UnetChunk2.mlmodelc/model.mil

program(1.3)
[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3600.16.1"}, {"coremlc-version", "3600.22.1"}})]
{
    func main<ios18>(tensor<fp16, [1, 768, 1, 77]> encoder_hidden_states, tensor<fp32, [1, 1280, 16, 16]> hidden_states_61_cast_fp16, tensor<fp32, [1, 1280, 1, 1]> input_15_cast_fp16, tensor<fp32, [1, 320, 64, 64]> input_35_cast_fp16, tensor<fp32, [1, 320, 32, 32]> input_37_cast_fp16, tensor<fp32, [1, 640, 32, 32]> input_63_cast_fp16, tensor<fp32, [1, 640, 16, 16]> input_65_cast_fp16, tensor<fp32, [1, 320, 64, 64]> input_7_cast_fp16, tensor<fp32, [1, 1280, 1, 256]> inputs_23_cast_fp16, tensor<fp32, [1, 10240, 1, 256]> var_2337_cast_fp16) {
            string cast_8_dtype_0 = const()[name = string("cast_8_dtype_0"), val = string("fp16")];
            tensor<fp16, [320]> add_1_mean_0_to_fp16 = const()[name = string("add_1_mean_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [320]> add_1_variance_0_to_fp16 = const()[name = string("add_1_variance_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(768)))];
            string cast_7_dtype_0 = const()[name = string("cast_7_dtype_0"), val = string("fp16")];
            string cast_2_dtype_0 = const()[name = string("cast_2_dtype_0"), val = string("fp16")];
            string cast_5_dtype_0 = const()[name = string("cast_5_dtype_0"), val = string("fp16")];
            tensor<fp16, [640]> add_9_mean_0_to_fp16 = const()[name = string("add_9_mean_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1472)))];
            tensor<fp16, [640]> add_9_variance_0_to_fp16 = const()[name = string("add_9_variance_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2816)))];
            string cast_6_dtype_0 = const()[name = string("cast_6_dtype_0"), val = string("fp16")];
            string cast_0_dtype_0 = const()[name = string("cast_0_dtype_0"), val = string("fp16")];
            tensor<fp16, [1280]> add_15_mean_0_to_fp16 = const()[name = string("add_15_mean_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4160)))];
            tensor<fp16, [1280]> add_15_variance_0_to_fp16 = const()[name = string("add_15_variance_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6784)))];
            int32 var_1812 = const()[name = string("op_1812"), val = int32(1)];
            string cast_3_dtype_0 = const()[name = string("cast_3_dtype_0"), val = string("fp16")];
            string cast_1_dtype_0 = const()[name = string("cast_1_dtype_0"), val = string("fp16")];
            string cast_4_dtype_0 = const()[name = string("cast_4_dtype_0"), val = string("fp16")];
            tensor<int32, [2]> var_2338_split_sizes_0 = const()[name = string("op_2338_split_sizes_0"), val = tensor<int32, [2]>([5120, 5120])];
            int32 var_2338_axis_0 = const()[name = string("op_2338_axis_0"), val = int32(1)];
            tensor<fp16, [1, 10240, 1, 256]> cast_4 = cast(dtype = cast_4_dtype_0, x = var_2337_cast_fp16)[name = string("cast_1")];
            tensor<fp16, [1, 5120, 1, 256]> var_2338_cast_fp16_0, tensor<fp16, [1, 5120, 1, 256]> var_2338_cast_fp16_1 = split(axis = var_2338_axis_0, split_sizes = var_2338_split_sizes_0, x = cast_4)[name = string("op_2338_cast_fp16")];
            string var_2340_mode_0 = const()[name = string("op_2340_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 5120, 1, 256]> var_2340_cast_fp16 = gelu(mode = var_2340_mode_0, x = var_2338_cast_fp16_1)[name = string("op_2340_cast_fp16")];
            tensor<fp16, [1, 5120, 1, 256]> input_113_cast_fp16 = mul(x = var_2338_cast_fp16_0, y = var_2340_cast_fp16)[name = string("input_113_cast_fp16")];
            string var_2348_pad_type_0 = const()[name = string("op_2348_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_2348_strides_0 = const()[name = string("op_2348_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_2348_pad_0 = const()[name = string("op_2348_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_2348_dilations_0 = const()[name = string("op_2348_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_2348_groups_0 = const()[name = string("op_2348_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 5120, 1, 1]> up_blocks_0_attentions_0_transformer_blocks_0_ff_net_2_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_0_transformer_blocks_0_ff_net_2_weight_to_fp16"), val = tensor<fp16, [1280, 5120, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9408)))];
            tensor<fp16, [1280]> up_blocks_0_attentions_0_transformer_blocks_0_ff_net_2_bias_to_fp16 = const()[name = string("up_blocks_0_attentions_0_transformer_blocks_0_ff_net_2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13116672)))];
            tensor<fp16, [1, 1280, 1, 256]> var_2348_cast_fp16 = conv(bias = up_blocks_0_attentions_0_transformer_blocks_0_ff_net_2_bias_to_fp16, dilations = var_2348_dilations_0, groups = var_2348_groups_0, pad = var_2348_pad_0, pad_type = var_2348_pad_type_0, strides = var_2348_strides_0, weight = up_blocks_0_attentions_0_transformer_blocks_0_ff_net_2_weight_to_fp16, x = input_113_cast_fp16)[name = string("op_2348_cast_fp16")];
            tensor<fp16, [1, 1280, 1, 256]> cast_1 = cast(dtype = cast_1_dtype_0, x = inputs_23_cast_fp16)[name = string("cast_2")];
            tensor<fp16, [1, 1280, 1, 256]> hidden_states_71_cast_fp16 = add(x = var_2348_cast_fp16, y = cast_1)[name = string("hidden_states_71_cast_fp16")];
            tensor<int32, [4]> var_2350 = const()[name = string("op_2350"), val = tensor<int32, [4]>([1, 1280, 16, 16])];
            tensor<fp16, [1, 1280, 16, 16]> input_115_cast_fp16 = reshape(shape = var_2350, x = hidden_states_71_cast_fp16)[name = string("input_115_cast_fp16")];
            string hidden_states_73_pad_type_0 = const()[name = string("hidden_states_73_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> hidden_states_73_strides_0 = const()[name = string("hidden_states_73_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> hidden_states_73_pad_0 = const()[name = string("hidden_states_73_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> hidden_states_73_dilations_0 = const()[name = string("hidden_states_73_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_73_groups_0 = const()[name = string("hidden_states_73_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1280, 1, 1]> up_blocks_0_attentions_0_proj_out_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_0_proj_out_weight_to_fp16"), val = tensor<fp16, [1280, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13119296)))];
            tensor<fp16, [1280]> up_blocks_0_attentions_0_proj_out_bias_to_fp16 = const()[name = string("up_blocks_0_attentions_0_proj_out_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16396160)))];
            tensor<fp16, [1, 1280, 16, 16]> hidden_states_73_cast_fp16 = conv(bias = up_blocks_0_attentions_0_proj_out_bias_to_fp16, dilations = hidden_states_73_dilations_0, groups = hidden_states_73_groups_0, pad = hidden_states_73_pad_0, pad_type = hidden_states_73_pad_type_0, strides = hidden_states_73_strides_0, weight = up_blocks_0_attentions_0_proj_out_weight_to_fp16, x = input_115_cast_fp16)[name = string("hidden_states_73_cast_fp16")];
            tensor<fp16, [1, 1280, 16, 16]> cast_3 = cast(dtype = cast_3_dtype_0, x = hidden_states_61_cast_fp16)[name = string("cast_3")];
            tensor<fp16, [1, 1280, 16, 16]> hidden_states_75_cast_fp16 = add(x = hidden_states_73_cast_fp16, y = cast_3)[name = string("hidden_states_75_cast_fp16")];
            bool input_117_interleave_0 = const()[name = string("input_117_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 640, 16, 16]> cast_0 = cast(dtype = cast_0_dtype_0, x = input_65_cast_fp16)[name = string("cast_4")];
            tensor<fp16, [1, 1920, 16, 16]> input_117_cast_fp16 = concat(axis = var_1812, interleave = input_117_interleave_0, values = (hidden_states_75_cast_fp16, cast_0))[name = string("input_117_cast_fp16")];
            tensor<int32, [5]> reshape_48_shape_0 = const()[name = string("reshape_48_shape_0"), val = tensor<int32, [5]>([1, 32, 60, 16, 16])];
            tensor<fp16, [1, 32, 60, 16, 16]> reshape_48_cast_fp16 = reshape(shape = reshape_48_shape_0, x = input_117_cast_fp16)[name = string("reshape_48_cast_fp16")];
            tensor<int32, [3]> reduce_mean_36_axes_0 = const()[name = string("reduce_mean_36_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_36_keep_dims_0 = const()[name = string("reduce_mean_36_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_36_cast_fp16 = reduce_mean(axes = reduce_mean_36_axes_0, keep_dims = reduce_mean_36_keep_dims_0, x = reshape_48_cast_fp16)[name = string("reduce_mean_36_cast_fp16")];
            tensor<fp16, [1, 32, 60, 16, 16]> sub_24_cast_fp16 = sub(x = reshape_48_cast_fp16, y = reduce_mean_36_cast_fp16)[name = string("sub_24_cast_fp16")];
            tensor<fp16, [1, 32, 60, 16, 16]> square_12_cast_fp16 = square(x = sub_24_cast_fp16)[name = string("square_12_cast_fp16")];
            tensor<int32, [3]> reduce_mean_38_axes_0 = const()[name = string("reduce_mean_38_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_38_keep_dims_0 = const()[name = string("reduce_mean_38_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_38_cast_fp16 = reduce_mean(axes = reduce_mean_38_axes_0, keep_dims = reduce_mean_38_keep_dims_0, x = square_12_cast_fp16)[name = string("reduce_mean_38_cast_fp16")];
            fp16 add_24_y_0_to_fp16 = const()[name = string("add_24_y_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_24_cast_fp16 = add(x = reduce_mean_38_cast_fp16, y = add_24_y_0_to_fp16)[name = string("add_24_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_12_cast_fp16 = sqrt(x = add_24_cast_fp16)[name = string("sqrt_12_cast_fp16")];
            tensor<fp16, [1, 32, 60, 16, 16]> real_div_12_cast_fp16 = real_div(x = sub_24_cast_fp16, y = sqrt_12_cast_fp16)[name = string("real_div_12_cast_fp16")];
            tensor<int32, [4]> reshape_49_shape_0 = const()[name = string("reshape_49_shape_0"), val = tensor<int32, [4]>([1, 1920, 16, 16])];
            tensor<fp16, [1, 1920, 16, 16]> reshape_49_cast_fp16 = reshape(shape = reshape_49_shape_0, x = real_div_12_cast_fp16)[name = string("reshape_49_cast_fp16")];
            tensor<fp16, [1920]> add_25_mean_0_to_fp16 = const()[name = string("add_25_mean_0_to_fp16"), val = tensor<fp16, [1920]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16398784)))];
            tensor<fp16, [1920]> add_25_variance_0_to_fp16 = const()[name = string("add_25_variance_0_to_fp16"), val = tensor<fp16, [1920]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16402688)))];
            tensor<fp16, [1920]> add_25_gamma_0_to_fp16 = const()[name = string("add_25_gamma_0_to_fp16"), val = tensor<fp16, [1920]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16406592)))];
            tensor<fp16, [1920]> add_25_beta_0_to_fp16 = const()[name = string("add_25_beta_0_to_fp16"), val = tensor<fp16, [1920]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16410496)))];
            fp16 add_25_epsilon_0_to_fp16 = const()[name = string("add_25_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 1920, 16, 16]> add_25_cast_fp16 = batch_norm(beta = add_25_beta_0_to_fp16, epsilon = add_25_epsilon_0_to_fp16, gamma = add_25_gamma_0_to_fp16, mean = add_25_mean_0_to_fp16, variance = add_25_variance_0_to_fp16, x = reshape_49_cast_fp16)[name = string("add_25_cast_fp16")];
            tensor<fp16, [1, 1920, 16, 16]> input_121_cast_fp16 = silu(x = add_25_cast_fp16)[name = string("input_121_cast_fp16")];
            string hidden_states_77_pad_type_0 = const()[name = string("hidden_states_77_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> hidden_states_77_pad_0 = const()[name = string("hidden_states_77_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> hidden_states_77_strides_0 = const()[name = string("hidden_states_77_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> hidden_states_77_dilations_0 = const()[name = string("hidden_states_77_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_77_groups_0 = const()[name = string("hidden_states_77_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1920, 3, 3]> up_blocks_0_resnets_1_conv1_weight_to_fp16 = const()[name = string("up_blocks_0_resnets_1_conv1_weight_to_fp16"), val = tensor<fp16, [1280, 1920, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16414400)))];
            tensor<fp16, [1280]> up_blocks_0_resnets_1_conv1_bias_to_fp16 = const()[name = string("up_blocks_0_resnets_1_conv1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(60651264)))];
            tensor<fp16, [1, 1280, 16, 16]> hidden_states_77_cast_fp16 = conv(bias = up_blocks_0_resnets_1_conv1_bias_to_fp16, dilations = hidden_states_77_dilations_0, groups = hidden_states_77_groups_0, pad = hidden_states_77_pad_0, pad_type = hidden_states_77_pad_type_0, strides = hidden_states_77_strides_0, weight = up_blocks_0_resnets_1_conv1_weight_to_fp16, x = input_121_cast_fp16)[name = string("hidden_states_77_cast_fp16")];
            string temb_9_pad_type_0 = const()[name = string("temb_9_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> temb_9_strides_0 = const()[name = string("temb_9_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> temb_9_pad_0 = const()[name = string("temb_9_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> temb_9_dilations_0 = const()[name = string("temb_9_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 temb_9_groups_0 = const()[name = string("temb_9_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1280, 1, 1]> up_blocks_0_resnets_1_time_emb_proj_weight_to_fp16 = const()[name = string("up_blocks_0_resnets_1_time_emb_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(60653888)))];
            tensor<fp16, [1280]> up_blocks_0_resnets_1_time_emb_proj_bias_to_fp16 = const()[name = string("up_blocks_0_resnets_1_time_emb_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(63930752)))];
            tensor<fp16, [1, 1280, 1, 1]> cast_7 = cast(dtype = cast_7_dtype_0, x = input_15_cast_fp16)[name = string("cast_8")];
            tensor<fp16, [1, 1280, 1, 1]> temb_9_cast_fp16 = conv(bias = up_blocks_0_resnets_1_time_emb_proj_bias_to_fp16, dilations = temb_9_dilations_0, groups = temb_9_groups_0, pad = temb_9_pad_0, pad_type = temb_9_pad_type_0, strides = temb_9_strides_0, weight = up_blocks_0_resnets_1_time_emb_proj_weight_to_fp16, x = cast_7)[name = string("temb_9_cast_fp16")];
            tensor<fp16, [1, 1280, 16, 16]> input_125_cast_fp16 = add(x = hidden_states_77_cast_fp16, y = temb_9_cast_fp16)[name = string("input_125_cast_fp16")];
            tensor<int32, [5]> reshape_52_shape_0 = const()[name = string("reshape_52_shape_0"), val = tensor<int32, [5]>([1, 32, 40, 16, 16])];
            tensor<fp16, [1, 32, 40, 16, 16]> reshape_52_cast_fp16 = reshape(shape = reshape_52_shape_0, x = input_125_cast_fp16)[name = string("reshape_52_cast_fp16")];
            tensor<int32, [3]> reduce_mean_39_axes_0 = const()[name = string("reduce_mean_39_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_39_keep_dims_0 = const()[name = string("reduce_mean_39_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_39_cast_fp16 = reduce_mean(axes = reduce_mean_39_axes_0, keep_dims = reduce_mean_39_keep_dims_0, x = reshape_52_cast_fp16)[name = string("reduce_mean_39_cast_fp16")];
            tensor<fp16, [1, 32, 40, 16, 16]> sub_26_cast_fp16 = sub(x = reshape_52_cast_fp16, y = reduce_mean_39_cast_fp16)[name = string("sub_26_cast_fp16")];
            tensor<fp16, [1, 32, 40, 16, 16]> square_13_cast_fp16 = square(x = sub_26_cast_fp16)[name = string("square_13_cast_fp16")];
            tensor<int32, [3]> reduce_mean_41_axes_0 = const()[name = string("reduce_mean_41_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_41_keep_dims_0 = const()[name = string("reduce_mean_41_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_41_cast_fp16 = reduce_mean(axes = reduce_mean_41_axes_0, keep_dims = reduce_mean_41_keep_dims_0, x = square_13_cast_fp16)[name = string("reduce_mean_41_cast_fp16")];
            fp16 add_26_y_0_to_fp16 = const()[name = string("add_26_y_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_26_cast_fp16 = add(x = reduce_mean_41_cast_fp16, y = add_26_y_0_to_fp16)[name = string("add_26_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_13_cast_fp16 = sqrt(x = add_26_cast_fp16)[name = string("sqrt_13_cast_fp16")];
            tensor<fp16, [1, 32, 40, 16, 16]> real_div_13_cast_fp16 = real_div(x = sub_26_cast_fp16, y = sqrt_13_cast_fp16)[name = string("real_div_13_cast_fp16")];
            tensor<int32, [4]> reshape_53_shape_0 = const()[name = string("reshape_53_shape_0"), val = tensor<int32, [4]>([1, 1280, 16, 16])];
            tensor<fp16, [1, 1280, 16, 16]> reshape_53_cast_fp16 = reshape(shape = reshape_53_shape_0, x = real_div_13_cast_fp16)[name = string("reshape_53_cast_fp16")];
            tensor<fp16, [1280]> add_27_gamma_0_to_fp16 = const()[name = string("add_27_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(63933376)))];
            tensor<fp16, [1280]> add_27_beta_0_to_fp16 = const()[name = string("add_27_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(63936000)))];
            fp16 add_27_epsilon_0_to_fp16 = const()[name = string("add_27_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 1280, 16, 16]> add_27_cast_fp16 = batch_norm(beta = add_27_beta_0_to_fp16, epsilon = add_27_epsilon_0_to_fp16, gamma = add_27_gamma_0_to_fp16, mean = add_15_mean_0_to_fp16, variance = add_15_variance_0_to_fp16, x = reshape_53_cast_fp16)[name = string("add_27_cast_fp16")];
            tensor<fp16, [1, 1280, 16, 16]> input_129_cast_fp16 = silu(x = add_27_cast_fp16)[name = string("input_129_cast_fp16")];
            string hidden_states_79_pad_type_0 = const()[name = string("hidden_states_79_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> hidden_states_79_pad_0 = const()[name = string("hidden_states_79_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> hidden_states_79_strides_0 = const()[name = string("hidden_states_79_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> hidden_states_79_dilations_0 = const()[name = string("hidden_states_79_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_79_groups_0 = const()[name = string("hidden_states_79_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1280, 3, 3]> up_blocks_0_resnets_1_conv2_weight_to_fp16 = const()[name = string("up_blocks_0_resnets_1_conv2_weight_to_fp16"), val = tensor<fp16, [1280, 1280, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(63938624)))];
            tensor<fp16, [1280]> up_blocks_0_resnets_1_conv2_bias_to_fp16 = const()[name = string("up_blocks_0_resnets_1_conv2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(93429888)))];
