var_2122_cast_fp16)[name = tensor<string, []>("op_2123_cast_fp16")];
            tensor<fp16, [1, 640, 8, 8]> input_699_cast_fp16 = add(x = input_689_cast_fp16, y = var_2123_cast_fp16)[name = tensor<string, []>("input_699_cast_fp16")];
            tensor<int32, [2]> var_2131 = const()[name = tensor<string, []>("op_2131"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2133 = const()[name = tensor<string, []>("op_2133"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_701_pad_type_0 = const()[name = tensor<string, []>("input_701_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_701_pad_0 = const()[name = tensor<string, []>("input_701_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [640, 1, 7, 7]> input_703_weight_0_to_fp16 = const()[name = tensor<string, []>("input_703_weight_0_to_fp16"), val = tensor<fp16, [640, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39853632)))];
            tensor<fp16, [640]> input_703_bias_0_to_fp16 = const()[name = tensor<string, []>("input_703_bias_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39916416)))];
            tensor<fp16, [1, 640, 8, 8]> input_703_cast_fp16 = conv(bias = input_703_bias_0_to_fp16, dilations = var_2133, groups = var_18, pad = input_701_pad_0, pad_type = input_701_pad_type_0, strides = var_2131, weight = input_703_weight_0_to_fp16, x = input_699_cast_fp16)[name = tensor<string, []>("input_703_cast_fp16")];
            tensor<int32, [2]> var_2143 = const()[name = tensor<string, []>("op_2143"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2145 = const()[name = tensor<string, []>("op_2145"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_705_pad_type_0 = const()[name = tensor<string, []>("input_705_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_705_pad_0 = const()[name = tensor<string, []>("input_705_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1920, 640, 1, 1]> original_model_image_encoder_model_network_7_0_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_0_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [1920, 640, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39917760)))];
            tensor<fp16, [1920]> original_model_image_encoder_model_network_7_0_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_0_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [1920]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42375424)))];
            tensor<fp16, [1, 1920, 8, 8]> input_705_cast_fp16 = conv(bias = original_model_image_encoder_model_network_7_0_convffn_fc1_bias_to_fp16, dilations = var_2145, groups = var_8, pad = input_705_pad_0, pad_type = input_705_pad_type_0, strides = var_2143, weight = original_model_image_encoder_model_network_7_0_convffn_fc1_weight_to_fp16, x = input_703_cast_fp16)[name = tensor<string, []>("input_705_cast_fp16")];
            tensor<string, []> input_707_mode_0 = const()[name = tensor<string, []>("input_707_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 1920, 8, 8]> input_707_cast_fp16 = gelu(mode = input_707_mode_0, x = input_705_cast_fp16)[name = tensor<string, []>("input_707_cast_fp16")];
            tensor<int32, [2]> var_2152 = const()[name = tensor<string, []>("op_2152"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2154 = const()[name = tensor<string, []>("op_2154"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_711_pad_type_0 = const()[name = tensor<string, []>("input_711_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_711_pad_0 = const()[name = tensor<string, []>("input_711_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [640, 1920, 1, 1]> var_2158_weight_0_to_fp16 = const()[name = tensor<string, []>("op_2158_weight_0_to_fp16"), val = tensor<fp16, [640, 1920, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42379328)))];
            tensor<fp16, [640]> var_2158_bias_0_to_fp16 = const()[name = tensor<string, []>("op_2158_bias_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44836992)))];
            tensor<fp16, [1, 640, 8, 8]> var_2158_cast_fp16 = conv(bias = var_2158_bias_0_to_fp16, dilations = var_2154, groups = var_8, pad = input_711_pad_0, pad_type = input_711_pad_type_0, strides = var_2152, weight = var_2158_weight_0_to_fp16, x = input_707_cast_fp16)[name = tensor<string, []>("op_2158_cast_fp16")];
            tensor<fp16, [1, 640, 8, 8]> input_713_cast_fp16 = add(x = input_699_cast_fp16, y = var_2158_cast_fp16)[name = tensor<string, []>("input_713_cast_fp16")];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_1_norm_running_mean_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_1_norm_running_mean_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44838336)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_1_norm_running_var_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_1_norm_running_var_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44839680)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_1_norm_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_1_norm_weight_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44841024)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_1_norm_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_1_norm_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44842368)))];
            tensor<fp16, [1, 640, 8, 8]> x_13_cast_fp16 = batch_norm(beta = original_model_image_encoder_model_network_7_1_norm_bias_to_fp16, epsilon = var_14_to_fp16, gamma = original_model_image_encoder_model_network_7_1_norm_weight_to_fp16, mean = original_model_image_encoder_model_network_7_1_norm_running_mean_to_fp16, variance = original_model_image_encoder_model_network_7_1_norm_running_var_to_fp16, x = input_713_cast_fp16)[name = tensor<string, []>("x_13_cast_fp16")];
            tensor<int32, [3]> concat_1 = const()[name = tensor<string, []>("concat_1"), val = tensor<int32, [3]>([1, 640, 64])];
            tensor<fp16, [1, 640, 64]> var_2181_cast_fp16 = reshape(shape = concat_1, x = x_13_cast_fp16)[name = tensor<string, []>("op_2181_cast_fp16")];
            tensor<int32, [3]> input_715_perm_0 = const()[name = tensor<string, []>("input_715_perm_0"), val = tensor<int32, [3]>([0, -1, -2])];
            tensor<fp16, [1920, 640]> original_model_image_encoder_model_network_7_1_token_mixer_qkv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_1_token_mixer_qkv_weight_to_fp16"), val = tensor<fp16, [1920, 640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44843712)))];