            tensor<fp16, [1, 1280, 16, 16]> hidden_states_79_cast_fp16 = conv(bias = up_blocks_0_resnets_1_conv2_bias_to_fp16, dilations = hidden_states_79_dilations_0, groups = hidden_states_79_groups_0, pad = hidden_states_79_pad_0, pad_type = hidden_states_79_pad_type_0, strides = hidden_states_79_strides_0, weight = up_blocks_0_resnets_1_conv2_weight_to_fp16, x = input_129_cast_fp16)[name = string("hidden_states_79_cast_fp16")];
            string x_7_pad_type_0 = const()[name = string("x_7_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_7_strides_0 = const()[name = string("x_7_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_7_pad_0 = const()[name = string("x_7_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_7_dilations_0 = const()[name = string("x_7_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_7_groups_0 = const()[name = string("x_7_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1920, 1, 1]> up_blocks_0_resnets_1_conv_shortcut_weight_to_fp16 = const()[name = string("up_blocks_0_resnets_1_conv_shortcut_weight_to_fp16"), val = tensor<fp16, [1280, 1920, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(93432512)))];
            tensor<fp16, [1280]> up_blocks_0_resnets_1_conv_shortcut_bias_to_fp16 = const()[name = string("up_blocks_0_resnets_1_conv_shortcut_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(98347776)))];
            tensor<fp16, [1, 1280, 16, 16]> x_7_cast_fp16 = conv(bias = up_blocks_0_resnets_1_conv_shortcut_bias_to_fp16, dilations = x_7_dilations_0, groups = x_7_groups_0, pad = x_7_pad_0, pad_type = x_7_pad_type_0, strides = x_7_strides_0, weight = up_blocks_0_resnets_1_conv_shortcut_weight_to_fp16, x = input_117_cast_fp16)[name = string("x_7_cast_fp16")];
            tensor<fp16, [1, 1280, 16, 16]> hidden_states_81_cast_fp16 = add(x = x_7_cast_fp16, y = hidden_states_79_cast_fp16)[name = string("hidden_states_81_cast_fp16")];
            tensor<int32, [5]> reshape_56_shape_0 = const()[name = string("reshape_56_shape_0"), val = tensor<int32, [5]>([1, 32, 40, 16, 16])];
            tensor<fp16, [1, 32, 40, 16, 16]> reshape_56_cast_fp16 = reshape(shape = reshape_56_shape_0, x = hidden_states_81_cast_fp16)[name = string("reshape_56_cast_fp16")];
            tensor<int32, [3]> reduce_mean_42_axes_0 = const()[name = string("reduce_mean_42_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_42_keep_dims_0 = const()[name = string("reduce_mean_42_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_42_cast_fp16 = reduce_mean(axes = reduce_mean_42_axes_0, keep_dims = reduce_mean_42_keep_dims_0, x = reshape_56_cast_fp16)[name = string("reduce_mean_42_cast_fp16")];
            tensor<fp16, [1, 32, 40, 16, 16]> sub_28_cast_fp16 = sub(x = reshape_56_cast_fp16, y = reduce_mean_42_cast_fp16)[name = string("sub_28_cast_fp16")];
            tensor<fp16, [1, 32, 40, 16, 16]> square_14_cast_fp16 = square(x = sub_28_cast_fp16)[name = string("square_14_cast_fp16")];
            tensor<int32, [3]> reduce_mean_44_axes_0 = const()[name = string("reduce_mean_44_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_44_keep_dims_0 = const()[name = string("reduce_mean_44_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_44_cast_fp16 = reduce_mean(axes = reduce_mean_44_axes_0, keep_dims = reduce_mean_44_keep_dims_0, x = square_14_cast_fp16)[name = string("reduce_mean_44_cast_fp16")];
            fp16 add_28_y_0_to_fp16 = const()[name = string("add_28_y_0_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_28_cast_fp16 = add(x = reduce_mean_44_cast_fp16, y = add_28_y_0_to_fp16)[name = string("add_28_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_14_cast_fp16 = sqrt(x = add_28_cast_fp16)[name = string("sqrt_14_cast_fp16")];
            tensor<fp16, [1, 32, 40, 16, 16]> real_div_14_cast_fp16 = real_div(x = sub_28_cast_fp16, y = sqrt_14_cast_fp16)[name = string("real_div_14_cast_fp16")];
            tensor<int32, [4]> reshape_57_shape_0 = const()[name = string("reshape_57_shape_0"), val = tensor<int32, [4]>([1, 1280, 16, 16])];
            tensor<fp16, [1, 1280, 16, 16]> reshape_57_cast_fp16 = reshape(shape = reshape_57_shape_0, x = real_div_14_cast_fp16)[name = string("reshape_57_cast_fp16")];
            tensor<fp16, [1280]> add_29_gamma_0_to_fp16 = const()[name = string("add_29_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(98350400)))];
            tensor<fp16, [1280]> add_29_beta_0_to_fp16 = const()[name = string("add_29_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(98353024)))];
            fp16 add_29_epsilon_0_to_fp16 = const()[name = string("add_29_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 1280, 16, 16]> add_29_cast_fp16 = batch_norm(beta = add_29_beta_0_to_fp16, epsilon = add_29_epsilon_0_to_fp16, gamma = add_29_gamma_0_to_fp16, mean = add_15_mean_0_to_fp16, variance = add_15_variance_0_to_fp16, x = reshape_57_cast_fp16)[name = string("add_29_cast_fp16")];
            string hidden_states_83_pad_type_0 = const()[name = string("hidden_states_83_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> hidden_states_83_strides_0 = const()[name = string("hidden_states_83_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> hidden_states_83_pad_0 = const()[name = string("hidden_states_83_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> hidden_states_83_dilations_0 = const()[name = string("hidden_states_83_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_83_groups_0 = const()[name = string("hidden_states_83_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1280, 1, 1]> up_blocks_0_attentions_1_proj_in_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_1_proj_in_weight_to_fp16"), val = tensor<fp16, [1280, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(98355648)))];
            tensor<fp16, [1280]> up_blocks_0_attentions_1_proj_in_bias_to_fp16 = const()[name = string("up_blocks_0_attentions_1_proj_in_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(101632512)))];
            tensor<fp16, [1, 1280, 16, 16]> hidden_states_83_cast_fp16 = conv(bias = up_blocks_0_attentions_1_proj_in_bias_to_fp16, dilations = hidden_states_83_dilations_0, groups = hidden_states_83_groups_0, pad = hidden_states_83_pad_0, pad_type = hidden_states_83_pad_type_0, strides = hidden_states_83_strides_0, weight = up_blocks_0_attentions_1_proj_in_weight_to_fp16, x = add_29_cast_fp16)[name = string("hidden_states_83_cast_fp16")];
            tensor<int32, [4]> var_2430 = const()[name = string("op_2430"), val = tensor<int32, [4]>([1, 1280, 1, 256])];
            tensor<fp16, [1, 1280, 1, 256]> inputs_25_cast_fp16 = reshape(shape = var_2430, x = hidden_states_83_cast_fp16)[name = string("inputs_25_cast_fp16")];
            tensor<int32, [1]> hidden_states_85_axes_0 = const()[name = string("hidden_states_85_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1280]> hidden_states_85_gamma_0_to_fp16 = const()[name = string("hidden_states_85_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(101635136)))];
            tensor<fp16, [1280]> hidden_states_85_beta_0_to_fp16 = const()[name = string("hidden_states_85_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(101637760)))];
            fp16 var_2446_to_fp16 = const()[name = string("op_2446_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 1280, 1, 256]> hidden_states_85_cast_fp16 = layer_norm(axes = hidden_states_85_axes_0, beta = hidden_states_85_beta_0_to_fp16, epsilon = var_2446_to_fp16, gamma = hidden_states_85_gamma_0_to_fp16, x = inputs_25_cast_fp16)[name = string("hidden_states_85_cast_fp16")];
            string q_17_pad_type_0 = const()[name = string("q_17_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> q_17_strides_0 = const()[name = string("q_17_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> q_17_pad_0 = const()[name = string("q_17_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> q_17_dilations_0 = const()[name = string("q_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 q_17_groups_0 = const()[name = string("q_17_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1280, 1, 1]> up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_q_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_q_weight_to_fp16"), val = tensor<fp16, [1280, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(101640384)))];
            tensor<fp16, [1, 1280, 1, 256]> q_17_cast_fp16 = conv(dilations = q_17_dilations_0, groups = q_17_groups_0, pad = q_17_pad_0, pad_type = q_17_pad_type_0, strides = q_17_strides_0, weight = up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_q_weight_to_fp16, x = hidden_states_85_cast_fp16)[name = string("q_17_cast_fp16")];
            string k_33_pad_type_0 = const()[name = string("k_33_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> k_33_strides_0 = const()[name = string("k_33_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> k_33_pad_0 = const()[name = string("k_33_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> k_33_dilations_0 = const()[name = string("k_33_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 k_33_groups_0 = const()[name = string("k_33_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1280, 1, 1]> up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_k_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_k_weight_to_fp16"), val = tensor<fp16, [1280, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(104917248)))];
            tensor<fp16, [1, 1280, 1, 256]> k_33_cast_fp16 = conv(dilations = k_33_dilations_0, groups = k_33_groups_0, pad = k_33_pad_0, pad_type = k_33_pad_type_0, strides = k_33_strides_0, weight = up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_k_weight_to_fp16, x = hidden_states_85_cast_fp16)[name = string("k_33_cast_fp16")];
            string v_17_pad_type_0 = const()[name = string("v_17_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> v_17_strides_0 = const()[name = string("v_17_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> v_17_pad_0 = const()[name = string("v_17_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> v_17_dilations_0 = const()[name = string("v_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 v_17_groups_0 = const()[name = string("v_17_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1280, 1, 1]> up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_v_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_v_weight_to_fp16"), val = tensor<fp16, [1280, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(108194112)))];
            tensor<fp16, [1, 1280, 1, 256]> v_17_cast_fp16 = conv(dilations = v_17_dilations_0, groups = v_17_groups_0, pad = v_17_pad_0, pad_type = v_17_pad_type_0, strides = v_17_strides_0, weight = up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_v_weight_to_fp16, x = hidden_states_85_cast_fp16)[name = string("v_17_cast_fp16")];
            tensor<int32, [4]> var_2479_begin_0 = const()[name = string("op_2479_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_2479_end_0 = const()[name = string("op_2479_end_0"), val = tensor<int32, [4]>([1, 160, 1, 256])];
            tensor<bool, [4]> var_2479_end_mask_0 = const()[name = string("op_2479_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2479_cast_fp16 = slice_by_index(begin = var_2479_begin_0, end = var_2479_end_0, end_mask = var_2479_end_mask_0, x = q_17_cast_fp16)[name = string("op_2479_cast_fp16")];
            tensor<int32, [4]> var_2483_begin_0 = const()[name = string("op_2483_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_2483_end_0 = const()[name = string("op_2483_end_0"), val = tensor<int32, [4]>([1, 320, 1, 256])];
            tensor<bool, [4]> var_2483_end_mask_0 = const()[name = string("op_2483_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2483_cast_fp16 = slice_by_index(begin = var_2483_begin_0, end = var_2483_end_0, end_mask = var_2483_end_mask_0, x = q_17_cast_fp16)[name = string("op_2483_cast_fp16")];
            tensor<int32, [4]> var_2487_begin_0 = const()[name = string("op_2487_begin_0"), val = tensor<int32, [4]>([0, 320, 0, 0])];
            tensor<int32, [4]> var_2487_end_0 = const()[name = string("op_2487_end_0"), val = tensor<int32, [4]>([1, 480, 1, 256])];
            tensor<bool, [4]> var_2487_end_mask_0 = const()[name = string("op_2487_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2487_cast_fp16 = slice_by_index(begin = var_2487_begin_0, end = var_2487_end_0, end_mask = var_2487_end_mask_0, x = q_17_cast_fp16)[name = string("op_2487_cast_fp16")];
            tensor<int32, [4]> var_2491_begin_0 = const()[name = string("op_2491_begin_0"), val = tensor<int32, [4]>([0, 480, 0, 0])];
            tensor<int32, [4]> var_2491_end_0 = const()[name = string("op_2491_end_0"), val = tensor<int32, [4]>([1, 640, 1, 256])];
            tensor<bool, [4]> var_2491_end_mask_0 = const()[name = string("op_2491_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2491_cast_fp16 = slice_by_index(begin = var_2491_begin_0, end = var_2491_end_0, end_mask = var_2491_end_mask_0, x = q_17_cast_fp16)[name = string("op_2491_cast_fp16")];
            tensor<int32, [4]> var_2495_begin_0 = const()[name = string("op_2495_begin_0"), val = tensor<int32, [4]>([0, 640, 0, 0])];
            tensor<int32, [4]> var_2495_end_0 = const()[name = string("op_2495_end_0"), val = tensor<int32, [4]>([1, 800, 1, 256])];
            tensor<bool, [4]> var_2495_end_mask_0 = const()[name = string("op_2495_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2495_cast_fp16 = slice_by_index(begin = var_2495_begin_0, end = var_2495_end_0, end_mask = var_2495_end_mask_0, x = q_17_cast_fp16)[name = string("op_2495_cast_fp16")];
            tensor<int32, [4]> var_2499_begin_0 = const()[name = string("op_2499_begin_0"), val = tensor<int32, [4]>([0, 800, 0, 0])];
            tensor<int32, [4]> var_2499_end_0 = const()[name = string("op_2499_end_0"), val = tensor<int32, [4]>([1, 960, 1, 256])];
            tensor<bool, [4]> var_2499_end_mask_0 = const()[name = string("op_2499_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2499_cast_fp16 = slice_by_index(begin = var_2499_begin_0, end = var_2499_end_0, end_mask = var_2499_end_mask_0, x = q_17_cast_fp16)[name = string("op_2499_cast_fp16")];
            tensor<int32, [4]> var_2503_begin_0 = const()[name = string("op_2503_begin_0"), val = tensor<int32, [4]>([0, 960, 0, 0])];
            tensor<int32, [4]> var_2503_end_0 = const()[name = string("op_2503_end_0"), val = tensor<int32, [4]>([1, 1120, 1, 256])];
            tensor<bool, [4]> var_2503_end_mask_0 = const()[name = string("op_2503_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2503_cast_fp16 = slice_by_index(begin = var_2503_begin_0, end = var_2503_end_0, end_mask = var_2503_end_mask_0, x = q_17_cast_fp16)[name = string("op_2503_cast_fp16")];
            tensor<int32, [4]> var_2507_begin_0 = const()[name = string("op_2507_begin_0"), val = tensor<int32, [4]>([0, 1120, 0, 0])];
            tensor<int32, [4]> var_2507_end_0 = const()[name = string("op_2507_end_0"), val = tensor<int32, [4]>([1, 1, 1, 256])];
            tensor<bool, [4]> var_2507_end_mask_0 = const()[name = string("op_2507_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2507_cast_fp16 = slice_by_index(begin = var_2507_begin_0, end = var_2507_end_0, end_mask = var_2507_end_mask_0, x = q_17_cast_fp16)[name = string("op_2507_cast_fp16")];
            tensor<int32, [4]> k_35_perm_0 = const()[name = string("k_35_perm_0"), val = tensor<int32, [4]>([0, 3, 2, 1])];
            tensor<int32, [4]> var_2514_begin_0 = const()[name = string("op_2514_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_2514_end_0 = const()[name = string("op_2514_end_0"), val = tensor<int32, [4]>([1, 256, 1, 160])];
            tensor<bool, [4]> var_2514_end_mask_0 = const()[name = string("op_2514_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 256, 1, 1280]> k_35_cast_fp16 = transpose(perm = k_35_perm_0, x = k_33_cast_fp16)[name = string("transpose_9")];
            tensor<fp16, [1, 256, 1, 160]> var_2514_cast_fp16 = slice_by_index(begin = var_2514_begin_0, end = var_2514_end_0, end_mask = var_2514_end_mask_0, x = k_35_cast_fp16)[name = string("op_2514_cast_fp16")];
            tensor<int32, [4]> var_2518_begin_0 = const()[name = string("op_2518_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 160])];
            tensor<int32, [4]> var_2518_end_0 = const()[name = string("op_2518_end_0"), val = tensor<int32, [4]>([1, 256, 1, 320])];
            tensor<bool, [4]> var_2518_end_mask_0 = const()[name = string("op_2518_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 256, 1, 160]> var_2518_cast_fp16 = slice_by_index(begin = var_2518_begin_0, end = var_2518_end_0, end_mask = var_2518_end_mask_0, x = k_35_cast_fp16)[name = string("op_2518_cast_fp16")];
            tensor<int32, [4]> var_2522_begin_0 = const()[name = string("op_2522_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 320])];
            tensor<int32, [4]> var_2522_end_0 = const()[name = string("op_2522_end_0"), val = tensor<int32, [4]>([1, 256, 1, 480])];
            tensor<bool, [4]> var_2522_end_mask_0 = const()[name = string("op_2522_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 256, 1, 160]> var_2522_cast_fp16 = slice_by_index(begin = var_2522_begin_0, end = var_2522_end_0, end_mask = var_2522_end_mask_0, x = k_35_cast_fp16)[name = string("op_2522_cast_fp16")];
            tensor<int32, [4]> var_2526_begin_0 = const()[name = string("op_2526_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 480])];
            tensor<int32, [4]> var_2526_end_0 = const()[name = string("op_2526_end_0"), val = tensor<int32, [4]>([1, 256, 1, 640])];
            tensor<bool, [4]> var_2526_end_mask_0 = const()[name = string("op_2526_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 256, 1, 160]> var_2526_cast_fp16 = slice_by_index(begin = var_2526_begin_0, end = var_2526_end_0, end_mask = var_2526_end_mask_0, x = k_35_cast_fp16)[name = string("op_2526_cast_fp16")];
            tensor<int32, [4]> var_2530_begin_0 = const()[name = string("op_2530_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 640])];
            tensor<int32, [4]> var_2530_end_0 = const()[name = string("op_2530_end_0"), val = tensor<int32, [4]>([1, 256, 1, 800])];
            tensor<bool, [4]> var_2530_end_mask_0 = const()[name = string("op_2530_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 256, 1, 160]> var_2530_cast_fp16 = slice_by_index(begin = var_2530_begin_0, end = var_2530_end_0, end_mask = var_2530_end_mask_0, x = k_35_cast_fp16)[name = string("op_2530_cast_fp16")];
            tensor<int32, [4]> var_2534_begin_0 = const()[name = string("op_2534_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 800])];
            tensor<int32, [4]> var_2534_end_0 = const()[name = string("op_2534_end_0"), val = tensor<int32, [4]>([1, 256, 1, 960])];
            tensor<bool, [4]> var_2534_end_mask_0 = const()[name = string("op_2534_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 256, 1, 160]> var_2534_cast_fp16 = slice_by_index(begin = var_2534_begin_0, end = var_2534_end_0, end_mask = var_2534_end_mask_0, x = k_35_cast_fp16)[name = string("op_2534_cast_fp16")];
            tensor<int32, [4]> var_2538_begin_0 = const()[name = string("op_2538_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 960])];
            tensor<int32, [4]> var_2538_end_0 = const()[name = string("op_2538_end_0"), val = tensor<int32, [4]>([1, 256, 1, 1120])];
            tensor<bool, [4]> var_2538_end_mask_0 = const()[name = string("op_2538_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 256, 1, 160]> var_2538_cast_fp16 = slice_by_index(begin = var_2538_begin_0, end = var_2538_end_0, end_mask = var_2538_end_mask_0, x = k_35_cast_fp16)[name = string("op_2538_cast_fp16")];
            tensor<int32, [4]> var_2542_begin_0 = const()[name = string("op_2542_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1120])];
            tensor<int32, [4]> var_2542_end_0 = const()[name = string("op_2542_end_0"), val = tensor<int32, [4]>([1, 256, 1, 1])];
            tensor<bool, [4]> var_2542_end_mask_0 = const()[name = string("op_2542_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 256, 1, 160]> var_2542_cast_fp16 = slice_by_index(begin = var_2542_begin_0, end = var_2542_end_0, end_mask = var_2542_end_mask_0, x = k_35_cast_fp16)[name = string("op_2542_cast_fp16")];
            tensor<int32, [4]> var_2544_begin_0 = const()[name = string("op_2544_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_2544_end_0 = const()[name = string("op_2544_end_0"), val = tensor<int32, [4]>([1, 160, 1, 256])];
            tensor<bool, [4]> var_2544_end_mask_0 = const()[name = string("op_2544_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2544_cast_fp16 = slice_by_index(begin = var_2544_begin_0, end = var_2544_end_0, end_mask = var_2544_end_mask_0, x = v_17_cast_fp16)[name = string("op_2544_cast_fp16")];
            tensor<int32, [4]> var_2548_begin_0 = const()[name = string("op_2548_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_2548_end_0 = const()[name = string("op_2548_end_0"), val = tensor<int32, [4]>([1, 320, 1, 256])];
            tensor<bool, [4]> var_2548_end_mask_0 = const()[name = string("op_2548_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2548_cast_fp16 = slice_by_index(begin = var_2548_begin_0, end = var_2548_end_0, end_mask = var_2548_end_mask_0, x = v_17_cast_fp16)[name = string("op_2548_cast_fp16")];
            tensor<int32, [4]> var_2552_begin_0 = const()[name = string("op_2552_begin_0"), val = tensor<int32, [4]>([0, 320, 0, 0])];
            tensor<int32, [4]> var_2552_end_0 = const()[name = string("op_2552_end_0"), val = tensor<int32, [4]>([1, 480, 1, 256])];
            tensor<bool, [4]> var_2552_end_mask_0 = const()[name = string("op_2552_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2552_cast_fp16 = slice_by_index(begin = var_2552_begin_0, end = var_2552_end_0, end_mask = var_2552_end_mask_0, x = v_17_cast_fp16)[name = string("op_2552_cast_fp16")];
            tensor<int32, [4]> var_2556_begin_0 = const()[name = string("op_2556_begin_0"), val = tensor<int32, [4]>([0, 480, 0, 0])];
            tensor<int32, [4]> var_2556_end_0 = const()[name = string("op_2556_end_0"), val = tensor<int32, [4]>([1, 640, 1, 256])];
            tensor<bool, [4]> var_2556_end_mask_0 = const()[name = string("op_2556_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2556_cast_fp16 = slice_by_index(begin = var_2556_begin_0, end = var_2556_end_0, end_mask = var_2556_end_mask_0, x = v_17_cast_fp16)[name = string("op_2556_cast_fp16")];
            tensor<int32, [4]> var_2560_begin_0 = const()[name = string("op_2560_begin_0"), val = tensor<int32, [4]>([0, 640, 0, 0])];
            tensor<int32, [4]> var_2560_end_0 = const()[name = string("op_2560_end_0"), val = tensor<int32, [4]>([1, 800, 1, 256])];
            tensor<bool, [4]> var_2560_end_mask_0 = const()[name = string("op_2560_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2560_cast_fp16 = slice_by_index(begin = var_2560_begin_0, end = var_2560_end_0, end_mask = var_2560_end_mask_0, x = v_17_cast_fp16)[name = string("op_2560_cast_fp16")];
            tensor<int32, [4]> var_2564_begin_0 = const()[name = string("op_2564_begin_0"), val = tensor<int32, [4]>([0, 800, 0, 0])];
            tensor<int32, [4]> var_2564_end_0 = const()[name = string("op_2564_end_0"), val = tensor<int32, [4]>([1, 960, 1, 256])];
            tensor<bool, [4]> var_2564_end_mask_0 = const()[name = string("op_2564_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2564_cast_fp16 = slice_by_index(begin = var_2564_begin_0, end = var_2564_end_0, end_mask = var_2564_end_mask_0, x = v_17_cast_fp16)[name = string("op_2564_cast_fp16")];
            tensor<int32, [4]> var_2568_begin_0 = const()[name = string("op_2568_begin_0"), val = tensor<int32, [4]>([0, 960, 0, 0])];
            tensor<int32, [4]> var_2568_end_0 = const()[name = string("op_2568_end_0"), val = tensor<int32, [4]>([1, 1120, 1, 256])];
            tensor<bool, [4]> var_2568_end_mask_0 = const()[name = string("op_2568_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2568_cast_fp16 = slice_by_index(begin = var_2568_begin_0, end = var_2568_end_0, end_mask = var_2568_end_mask_0, x = v_17_cast_fp16)[name = string("op_2568_cast_fp16")];
            tensor<int32, [4]> var_2572_begin_0 = const()[name = string("op_2572_begin_0"), val = tensor<int32, [4]>([0, 1120, 0, 0])];
            tensor<int32, [4]> var_2572_end_0 = const()[name = string("op_2572_end_0"), val = tensor<int32, [4]>([1, 1, 1, 256])];
            tensor<bool, [4]> var_2572_end_mask_0 = const()[name = string("op_2572_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2572_cast_fp16 = slice_by_index(begin = var_2572_begin_0, end = var_2572_end_0, end_mask = var_2572_end_mask_0, x = v_17_cast_fp16)[name = string("op_2572_cast_fp16")];
            string var_2576_equation_0 = const()[name = string("op_2576_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 256, 1, 256]> var_2576_cast_fp16 = einsum(equation = var_2576_equation_0, values = (var_2514_cast_fp16, var_2479_cast_fp16))[name = string("op_2576_cast_fp16")];
            fp16 var_2577_to_fp16 = const()[name = string("op_2577_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 256, 1, 256]> aw_129_cast_fp16 = mul(x = var_2576_cast_fp16, y = var_2577_to_fp16)[name = string("aw_129_cast_fp16")];
            string var_2580_equation_0 = const()[name = string("op_2580_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 256, 1, 256]> var_2580_cast_fp16 = einsum(equation = var_2580_equation_0, values = (var_2518_cast_fp16, var_2483_cast_fp16))[name = string("op_2580_cast_fp16")];
            fp16 var_2581_to_fp16 = const()[name = string("op_2581_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 256, 1, 256]> aw_131_cast_fp16 = mul(x = var_2580_cast_fp16, y = var_2581_to_fp16)[name = string("aw_131_cast_fp16")];
            string var_2584_equation_0 = const()[name = string("op_2584_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 256, 1, 256]> var_2584_cast_fp16 = einsum(equation = var_2584_equation_0, values = (var_2522_cast_fp16, var_2487_cast_fp16))[name = string("op_2584_cast_fp16")];
            fp16 var_2585_to_fp16 = const()[name = string("op_2585_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 256, 1, 256]> aw_133_cast_fp16 = mul(x = var_2584_cast_fp16, y = var_2585_to_fp16)[name = string("aw_133_cast_fp16")];
            string var_2588_equation_0 = const()[name = string("op_2588_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 256, 1, 256]> var_2588_cast_fp16 = einsum(equation = var_2588_equation_0, values = (var_2526_cast_fp16, var_2491_cast_fp16))[name = string("op_2588_cast_fp16")];
            fp16 var_2589_to_fp16 = const()[name = string("op_2589_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 256, 1, 256]> aw_135_cast_fp16 = mul(x = var_2588_cast_fp16, y = var_2589_to_fp16)[name = string("aw_135_cast_fp16")];
            string var_2592_equation_0 = const()[name = string("op_2592_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 256, 1, 256]> var_2592_cast_fp16 = einsum(equation = var_2592_equation_0, values = (var_2530_cast_fp16, var_2495_cast_fp16))[name = string("op_2592_cast_fp16")];
            fp16 var_2593_to_fp16 = const()[name = string("op_2593_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 256, 1, 256]> aw_137_cast_fp16 = mul(x = var_2592_cast_fp16, y = var_2593_to_fp16)[name = string("aw_137_cast_fp16")];
            string var_2596_equation_0 = const()[name = string("op_2596_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 256, 1, 256]> var_2596_cast_fp16 = einsum(equation = var_2596_equation_0, values = (var_2534_cast_fp16, var_2499_cast_fp16))[name = string("op_2596_cast_fp16")];
            fp16 var_2597_to_fp16 = const()[name = string("op_2597_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 256, 1, 256]> aw_139_cast_fp16 = mul(x = var_2596_cast_fp16, y = var_2597_to_fp16)[name = string("aw_139_cast_fp16")];
            string var_2600_equation_0 = const()[name = string("op_2600_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 256, 1, 256]> var_2600_cast_fp16 = einsum(equation = var_2600_equation_0, values = (var_2538_cast_fp16, var_2503_cast_fp16))[name = string("op_2600_cast_fp16")];
            fp16 var_2601_to_fp16 = const()[name = string("op_2601_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 256, 1, 256]> aw_141_cast_fp16 = mul(x = var_2600_cast_fp16, y = var_2601_to_fp16)[name = string("aw_141_cast_fp16")];
            string var_2604_equation_0 = const()[name = string("op_2604_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 256, 1, 256]> var_2604_cast_fp16 = einsum(equation = var_2604_equation_0, values = (var_2542_cast_fp16, var_2507_cast_fp16))[name = string("op_2604_cast_fp16")];
            fp16 var_2605_to_fp16 = const()[name = string("op_2605_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 256, 1, 256]> aw_143_cast_fp16 = mul(x = var_2604_cast_fp16, y = var_2605_to_fp16)[name = string("aw_143_cast_fp16")];
            tensor<fp16, [1, 256, 1, 256]> var_2607_cast_fp16 = softmax(axis = var_1812, x = aw_129_cast_fp16)[name = string("op_2607_cast_fp16")];
            tensor<fp16, [1, 256, 1, 256]> var_2608_cast_fp16 = softmax(axis = var_1812, x = aw_131_cast_fp16)[name = string("op_2608_cast_fp16")];
            tensor<fp16, [1, 256, 1, 256]> var_2609_cast_fp16 = softmax(axis = var_1812, x = aw_133_cast_fp16)[name = string("op_2609_cast_fp16")];
            tensor<fp16, [1, 256, 1, 256]> var_2610_cast_fp16 = softmax(axis = var_1812, x = aw_135_cast_fp16)[name = string("op_2610_cast_fp16")];
            tensor<fp16, [1, 256, 1, 256]> var_2611_cast_fp16 = softmax(axis = var_1812, x = aw_137_cast_fp16)[name = string("op_2611_cast_fp16")];
            tensor<fp16, [1, 256, 1, 256]> var_2612_cast_fp16 = softmax(axis = var_1812, x = aw_139_cast_fp16)[name = string("op_2612_cast_fp16")];
            tensor<fp16, [1, 256, 1, 256]> var_2613_cast_fp16 = softmax(axis = var_1812, x = aw_141_cast_fp16)[name = string("op_2613_cast_fp16")];
            tensor<fp16, [1, 256, 1, 256]> var_2614_cast_fp16 = softmax(axis = var_1812, x = aw_143_cast_fp16)[name = string("op_2614_cast_fp16")];
            string var_2616_equation_0 = const()[name = string("op_2616_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2616_cast_fp16 = einsum(equation = var_2616_equation_0, values = (var_2544_cast_fp16, var_2607_cast_fp16))[name = string("op_2616_cast_fp16")];
            string var_2618_equation_0 = const()[name = string("op_2618_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2618_cast_fp16 = einsum(equation = var_2618_equation_0, values = (var_2548_cast_fp16, var_2608_cast_fp16))[name = string("op_2618_cast_fp16")];
            string var_2620_equation_0 = const()[name = string("op_2620_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2620_cast_fp16 = einsum(equation = var_2620_equation_0, values = (var_2552_cast_fp16, var_2609_cast_fp16))[name = string("op_2620_cast_fp16")];
            string var_2622_equation_0 = const()[name = string("op_2622_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2622_cast_fp16 = einsum(equation = var_2622_equation_0, values = (var_2556_cast_fp16, var_2610_cast_fp16))[name = string("op_2622_cast_fp16")];
            string var_2624_equation_0 = const()[name = string("op_2624_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2624_cast_fp16 = einsum(equation = var_2624_equation_0, values = (var_2560_cast_fp16, var_2611_cast_fp16))[name = string("op_2624_cast_fp16")];
            string var_2626_equation_0 = const()[name = string("op_2626_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2626_cast_fp16 = einsum(equation = var_2626_equation_0, values = (var_2564_cast_fp16, var_2612_cast_fp16))[name = string("op_2626_cast_fp16")];
            string var_2628_equation_0 = const()[name = string("op_2628_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2628_cast_fp16 = einsum(equation = var_2628_equation_0, values = (var_2568_cast_fp16, var_2613_cast_fp16))[name = string("op_2628_cast_fp16")];
            string var_2630_equation_0 = const()[name = string("op_2630_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2630_cast_fp16 = einsum(equation = var_2630_equation_0, values = (var_2572_cast_fp16, var_2614_cast_fp16))[name = string("op_2630_cast_fp16")];
            bool input_133_interleave_0 = const()[name = string("input_133_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1280, 1, 256]> input_133_cast_fp16 = concat(axis = var_1812, interleave = input_133_interleave_0, values = (var_2616_cast_fp16, var_2618_cast_fp16, var_2620_cast_fp16, var_2622_cast_fp16, var_2624_cast_fp16, var_2626_cast_fp16, var_2628_cast_fp16, var_2630_cast_fp16))[name = string("input_133_cast_fp16")];
            string var_2640_pad_type_0 = const()[name = string("op_2640_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_2640_strides_0 = const()[name = string("op_2640_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_2640_pad_0 = const()[name = string("op_2640_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_2640_dilations_0 = const()[name = string("op_2640_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_2640_groups_0 = const()[name = string("op_2640_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1280, 1, 1]> up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_out_0_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_out_0_weight_to_fp16"), val = tensor<fp16, [1280, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(111470976)))];
            tensor<fp16, [1280]> up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_out_0_bias_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_out_0_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(114747840)))];
            tensor<fp16, [1, 1280, 1, 256]> var_2640_cast_fp16 = conv(bias = up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_out_0_bias_to_fp16, dilations = var_2640_dilations_0, groups = var_2640_groups_0, pad = var_2640_pad_0, pad_type = var_2640_pad_type_0, strides = var_2640_strides_0, weight = up_blocks_0_attentions_1_transformer_blocks_0_attn1_to_out_0_weight_to_fp16, x = input_133_cast_fp16)[name = string("op_2640_cast_fp16")];
            tensor<fp16, [1, 1280, 1, 256]> inputs_27_cast_fp16 = add(x = var_2640_cast_fp16, y = inputs_25_cast_fp16)[name = string("inputs_27_cast_fp16")];
            tensor<int32, [1]> hidden_states_87_axes_0 = const()[name = string("hidden_states_87_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1280]> hidden_states_87_gamma_0_to_fp16 = const()[name = string("hidden_states_87_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(114750464)))];
            tensor<fp16, [1280]> hidden_states_87_beta_0_to_fp16 = const()[name = string("hidden_states_87_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(114753088)))];
            fp16 var_2650_to_fp16 = const()[name = string("op_2650_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 1280, 1, 256]> hidden_states_87_cast_fp16 = layer_norm(axes = hidden_states_87_axes_0, beta = hidden_states_87_beta_0_to_fp16, epsilon = var_2650_to_fp16, gamma = hidden_states_87_gamma_0_to_fp16, x = inputs_27_cast_fp16)[name = string("hidden_states_87_cast_fp16")];
            string q_19_pad_type_0 = const()[name = string("q_19_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> q_19_strides_0 = const()[name = string("q_19_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> q_19_pad_0 = const()[name = string("q_19_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> q_19_dilations_0 = const()[name = string("q_19_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 q_19_groups_0 = const()[name = string("q_19_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1280, 1, 1]> up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_q_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_q_weight_to_fp16"), val = tensor<fp16, [1280, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(114755712)))];
            tensor<fp16, [1, 1280, 1, 256]> q_19_cast_fp16 = conv(dilations = q_19_dilations_0, groups = q_19_groups_0, pad = q_19_pad_0, pad_type = q_19_pad_type_0, strides = q_19_strides_0, weight = up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_q_weight_to_fp16, x = hidden_states_87_cast_fp16)[name = string("q_19_cast_fp16")];
            string k_37_pad_type_0 = const()[name = string("k_37_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> k_37_strides_0 = const()[name = string("k_37_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> k_37_pad_0 = const()[name = string("k_37_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> k_37_dilations_0 = const()[name = string("k_37_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 k_37_groups_0 = const()[name = string("k_37_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 768, 1, 1]> up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_k_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_k_weight_to_fp16"), val = tensor<fp16, [1280, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(118032576)))];