            tensor<fp16, [1, 64, 640]> transpose_14 = transpose(perm = input_715_perm_0, x = var_2181_cast_fp16)[name = tensor<string, []>("transpose_14")];
            tensor<fp16, [1, 64, 1920]> linear_2_cast_fp16 = linear(bias = linear_0_bias_0_to_fp16, weight = original_model_image_encoder_model_network_7_1_token_mixer_qkv_weight_to_fp16, x = transpose_14)[name = tensor<string, []>("linear_2_cast_fp16")];
            tensor<int32, [5]> var_2185 = const()[name = tensor<string, []>("op_2185"), val = tensor<int32, [5]>([1, 64, 3, 20, 32])];
            tensor<fp16, [1, 64, 3, 20, 32]> var_2186_cast_fp16 = reshape(shape = var_2185, x = linear_2_cast_fp16)[name = tensor<string, []>("op_2186_cast_fp16")];
            tensor<int32, [5]> var_2187 = const()[name = tensor<string, []>("op_2187"), val = tensor<int32, [5]>([2, 0, 3, 1, 4])];
            tensor<int32, [3]> var_2189_split_sizes_0 = const()[name = tensor<string, []>("op_2189_split_sizes_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<int32, []> var_2189_axis_0 = const()[name = tensor<string, []>("op_2189_axis_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [3, 1, 20, 64, 32]> transpose_13 = transpose(perm = var_2187, x = var_2186_cast_fp16)[name = tensor<string, []>("transpose_13")];
            tensor<fp16, [1, 1, 20, 64, 32]> var_2189_cast_fp16_0, tensor<fp16, [1, 1, 20, 64, 32]> var_2189_cast_fp16_1, tensor<fp16, [1, 1, 20, 64, 32]> var_2189_cast_fp16_2 = split(axis = var_2189_axis_0, split_sizes = var_2189_split_sizes_0, x = transpose_13)[name = tensor<string, []>("op_2189_cast_fp16")];
            tensor<int32, [1]> squeeze_3_axes_0 = const()[name = tensor<string, []>("squeeze_3_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 20, 64, 32]> squeeze_3_cast_fp16 = squeeze(axes = squeeze_3_axes_0, x = var_2189_cast_fp16_0)[name = tensor<string, []>("squeeze_3_cast_fp16")];
            tensor<int32, [1]> squeeze_4_axes_0 = const()[name = tensor<string, []>("squeeze_4_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 20, 64, 32]> squeeze_4_cast_fp16 = squeeze(axes = squeeze_4_axes_0, x = var_2189_cast_fp16_1)[name = tensor<string, []>("squeeze_4_cast_fp16")];
            tensor<int32, [1]> squeeze_5_axes_0 = const()[name = tensor<string, []>("squeeze_5_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 20, 64, 32]> squeeze_5_cast_fp16 = squeeze(axes = squeeze_5_axes_0, x = var_2189_cast_fp16_2)[name = tensor<string, []>("squeeze_5_cast_fp16")];
            tensor<fp16, []> var_2193_to_fp16 = const()[name = tensor<string, []>("op_2193_to_fp16"), val = tensor<fp16, []>(0x1.6ap-3)];
            tensor<fp16, [1, 20, 64, 32]> var_2194_cast_fp16 = mul(x = squeeze_3_cast_fp16, y = var_2193_to_fp16)[name = tensor<string, []>("op_2194_cast_fp16")];
            tensor<int32, [4]> var_2195_perm_0 = const()[name = tensor<string, []>("op_2195_perm_0"), val = tensor<int32, [4]>([0, 1, -1, -2])];
            tensor<bool, []> attn_5_transpose_x_0 = const()[name = tensor<string, []>("attn_5_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_5_transpose_y_0 = const()[name = tensor<string, []>("attn_5_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 20, 32, 64]> transpose_12 = transpose(perm = var_2195_perm_0, x = squeeze_4_cast_fp16)[name = tensor<string, []>("transpose_12")];
            tensor<fp16, [1, 20, 64, 64]> attn_5_cast_fp16 = matmul(transpose_x = attn_5_transpose_x_0, transpose_y = attn_5_transpose_y_0, x = var_2194_cast_fp16, y = transpose_12)[name = tensor<string, []>("attn_5_cast_fp16")];
            tensor<fp16, [1, 20, 64, 64]> input_717_cast_fp16 = softmax(axis = var_23, x = attn_5_cast_fp16)[name = tensor<string, []>("input_717_cast_fp16")];
            tensor<bool, []> var_2199_transpose_x_0 = const()[name = tensor<string, []>("op_2199_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> var_2199_transpose_y_0 = const()[name = tensor<string, []>("op_2199_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 20, 64, 32]> var_2199_cast_fp16 = matmul(transpose_x = var_2199_transpose_x_0, transpose_y = var_2199_transpose_y_0, x = input_717_cast_fp16, y = squeeze_5_cast_fp16)[name = tensor<string, []>("op_2199_cast_fp16")];
            tensor<int32, [4]> var_2200_perm_0 = const()[name = tensor<string, []>("op_2200_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2201 = const()[name = tensor<string, []>("op_2201"), val = tensor<int32, [3]>([1, 64, 640])];
            tensor<fp16, [1, 64, 20, 32]> transpose_11 = transpose(perm = var_2200_perm_0, x = var_2199_cast_fp16)[name = tensor<string, []>("transpose_11")];
            tensor<fp16, [1, 64, 640]> input_719_cast_fp16 = reshape(shape = var_2201, x = transpose_11)[name = tensor<string, []>("input_719_cast_fp16")];
            tensor<fp16, [640, 640]> original_model_image_encoder_model_network_7_1_token_mixer_proj_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_1_token_mixer_proj_weight_to_fp16"), val = tensor<fp16, [640, 640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47301376)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_1_token_mixer_proj_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_1_token_mixer_proj_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48120640)))];
            tensor<fp16, [1, 64, 640]> linear_3_cast_fp16 = linear(bias = original_model_image_encoder_model_network_7_1_token_mixer_proj_bias_to_fp16, weight = original_model_image_encoder_model_network_7_1_token_mixer_proj_weight_to_fp16, x = input_719_cast_fp16)[name = tensor<string, []>("linear_3_cast_fp16")];
            tensor<int32, [3]> var_2207_perm_0 = const()[name = tensor<string, []>("op_2207_perm_0"), val = tensor<int32, [3]>([0, -1, -2])];
            tensor<int32, [4]> var_2208 = const()[name = tensor<string, []>("op_2208"), val = tensor<int32, [4]>([1, 640, 8, 8])];
            tensor<fp16, [1, 640, 64]> transpose_10 = transpose(perm = var_2207_perm_0, x = linear_3_cast_fp16)[name = tensor<string, []>("transpose_10")];
            tensor<fp16, [1, 640, 8, 8]> var_2209_cast_fp16 = reshape(shape = var_2208, x = transpose_10)[name = tensor<string, []>("op_2209_cast_fp16")];