            tensor<fp16, [1, 1280, 1, 77]> k_37_cast_fp16 = conv(dilations = k_37_dilations_0, groups = k_37_groups_0, pad = k_37_pad_0, pad_type = k_37_pad_type_0, strides = k_37_strides_0, weight = up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_k_weight_to_fp16, x = encoder_hidden_states)[name = string("k_37_cast_fp16")];
            string v_19_pad_type_0 = const()[name = string("v_19_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> v_19_strides_0 = const()[name = string("v_19_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> v_19_pad_0 = const()[name = string("v_19_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> v_19_dilations_0 = const()[name = string("v_19_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 v_19_groups_0 = const()[name = string("v_19_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 768, 1, 1]> up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_v_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_v_weight_to_fp16"), val = tensor<fp16, [1280, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(119998720)))];
            tensor<fp16, [1, 1280, 1, 77]> v_19_cast_fp16 = conv(dilations = v_19_dilations_0, groups = v_19_groups_0, pad = v_19_pad_0, pad_type = v_19_pad_type_0, strides = v_19_strides_0, weight = up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_v_weight_to_fp16, x = encoder_hidden_states)[name = string("v_19_cast_fp16")];
            tensor<int32, [4]> var_2683_begin_0 = const()[name = string("op_2683_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_2683_end_0 = const()[name = string("op_2683_end_0"), val = tensor<int32, [4]>([1, 160, 1, 256])];
            tensor<bool, [4]> var_2683_end_mask_0 = const()[name = string("op_2683_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2683_cast_fp16 = slice_by_index(begin = var_2683_begin_0, end = var_2683_end_0, end_mask = var_2683_end_mask_0, x = q_19_cast_fp16)[name = string("op_2683_cast_fp16")];
            tensor<int32, [4]> var_2687_begin_0 = const()[name = string("op_2687_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_2687_end_0 = const()[name = string("op_2687_end_0"), val = tensor<int32, [4]>([1, 320, 1, 256])];
            tensor<bool, [4]> var_2687_end_mask_0 = const()[name = string("op_2687_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2687_cast_fp16 = slice_by_index(begin = var_2687_begin_0, end = var_2687_end_0, end_mask = var_2687_end_mask_0, x = q_19_cast_fp16)[name = string("op_2687_cast_fp16")];
            tensor<int32, [4]> var_2691_begin_0 = const()[name = string("op_2691_begin_0"), val = tensor<int32, [4]>([0, 320, 0, 0])];
            tensor<int32, [4]> var_2691_end_0 = const()[name = string("op_2691_end_0"), val = tensor<int32, [4]>([1, 480, 1, 256])];
            tensor<bool, [4]> var_2691_end_mask_0 = const()[name = string("op_2691_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2691_cast_fp16 = slice_by_index(begin = var_2691_begin_0, end = var_2691_end_0, end_mask = var_2691_end_mask_0, x = q_19_cast_fp16)[name = string("op_2691_cast_fp16")];
            tensor<int32, [4]> var_2695_begin_0 = const()[name = string("op_2695_begin_0"), val = tensor<int32, [4]>([0, 480, 0, 0])];
            tensor<int32, [4]> var_2695_end_0 = const()[name = string("op_2695_end_0"), val = tensor<int32, [4]>([1, 640, 1, 256])];
            tensor<bool, [4]> var_2695_end_mask_0 = const()[name = string("op_2695_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2695_cast_fp16 = slice_by_index(begin = var_2695_begin_0, end = var_2695_end_0, end_mask = var_2695_end_mask_0, x = q_19_cast_fp16)[name = string("op_2695_cast_fp16")];
            tensor<int32, [4]> var_2699_begin_0 = const()[name = string("op_2699_begin_0"), val = tensor<int32, [4]>([0, 640, 0, 0])];
            tensor<int32, [4]> var_2699_end_0 = const()[name = string("op_2699_end_0"), val = tensor<int32, [4]>([1, 800, 1, 256])];
            tensor<bool, [4]> var_2699_end_mask_0 = const()[name = string("op_2699_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2699_cast_fp16 = slice_by_index(begin = var_2699_begin_0, end = var_2699_end_0, end_mask = var_2699_end_mask_0, x = q_19_cast_fp16)[name = string("op_2699_cast_fp16")];
            tensor<int32, [4]> var_2703_begin_0 = const()[name = string("op_2703_begin_0"), val = tensor<int32, [4]>([0, 800, 0, 0])];
            tensor<int32, [4]> var_2703_end_0 = const()[name = string("op_2703_end_0"), val = tensor<int32, [4]>([1, 960, 1, 256])];
            tensor<bool, [4]> var_2703_end_mask_0 = const()[name = string("op_2703_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2703_cast_fp16 = slice_by_index(begin = var_2703_begin_0, end = var_2703_end_0, end_mask = var_2703_end_mask_0, x = q_19_cast_fp16)[name = string("op_2703_cast_fp16")];
            tensor<int32, [4]> var_2707_begin_0 = const()[name = string("op_2707_begin_0"), val = tensor<int32, [4]>([0, 960, 0, 0])];
            tensor<int32, [4]> var_2707_end_0 = const()[name = string("op_2707_end_0"), val = tensor<int32, [4]>([1, 1120, 1, 256])];
            tensor<bool, [4]> var_2707_end_mask_0 = const()[name = string("op_2707_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2707_cast_fp16 = slice_by_index(begin = var_2707_begin_0, end = var_2707_end_0, end_mask = var_2707_end_mask_0, x = q_19_cast_fp16)[name = string("op_2707_cast_fp16")];
            tensor<int32, [4]> var_2711_begin_0 = const()[name = string("op_2711_begin_0"), val = tensor<int32, [4]>([0, 1120, 0, 0])];
            tensor<int32, [4]> var_2711_end_0 = const()[name = string("op_2711_end_0"), val = tensor<int32, [4]>([1, 1, 1, 256])];
            tensor<bool, [4]> var_2711_end_mask_0 = const()[name = string("op_2711_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 160, 1, 256]> var_2711_cast_fp16 = slice_by_index(begin = var_2711_begin_0, end = var_2711_end_0, end_mask = var_2711_end_mask_0, x = q_19_cast_fp16)[name = string("op_2711_cast_fp16")];
            tensor<int32, [4]> k_39_perm_0 = const()[name = string("k_39_perm_0"), val = tensor<int32, [4]>([0, 3, 2, 1])];
            tensor<int32, [4]> var_2718_begin_0 = const()[name = string("op_2718_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_2718_end_0 = const()[name = string("op_2718_end_0"), val = tensor<int32, [4]>([1, 77, 1, 160])];
            tensor<bool, [4]> var_2718_end_mask_0 = const()[name = string("op_2718_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 1280]> k_39_cast_fp16 = transpose(perm = k_39_perm_0, x = k_37_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 77, 1, 160]> var_2718_cast_fp16 = slice_by_index(begin = var_2718_begin_0, end = var_2718_end_0, end_mask = var_2718_end_mask_0, x = k_39_cast_fp16)[name = string("op_2718_cast_fp16")];
            tensor<int32, [4]> var_2722_begin_0 = const()[name = string("op_2722_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 160])];
            tensor<int32, [4]> var_2722_end_0 = const()[name = string("op_2722_end_0"), val = tensor<int32, [4]>([1, 77, 1, 320])];
            tensor<bool, [4]> var_2722_end_mask_0 = const()[name = string("op_2722_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 160]> var_2722_cast_fp16 = slice_by_index(begin = var_2722_begin_0, end = var_2722_end_0, end_mask = var_2722_end_mask_0, x = k_39_cast_fp16)[name = string("op_2722_cast_fp16")];
            tensor<int32, [4]> var_2726_begin_0 = const()[name = string("op_2726_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 320])];
            tensor<int32, [4]> var_2726_end_0 = const()[name = string("op_2726_end_0"), val = tensor<int32, [4]>([1, 77, 1, 480])];
            tensor<bool, [4]> var_2726_end_mask_0 = const()[name = string("op_2726_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 160]> var_2726_cast_fp16 = slice_by_index(begin = var_2726_begin_0, end = var_2726_end_0, end_mask = var_2726_end_mask_0, x = k_39_cast_fp16)[name = string("op_2726_cast_fp16")];
            tensor<int32, [4]> var_2730_begin_0 = const()[name = string("op_2730_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 480])];
            tensor<int32, [4]> var_2730_end_0 = const()[name = string("op_2730_end_0"), val = tensor<int32, [4]>([1, 77, 1, 640])];
            tensor<bool, [4]> var_2730_end_mask_0 = const()[name = string("op_2730_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 160]> var_2730_cast_fp16 = slice_by_index(begin = var_2730_begin_0, end = var_2730_end_0, end_mask = var_2730_end_mask_0, x = k_39_cast_fp16)[name = string("op_2730_cast_fp16")];
            tensor<int32, [4]> var_2734_begin_0 = const()[name = string("op_2734_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 640])];
            tensor<int32, [4]> var_2734_end_0 = const()[name = string("op_2734_end_0"), val = tensor<int32, [4]>([1, 77, 1, 800])];
            tensor<bool, [4]> var_2734_end_mask_0 = const()[name = string("op_2734_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 160]> var_2734_cast_fp16 = slice_by_index(begin = var_2734_begin_0, end = var_2734_end_0, end_mask = var_2734_end_mask_0, x = k_39_cast_fp16)[name = string("op_2734_cast_fp16")];
            tensor<int32, [4]> var_2738_begin_0 = const()[name = string("op_2738_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 800])];
            tensor<int32, [4]> var_2738_end_0 = const()[name = string("op_2738_end_0"), val = tensor<int32, [4]>([1, 77, 1, 960])];
            tensor<bool, [4]> var_2738_end_mask_0 = const()[name = string("op_2738_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 160]> var_2738_cast_fp16 = slice_by_index(begin = var_2738_begin_0, end = var_2738_end_0, end_mask = var_2738_end_mask_0, x = k_39_cast_fp16)[name = string("op_2738_cast_fp16")];
            tensor<int32, [4]> var_2742_begin_0 = const()[name = string("op_2742_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 960])];
            tensor<int32, [4]> var_2742_end_0 = const()[name = string("op_2742_end_0"), val = tensor<int32, [4]>([1, 77, 1, 1120])];
            tensor<bool, [4]> var_2742_end_mask_0 = const()[name = string("op_2742_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 160]> var_2742_cast_fp16 = slice_by_index(begin = var_2742_begin_0, end = var_2742_end_0, end_mask = var_2742_end_mask_0, x = k_39_cast_fp16)[name = string("op_2742_cast_fp16")];
            tensor<int32, [4]> var_2746_begin_0 = const()[name = string("op_2746_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1120])];
            tensor<int32, [4]> var_2746_end_0 = const()[name = string("op_2746_end_0"), val = tensor<int32, [4]>([1, 77, 1, 1])];
            tensor<bool, [4]> var_2746_end_mask_0 = const()[name = string("op_2746_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 77, 1, 160]> var_2746_cast_fp16 = slice_by_index(begin = var_2746_begin_0, end = var_2746_end_0, end_mask = var_2746_end_mask_0, x = k_39_cast_fp16)[name = string("op_2746_cast_fp16")];
            tensor<int32, [4]> var_2748_begin_0 = const()[name = string("op_2748_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_2748_end_0 = const()[name = string("op_2748_end_0"), val = tensor<int32, [4]>([1, 160, 1, 77])];
            tensor<bool, [4]> var_2748_end_mask_0 = const()[name = string("op_2748_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 77]> var_2748_cast_fp16 = slice_by_index(begin = var_2748_begin_0, end = var_2748_end_0, end_mask = var_2748_end_mask_0, x = v_19_cast_fp16)[name = string("op_2748_cast_fp16")];
            tensor<int32, [4]> var_2752_begin_0 = const()[name = string("op_2752_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_2752_end_0 = const()[name = string("op_2752_end_0"), val = tensor<int32, [4]>([1, 320, 1, 77])];
            tensor<bool, [4]> var_2752_end_mask_0 = const()[name = string("op_2752_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 77]> var_2752_cast_fp16 = slice_by_index(begin = var_2752_begin_0, end = var_2752_end_0, end_mask = var_2752_end_mask_0, x = v_19_cast_fp16)[name = string("op_2752_cast_fp16")];
            tensor<int32, [4]> var_2756_begin_0 = const()[name = string("op_2756_begin_0"), val = tensor<int32, [4]>([0, 320, 0, 0])];
            tensor<int32, [4]> var_2756_end_0 = const()[name = string("op_2756_end_0"), val = tensor<int32, [4]>([1, 480, 1, 77])];
            tensor<bool, [4]> var_2756_end_mask_0 = const()[name = string("op_2756_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 77]> var_2756_cast_fp16 = slice_by_index(begin = var_2756_begin_0, end = var_2756_end_0, end_mask = var_2756_end_mask_0, x = v_19_cast_fp16)[name = string("op_2756_cast_fp16")];
            tensor<int32, [4]> var_2760_begin_0 = const()[name = string("op_2760_begin_0"), val = tensor<int32, [4]>([0, 480, 0, 0])];
            tensor<int32, [4]> var_2760_end_0 = const()[name = string("op_2760_end_0"), val = tensor<int32, [4]>([1, 640, 1, 77])];
            tensor<bool, [4]> var_2760_end_mask_0 = const()[name = string("op_2760_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 77]> var_2760_cast_fp16 = slice_by_index(begin = var_2760_begin_0, end = var_2760_end_0, end_mask = var_2760_end_mask_0, x = v_19_cast_fp16)[name = string("op_2760_cast_fp16")];
            tensor<int32, [4]> var_2764_begin_0 = const()[name = string("op_2764_begin_0"), val = tensor<int32, [4]>([0, 640, 0, 0])];
            tensor<int32, [4]> var_2764_end_0 = const()[name = string("op_2764_end_0"), val = tensor<int32, [4]>([1, 800, 1, 77])];
            tensor<bool, [4]> var_2764_end_mask_0 = const()[name = string("op_2764_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 77]> var_2764_cast_fp16 = slice_by_index(begin = var_2764_begin_0, end = var_2764_end_0, end_mask = var_2764_end_mask_0, x = v_19_cast_fp16)[name = string("op_2764_cast_fp16")];
            tensor<int32, [4]> var_2768_begin_0 = const()[name = string("op_2768_begin_0"), val = tensor<int32, [4]>([0, 800, 0, 0])];
            tensor<int32, [4]> var_2768_end_0 = const()[name = string("op_2768_end_0"), val = tensor<int32, [4]>([1, 960, 1, 77])];
            tensor<bool, [4]> var_2768_end_mask_0 = const()[name = string("op_2768_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 77]> var_2768_cast_fp16 = slice_by_index(begin = var_2768_begin_0, end = var_2768_end_0, end_mask = var_2768_end_mask_0, x = v_19_cast_fp16)[name = string("op_2768_cast_fp16")];
            tensor<int32, [4]> var_2772_begin_0 = const()[name = string("op_2772_begin_0"), val = tensor<int32, [4]>([0, 960, 0, 0])];
            tensor<int32, [4]> var_2772_end_0 = const()[name = string("op_2772_end_0"), val = tensor<int32, [4]>([1, 1120, 1, 77])];
            tensor<bool, [4]> var_2772_end_mask_0 = const()[name = string("op_2772_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 160, 1, 77]> var_2772_cast_fp16 = slice_by_index(begin = var_2772_begin_0, end = var_2772_end_0, end_mask = var_2772_end_mask_0, x = v_19_cast_fp16)[name = string("op_2772_cast_fp16")];
            tensor<int32, [4]> var_2776_begin_0 = const()[name = string("op_2776_begin_0"), val = tensor<int32, [4]>([0, 1120, 0, 0])];
            tensor<int32, [4]> var_2776_end_0 = const()[name = string("op_2776_end_0"), val = tensor<int32, [4]>([1, 1, 1, 77])];
            tensor<bool, [4]> var_2776_end_mask_0 = const()[name = string("op_2776_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 160, 1, 77]> var_2776_cast_fp16 = slice_by_index(begin = var_2776_begin_0, end = var_2776_end_0, end_mask = var_2776_end_mask_0, x = v_19_cast_fp16)[name = string("op_2776_cast_fp16")];
            string var_2780_equation_0 = const()[name = string("op_2780_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 256]> var_2780_cast_fp16 = einsum(equation = var_2780_equation_0, values = (var_2718_cast_fp16, var_2683_cast_fp16))[name = string("op_2780_cast_fp16")];
            fp16 var_2781_to_fp16 = const()[name = string("op_2781_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 77, 1, 256]> aw_145_cast_fp16 = mul(x = var_2780_cast_fp16, y = var_2781_to_fp16)[name = string("aw_145_cast_fp16")];
            string var_2784_equation_0 = const()[name = string("op_2784_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 256]> var_2784_cast_fp16 = einsum(equation = var_2784_equation_0, values = (var_2722_cast_fp16, var_2687_cast_fp16))[name = string("op_2784_cast_fp16")];
            fp16 var_2785_to_fp16 = const()[name = string("op_2785_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 77, 1, 256]> aw_147_cast_fp16 = mul(x = var_2784_cast_fp16, y = var_2785_to_fp16)[name = string("aw_147_cast_fp16")];
            string var_2788_equation_0 = const()[name = string("op_2788_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 256]> var_2788_cast_fp16 = einsum(equation = var_2788_equation_0, values = (var_2726_cast_fp16, var_2691_cast_fp16))[name = string("op_2788_cast_fp16")];
            fp16 var_2789_to_fp16 = const()[name = string("op_2789_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 77, 1, 256]> aw_149_cast_fp16 = mul(x = var_2788_cast_fp16, y = var_2789_to_fp16)[name = string("aw_149_cast_fp16")];
            string var_2792_equation_0 = const()[name = string("op_2792_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 256]> var_2792_cast_fp16 = einsum(equation = var_2792_equation_0, values = (var_2730_cast_fp16, var_2695_cast_fp16))[name = string("op_2792_cast_fp16")];
            fp16 var_2793_to_fp16 = const()[name = string("op_2793_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 77, 1, 256]> aw_151_cast_fp16 = mul(x = var_2792_cast_fp16, y = var_2793_to_fp16)[name = string("aw_151_cast_fp16")];
            string var_2796_equation_0 = const()[name = string("op_2796_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 256]> var_2796_cast_fp16 = einsum(equation = var_2796_equation_0, values = (var_2734_cast_fp16, var_2699_cast_fp16))[name = string("op_2796_cast_fp16")];
            fp16 var_2797_to_fp16 = const()[name = string("op_2797_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 77, 1, 256]> aw_153_cast_fp16 = mul(x = var_2796_cast_fp16, y = var_2797_to_fp16)[name = string("aw_153_cast_fp16")];
            string var_2800_equation_0 = const()[name = string("op_2800_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 256]> var_2800_cast_fp16 = einsum(equation = var_2800_equation_0, values = (var_2738_cast_fp16, var_2703_cast_fp16))[name = string("op_2800_cast_fp16")];
            fp16 var_2801_to_fp16 = const()[name = string("op_2801_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 77, 1, 256]> aw_155_cast_fp16 = mul(x = var_2800_cast_fp16, y = var_2801_to_fp16)[name = string("aw_155_cast_fp16")];
            string var_2804_equation_0 = const()[name = string("op_2804_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 256]> var_2804_cast_fp16 = einsum(equation = var_2804_equation_0, values = (var_2742_cast_fp16, var_2707_cast_fp16))[name = string("op_2804_cast_fp16")];
            fp16 var_2805_to_fp16 = const()[name = string("op_2805_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 77, 1, 256]> aw_157_cast_fp16 = mul(x = var_2804_cast_fp16, y = var_2805_to_fp16)[name = string("aw_157_cast_fp16")];
            string var_2808_equation_0 = const()[name = string("op_2808_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 256]> var_2808_cast_fp16 = einsum(equation = var_2808_equation_0, values = (var_2746_cast_fp16, var_2711_cast_fp16))[name = string("op_2808_cast_fp16")];
            fp16 var_2809_to_fp16 = const()[name = string("op_2809_to_fp16"), val = fp16(0x1.43cp-4)];
            tensor<fp16, [1, 77, 1, 256]> aw_159_cast_fp16 = mul(x = var_2808_cast_fp16, y = var_2809_to_fp16)[name = string("aw_159_cast_fp16")];
            tensor<fp16, [1, 77, 1, 256]> var_2811_cast_fp16 = softmax(axis = var_1812, x = aw_145_cast_fp16)[name = string("op_2811_cast_fp16")];
            tensor<fp16, [1, 77, 1, 256]> var_2812_cast_fp16 = softmax(axis = var_1812, x = aw_147_cast_fp16)[name = string("op_2812_cast_fp16")];
            tensor<fp16, [1, 77, 1, 256]> var_2813_cast_fp16 = softmax(axis = var_1812, x = aw_149_cast_fp16)[name = string("op_2813_cast_fp16")];
            tensor<fp16, [1, 77, 1, 256]> var_2814_cast_fp16 = softmax(axis = var_1812, x = aw_151_cast_fp16)[name = string("op_2814_cast_fp16")];
            tensor<fp16, [1, 77, 1, 256]> var_2815_cast_fp16 = softmax(axis = var_1812, x = aw_153_cast_fp16)[name = string("op_2815_cast_fp16")];
            tensor<fp16, [1, 77, 1, 256]> var_2816_cast_fp16 = softmax(axis = var_1812, x = aw_155_cast_fp16)[name = string("op_2816_cast_fp16")];
            tensor<fp16, [1, 77, 1, 256]> var_2817_cast_fp16 = softmax(axis = var_1812, x = aw_157_cast_fp16)[name = string("op_2817_cast_fp16")];
            tensor<fp16, [1, 77, 1, 256]> var_2818_cast_fp16 = softmax(axis = var_1812, x = aw_159_cast_fp16)[name = string("op_2818_cast_fp16")];
            string var_2820_equation_0 = const()[name = string("op_2820_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2820_cast_fp16 = einsum(equation = var_2820_equation_0, values = (var_2748_cast_fp16, var_2811_cast_fp16))[name = string("op_2820_cast_fp16")];
            string var_2822_equation_0 = const()[name = string("op_2822_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2822_cast_fp16 = einsum(equation = var_2822_equation_0, values = (var_2752_cast_fp16, var_2812_cast_fp16))[name = string("op_2822_cast_fp16")];
            string var_2824_equation_0 = const()[name = string("op_2824_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2824_cast_fp16 = einsum(equation = var_2824_equation_0, values = (var_2756_cast_fp16, var_2813_cast_fp16))[name = string("op_2824_cast_fp16")];
            string var_2826_equation_0 = const()[name = string("op_2826_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2826_cast_fp16 = einsum(equation = var_2826_equation_0, values = (var_2760_cast_fp16, var_2814_cast_fp16))[name = string("op_2826_cast_fp16")];
            string var_2828_equation_0 = const()[name = string("op_2828_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2828_cast_fp16 = einsum(equation = var_2828_equation_0, values = (var_2764_cast_fp16, var_2815_cast_fp16))[name = string("op_2828_cast_fp16")];
            string var_2830_equation_0 = const()[name = string("op_2830_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2830_cast_fp16 = einsum(equation = var_2830_equation_0, values = (var_2768_cast_fp16, var_2816_cast_fp16))[name = string("op_2830_cast_fp16")];
            string var_2832_equation_0 = const()[name = string("op_2832_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2832_cast_fp16 = einsum(equation = var_2832_equation_0, values = (var_2772_cast_fp16, var_2817_cast_fp16))[name = string("op_2832_cast_fp16")];
            string var_2834_equation_0 = const()[name = string("op_2834_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 160, 1, 256]> var_2834_cast_fp16 = einsum(equation = var_2834_equation_0, values = (var_2776_cast_fp16, var_2818_cast_fp16))[name = string("op_2834_cast_fp16")];
            bool input_135_interleave_0 = const()[name = string("input_135_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1280, 1, 256]> input_135_cast_fp16 = concat(axis = var_1812, interleave = input_135_interleave_0, values = (var_2820_cast_fp16, var_2822_cast_fp16, var_2824_cast_fp16, var_2826_cast_fp16, var_2828_cast_fp16, var_2830_cast_fp16, var_2832_cast_fp16, var_2834_cast_fp16))[name = string("input_135_cast_fp16")];
            string var_2844_pad_type_0 = const()[name = string("op_2844_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_2844_strides_0 = const()[name = string("op_2844_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_2844_pad_0 = const()[name = string("op_2844_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_2844_dilations_0 = const()[name = string("op_2844_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_2844_groups_0 = const()[name = string("op_2844_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1280, 1, 1]> up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_out_0_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_out_0_weight_to_fp16"), val = tensor<fp16, [1280, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(121964864)))];
            tensor<fp16, [1280]> up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_out_0_bias_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_out_0_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(125241728)))];
            tensor<fp16, [1, 1280, 1, 256]> var_2844_cast_fp16 = conv(bias = up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_out_0_bias_to_fp16, dilations = var_2844_dilations_0, groups = var_2844_groups_0, pad = var_2844_pad_0, pad_type = var_2844_pad_type_0, strides = var_2844_strides_0, weight = up_blocks_0_attentions_1_transformer_blocks_0_attn2_to_out_0_weight_to_fp16, x = input_135_cast_fp16)[name = string("op_2844_cast_fp16")];
            tensor<fp16, [1, 1280, 1, 256]> inputs_29_cast_fp16 = add(x = var_2844_cast_fp16, y = inputs_27_cast_fp16)[name = string("inputs_29_cast_fp16")];
            tensor<int32, [1]> input_137_axes_0 = const()[name = string("input_137_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1280]> input_137_gamma_0_to_fp16 = const()[name = string("input_137_gamma_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(125244352)))];
            tensor<fp16, [1280]> input_137_beta_0_to_fp16 = const()[name = string("input_137_beta_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(125246976)))];
            fp16 var_2854_to_fp16 = const()[name = string("op_2854_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 1280, 1, 256]> input_137_cast_fp16 = layer_norm(axes = input_137_axes_0, beta = input_137_beta_0_to_fp16, epsilon = var_2854_to_fp16, gamma = input_137_gamma_0_to_fp16, x = inputs_29_cast_fp16)[name = string("input_137_cast_fp16")];
            string var_2874_pad_type_0 = const()[name = string("op_2874_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_2874_strides_0 = const()[name = string("op_2874_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_2874_pad_0 = const()[name = string("op_2874_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_2874_dilations_0 = const()[name = string("op_2874_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_2874_groups_0 = const()[name = string("op_2874_groups_0"), val = int32(1)];
            tensor<fp16, [10240, 1280, 1, 1]> up_blocks_0_attentions_1_transformer_blocks_0_ff_net_0_proj_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_ff_net_0_proj_weight_to_fp16"), val = tensor<fp16, [10240, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(125249600)))];
            tensor<fp16, [10240]> up_blocks_0_attentions_1_transformer_blocks_0_ff_net_0_proj_bias_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_ff_net_0_proj_bias_to_fp16"), val = tensor<fp16, [10240]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(151464064)))];
            tensor<fp16, [1, 10240, 1, 256]> var_2874_cast_fp16 = conv(bias = up_blocks_0_attentions_1_transformer_blocks_0_ff_net_0_proj_bias_to_fp16, dilations = var_2874_dilations_0, groups = var_2874_groups_0, pad = var_2874_pad_0, pad_type = var_2874_pad_type_0, strides = var_2874_strides_0, weight = up_blocks_0_attentions_1_transformer_blocks_0_ff_net_0_proj_weight_to_fp16, x = input_137_cast_fp16)[name = string("op_2874_cast_fp16")];
            tensor<int32, [2]> var_2875_split_sizes_0 = const()[name = string("op_2875_split_sizes_0"), val = tensor<int32, [2]>([5120, 5120])];
            int32 var_2875_axis_0 = const()[name = string("op_2875_axis_0"), val = int32(1)];
            tensor<fp16, [1, 5120, 1, 256]> var_2875_cast_fp16_0, tensor<fp16, [1, 5120, 1, 256]> var_2875_cast_fp16_1 = split(axis = var_2875_axis_0, split_sizes = var_2875_split_sizes_0, x = var_2874_cast_fp16)[name = string("op_2875_cast_fp16")];
            string var_2877_mode_0 = const()[name = string("op_2877_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 5120, 1, 256]> var_2877_cast_fp16 = gelu(mode = var_2877_mode_0, x = var_2875_cast_fp16_1)[name = string("op_2877_cast_fp16")];
            tensor<fp16, [1, 5120, 1, 256]> input_139_cast_fp16 = mul(x = var_2875_cast_fp16_0, y = var_2877_cast_fp16)[name = string("input_139_cast_fp16")];
            string var_2885_pad_type_0 = const()[name = string("op_2885_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_2885_strides_0 = const()[name = string("op_2885_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_2885_pad_0 = const()[name = string("op_2885_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_2885_dilations_0 = const()[name = string("op_2885_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_2885_groups_0 = const()[name = string("op_2885_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 5120, 1, 1]> up_blocks_0_attentions_1_transformer_blocks_0_ff_net_2_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_ff_net_2_weight_to_fp16"), val = tensor<fp16, [1280, 5120, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(151484608)))];
            tensor<fp16, [1280]> up_blocks_0_attentions_1_transformer_blocks_0_ff_net_2_bias_to_fp16 = const()[name = string("up_blocks_0_attentions_1_transformer_blocks_0_ff_net_2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(164591872)))];
            tensor<fp16, [1, 1280, 1, 256]> var_2885_cast_fp16 = conv(bias = up_blocks_0_attentions_1_transformer_blocks_0_ff_net_2_bias_to_fp16, dilations = var_2885_dilations_0, groups = var_2885_groups_0, pad = var_2885_pad_0, pad_type = var_2885_pad_type_0, strides = var_2885_strides_0, weight = up_blocks_0_attentions_1_transformer_blocks_0_ff_net_2_weight_to_fp16, x = input_139_cast_fp16)[name = string("op_2885_cast_fp16")];
            tensor<fp16, [1, 1280, 1, 256]> hidden_states_91_cast_fp16 = add(x = var_2885_cast_fp16, y = inputs_29_cast_fp16)[name = string("hidden_states_91_cast_fp16")];
            tensor<int32, [4]> var_2887 = const()[name = string("op_2887"), val = tensor<int32, [4]>([1, 1280, 16, 16])];
            tensor<fp16, [1, 1280, 16, 16]> input_141_cast_fp16 = reshape(shape = var_2887, x = hidden_states_91_cast_fp16)[name = string("input_141_cast_fp16")];
            string hidden_states_93_pad_type_0 = const()[name = string("hidden_states_93_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> hidden_states_93_strides_0 = const()[name = string("hidden_states_93_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> hidden_states_93_pad_0 = const()[name = string("hidden_states_93_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> hidden_states_93_dilations_0 = const()[name = string("hidden_states_93_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_93_groups_0 = const()[name = string("hidden_states_93_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1280, 1, 1]> up_blocks_0_attentions_1_proj_out_weight_to_fp16 = const()[name = string("up_blocks_0_attentions_1_proj_out_weight_to_fp16"), val = tensor<fp16, [1280, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(164594496)))];
            tensor<fp16, [1280]> up_blocks_0_attentions_1_proj_out_bias_to_fp16 = const()[name = string("up_blocks_0_attentions_1_proj_out_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(167871360)))];
            tensor<fp16, [1, 1280, 16, 16]> hidden_states_93_cast_fp16 = conv(bias = up_blocks_0_attentions_1_proj_out_bias_to_fp16, dilations = hidden_states_93_dilations_0, groups = hidden_states_93_groups_0, pad = hidden_states_93_pad_0, pad_type = hidden_states_93_pad_type_0, strides = hidden_states_93_strides_0, weight = up_blocks_0_attentions_1_proj_out_weight_to_fp16, x = input_141_cast_fp16)[name = string("hidden_states_93_cast_fp16")];
            tensor<fp16, [1, 1280, 16, 16]> input_143_cast_fp16 = add(x = hidden_states_93_cast_fp16, y = hidden_states_81_cast_fp16)[name = string("input_143_cast_fp16")];
            fp32 input_145_scale_factor_height_0 = const()[name = string("input_145_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 input_145_scale_factor_width_0 = const()[name = string("input_145_scale_factor_width_0"), val = fp32(0x1p+1)];
            tensor<fp16, [1, 1280, 32, 32]> input_145_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = input_145_scale_factor_height_0, scale_factor_width = input_145_scale_factor_width_0, x = input_143_cast_fp16)[name = string("input_145_cast_fp16")];
            string hidden_states_95_pad_type_0 = const()[name = string("hidden_states_95_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> hidden_states_95_pad_0 = const()[name = string("hidden_states_95_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> hidden_states_95_strides_0 = const()[name = string("hidden_states_95_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> hidden_states_95_dilations_0 = const()[name = string("hidden_states_95_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_95_groups_0 = const()[name = string("hidden_states_95_groups_0"), val = int32(1)];
            tensor<fp16, [1280, 1280, 3, 3]> up_blocks_0_upsamplers_0_conv_weight_to_fp16 = const()[name = string("up_blocks_0_upsamplers_0_conv_weight_to_fp16"), val = tensor<fp16, [1280, 1280, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(167873984)))];
            tensor<fp16, [1280]> up_blocks_0_upsamplers_0_conv_bias_to_fp16 = const()[name = string("up_blocks_0_upsamplers_0_conv_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(197365248)))];
            tensor<fp16, [1, 1280, 32, 32]> hidden_states_95_cast_fp16 = conv(bias = up_blocks_0_upsamplers_0_conv_bias_to_fp16, dilations = hidden_states_95_dilations_0, groups = hidden_states_95_groups_0, pad = hidden_states_95_pad_0, pad_type = hidden_states_95_pad_type_0, strides = hidden_states_95_strides_0, weight = up_blocks_0_upsamplers_0_conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("hidden_states_95_cast_fp16")];
            int32 var_2929 = const()[name = string("op_2929"), val = int32(1)];
            bool input_147_interleave_0 = const()[name = string("input_147_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 640, 32, 32]> cast_6 = cast(dtype = cast_6_dtype_0, x = input_63_cast_fp16)[name = string("cast_5")];
            tensor<fp16, [1, 1920, 32, 32]> input_147_cast_fp16 = concat(axis = var_2929, interleave = input_147_interleave_0, values = (hidden_states_95_cast_fp16, cast_6))[name = string("input_147_cast_fp16")];
            tensor<int32, [5]> reshape_60_shape_0 = const()[name = string("reshape_60_shape_0"), val = tensor<int32, [5]>([1, 32, 60, 32, 32])];
            tensor<fp16, [1, 32, 60, 32, 32]> reshape_60_cast_fp16 = reshape(shape = reshape_60_shape_0, x = input_147_cast_fp16)[name = string("reshape_60_cast_fp16")];
            tensor<int32, [3]> reduce_mean_45_axes_0 = const()[name = string("reduce_mean_45_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_45_keep_dims_0 = const()[name = string("reduce_mean_45_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_45_cast_fp16 = reduce_mean(axes = reduce_mean_45_axes_0, keep_dims = reduce_mean_45_keep_dims_0, x = reshape_60_cast_fp16)[name = string("reduce_mean_45_cast_fp16")];
            tensor<fp16, [1, 32, 60, 32, 32]> sub_30_cast_fp16 = sub(x = reshape_60_cast_fp16, y = reduce_mean_45_cast_fp16)[name = string("sub_30_cast_fp16")];
            tensor<fp16, [1, 32, 60, 32, 32]> square_15_cast_fp16 = square(x = sub_30_cast_fp16)[name = string("square_15_cast_fp16")];
            tensor<int32, [3]> reduce_mean_47_axes_0 = const()[name = string("reduce_mean_47_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_47_keep_dims_0 = const()[name = string("reduce_mean_47_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_47_cast_fp16 = reduce_mean(axes = reduce_mean_47_axes_0, keep_dims = reduce_mean_47_keep_dims_0, x = square_15_cast_fp16)[name = string("reduce_mean_47_cast_fp16")];
            fp16 add_30_y_0_to_fp16 = const()[name = string("add_30_y_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_30_cast_fp16 = add(x = reduce_mean_47_cast_fp16, y = add_30_y_0_to_fp16)[name = string("add_30_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_15_cast_fp16 = sqrt(x = add_30_cast_fp16)[name = string("sqrt_15_cast_fp16")];
            tensor<fp16, [1, 32, 60, 32, 32]> real_div_15_cast_fp16 = real_div(x = sub_30_cast_fp16, y = sqrt_15_cast_fp16)[name = string("real_div_15_cast_fp16")];
            tensor<int32, [4]> reshape_61_shape_0 = const()[name = string("reshape_61_shape_0"), val = tensor<int32, [4]>([1, 1920, 32, 32])];
            tensor<fp16, [1, 1920, 32, 32]> reshape_61_cast_fp16 = reshape(shape = reshape_61_shape_0, x = real_div_15_cast_fp16)[name = string("reshape_61_cast_fp16")];
            tensor<fp16, [1920]> add_31_gamma_0_to_fp16 = const()[name = string("add_31_gamma_0_to_fp16"), val = tensor<fp16, [1920]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(197367872)))];
            tensor<fp16, [1920]> add_31_beta_0_to_fp16 = const()[name = string("add_31_beta_0_to_fp16"), val = tensor<fp16, [1920]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(197371776)))];
            fp16 add_31_epsilon_0_to_fp16 = const()[name = string("add_31_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 1920, 32, 32]> add_31_cast_fp16 = batch_norm(beta = add_31_beta_0_to_fp16, epsilon = add_31_epsilon_0_to_fp16, gamma = add_31_gamma_0_to_fp16, mean = add_25_mean_0_to_fp16, variance = add_25_variance_0_to_fp16, x = reshape_61_cast_fp16)[name = string("add_31_cast_fp16")];