            tensor<fp16, [640, 1, 1]> original_model_image_encoder_model_network_7_1_layer_scale_1_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_1_layer_scale_1_to_fp16"), val = tensor<fp16, [640, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48121984)))];
            tensor<fp16, [1, 640, 8, 8]> var_2210_cast_fp16 = mul(x = original_model_image_encoder_model_network_7_1_layer_scale_1_to_fp16, y = var_2209_cast_fp16)[name = tensor<string, []>("op_2210_cast_fp16")];
            tensor<fp16, [1, 640, 8, 8]> input_723_cast_fp16 = add(x = input_713_cast_fp16, y = var_2210_cast_fp16)[name = tensor<string, []>("input_723_cast_fp16")];
            tensor<int32, [2]> var_2218 = const()[name = tensor<string, []>("op_2218"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2220 = const()[name = tensor<string, []>("op_2220"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_725_pad_type_0 = const()[name = tensor<string, []>("input_725_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_725_pad_0 = const()[name = tensor<string, []>("input_725_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [640, 1, 7, 7]> input_727_weight_0_to_fp16 = const()[name = tensor<string, []>("input_727_weight_0_to_fp16"), val = tensor<fp16, [640, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48123328)))];
            tensor<fp16, [640]> input_727_bias_0_to_fp16 = const()[name = tensor<string, []>("input_727_bias_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48186112)))];
            tensor<fp16, [1, 640, 8, 8]> input_727_cast_fp16 = conv(bias = input_727_bias_0_to_fp16, dilations = var_2220, groups = var_18, pad = input_725_pad_0, pad_type = input_725_pad_type_0, strides = var_2218, weight = input_727_weight_0_to_fp16, x = input_723_cast_fp16)[name = tensor<string, []>("input_727_cast_fp16")];
            tensor<int32, [2]> var_2230 = const()[name = tensor<string, []>("op_2230"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2232 = const()[name = tensor<string, []>("op_2232"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_729_pad_type_0 = const()[name = tensor<string, []>("input_729_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_729_pad_0 = const()[name = tensor<string, []>("input_729_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1920, 640, 1, 1]> original_model_image_encoder_model_network_7_1_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_1_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [1920, 640, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48187456)))];
            tensor<fp16, [1920]> original_model_image_encoder_model_network_7_1_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_1_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [1920]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(50645120)))];
            tensor<fp16, [1, 1920, 8, 8]> input_729_cast_fp16 = conv(bias = original_model_image_encoder_model_network_7_1_convffn_fc1_bias_to_fp16, dilations = var_2232, groups = var_8, pad = input_729_pad_0, pad_type = input_729_pad_type_0, strides = var_2230, weight = original_model_image_encoder_model_network_7_1_convffn_fc1_weight_to_fp16, x = input_727_cast_fp16)[name = tensor<string, []>("input_729_cast_fp16")];
            tensor<string, []> input_731_mode_0 = const()[name = tensor<string, []>("input_731_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 1920, 8, 8]> input_731_cast_fp16 = gelu(mode = input_731_mode_0, x = input_729_cast_fp16)[name = tensor<string, []>("input_731_cast_fp16")];
            tensor<int32, [2]> var_2239 = const()[name = tensor<string, []>("op_2239"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2241 = const()[name = tensor<string, []>("op_2241"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_735_pad_type_0 = const()[name = tensor<string, []>("input_735_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_735_pad_0 = const()[name = tensor<string, []>("input_735_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [640, 1920, 1, 1]> var_2245_weight_0_to_fp16 = const()[name = tensor<string, []>("op_2245_weight_0_to_fp16"), val = tensor<fp16, [640, 1920, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(50649024)))];
            tensor<fp16, [640]> var_2245_bias_0_to_fp16 = const()[name = tensor<string, []>("op_2245_bias_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53106688)))];
            tensor<fp16, [1, 640, 8, 8]> var_2245_cast_fp16 = conv(bias = var_2245_bias_0_to_fp16, dilations = var_2241, groups = var_8, pad = input_735_pad_0, pad_type = input_735_pad_type_0, strides = var_2239, weight = var_2245_weight_0_to_fp16, x = input_731_cast_fp16)[name = tensor<string, []>("op_2245_cast_fp16")];
            tensor<fp16, [1, 640, 8, 8]> input_737_cast_fp16 = add(x = input_723_cast_fp16, y = var_2245_cast_fp16)[name = tensor<string, []>("input_737_cast_fp16")];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_2_norm_running_mean_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_2_norm_running_mean_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53108032)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_2_norm_running_var_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_2_norm_running_var_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53109376)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_2_norm_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_2_norm_weight_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53110720)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_2_norm_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_2_norm_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53112064)))];
            tensor<fp16, [1, 640, 8, 8]> x_17_cast_fp16 = batch_norm(beta = original_model_image_encoder_model_network_7_2_norm_bias_to_fp16, epsilon = var_14_to_fp16, gamma = original_model_image_encoder_model_network_7_2_norm_weight_to_fp16, mean = original_model_image_encoder_model_network_7_2_norm_running_mean_to_fp16, variance = original_model_image_encoder_model_network_7_2_norm_running_var_to_fp16, x = input_737_cast_fp16)[name = tensor<string, []>("x_17_cast_fp16")];
            tensor<int32, [3]> concat_2 = const()[name = tensor<string, []>("concat_2"), val = tensor<int32, [3]>([1, 640, 64])];
            tensor<fp16, [1, 640, 64]> var_2268_cast_fp16 = reshape(shape = concat_2, x = x_17_cast_fp16)[name = tensor<string, []>("op_2268_cast_fp16")];