            tensor<fp16, [1, 1920, 32, 32]> input_151_cast_fp16 = silu(x = add_31_cast_fp16)[name = string("input_151_cast_fp16")];
            string hidden_states_97_pad_type_0 = const()[name = string("hidden_states_97_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> hidden_states_97_pad_0 = const()[name = string("hidden_states_97_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> hidden_states_97_strides_0 = const()[name = string("hidden_states_97_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> hidden_states_97_dilations_0 = const()[name = string("hidden_states_97_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_97_groups_0 = const()[name = string("hidden_states_97_groups_0"), val = int32(1)];
            tensor<fp16, [640, 1920, 3, 3]> up_blocks_1_resnets_0_conv1_weight_to_fp16 = const()[name = string("up_blocks_1_resnets_0_conv1_weight_to_fp16"), val = tensor<fp16, [640, 1920, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(197375680)))];
            tensor<fp16, [640]> up_blocks_1_resnets_0_conv1_bias_to_fp16 = const()[name = string("up_blocks_1_resnets_0_conv1_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(219494144)))];
            tensor<fp16, [1, 640, 32, 32]> hidden_states_97_cast_fp16 = conv(bias = up_blocks_1_resnets_0_conv1_bias_to_fp16, dilations = hidden_states_97_dilations_0, groups = hidden_states_97_groups_0, pad = hidden_states_97_pad_0, pad_type = hidden_states_97_pad_type_0, strides = hidden_states_97_strides_0, weight = up_blocks_1_resnets_0_conv1_weight_to_fp16, x = input_151_cast_fp16)[name = string("hidden_states_97_cast_fp16")];
            string temb_11_pad_type_0 = const()[name = string("temb_11_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> temb_11_strides_0 = const()[name = string("temb_11_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> temb_11_pad_0 = const()[name = string("temb_11_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> temb_11_dilations_0 = const()[name = string("temb_11_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 temb_11_groups_0 = const()[name = string("temb_11_groups_0"), val = int32(1)];
            tensor<fp16, [640, 1280, 1, 1]> up_blocks_1_resnets_0_time_emb_proj_weight_to_fp16 = const()[name = string("up_blocks_1_resnets_0_time_emb_proj_weight_to_fp16"), val = tensor<fp16, [640, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(219495488)))];
            tensor<fp16, [640]> up_blocks_1_resnets_0_time_emb_proj_bias_to_fp16 = const()[name = string("up_blocks_1_resnets_0_time_emb_proj_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(221133952)))];
            tensor<fp16, [1, 640, 1, 1]> temb_11_cast_fp16 = conv(bias = up_blocks_1_resnets_0_time_emb_proj_bias_to_fp16, dilations = temb_11_dilations_0, groups = temb_11_groups_0, pad = temb_11_pad_0, pad_type = temb_11_pad_type_0, strides = temb_11_strides_0, weight = up_blocks_1_resnets_0_time_emb_proj_weight_to_fp16, x = cast_7)[name = string("temb_11_cast_fp16")];
            tensor<fp16, [1, 640, 32, 32]> input_155_cast_fp16 = add(x = hidden_states_97_cast_fp16, y = temb_11_cast_fp16)[name = string("input_155_cast_fp16")];
            tensor<int32, [5]> reshape_64_shape_0 = const()[name = string("reshape_64_shape_0"), val = tensor<int32, [5]>([1, 32, 20, 32, 32])];
            tensor<fp16, [1, 32, 20, 32, 32]> reshape_64_cast_fp16 = reshape(shape = reshape_64_shape_0, x = input_155_cast_fp16)[name = string("reshape_64_cast_fp16")];
            tensor<int32, [3]> reduce_mean_48_axes_0 = const()[name = string("reduce_mean_48_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_48_keep_dims_0 = const()[name = string("reduce_mean_48_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_48_cast_fp16 = reduce_mean(axes = reduce_mean_48_axes_0, keep_dims = reduce_mean_48_keep_dims_0, x = reshape_64_cast_fp16)[name = string("reduce_mean_48_cast_fp16")];
            tensor<fp16, [1, 32, 20, 32, 32]> sub_32_cast_fp16 = sub(x = reshape_64_cast_fp16, y = reduce_mean_48_cast_fp16)[name = string("sub_32_cast_fp16")];
            tensor<fp16, [1, 32, 20, 32, 32]> square_16_cast_fp16 = square(x = sub_32_cast_fp16)[name = string("square_16_cast_fp16")];
            tensor<int32, [3]> reduce_mean_50_axes_0 = const()[name = string("reduce_mean_50_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_50_keep_dims_0 = const()[name = string("reduce_mean_50_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_50_cast_fp16 = reduce_mean(axes = reduce_mean_50_axes_0, keep_dims = reduce_mean_50_keep_dims_0, x = square_16_cast_fp16)[name = string("reduce_mean_50_cast_fp16")];
            fp16 add_32_y_0_to_fp16 = const()[name = string("add_32_y_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_32_cast_fp16 = add(x = reduce_mean_50_cast_fp16, y = add_32_y_0_to_fp16)[name = string("add_32_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_16_cast_fp16 = sqrt(x = add_32_cast_fp16)[name = string("sqrt_16_cast_fp16")];
            tensor<fp16, [1, 32, 20, 32, 32]> real_div_16_cast_fp16 = real_div(x = sub_32_cast_fp16, y = sqrt_16_cast_fp16)[name = string("real_div_16_cast_fp16")];
            tensor<int32, [4]> reshape_65_shape_0 = const()[name = string("reshape_65_shape_0"), val = tensor<int32, [4]>([1, 640, 32, 32])];
            tensor<fp16, [1, 640, 32, 32]> reshape_65_cast_fp16 = reshape(shape = reshape_65_shape_0, x = real_div_16_cast_fp16)[name = string("reshape_65_cast_fp16")];
            tensor<fp16, [640]> add_33_gamma_0_to_fp16 = const()[name = string("add_33_gamma_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(221135296)))];
            tensor<fp16, [640]> add_33_beta_0_to_fp16 = const()[name = string("add_33_beta_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(221136640)))];
            fp16 add_33_epsilon_0_to_fp16 = const()[name = string("add_33_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 640, 32, 32]> add_33_cast_fp16 = batch_norm(beta = add_33_beta_0_to_fp16, epsilon = add_33_epsilon_0_to_fp16, gamma = add_33_gamma_0_to_fp16, mean = add_9_mean_0_to_fp16, variance = add_9_variance_0_to_fp16, x = reshape_65_cast_fp16)[name = string("add_33_cast_fp16")];
            tensor<fp16, [1, 640, 32, 32]> input_159_cast_fp16 = silu(x = add_33_cast_fp16)[name = string("input_159_cast_fp16")];
            string hidden_states_99_pad_type_0 = const()[name = string("hidden_states_99_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> hidden_states_99_pad_0 = const()[name = string("hidden_states_99_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> hidden_states_99_strides_0 = const()[name = string("hidden_states_99_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> hidden_states_99_dilations_0 = const()[name = string("hidden_states_99_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_99_groups_0 = const()[name = string("hidden_states_99_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 3, 3]> up_blocks_1_resnets_0_conv2_weight_to_fp16 = const()[name = string("up_blocks_1_resnets_0_conv2_weight_to_fp16"), val = tensor<fp16, [640, 640, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(221137984)))];
            tensor<fp16, [640]> up_blocks_1_resnets_0_conv2_bias_to_fp16 = const()[name = string("up_blocks_1_resnets_0_conv2_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(228510848)))];
            tensor<fp16, [1, 640, 32, 32]> hidden_states_99_cast_fp16 = conv(bias = up_blocks_1_resnets_0_conv2_bias_to_fp16, dilations = hidden_states_99_dilations_0, groups = hidden_states_99_groups_0, pad = hidden_states_99_pad_0, pad_type = hidden_states_99_pad_type_0, strides = hidden_states_99_strides_0, weight = up_blocks_1_resnets_0_conv2_weight_to_fp16, x = input_159_cast_fp16)[name = string("hidden_states_99_cast_fp16")];
            string x_9_pad_type_0 = const()[name = string("x_9_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_9_strides_0 = const()[name = string("x_9_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_9_pad_0 = const()[name = string("x_9_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_9_dilations_0 = const()[name = string("x_9_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_9_groups_0 = const()[name = string("x_9_groups_0"), val = int32(1)];
            tensor<fp16, [640, 1920, 1, 1]> up_blocks_1_resnets_0_conv_shortcut_weight_to_fp16 = const()[name = string("up_blocks_1_resnets_0_conv_shortcut_weight_to_fp16"), val = tensor<fp16, [640, 1920, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(228512192)))];
            tensor<fp16, [640]> up_blocks_1_resnets_0_conv_shortcut_bias_to_fp16 = const()[name = string("up_blocks_1_resnets_0_conv_shortcut_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(230969856)))];
            tensor<fp16, [1, 640, 32, 32]> x_9_cast_fp16 = conv(bias = up_blocks_1_resnets_0_conv_shortcut_bias_to_fp16, dilations = x_9_dilations_0, groups = x_9_groups_0, pad = x_9_pad_0, pad_type = x_9_pad_type_0, strides = x_9_strides_0, weight = up_blocks_1_resnets_0_conv_shortcut_weight_to_fp16, x = input_147_cast_fp16)[name = string("x_9_cast_fp16")];
            tensor<fp16, [1, 640, 32, 32]> hidden_states_101_cast_fp16 = add(x = x_9_cast_fp16, y = hidden_states_99_cast_fp16)[name = string("hidden_states_101_cast_fp16")];
            tensor<int32, [5]> reshape_68_shape_0 = const()[name = string("reshape_68_shape_0"), val = tensor<int32, [5]>([1, 32, 20, 32, 32])];
            tensor<fp16, [1, 32, 20, 32, 32]> reshape_68_cast_fp16 = reshape(shape = reshape_68_shape_0, x = hidden_states_101_cast_fp16)[name = string("reshape_68_cast_fp16")];
            tensor<int32, [3]> reduce_mean_51_axes_0 = const()[name = string("reduce_mean_51_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_51_keep_dims_0 = const()[name = string("reduce_mean_51_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_51_cast_fp16 = reduce_mean(axes = reduce_mean_51_axes_0, keep_dims = reduce_mean_51_keep_dims_0, x = reshape_68_cast_fp16)[name = string("reduce_mean_51_cast_fp16")];
            tensor<fp16, [1, 32, 20, 32, 32]> sub_34_cast_fp16 = sub(x = reshape_68_cast_fp16, y = reduce_mean_51_cast_fp16)[name = string("sub_34_cast_fp16")];
            tensor<fp16, [1, 32, 20, 32, 32]> square_17_cast_fp16 = square(x = sub_34_cast_fp16)[name = string("square_17_cast_fp16")];
            tensor<int32, [3]> reduce_mean_53_axes_0 = const()[name = string("reduce_mean_53_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_53_keep_dims_0 = const()[name = string("reduce_mean_53_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_53_cast_fp16 = reduce_mean(axes = reduce_mean_53_axes_0, keep_dims = reduce_mean_53_keep_dims_0, x = square_17_cast_fp16)[name = string("reduce_mean_53_cast_fp16")];
            fp16 add_34_y_0_to_fp16 = const()[name = string("add_34_y_0_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_34_cast_fp16 = add(x = reduce_mean_53_cast_fp16, y = add_34_y_0_to_fp16)[name = string("add_34_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_17_cast_fp16 = sqrt(x = add_34_cast_fp16)[name = string("sqrt_17_cast_fp16")];
            tensor<fp16, [1, 32, 20, 32, 32]> real_div_17_cast_fp16 = real_div(x = sub_34_cast_fp16, y = sqrt_17_cast_fp16)[name = string("real_div_17_cast_fp16")];
            tensor<int32, [4]> reshape_69_shape_0 = const()[name = string("reshape_69_shape_0"), val = tensor<int32, [4]>([1, 640, 32, 32])];
            tensor<fp16, [1, 640, 32, 32]> reshape_69_cast_fp16 = reshape(shape = reshape_69_shape_0, x = real_div_17_cast_fp16)[name = string("reshape_69_cast_fp16")];
            tensor<fp16, [640]> add_35_gamma_0_to_fp16 = const()[name = string("add_35_gamma_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(230971200)))];
            tensor<fp16, [640]> add_35_beta_0_to_fp16 = const()[name = string("add_35_beta_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(230972544)))];
            fp16 add_35_epsilon_0_to_fp16 = const()[name = string("add_35_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 640, 32, 32]> add_35_cast_fp16 = batch_norm(beta = add_35_beta_0_to_fp16, epsilon = add_35_epsilon_0_to_fp16, gamma = add_35_gamma_0_to_fp16, mean = add_9_mean_0_to_fp16, variance = add_9_variance_0_to_fp16, x = reshape_69_cast_fp16)[name = string("add_35_cast_fp16")];
            string hidden_states_103_pad_type_0 = const()[name = string("hidden_states_103_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> hidden_states_103_strides_0 = const()[name = string("hidden_states_103_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> hidden_states_103_pad_0 = const()[name = string("hidden_states_103_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> hidden_states_103_dilations_0 = const()[name = string("hidden_states_103_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_103_groups_0 = const()[name = string("hidden_states_103_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_0_proj_in_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_0_proj_in_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(230973888)))];
            tensor<fp16, [640]> up_blocks_1_attentions_0_proj_in_bias_to_fp16 = const()[name = string("up_blocks_1_attentions_0_proj_in_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(231793152)))];
            tensor<fp16, [1, 640, 32, 32]> hidden_states_103_cast_fp16 = conv(bias = up_blocks_1_attentions_0_proj_in_bias_to_fp16, dilations = hidden_states_103_dilations_0, groups = hidden_states_103_groups_0, pad = hidden_states_103_pad_0, pad_type = hidden_states_103_pad_type_0, strides = hidden_states_103_strides_0, weight = up_blocks_1_attentions_0_proj_in_weight_to_fp16, x = add_35_cast_fp16)[name = string("hidden_states_103_cast_fp16")];
            tensor<int32, [4]> var_3010 = const()[name = string("op_3010"), val = tensor<int32, [4]>([1, 640, 1, 1024])];
            tensor<fp16, [1, 640, 1, 1024]> inputs_31_cast_fp16 = reshape(shape = var_3010, x = hidden_states_103_cast_fp16)[name = string("inputs_31_cast_fp16")];
            tensor<int32, [1]> hidden_states_105_axes_0 = const()[name = string("hidden_states_105_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [640]> hidden_states_105_gamma_0_to_fp16 = const()[name = string("hidden_states_105_gamma_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(231794496)))];
            tensor<fp16, [640]> hidden_states_105_beta_0_to_fp16 = const()[name = string("hidden_states_105_beta_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(231795840)))];
            fp16 var_3026_to_fp16 = const()[name = string("op_3026_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 640, 1, 1024]> hidden_states_105_cast_fp16 = layer_norm(axes = hidden_states_105_axes_0, beta = hidden_states_105_beta_0_to_fp16, epsilon = var_3026_to_fp16, gamma = hidden_states_105_gamma_0_to_fp16, x = inputs_31_cast_fp16)[name = string("hidden_states_105_cast_fp16")];
            string q_21_pad_type_0 = const()[name = string("q_21_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> q_21_strides_0 = const()[name = string("q_21_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> q_21_pad_0 = const()[name = string("q_21_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> q_21_dilations_0 = const()[name = string("q_21_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 q_21_groups_0 = const()[name = string("q_21_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_q_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_q_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(231797184)))];
            tensor<fp16, [1, 640, 1, 1024]> q_21_cast_fp16 = conv(dilations = q_21_dilations_0, groups = q_21_groups_0, pad = q_21_pad_0, pad_type = q_21_pad_type_0, strides = q_21_strides_0, weight = up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_q_weight_to_fp16, x = hidden_states_105_cast_fp16)[name = string("q_21_cast_fp16")];
            string k_41_pad_type_0 = const()[name = string("k_41_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> k_41_strides_0 = const()[name = string("k_41_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> k_41_pad_0 = const()[name = string("k_41_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> k_41_dilations_0 = const()[name = string("k_41_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 k_41_groups_0 = const()[name = string("k_41_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_k_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_k_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(232616448)))];
            tensor<fp16, [1, 640, 1, 1024]> k_41_cast_fp16 = conv(dilations = k_41_dilations_0, groups = k_41_groups_0, pad = k_41_pad_0, pad_type = k_41_pad_type_0, strides = k_41_strides_0, weight = up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_k_weight_to_fp16, x = hidden_states_105_cast_fp16)[name = string("k_41_cast_fp16")];
            string v_21_pad_type_0 = const()[name = string("v_21_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> v_21_strides_0 = const()[name = string("v_21_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> v_21_pad_0 = const()[name = string("v_21_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> v_21_dilations_0 = const()[name = string("v_21_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 v_21_groups_0 = const()[name = string("v_21_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_v_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_v_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(233435712)))];
            tensor<fp16, [1, 640, 1, 1024]> v_21_cast_fp16 = conv(dilations = v_21_dilations_0, groups = v_21_groups_0, pad = v_21_pad_0, pad_type = v_21_pad_type_0, strides = v_21_strides_0, weight = up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_v_weight_to_fp16, x = hidden_states_105_cast_fp16)[name = string("v_21_cast_fp16")];
            tensor<int32, [4]> var_3059_begin_0 = const()[name = string("op_3059_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_3059_end_0 = const()[name = string("op_3059_end_0"), val = tensor<int32, [4]>([1, 80, 1, 1024])];
            tensor<bool, [4]> var_3059_end_mask_0 = const()[name = string("op_3059_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3059_cast_fp16 = slice_by_index(begin = var_3059_begin_0, end = var_3059_end_0, end_mask = var_3059_end_mask_0, x = q_21_cast_fp16)[name = string("op_3059_cast_fp16")];
            tensor<int32, [4]> var_3063_begin_0 = const()[name = string("op_3063_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_3063_end_0 = const()[name = string("op_3063_end_0"), val = tensor<int32, [4]>([1, 160, 1, 1024])];
            tensor<bool, [4]> var_3063_end_mask_0 = const()[name = string("op_3063_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3063_cast_fp16 = slice_by_index(begin = var_3063_begin_0, end = var_3063_end_0, end_mask = var_3063_end_mask_0, x = q_21_cast_fp16)[name = string("op_3063_cast_fp16")];
            tensor<int32, [4]> var_3067_begin_0 = const()[name = string("op_3067_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_3067_end_0 = const()[name = string("op_3067_end_0"), val = tensor<int32, [4]>([1, 240, 1, 1024])];
            tensor<bool, [4]> var_3067_end_mask_0 = const()[name = string("op_3067_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3067_cast_fp16 = slice_by_index(begin = var_3067_begin_0, end = var_3067_end_0, end_mask = var_3067_end_mask_0, x = q_21_cast_fp16)[name = string("op_3067_cast_fp16")];
            tensor<int32, [4]> var_3071_begin_0 = const()[name = string("op_3071_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_3071_end_0 = const()[name = string("op_3071_end_0"), val = tensor<int32, [4]>([1, 320, 1, 1024])];
            tensor<bool, [4]> var_3071_end_mask_0 = const()[name = string("op_3071_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3071_cast_fp16 = slice_by_index(begin = var_3071_begin_0, end = var_3071_end_0, end_mask = var_3071_end_mask_0, x = q_21_cast_fp16)[name = string("op_3071_cast_fp16")];
            tensor<int32, [4]> var_3075_begin_0 = const()[name = string("op_3075_begin_0"), val = tensor<int32, [4]>([0, 320, 0, 0])];
            tensor<int32, [4]> var_3075_end_0 = const()[name = string("op_3075_end_0"), val = tensor<int32, [4]>([1, 400, 1, 1024])];
            tensor<bool, [4]> var_3075_end_mask_0 = const()[name = string("op_3075_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3075_cast_fp16 = slice_by_index(begin = var_3075_begin_0, end = var_3075_end_0, end_mask = var_3075_end_mask_0, x = q_21_cast_fp16)[name = string("op_3075_cast_fp16")];
            tensor<int32, [4]> var_3079_begin_0 = const()[name = string("op_3079_begin_0"), val = tensor<int32, [4]>([0, 400, 0, 0])];
            tensor<int32, [4]> var_3079_end_0 = const()[name = string("op_3079_end_0"), val = tensor<int32, [4]>([1, 480, 1, 1024])];
            tensor<bool, [4]> var_3079_end_mask_0 = const()[name = string("op_3079_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3079_cast_fp16 = slice_by_index(begin = var_3079_begin_0, end = var_3079_end_0, end_mask = var_3079_end_mask_0, x = q_21_cast_fp16)[name = string("op_3079_cast_fp16")];
            tensor<int32, [4]> var_3083_begin_0 = const()[name = string("op_3083_begin_0"), val = tensor<int32, [4]>([0, 480, 0, 0])];
            tensor<int32, [4]> var_3083_end_0 = const()[name = string("op_3083_end_0"), val = tensor<int32, [4]>([1, 560, 1, 1024])];
            tensor<bool, [4]> var_3083_end_mask_0 = const()[name = string("op_3083_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3083_cast_fp16 = slice_by_index(begin = var_3083_begin_0, end = var_3083_end_0, end_mask = var_3083_end_mask_0, x = q_21_cast_fp16)[name = string("op_3083_cast_fp16")];
            tensor<int32, [4]> var_3087_begin_0 = const()[name = string("op_3087_begin_0"), val = tensor<int32, [4]>([0, 560, 0, 0])];
            tensor<int32, [4]> var_3087_end_0 = const()[name = string("op_3087_end_0"), val = tensor<int32, [4]>([1, 1, 1, 1024])];
            tensor<bool, [4]> var_3087_end_mask_0 = const()[name = string("op_3087_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3087_cast_fp16 = slice_by_index(begin = var_3087_begin_0, end = var_3087_end_0, end_mask = var_3087_end_mask_0, x = q_21_cast_fp16)[name = string("op_3087_cast_fp16")];
            tensor<int32, [4]> k_43_perm_0 = const()[name = string("k_43_perm_0"), val = tensor<int32, [4]>([0, 3, 2, 1])];
            tensor<int32, [4]> var_3094_begin_0 = const()[name = string("op_3094_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_3094_end_0 = const()[name = string("op_3094_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 80])];
            tensor<bool, [4]> var_3094_end_mask_0 = const()[name = string("op_3094_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 640]> k_43_cast_fp16 = transpose(perm = k_43_perm_0, x = k_41_cast_fp16)[name = string("transpose_7")];
            tensor<fp16, [1, 1024, 1, 80]> var_3094_cast_fp16 = slice_by_index(begin = var_3094_begin_0, end = var_3094_end_0, end_mask = var_3094_end_mask_0, x = k_43_cast_fp16)[name = string("op_3094_cast_fp16")];
            tensor<int32, [4]> var_3098_begin_0 = const()[name = string("op_3098_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 80])];
            tensor<int32, [4]> var_3098_end_0 = const()[name = string("op_3098_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 160])];
            tensor<bool, [4]> var_3098_end_mask_0 = const()[name = string("op_3098_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 80]> var_3098_cast_fp16 = slice_by_index(begin = var_3098_begin_0, end = var_3098_end_0, end_mask = var_3098_end_mask_0, x = k_43_cast_fp16)[name = string("op_3098_cast_fp16")];
            tensor<int32, [4]> var_3102_begin_0 = const()[name = string("op_3102_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 160])];
            tensor<int32, [4]> var_3102_end_0 = const()[name = string("op_3102_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 240])];
            tensor<bool, [4]> var_3102_end_mask_0 = const()[name = string("op_3102_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 80]> var_3102_cast_fp16 = slice_by_index(begin = var_3102_begin_0, end = var_3102_end_0, end_mask = var_3102_end_mask_0, x = k_43_cast_fp16)[name = string("op_3102_cast_fp16")];
            tensor<int32, [4]> var_3106_begin_0 = const()[name = string("op_3106_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 240])];
            tensor<int32, [4]> var_3106_end_0 = const()[name = string("op_3106_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 320])];
            tensor<bool, [4]> var_3106_end_mask_0 = const()[name = string("op_3106_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 80]> var_3106_cast_fp16 = slice_by_index(begin = var_3106_begin_0, end = var_3106_end_0, end_mask = var_3106_end_mask_0, x = k_43_cast_fp16)[name = string("op_3106_cast_fp16")];
            tensor<int32, [4]> var_3110_begin_0 = const()[name = string("op_3110_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 320])];
            tensor<int32, [4]> var_3110_end_0 = const()[name = string("op_3110_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 400])];
            tensor<bool, [4]> var_3110_end_mask_0 = const()[name = string("op_3110_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 80]> var_3110_cast_fp16 = slice_by_index(begin = var_3110_begin_0, end = var_3110_end_0, end_mask = var_3110_end_mask_0, x = k_43_cast_fp16)[name = string("op_3110_cast_fp16")];
            tensor<int32, [4]> var_3114_begin_0 = const()[name = string("op_3114_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 400])];
            tensor<int32, [4]> var_3114_end_0 = const()[name = string("op_3114_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 480])];
            tensor<bool, [4]> var_3114_end_mask_0 = const()[name = string("op_3114_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 80]> var_3114_cast_fp16 = slice_by_index(begin = var_3114_begin_0, end = var_3114_end_0, end_mask = var_3114_end_mask_0, x = k_43_cast_fp16)[name = string("op_3114_cast_fp16")];
            tensor<int32, [4]> var_3118_begin_0 = const()[name = string("op_3118_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 480])];
            tensor<int32, [4]> var_3118_end_0 = const()[name = string("op_3118_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 560])];
            tensor<bool, [4]> var_3118_end_mask_0 = const()[name = string("op_3118_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 80]> var_3118_cast_fp16 = slice_by_index(begin = var_3118_begin_0, end = var_3118_end_0, end_mask = var_3118_end_mask_0, x = k_43_cast_fp16)[name = string("op_3118_cast_fp16")];
            tensor<int32, [4]> var_3122_begin_0 = const()[name = string("op_3122_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 560])];
            tensor<int32, [4]> var_3122_end_0 = const()[name = string("op_3122_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 1])];
            tensor<bool, [4]> var_3122_end_mask_0 = const()[name = string("op_3122_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 1024, 1, 80]> var_3122_cast_fp16 = slice_by_index(begin = var_3122_begin_0, end = var_3122_end_0, end_mask = var_3122_end_mask_0, x = k_43_cast_fp16)[name = string("op_3122_cast_fp16")];
            tensor<int32, [4]> var_3124_begin_0 = const()[name = string("op_3124_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_3124_end_0 = const()[name = string("op_3124_end_0"), val = tensor<int32, [4]>([1, 80, 1, 1024])];
            tensor<bool, [4]> var_3124_end_mask_0 = const()[name = string("op_3124_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3124_cast_fp16 = slice_by_index(begin = var_3124_begin_0, end = var_3124_end_0, end_mask = var_3124_end_mask_0, x = v_21_cast_fp16)[name = string("op_3124_cast_fp16")];
            tensor<int32, [4]> var_3128_begin_0 = const()[name = string("op_3128_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_3128_end_0 = const()[name = string("op_3128_end_0"), val = tensor<int32, [4]>([1, 160, 1, 1024])];
            tensor<bool, [4]> var_3128_end_mask_0 = const()[name = string("op_3128_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3128_cast_fp16 = slice_by_index(begin = var_3128_begin_0, end = var_3128_end_0, end_mask = var_3128_end_mask_0, x = v_21_cast_fp16)[name = string("op_3128_cast_fp16")];
            tensor<int32, [4]> var_3132_begin_0 = const()[name = string("op_3132_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_3132_end_0 = const()[name = string("op_3132_end_0"), val = tensor<int32, [4]>([1, 240, 1, 1024])];
            tensor<bool, [4]> var_3132_end_mask_0 = const()[name = string("op_3132_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3132_cast_fp16 = slice_by_index(begin = var_3132_begin_0, end = var_3132_end_0, end_mask = var_3132_end_mask_0, x = v_21_cast_fp16)[name = string("op_3132_cast_fp16")];
            tensor<int32, [4]> var_3136_begin_0 = const()[name = string("op_3136_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_3136_end_0 = const()[name = string("op_3136_end_0"), val = tensor<int32, [4]>([1, 320, 1, 1024])];
            tensor<bool, [4]> var_3136_end_mask_0 = const()[name = string("op_3136_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3136_cast_fp16 = slice_by_index(begin = var_3136_begin_0, end = var_3136_end_0, end_mask = var_3136_end_mask_0, x = v_21_cast_fp16)[name = string("op_3136_cast_fp16")];
            tensor<int32, [4]> var_3140_begin_0 = const()[name = string("op_3140_begin_0"), val = tensor<int32, [4]>([0, 320, 0, 0])];
            tensor<int32, [4]> var_3140_end_0 = const()[name = string("op_3140_end_0"), val = tensor<int32, [4]>([1, 400, 1, 1024])];
            tensor<bool, [4]> var_3140_end_mask_0 = const()[name = string("op_3140_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3140_cast_fp16 = slice_by_index(begin = var_3140_begin_0, end = var_3140_end_0, end_mask = var_3140_end_mask_0, x = v_21_cast_fp16)[name = string("op_3140_cast_fp16")];
            tensor<int32, [4]> var_3144_begin_0 = const()[name = string("op_3144_begin_0"), val = tensor<int32, [4]>([0, 400, 0, 0])];
            tensor<int32, [4]> var_3144_end_0 = const()[name = string("op_3144_end_0"), val = tensor<int32, [4]>([1, 480, 1, 1024])];
            tensor<bool, [4]> var_3144_end_mask_0 = const()[name = string("op_3144_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3144_cast_fp16 = slice_by_index(begin = var_3144_begin_0, end = var_3144_end_0, end_mask = var_3144_end_mask_0, x = v_21_cast_fp16)[name = string("op_3144_cast_fp16")];
            tensor<int32, [4]> var_3148_begin_0 = const()[name = string("op_3148_begin_0"), val = tensor<int32, [4]>([0, 480, 0, 0])];
            tensor<int32, [4]> var_3148_end_0 = const()[name = string("op_3148_end_0"), val = tensor<int32, [4]>([1, 560, 1, 1024])];
            tensor<bool, [4]> var_3148_end_mask_0 = const()[name = string("op_3148_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3148_cast_fp16 = slice_by_index(begin = var_3148_begin_0, end = var_3148_end_0, end_mask = var_3148_end_mask_0, x = v_21_cast_fp16)[name = string("op_3148_cast_fp16")];
            tensor<int32, [4]> var_3152_begin_0 = const()[name = string("op_3152_begin_0"), val = tensor<int32, [4]>([0, 560, 0, 0])];
            tensor<int32, [4]> var_3152_end_0 = const()[name = string("op_3152_end_0"), val = tensor<int32, [4]>([1, 1, 1, 1024])];
            tensor<bool, [4]> var_3152_end_mask_0 = const()[name = string("op_3152_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3152_cast_fp16 = slice_by_index(begin = var_3152_begin_0, end = var_3152_end_0, end_mask = var_3152_end_mask_0, x = v_21_cast_fp16)[name = string("op_3152_cast_fp16")];
            string var_3156_equation_0 = const()[name = string("op_3156_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3156_cast_fp16 = einsum(equation = var_3156_equation_0, values = (var_3094_cast_fp16, var_3059_cast_fp16))[name = string("op_3156_cast_fp16")];
            fp16 var_3157_to_fp16 = const()[name = string("op_3157_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_161_cast_fp16 = mul(x = var_3156_cast_fp16, y = var_3157_to_fp16)[name = string("aw_161_cast_fp16")];
            string var_3160_equation_0 = const()[name = string("op_3160_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3160_cast_fp16 = einsum(equation = var_3160_equation_0, values = (var_3098_cast_fp16, var_3063_cast_fp16))[name = string("op_3160_cast_fp16")];
            fp16 var_3161_to_fp16 = const()[name = string("op_3161_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_163_cast_fp16 = mul(x = var_3160_cast_fp16, y = var_3161_to_fp16)[name = string("aw_163_cast_fp16")];
            string var_3164_equation_0 = const()[name = string("op_3164_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3164_cast_fp16 = einsum(equation = var_3164_equation_0, values = (var_3102_cast_fp16, var_3067_cast_fp16))[name = string("op_3164_cast_fp16")];
            fp16 var_3165_to_fp16 = const()[name = string("op_3165_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_165_cast_fp16 = mul(x = var_3164_cast_fp16, y = var_3165_to_fp16)[name = string("aw_165_cast_fp16")];
            string var_3168_equation_0 = const()[name = string("op_3168_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3168_cast_fp16 = einsum(equation = var_3168_equation_0, values = (var_3106_cast_fp16, var_3071_cast_fp16))[name = string("op_3168_cast_fp16")];
            fp16 var_3169_to_fp16 = const()[name = string("op_3169_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_167_cast_fp16 = mul(x = var_3168_cast_fp16, y = var_3169_to_fp16)[name = string("aw_167_cast_fp16")];
            string var_3172_equation_0 = const()[name = string("op_3172_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3172_cast_fp16 = einsum(equation = var_3172_equation_0, values = (var_3110_cast_fp16, var_3075_cast_fp16))[name = string("op_3172_cast_fp16")];
            fp16 var_3173_to_fp16 = const()[name = string("op_3173_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_169_cast_fp16 = mul(x = var_3172_cast_fp16, y = var_3173_to_fp16)[name = string("aw_169_cast_fp16")];
            string var_3176_equation_0 = const()[name = string("op_3176_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3176_cast_fp16 = einsum(equation = var_3176_equation_0, values = (var_3114_cast_fp16, var_3079_cast_fp16))[name = string("op_3176_cast_fp16")];
            fp16 var_3177_to_fp16 = const()[name = string("op_3177_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_171_cast_fp16 = mul(x = var_3176_cast_fp16, y = var_3177_to_fp16)[name = string("aw_171_cast_fp16")];
            string var_3180_equation_0 = const()[name = string("op_3180_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3180_cast_fp16 = einsum(equation = var_3180_equation_0, values = (var_3118_cast_fp16, var_3083_cast_fp16))[name = string("op_3180_cast_fp16")];
            fp16 var_3181_to_fp16 = const()[name = string("op_3181_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_173_cast_fp16 = mul(x = var_3180_cast_fp16, y = var_3181_to_fp16)[name = string("aw_173_cast_fp16")];
            string var_3184_equation_0 = const()[name = string("op_3184_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3184_cast_fp16 = einsum(equation = var_3184_equation_0, values = (var_3122_cast_fp16, var_3087_cast_fp16))[name = string("op_3184_cast_fp16")];
            fp16 var_3185_to_fp16 = const()[name = string("op_3185_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_175_cast_fp16 = mul(x = var_3184_cast_fp16, y = var_3185_to_fp16)[name = string("aw_175_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3187_cast_fp16 = softmax(axis = var_2929, x = aw_161_cast_fp16)[name = string("op_3187_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3188_cast_fp16 = softmax(axis = var_2929, x = aw_163_cast_fp16)[name = string("op_3188_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3189_cast_fp16 = softmax(axis = var_2929, x = aw_165_cast_fp16)[name = string("op_3189_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3190_cast_fp16 = softmax(axis = var_2929, x = aw_167_cast_fp16)[name = string("op_3190_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3191_cast_fp16 = softmax(axis = var_2929, x = aw_169_cast_fp16)[name = string("op_3191_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3192_cast_fp16 = softmax(axis = var_2929, x = aw_171_cast_fp16)[name = string("op_3192_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3193_cast_fp16 = softmax(axis = var_2929, x = aw_173_cast_fp16)[name = string("op_3193_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3194_cast_fp16 = softmax(axis = var_2929, x = aw_175_cast_fp16)[name = string("op_3194_cast_fp16")];
            string var_3196_equation_0 = const()[name = string("op_3196_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3196_cast_fp16 = einsum(equation = var_3196_equation_0, values = (var_3124_cast_fp16, var_3187_cast_fp16))[name = string("op_3196_cast_fp16")];