            tensor<int32, [3]> input_739_perm_0 = const()[name = tensor<string, []>("input_739_perm_0"), val = tensor<int32, [3]>([0, -1, -2])];
            tensor<fp16, [1920, 640]> original_model_image_encoder_model_network_7_2_token_mixer_qkv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_2_token_mixer_qkv_weight_to_fp16"), val = tensor<fp16, [1920, 640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53113408)))];
            tensor<fp16, [1, 64, 640]> transpose_9 = transpose(perm = input_739_perm_0, x = var_2268_cast_fp16)[name = tensor<string, []>("transpose_9")];
            tensor<fp16, [1, 64, 1920]> linear_4_cast_fp16 = linear(bias = linear_0_bias_0_to_fp16, weight = original_model_image_encoder_model_network_7_2_token_mixer_qkv_weight_to_fp16, x = transpose_9)[name = tensor<string, []>("linear_4_cast_fp16")];
            tensor<int32, [5]> var_2272 = const()[name = tensor<string, []>("op_2272"), val = tensor<int32, [5]>([1, 64, 3, 20, 32])];
            tensor<fp16, [1, 64, 3, 20, 32]> var_2273_cast_fp16 = reshape(shape = var_2272, x = linear_4_cast_fp16)[name = tensor<string, []>("op_2273_cast_fp16")];
            tensor<int32, [5]> var_2274 = const()[name = tensor<string, []>("op_2274"), val = tensor<int32, [5]>([2, 0, 3, 1, 4])];
            tensor<int32, [3]> var_2276_split_sizes_0 = const()[name = tensor<string, []>("op_2276_split_sizes_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<int32, []> var_2276_axis_0 = const()[name = tensor<string, []>("op_2276_axis_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [3, 1, 20, 64, 32]> transpose_8 = transpose(perm = var_2274, x = var_2273_cast_fp16)[name = tensor<string, []>("transpose_8")];
            tensor<fp16, [1, 1, 20, 64, 32]> var_2276_cast_fp16_0, tensor<fp16, [1, 1, 20, 64, 32]> var_2276_cast_fp16_1, tensor<fp16, [1, 1, 20, 64, 32]> var_2276_cast_fp16_2 = split(axis = var_2276_axis_0, split_sizes = var_2276_split_sizes_0, x = transpose_8)[name = tensor<string, []>("op_2276_cast_fp16")];
            tensor<int32, [1]> squeeze_6_axes_0 = const()[name = tensor<string, []>("squeeze_6_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 20, 64, 32]> squeeze_6_cast_fp16 = squeeze(axes = squeeze_6_axes_0, x = var_2276_cast_fp16_0)[name = tensor<string, []>("squeeze_6_cast_fp16")];
            tensor<int32, [1]> squeeze_7_axes_0 = const()[name = tensor<string, []>("squeeze_7_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 20, 64, 32]> squeeze_7_cast_fp16 = squeeze(axes = squeeze_7_axes_0, x = var_2276_cast_fp16_1)[name = tensor<string, []>("squeeze_7_cast_fp16")];
            tensor<int32, [1]> squeeze_8_axes_0 = const()[name = tensor<string, []>("squeeze_8_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 20, 64, 32]> squeeze_8_cast_fp16 = squeeze(axes = squeeze_8_axes_0, x = var_2276_cast_fp16_2)[name = tensor<string, []>("squeeze_8_cast_fp16")];
            tensor<fp16, []> var_2280_to_fp16 = const()[name = tensor<string, []>("op_2280_to_fp16"), val = tensor<fp16, []>(0x1.6ap-3)];
            tensor<fp16, [1, 20, 64, 32]> var_2281_cast_fp16 = mul(x = squeeze_6_cast_fp16, y = var_2280_to_fp16)[name = tensor<string, []>("op_2281_cast_fp16")];
            tensor<int32, [4]> var_2282_perm_0 = const()[name = tensor<string, []>("op_2282_perm_0"), val = tensor<int32, [4]>([0, 1, -1, -2])];
            tensor<bool, []> attn_9_transpose_x_0 = const()[name = tensor<string, []>("attn_9_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_9_transpose_y_0 = const()[name = tensor<string, []>("attn_9_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 20, 32, 64]> transpose_7 = transpose(perm = var_2282_perm_0, x = squeeze_7_cast_fp16)[name = tensor<string, []>("transpose_7")];
            tensor<fp16, [1, 20, 64, 64]> attn_9_cast_fp16 = matmul(transpose_x = attn_9_transpose_x_0, transpose_y = attn_9_transpose_y_0, x = var_2281_cast_fp16, y = transpose_7)[name = tensor<string, []>("attn_9_cast_fp16")];
            tensor<fp16, [1, 20, 64, 64]> input_741_cast_fp16 = softmax(axis = var_23, x = attn_9_cast_fp16)[name = tensor<string, []>("input_741_cast_fp16")];
            tensor<bool, []> var_2286_transpose_x_0 = const()[name = tensor<string, []>("op_2286_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> var_2286_transpose_y_0 = const()[name = tensor<string, []>("op_2286_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 20, 64, 32]> var_2286_cast_fp16 = matmul(transpose_x = var_2286_transpose_x_0, transpose_y = var_2286_transpose_y_0, x = input_741_cast_fp16, y = squeeze_8_cast_fp16)[name = tensor<string, []>("op_2286_cast_fp16")];
            tensor<int32, [4]> var_2287_perm_0 = const()[name = tensor<string, []>("op_2287_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2288 = const()[name = tensor<string, []>("op_2288"), val = tensor<int32, [3]>([1, 64, 640])];
            tensor<fp16, [1, 64, 20, 32]> transpose_6 = transpose(perm = var_2287_perm_0, x = var_2286_cast_fp16)[name = tensor<string, []>("transpose_6")];
            tensor<fp16, [1, 64, 640]> input_743_cast_fp16 = reshape(shape = var_2288, x = transpose_6)[name = tensor<string, []>("input_743_cast_fp16")];
            tensor<fp16, [640, 640]> original_model_image_encoder_model_network_7_2_token_mixer_proj_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_2_token_mixer_proj_weight_to_fp16"), val = tensor<fp16, [640, 640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(55571072)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_2_token_mixer_proj_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_2_token_mixer_proj_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(56390336)))];
            tensor<fp16, [1, 64, 640]> linear_5_cast_fp16 = linear(bias = original_model_image_encoder_model_network_7_2_token_mixer_proj_bias_to_fp16, weight = original_model_image_encoder_model_network_7_2_token_mixer_proj_weight_to_fp16, x = input_743_cast_fp16)[name = tensor<string, []>("linear_5_cast_fp16")];
            tensor<int32, [3]> var_2294_perm_0 = const()[name = tensor<string, []>("op_2294_perm_0"), val = tensor<int32, [3]>([0, -1, -2])];
            tensor<int32, [4]> var_2295 = const()[name = tensor<string, []>("op_2295"), val = tensor<int32, [4]>([1, 640, 8, 8])];
            tensor<fp16, [1, 640, 64]> transpose_5 = transpose(perm = var_2294_perm_0, x = linear_5_cast_fp16)[name = tensor<string, []>("transpose_5")];
            tensor<fp16, [1, 640, 8, 8]> var_2296_cast_fp16 = reshape(shape = var_2295, x = transpose_5)[name = tensor<string, []>("op_2296_cast_fp16")];
            tensor<fp16, [640, 1, 1]> original_model_image_encoder_model_network_7_2_layer_scale_1_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_2_layer_scale_1_to_fp16"), val = tensor<fp16, [640, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(56391680)))];
            tensor<fp16, [1, 640, 8, 8]> var_2297_cast_fp16 = mul(x = original_model_image_encoder_model_network_7_2_layer_scale_1_to_fp16, y = var_2296_cast_fp16)[name = tensor<string, []>("op_2297_cast_fp16")];
            tensor<fp16, [1, 640, 8, 8]> input_747_cast_fp16 = add(x = input_737_cast_fp16, y = var_2297_cast_fp16)[name = tensor<string, []>("input_747_cast_fp16")];
            tensor<int32, [2]> var_2305 = const()[name = tensor<string, []>("op_2305"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2307 = const()[name = tensor<string, []>("op_2307"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_749_pad_type_0 = const()[name = tensor<string, []>("input_749_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_749_pad_0 = const()[name = tensor<string, []>("input_749_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [640, 1, 7, 7]> input_751_weight_0_to_fp16 = const()[name = tensor<string, []>("input_751_weight_0_to_fp16"), val = tensor<fp16, [640, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(56393024)))];
            tensor<fp16, [640]> input_751_bias_0_to_fp16 = const()[name = tensor<string, []>("input_751_bias_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(56455808)))];
            tensor<fp16, [1, 640, 8, 8]> input_751_cast_fp16 = conv(bias = input_751_bias_0_to_fp16, dilations = var_2307, groups = var_18, pad = input_749_pad_0, pad_type = input_749_pad_type_0, strides = var_2305, weight = input_751_weight_0_to_fp16, x = input_747_cast_fp16)[name = tensor<string, []>("input_751_cast_fp16")];
            tensor<int32, [2]> var_2317 = const()[name = tensor<string, []>("op_2317"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2319 = const()[name = tensor<string, []>("op_2319"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_753_pad_type_0 = const()[name = tensor<string, []>("input_753_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_753_pad_0 = const()[name = tensor<string, []>("input_753_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1920, 640, 1, 1]> original_model_image_encoder_model_network_7_2_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_2_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [1920, 640, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(56457152)))];
            tensor<fp16, [1920]> original_model_image_encoder_model_network_7_2_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_2_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [1920]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58914816)))];
            tensor<fp16, [1, 1920, 8, 8]> input_753_cast_fp16 = conv(bias = original_model_image_encoder_model_network_7_2_convffn_fc1_bias_to_fp16, dilations = var_2319, groups = var_8, pad = input_753_pad_0, pad_type = input_753_pad_type_0, strides = var_2317, weight = original_model_image_encoder_model_network_7_2_convffn_fc1_weight_to_fp16, x = input_751_cast_fp16)[name = tensor<string, []>("input_753_cast_fp16")];
            tensor<string, []> input_755_mode_0 = const()[name = tensor<string, []>("input_755_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 1920, 8, 8]> input_755_cast_fp16 = gelu(mode = input_755_mode_0, x = input_753_cast_fp16)[name = tensor<string, []>("input_755_cast_fp16")];
            tensor<int32, [2]> var_2326 = const()[name = tensor<string, []>("op_2326"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2328 = const()[name = tensor<string, []>("op_2328"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_759_pad_type_0 = const()[name = tensor<string, []>("input_759_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_759_pad_0 = const()[name = tensor<string, []>("input_759_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [640, 1920, 1, 1]> var_2332_weight_0_to_fp16 = const()[name = tensor<string, []>("op_2332_weight_0_to_fp16"), val = tensor<fp16, [640, 1920, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58918720)))];
            tensor<fp16, [640]> var_2332_bias_0_to_fp16 = const()[name = tensor<string, []>("op_2332_bias_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61376384)))];
            tensor<fp16, [1, 640, 8, 8]> var_2332_cast_fp16 = conv(bias = var_2332_bias_0_to_fp16, dilations = var_2328, groups = var_8, pad = input_759_pad_0, pad_type = input_759_pad_type_0, strides = var_2326, weight = var_2332_weight_0_to_fp16, x = input_755_cast_fp16)[name = tensor<string, []>("op_2332_cast_fp16")];
            tensor<fp16, [1, 640, 8, 8]> input_761_cast_fp16 = add(x = input_747_cast_fp16, y = var_2332_cast_fp16)[name = tensor<string, []>("input_761_cast_fp16")];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_3_norm_running_mean_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_3_norm_running_mean_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61377728)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_3_norm_running_var_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_3_norm_running_var_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61379072)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_3_norm_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_3_norm_weight_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61380416)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_3_norm_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_3_norm_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61381760)))];
            tensor<fp16, [1, 640, 8, 8]> x_21_cast_fp16 = batch_norm(beta = original_model_image_encoder_model_network_7_3_norm_bias_to_fp16, epsilon = var_14_to_fp16, gamma = original_model_image_encoder_model_network_7_3_norm_weight_to_fp16, mean = original_model_image_encoder_model_network_7_3_norm_running_mean_to_fp16, variance = original_model_image_encoder_model_network_7_3_norm_running_var_to_fp16, x = input_761_cast_fp16)[name = tensor<string, []>("x_21_cast_fp16")];
            tensor<int32, [3]> concat_3 = const()[name = tensor<string, []>("concat_3"), val = tensor<int32, [3]>([1, 640, 64])];
            tensor<fp16, [1, 640, 64]> var_2355_cast_fp16 = reshape(shape = concat_3, x = x_21_cast_fp16)[name = tensor<string, []>("op_2355_cast_fp16")];
            tensor<int32, [3]> input_763_perm_0 = const()[name = tensor<string, []>("input_763_perm_0"), val = tensor<int32, [3]>([0, -1, -2])];
            tensor<fp16, [1920, 640]> original_model_image_encoder_model_network_7_3_token_mixer_qkv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_3_token_mixer_qkv_weight_to_fp16"), val = tensor<fp16, [1920, 640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61383104)))];
            tensor<fp16, [1, 64, 640]> transpose_4 = transpose(perm = input_763_perm_0, x = var_2355_cast_fp16)[name = tensor<string, []>("transpose_4")];
            tensor<fp16, [1, 64, 1920]> linear_6_cast_fp16 = linear(bias = linear_0_bias_0_to_fp16, weight = original_model_image_encoder_model_network_7_3_token_mixer_qkv_weight_to_fp16, x = transpose_4)[name = tensor<string, []>("linear_6_cast_fp16")];
            tensor<int32, [5]> var_2359 = const()[name = tensor<string, []>("op_2359"), val = tensor<int32, [5]>([1, 64, 3, 20, 32])];
            tensor<fp16, [1, 64, 3, 20, 32]> var_2360_cast_fp16 = reshape(shape = var_2359, x = linear_6_cast_fp16)[name = tensor<string, []>("op_2360_cast_fp16")];
            tensor<int32, [5]> var_2361 = const()[name = tensor<string, []>("op_2361"), val = tensor<int32, [5]>([2, 0, 3, 1, 4])];
            tensor<int32, [3]> var_2363_split_sizes_0 = const()[name = tensor<string, []>("op_2363_split_sizes_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<int32, []> var_2363_axis_0 = const()[name = tensor<string, []>("op_2363_axis_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [3, 1, 20, 64, 32]> transpose_3 = transpose(perm = var_2361, x = var_2360_cast_fp16)[name = tensor<string, []>("transpose_3")];
            tensor<fp16, [1, 1, 20, 64, 32]> var_2363_cast_fp16_0, tensor<fp16, [1, 1, 20, 64, 32]> var_2363_cast_fp16_1, tensor<fp16, [1, 1, 20, 64, 32]> var_2363_cast_fp16_2 = split(axis = var_2363_axis_0, split_sizes = var_2363_split_sizes_0, x = transpose_3)[name = tensor<string, []>("op_2363_cast_fp16")];
            tensor<int32, [1]> squeeze_9_axes_0 = const()[name = tensor<string, []>("squeeze_9_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 20, 64, 32]> squeeze_9_cast_fp16 = squeeze(axes = squeeze_9_axes_0, x = var_2363_cast_fp16_0)[name = tensor<string, []>("squeeze_9_cast_fp16")];
            tensor<int32, [1]> squeeze_10_axes_0 = const()[name = tensor<string, []>("squeeze_10_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 20, 64, 32]> squeeze_10_cast_fp16 = squeeze(axes = squeeze_10_axes_0, x = var_2363_cast_fp16_1)[name = tensor<string, []>("squeeze_10_cast_fp16")];
            tensor<int32, [1]> squeeze_11_axes_0 = const()[name = tensor<string, []>("squeeze_11_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 20, 64, 32]> squeeze_11_cast_fp16 = squeeze(axes = squeeze_11_axes_0, x = var_2363_cast_fp16_2)[name = tensor<string, []>("squeeze_11_cast_fp16")];
            tensor<fp16, []> var_2367_to_fp16 = const()[name = tensor<string, []>("op_2367_to_fp16"), val = tensor<fp16, []>(0x1.6ap-3)];
            tensor<fp16, [1, 20, 64, 32]> var_2368_cast_fp16 = mul(x = squeeze_9_cast_fp16, y = var_2367_to_fp16)[name = tensor<string, []>("op_2368_cast_fp16")];
            tensor<int32, [4]> var_2369_perm_0 = const()[name = tensor<string, []>("op_2369_perm_0"), val = tensor<int32, [4]>([0, 1, -1, -2])];
            tensor<bool, []> attn_13_transpose_x_0 = const()[name = tensor<string, []>("attn_13_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_13_transpose_y_0 = const()[name = tensor<string, []>("attn_13_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 20, 32, 64]> transpose_2 = transpose(perm = var_2369_perm_0, x = squeeze_10_cast_fp16)[name = tensor<string, []>("transpose_2")];
            tensor<fp16, [1, 20, 64, 64]> attn_13_cast_fp16 = matmul(transpose_x = attn_13_transpose_x_0, transpose_y = attn_13_transpose_y_0, x = var_2368_cast_fp16, y = transpose_2)[name = tensor<string, []>("attn_13_cast_fp16")];
            tensor<fp16, [1, 20, 64, 64]> input_765_cast_fp16 = softmax(axis = var_23, x = attn_13_cast_fp16)[name = tensor<string, []>("input_765_cast_fp16")];
            tensor<bool, []> var_2373_transpose_x_0 = const()[name = tensor<string, []>("op_2373_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> var_2373_transpose_y_0 = const()[name = tensor<string, []>("op_2373_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 20, 64, 32]> var_2373_cast_fp16 = matmul(transpose_x = var_2373_transpose_x_0, transpose_y = var_2373_transpose_y_0, x = input_765_cast_fp16, y = squeeze_11_cast_fp16)[name = tensor<string, []>("op_2373_cast_fp16")];
            tensor<int32, [4]> var_2374_perm_0 = const()[name = tensor<string, []>("op_2374_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2375 = const()[name = tensor<string, []>("op_2375"), val = tensor<int32, [3]>([1, 64, 640])];
            tensor<fp16, [1, 64, 20, 32]> transpose_1 = transpose(perm = var_2374_perm_0, x = var_2373_cast_fp16)[name = tensor<string, []>("transpose_1")];
            tensor<fp16, [1, 64, 640]> input_767_cast_fp16 = reshape(shape = var_2375, x = transpose_1)[name = tensor<string, []>("input_767_cast_fp16")];
            tensor<fp16, [640, 640]> original_model_image_encoder_model_network_7_3_token_mixer_proj_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_3_token_mixer_proj_weight_to_fp16"), val = tensor<fp16, [640, 640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(63840768)))];
            tensor<fp16, [640]> original_model_image_encoder_model_network_7_3_token_mixer_proj_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_3_token_mixer_proj_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64660032)))];
            tensor<fp16, [1, 64, 640]> linear_7_cast_fp16 = linear(bias = original_model_image_encoder_model_network_7_3_token_mixer_proj_bias_to_fp16, weight = original_model_image_encoder_model_network_7_3_token_mixer_proj_weight_to_fp16, x = input_767_cast_fp16)[name = tensor<string, []>("linear_7_cast_fp16")];
            tensor<int32, [3]> var_2381_perm_0 = const()[name = tensor<string, []>("op_2381_perm_0"), val = tensor<int32, [3]>([0, -1, -2])];
            tensor<int32, [4]> var_2382 = const()[name = tensor<string, []>("op_2382"), val = tensor<int32, [4]>([1, 640, 8, 8])];
            tensor<fp16, [1, 640, 64]> transpose_0 = transpose(perm = var_2381_perm_0, x = linear_7_cast_fp16)[name = tensor<string, []>("transpose_0")];
            tensor<fp16, [1, 640, 8, 8]> var_2383_cast_fp16 = reshape(shape = var_2382, x = transpose_0)[name = tensor<string, []>("op_2383_cast_fp16")];
            tensor<fp16, [640, 1, 1]> original_model_image_encoder_model_network_7_3_layer_scale_1_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_3_layer_scale_1_to_fp16"), val = tensor<fp16, [640, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64661376)))];
            tensor<fp16, [1, 640, 8, 8]> var_2384_cast_fp16 = mul(x = original_model_image_encoder_model_network_7_3_layer_scale_1_to_fp16, y = var_2383_cast_fp16)[name = tensor<string, []>("op_2384_cast_fp16")];
            tensor<fp16, [1, 640, 8, 8]> input_771_cast_fp16 = add(x = input_761_cast_fp16, y = var_2384_cast_fp16)[name = tensor<string, []>("input_771_cast_fp16")];
            tensor<int32, [2]> var_2392 = const()[name = tensor<string, []>("op_2392"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2394 = const()[name = tensor<string, []>("op_2394"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_773_pad_type_0 = const()[name = tensor<string, []>("input_773_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_773_pad_0 = const()[name = tensor<string, []>("input_773_pad_0"), val = tensor<int32, [4]>([3, 3, 3, 3])];
            tensor<fp16, [640, 1, 7, 7]> input_775_weight_0_to_fp16 = const()[name = tensor<string, []>("input_775_weight_0_to_fp16"), val = tensor<fp16, [640, 1, 7, 7]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64662720)))];
            tensor<fp16, [640]> input_775_bias_0_to_fp16 = const()[name = tensor<string, []>("input_775_bias_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64725504)))];
            tensor<fp16, [1, 640, 8, 8]> input_775_cast_fp16 = conv(bias = input_775_bias_0_to_fp16, dilations = var_2394, groups = var_18, pad = input_773_pad_0, pad_type = input_773_pad_type_0, strides = var_2392, weight = input_775_weight_0_to_fp16, x = input_771_cast_fp16)[name = tensor<string, []>("input_775_cast_fp16")];
            tensor<int32, [2]> var_2404 = const()[name = tensor<string, []>("op_2404"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2406 = const()[name = tensor<string, []>("op_2406"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_777_pad_type_0 = const()[name = tensor<string, []>("input_777_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_777_pad_0 = const()[name = tensor<string, []>("input_777_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1920, 640, 1, 1]> original_model_image_encoder_model_network_7_3_convffn_fc1_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_3_convffn_fc1_weight_to_fp16"), val = tensor<fp16, [1920, 640, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64726848)))];
            tensor<fp16, [1920]> original_model_image_encoder_model_network_7_3_convffn_fc1_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_network_7_3_convffn_fc1_bias_to_fp16"), val = tensor<fp16, [1920]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67184512)))];
            tensor<fp16, [1, 1920, 8, 8]> input_777_cast_fp16 = conv(bias = original_model_image_encoder_model_network_7_3_convffn_fc1_bias_to_fp16, dilations = var_2406, groups = var_8, pad = input_777_pad_0, pad_type = input_777_pad_type_0, strides = var_2404, weight = original_model_image_encoder_model_network_7_3_convffn_fc1_weight_to_fp16, x = input_775_cast_fp16)[name = tensor<string, []>("input_777_cast_fp16")];
            tensor<string, []> input_779_mode_0 = const()[name = tensor<string, []>("input_779_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 1920, 8, 8]> input_779_cast_fp16 = gelu(mode = input_779_mode_0, x = input_777_cast_fp16)[name = tensor<string, []>("input_779_cast_fp16")];
            tensor<int32, [2]> var_2413 = const()[name = tensor<string, []>("op_2413"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2415 = const()[name = tensor<string, []>("op_2415"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_783_pad_type_0 = const()[name = tensor<string, []>("input_783_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_783_pad_0 = const()[name = tensor<string, []>("input_783_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [640, 1920, 1, 1]> var_2419_weight_0_to_fp16 = const()[name = tensor<string, []>("op_2419_weight_0_to_fp16"), val = tensor<fp16, [640, 1920, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67188416)))];
            tensor<fp16, [640]> var_2419_bias_0_to_fp16 = const()[name = tensor<string, []>("op_2419_bias_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(69646080)))];
            tensor<fp16, [1, 640, 8, 8]> var_2419_cast_fp16 = conv(bias = var_2419_bias_0_to_fp16, dilations = var_2415, groups = var_8, pad = input_783_pad_0, pad_type = input_783_pad_type_0, strides = var_2413, weight = var_2419_weight_0_to_fp16, x = input_779_cast_fp16)[name = tensor<string, []>("op_2419_cast_fp16")];
            tensor<fp16, [1, 640, 8, 8]> input_785_cast_fp16 = add(x = input_771_cast_fp16, y = var_2419_cast_fp16)[name = tensor<string, []>("input_785_cast_fp16")];
            tensor<int32, [2]> var_2425 = const()[name = tensor<string, []>("op_2425"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2427 = const()[name = tensor<string, []>("op_2427"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> inputs_pad_type_0 = const()[name = tensor<string, []>("inputs_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> inputs_pad_0 = const()[name = tensor<string, []>("inputs_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<fp16, [1280, 1, 3, 3]> original_model_image_encoder_model_conv_exp_reparam_conv_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_conv_exp_reparam_conv_weight_to_fp16"), val = tensor<fp16, [1280, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(69647424)))];
            tensor<fp16, [1280]> original_model_image_encoder_model_conv_exp_reparam_conv_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_conv_exp_reparam_conv_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(69670528)))];
            tensor<fp16, [1, 1280, 8, 8]> inputs_cast_fp16 = conv(bias = original_model_image_encoder_model_conv_exp_reparam_conv_bias_to_fp16, dilations = var_2427, groups = var_18, pad = inputs_pad_0, pad_type = inputs_pad_type_0, strides = var_2425, weight = original_model_image_encoder_model_conv_exp_reparam_conv_weight_to_fp16, x = input_785_cast_fp16)[name = tensor<string, []>("inputs_cast_fp16")];
            tensor<int32, [2]> var_2435 = const()[name = tensor<string, []>("op_2435"), val = tensor<int32, [2]>([8, 8])];
            tensor<int32, [2]> var_2436 = const()[name = tensor<string, []>("op_2436"), val = tensor<int32, [2]>([8, 8])];
            tensor<string, []> input_787_pad_type_0 = const()[name = tensor<string, []>("input_787_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_787_pad_0 = const()[name = tensor<string, []>("input_787_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<bool, []> input_787_exclude_padding_from_average_0 = const()[name = tensor<string, []>("input_787_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> input_787_ceil_mode_0 = const()[name = tensor<string, []>("input_787_ceil_mode_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 1280, 1, 1]> input_787_cast_fp16 = avg_pool(ceil_mode = input_787_ceil_mode_0, exclude_padding_from_average = input_787_exclude_padding_from_average_0, kernel_sizes = var_2435, pad = input_787_pad_0, pad_type = input_787_pad_type_0, strides = var_2436, x = inputs_cast_fp16)[name = tensor<string, []>("input_787_cast_fp16")];
            tensor<int32, [2]> var_2441 = const()[name = tensor<string, []>("op_2441"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2443 = const()[name = tensor<string, []>("op_2443"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> input_789_pad_type_0 = const()[name = tensor<string, []>("input_789_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_789_pad_0 = const()[name = tensor<string, []>("input_789_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [80, 1280, 1, 1]> original_model_image_encoder_model_conv_exp_se_reduce_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_conv_exp_se_reduce_weight_to_fp16"), val = tensor<fp16, [80, 1280, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(69673152)))];
            tensor<fp16, [80]> original_model_image_encoder_model_conv_exp_se_reduce_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_conv_exp_se_reduce_bias_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(69878016)))];
            tensor<fp16, [1, 80, 1, 1]> input_789_cast_fp16 = conv(bias = original_model_image_encoder_model_conv_exp_se_reduce_bias_to_fp16, dilations = var_2443, groups = var_8, pad = input_789_pad_0, pad_type = input_789_pad_type_0, strides = var_2441, weight = original_model_image_encoder_model_conv_exp_se_reduce_weight_to_fp16, x = input_787_cast_fp16)[name = tensor<string, []>("input_789_cast_fp16")];
            tensor<fp16, [1, 80, 1, 1]> input_791_cast_fp16 = relu(x = input_789_cast_fp16)[name = tensor<string, []>("input_791_cast_fp16")];
            tensor<int32, [2]> var_2449 = const()[name = tensor<string, []>("op_2449"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_2451 = const()[name = tensor<string, []>("op_2451"), val = tensor<int32, [2]>([1, 1])];
            tensor<string, []> x_25_pad_type_0 = const()[name = tensor<string, []>("x_25_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> x_25_pad_0 = const()[name = tensor<string, []>("x_25_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<fp16, [1280, 80, 1, 1]> original_model_image_encoder_model_conv_exp_se_expand_weight_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_conv_exp_se_expand_weight_to_fp16"), val = tensor<fp16, [1280, 80, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(69878272)))];
            tensor<fp16, [1280]> original_model_image_encoder_model_conv_exp_se_expand_bias_to_fp16 = const()[name = tensor<string, []>("original_model_image_encoder_model_conv_exp_se_expand_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70083136)))];
            tensor<fp16, [1, 1280, 1, 1]> x_25_cast_fp16 = conv(bias = original_model_image_encoder_model_conv_exp_se_expand_bias_to_fp16, dilations = var_2451, groups = var_8, pad = x_25_pad_0, pad_type = x_25_pad_type_0, strides = var_2449, weight = original_model_image_encoder_model_conv_exp_se_expand_weight_to_fp16, x = input_791_cast_fp16)[name = tensor<string, []>("x_25_cast_fp16")];
            tensor<fp16, [1, 1280, 1, 1]> x_27_cast_fp16 = sigmoid(x = x_25_cast_fp16)[name = tensor<string, []>("x_27_cast_fp16")];
            tensor<fp16, [1, 1280, 8, 8]> input_cast_fp16 = mul(x = inputs_cast_fp16, y = x_27_cast_fp16)[name = tensor<string, []>("input_cast_fp16")];
            tensor<string, []> x_31_mode_0 = const()[name = tensor<string, []>("x_31_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 1280, 8, 8]> x_31_cast_fp16 = gelu(mode = x_31_mode_0, x = input_cast_fp16)[name = tensor<string, []>("x_31_cast_fp16")];
            tensor<int32, [2]> var_2460 = const()[name = tensor<string, []>("op_2460"), val = tensor<int32, [2]>([-2, -1])];
            tensor<fp16, [1, 1280]> x_cast_fp16 = reduce_mean(axes = var_2460, keep_dims = var_7, x = x_31_cast_fp16)[name = tensor<string, []>("x_cast_fp16")];
            tensor<fp16, [512, 1280]> var_2462_weight_0_to_fp16 = const()[name = tensor<string, []>("op_2462_weight_0_to_fp16"), val = tensor<fp16, [512, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70085760)))];
            tensor<fp16, [512]> var_2462_bias_0_to_fp16 = const()[name = tensor<string, []>("op_2462_bias_0_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(71396544)))];
            tensor<fp16, [1, 512]> var_2462_cast_fp16 = linear(bias = var_2462_bias_0_to_fp16, weight = var_2462_weight_0_to_fp16, x = x_cast_fp16)[name = tensor<string, []>("op_2462_cast_fp16")];
            tensor<string, []> var_2462_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("op_2462_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<fp32, [1, 512]> embOutput = cast(dtype = var_2462_cast_fp16_to_fp32_dtype_0, x = var_2462_cast_fp16)[name = tensor<string, []>("cast_17")];
        } -> (embOutput);
}