            string var_3198_equation_0 = const()[name = string("op_3198_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3198_cast_fp16 = einsum(equation = var_3198_equation_0, values = (var_3128_cast_fp16, var_3188_cast_fp16))[name = string("op_3198_cast_fp16")];
            string var_3200_equation_0 = const()[name = string("op_3200_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3200_cast_fp16 = einsum(equation = var_3200_equation_0, values = (var_3132_cast_fp16, var_3189_cast_fp16))[name = string("op_3200_cast_fp16")];
            string var_3202_equation_0 = const()[name = string("op_3202_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3202_cast_fp16 = einsum(equation = var_3202_equation_0, values = (var_3136_cast_fp16, var_3190_cast_fp16))[name = string("op_3202_cast_fp16")];
            string var_3204_equation_0 = const()[name = string("op_3204_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3204_cast_fp16 = einsum(equation = var_3204_equation_0, values = (var_3140_cast_fp16, var_3191_cast_fp16))[name = string("op_3204_cast_fp16")];
            string var_3206_equation_0 = const()[name = string("op_3206_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3206_cast_fp16 = einsum(equation = var_3206_equation_0, values = (var_3144_cast_fp16, var_3192_cast_fp16))[name = string("op_3206_cast_fp16")];
            string var_3208_equation_0 = const()[name = string("op_3208_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3208_cast_fp16 = einsum(equation = var_3208_equation_0, values = (var_3148_cast_fp16, var_3193_cast_fp16))[name = string("op_3208_cast_fp16")];
            string var_3210_equation_0 = const()[name = string("op_3210_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3210_cast_fp16 = einsum(equation = var_3210_equation_0, values = (var_3152_cast_fp16, var_3194_cast_fp16))[name = string("op_3210_cast_fp16")];
            bool input_163_interleave_0 = const()[name = string("input_163_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 640, 1, 1024]> input_163_cast_fp16 = concat(axis = var_2929, interleave = input_163_interleave_0, values = (var_3196_cast_fp16, var_3198_cast_fp16, var_3200_cast_fp16, var_3202_cast_fp16, var_3204_cast_fp16, var_3206_cast_fp16, var_3208_cast_fp16, var_3210_cast_fp16))[name = string("input_163_cast_fp16")];
            string var_3220_pad_type_0 = const()[name = string("op_3220_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_3220_strides_0 = const()[name = string("op_3220_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_3220_pad_0 = const()[name = string("op_3220_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_3220_dilations_0 = const()[name = string("op_3220_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3220_groups_0 = const()[name = string("op_3220_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_out_0_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_out_0_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(234254976)))];
            tensor<fp16, [640]> up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_out_0_bias_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_out_0_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(235074240)))];
            tensor<fp16, [1, 640, 1, 1024]> var_3220_cast_fp16 = conv(bias = up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_out_0_bias_to_fp16, dilations = var_3220_dilations_0, groups = var_3220_groups_0, pad = var_3220_pad_0, pad_type = var_3220_pad_type_0, strides = var_3220_strides_0, weight = up_blocks_1_attentions_0_transformer_blocks_0_attn1_to_out_0_weight_to_fp16, x = input_163_cast_fp16)[name = string("op_3220_cast_fp16")];
            tensor<fp16, [1, 640, 1, 1024]> inputs_33_cast_fp16 = add(x = var_3220_cast_fp16, y = inputs_31_cast_fp16)[name = string("inputs_33_cast_fp16")];
            tensor<int32, [1]> hidden_states_107_axes_0 = const()[name = string("hidden_states_107_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [640]> hidden_states_107_gamma_0_to_fp16 = const()[name = string("hidden_states_107_gamma_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(235075584)))];
            tensor<fp16, [640]> hidden_states_107_beta_0_to_fp16 = const()[name = string("hidden_states_107_beta_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(235076928)))];
            fp16 var_3230_to_fp16 = const()[name = string("op_3230_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 640, 1, 1024]> hidden_states_107_cast_fp16 = layer_norm(axes = hidden_states_107_axes_0, beta = hidden_states_107_beta_0_to_fp16, epsilon = var_3230_to_fp16, gamma = hidden_states_107_gamma_0_to_fp16, x = inputs_33_cast_fp16)[name = string("hidden_states_107_cast_fp16")];
            string q_23_pad_type_0 = const()[name = string("q_23_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> q_23_strides_0 = const()[name = string("q_23_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> q_23_pad_0 = const()[name = string("q_23_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> q_23_dilations_0 = const()[name = string("q_23_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 q_23_groups_0 = const()[name = string("q_23_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_q_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_q_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(235078272)))];
            tensor<fp16, [1, 640, 1, 1024]> q_23_cast_fp16 = conv(dilations = q_23_dilations_0, groups = q_23_groups_0, pad = q_23_pad_0, pad_type = q_23_pad_type_0, strides = q_23_strides_0, weight = up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_q_weight_to_fp16, x = hidden_states_107_cast_fp16)[name = string("q_23_cast_fp16")];
            string k_45_pad_type_0 = const()[name = string("k_45_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> k_45_strides_0 = const()[name = string("k_45_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> k_45_pad_0 = const()[name = string("k_45_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> k_45_dilations_0 = const()[name = string("k_45_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 k_45_groups_0 = const()[name = string("k_45_groups_0"), val = int32(1)];
            tensor<fp16, [640, 768, 1, 1]> up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_k_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_k_weight_to_fp16"), val = tensor<fp16, [640, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(235897536)))];
            tensor<fp16, [1, 640, 1, 77]> k_45_cast_fp16 = conv(dilations = k_45_dilations_0, groups = k_45_groups_0, pad = k_45_pad_0, pad_type = k_45_pad_type_0, strides = k_45_strides_0, weight = up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_k_weight_to_fp16, x = encoder_hidden_states)[name = string("k_45_cast_fp16")];
            string v_23_pad_type_0 = const()[name = string("v_23_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> v_23_strides_0 = const()[name = string("v_23_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> v_23_pad_0 = const()[name = string("v_23_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> v_23_dilations_0 = const()[name = string("v_23_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 v_23_groups_0 = const()[name = string("v_23_groups_0"), val = int32(1)];
            tensor<fp16, [640, 768, 1, 1]> up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_v_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_v_weight_to_fp16"), val = tensor<fp16, [640, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(236880640)))];
            tensor<fp16, [1, 640, 1, 77]> v_23_cast_fp16 = conv(dilations = v_23_dilations_0, groups = v_23_groups_0, pad = v_23_pad_0, pad_type = v_23_pad_type_0, strides = v_23_strides_0, weight = up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_v_weight_to_fp16, x = encoder_hidden_states)[name = string("v_23_cast_fp16")];
            tensor<int32, [4]> var_3263_begin_0 = const()[name = string("op_3263_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_3263_end_0 = const()[name = string("op_3263_end_0"), val = tensor<int32, [4]>([1, 80, 1, 1024])];
            tensor<bool, [4]> var_3263_end_mask_0 = const()[name = string("op_3263_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3263_cast_fp16 = slice_by_index(begin = var_3263_begin_0, end = var_3263_end_0, end_mask = var_3263_end_mask_0, x = q_23_cast_fp16)[name = string("op_3263_cast_fp16")];
            tensor<int32, [4]> var_3267_begin_0 = const()[name = string("op_3267_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_3267_end_0 = const()[name = string("op_3267_end_0"), val = tensor<int32, [4]>([1, 160, 1, 1024])];
            tensor<bool, [4]> var_3267_end_mask_0 = const()[name = string("op_3267_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3267_cast_fp16 = slice_by_index(begin = var_3267_begin_0, end = var_3267_end_0, end_mask = var_3267_end_mask_0, x = q_23_cast_fp16)[name = string("op_3267_cast_fp16")];
            tensor<int32, [4]> var_3271_begin_0 = const()[name = string("op_3271_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_3271_end_0 = const()[name = string("op_3271_end_0"), val = tensor<int32, [4]>([1, 240, 1, 1024])];
            tensor<bool, [4]> var_3271_end_mask_0 = const()[name = string("op_3271_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3271_cast_fp16 = slice_by_index(begin = var_3271_begin_0, end = var_3271_end_0, end_mask = var_3271_end_mask_0, x = q_23_cast_fp16)[name = string("op_3271_cast_fp16")];
            tensor<int32, [4]> var_3275_begin_0 = const()[name = string("op_3275_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_3275_end_0 = const()[name = string("op_3275_end_0"), val = tensor<int32, [4]>([1, 320, 1, 1024])];
            tensor<bool, [4]> var_3275_end_mask_0 = const()[name = string("op_3275_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3275_cast_fp16 = slice_by_index(begin = var_3275_begin_0, end = var_3275_end_0, end_mask = var_3275_end_mask_0, x = q_23_cast_fp16)[name = string("op_3275_cast_fp16")];
            tensor<int32, [4]> var_3279_begin_0 = const()[name = string("op_3279_begin_0"), val = tensor<int32, [4]>([0, 320, 0, 0])];
            tensor<int32, [4]> var_3279_end_0 = const()[name = string("op_3279_end_0"), val = tensor<int32, [4]>([1, 400, 1, 1024])];
            tensor<bool, [4]> var_3279_end_mask_0 = const()[name = string("op_3279_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3279_cast_fp16 = slice_by_index(begin = var_3279_begin_0, end = var_3279_end_0, end_mask = var_3279_end_mask_0, x = q_23_cast_fp16)[name = string("op_3279_cast_fp16")];
            tensor<int32, [4]> var_3283_begin_0 = const()[name = string("op_3283_begin_0"), val = tensor<int32, [4]>([0, 400, 0, 0])];
            tensor<int32, [4]> var_3283_end_0 = const()[name = string("op_3283_end_0"), val = tensor<int32, [4]>([1, 480, 1, 1024])];
            tensor<bool, [4]> var_3283_end_mask_0 = const()[name = string("op_3283_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3283_cast_fp16 = slice_by_index(begin = var_3283_begin_0, end = var_3283_end_0, end_mask = var_3283_end_mask_0, x = q_23_cast_fp16)[name = string("op_3283_cast_fp16")];
            tensor<int32, [4]> var_3287_begin_0 = const()[name = string("op_3287_begin_0"), val = tensor<int32, [4]>([0, 480, 0, 0])];
            tensor<int32, [4]> var_3287_end_0 = const()[name = string("op_3287_end_0"), val = tensor<int32, [4]>([1, 560, 1, 1024])];
            tensor<bool, [4]> var_3287_end_mask_0 = const()[name = string("op_3287_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3287_cast_fp16 = slice_by_index(begin = var_3287_begin_0, end = var_3287_end_0, end_mask = var_3287_end_mask_0, x = q_23_cast_fp16)[name = string("op_3287_cast_fp16")];
            tensor<int32, [4]> var_3291_begin_0 = const()[name = string("op_3291_begin_0"), val = tensor<int32, [4]>([0, 560, 0, 0])];
            tensor<int32, [4]> var_3291_end_0 = const()[name = string("op_3291_end_0"), val = tensor<int32, [4]>([1, 1, 1, 1024])];
            tensor<bool, [4]> var_3291_end_mask_0 = const()[name = string("op_3291_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3291_cast_fp16 = slice_by_index(begin = var_3291_begin_0, end = var_3291_end_0, end_mask = var_3291_end_mask_0, x = q_23_cast_fp16)[name = string("op_3291_cast_fp16")];
            tensor<int32, [4]> k_47_perm_0 = const()[name = string("k_47_perm_0"), val = tensor<int32, [4]>([0, 3, 2, 1])];
            tensor<int32, [4]> var_3298_begin_0 = const()[name = string("op_3298_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_3298_end_0 = const()[name = string("op_3298_end_0"), val = tensor<int32, [4]>([1, 77, 1, 80])];
            tensor<bool, [4]> var_3298_end_mask_0 = const()[name = string("op_3298_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 640]> k_47_cast_fp16 = transpose(perm = k_47_perm_0, x = k_45_cast_fp16)[name = string("transpose_6")];
            tensor<fp16, [1, 77, 1, 80]> var_3298_cast_fp16 = slice_by_index(begin = var_3298_begin_0, end = var_3298_end_0, end_mask = var_3298_end_mask_0, x = k_47_cast_fp16)[name = string("op_3298_cast_fp16")];
            tensor<int32, [4]> var_3302_begin_0 = const()[name = string("op_3302_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 80])];
            tensor<int32, [4]> var_3302_end_0 = const()[name = string("op_3302_end_0"), val = tensor<int32, [4]>([1, 77, 1, 160])];
            tensor<bool, [4]> var_3302_end_mask_0 = const()[name = string("op_3302_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 80]> var_3302_cast_fp16 = slice_by_index(begin = var_3302_begin_0, end = var_3302_end_0, end_mask = var_3302_end_mask_0, x = k_47_cast_fp16)[name = string("op_3302_cast_fp16")];
            tensor<int32, [4]> var_3306_begin_0 = const()[name = string("op_3306_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 160])];
            tensor<int32, [4]> var_3306_end_0 = const()[name = string("op_3306_end_0"), val = tensor<int32, [4]>([1, 77, 1, 240])];
            tensor<bool, [4]> var_3306_end_mask_0 = const()[name = string("op_3306_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 80]> var_3306_cast_fp16 = slice_by_index(begin = var_3306_begin_0, end = var_3306_end_0, end_mask = var_3306_end_mask_0, x = k_47_cast_fp16)[name = string("op_3306_cast_fp16")];
            tensor<int32, [4]> var_3310_begin_0 = const()[name = string("op_3310_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 240])];
            tensor<int32, [4]> var_3310_end_0 = const()[name = string("op_3310_end_0"), val = tensor<int32, [4]>([1, 77, 1, 320])];
            tensor<bool, [4]> var_3310_end_mask_0 = const()[name = string("op_3310_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 80]> var_3310_cast_fp16 = slice_by_index(begin = var_3310_begin_0, end = var_3310_end_0, end_mask = var_3310_end_mask_0, x = k_47_cast_fp16)[name = string("op_3310_cast_fp16")];
            tensor<int32, [4]> var_3314_begin_0 = const()[name = string("op_3314_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 320])];
            tensor<int32, [4]> var_3314_end_0 = const()[name = string("op_3314_end_0"), val = tensor<int32, [4]>([1, 77, 1, 400])];
            tensor<bool, [4]> var_3314_end_mask_0 = const()[name = string("op_3314_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 80]> var_3314_cast_fp16 = slice_by_index(begin = var_3314_begin_0, end = var_3314_end_0, end_mask = var_3314_end_mask_0, x = k_47_cast_fp16)[name = string("op_3314_cast_fp16")];
            tensor<int32, [4]> var_3318_begin_0 = const()[name = string("op_3318_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 400])];
            tensor<int32, [4]> var_3318_end_0 = const()[name = string("op_3318_end_0"), val = tensor<int32, [4]>([1, 77, 1, 480])];
            tensor<bool, [4]> var_3318_end_mask_0 = const()[name = string("op_3318_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 80]> var_3318_cast_fp16 = slice_by_index(begin = var_3318_begin_0, end = var_3318_end_0, end_mask = var_3318_end_mask_0, x = k_47_cast_fp16)[name = string("op_3318_cast_fp16")];
            tensor<int32, [4]> var_3322_begin_0 = const()[name = string("op_3322_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 480])];
            tensor<int32, [4]> var_3322_end_0 = const()[name = string("op_3322_end_0"), val = tensor<int32, [4]>([1, 77, 1, 560])];
            tensor<bool, [4]> var_3322_end_mask_0 = const()[name = string("op_3322_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 80]> var_3322_cast_fp16 = slice_by_index(begin = var_3322_begin_0, end = var_3322_end_0, end_mask = var_3322_end_mask_0, x = k_47_cast_fp16)[name = string("op_3322_cast_fp16")];
            tensor<int32, [4]> var_3326_begin_0 = const()[name = string("op_3326_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 560])];
            tensor<int32, [4]> var_3326_end_0 = const()[name = string("op_3326_end_0"), val = tensor<int32, [4]>([1, 77, 1, 1])];
            tensor<bool, [4]> var_3326_end_mask_0 = const()[name = string("op_3326_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 77, 1, 80]> var_3326_cast_fp16 = slice_by_index(begin = var_3326_begin_0, end = var_3326_end_0, end_mask = var_3326_end_mask_0, x = k_47_cast_fp16)[name = string("op_3326_cast_fp16")];
            tensor<int32, [4]> var_3328_begin_0 = const()[name = string("op_3328_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_3328_end_0 = const()[name = string("op_3328_end_0"), val = tensor<int32, [4]>([1, 80, 1, 77])];
            tensor<bool, [4]> var_3328_end_mask_0 = const()[name = string("op_3328_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3328_cast_fp16 = slice_by_index(begin = var_3328_begin_0, end = var_3328_end_0, end_mask = var_3328_end_mask_0, x = v_23_cast_fp16)[name = string("op_3328_cast_fp16")];
            tensor<int32, [4]> var_3332_begin_0 = const()[name = string("op_3332_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_3332_end_0 = const()[name = string("op_3332_end_0"), val = tensor<int32, [4]>([1, 160, 1, 77])];
            tensor<bool, [4]> var_3332_end_mask_0 = const()[name = string("op_3332_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3332_cast_fp16 = slice_by_index(begin = var_3332_begin_0, end = var_3332_end_0, end_mask = var_3332_end_mask_0, x = v_23_cast_fp16)[name = string("op_3332_cast_fp16")];
            tensor<int32, [4]> var_3336_begin_0 = const()[name = string("op_3336_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_3336_end_0 = const()[name = string("op_3336_end_0"), val = tensor<int32, [4]>([1, 240, 1, 77])];
            tensor<bool, [4]> var_3336_end_mask_0 = const()[name = string("op_3336_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3336_cast_fp16 = slice_by_index(begin = var_3336_begin_0, end = var_3336_end_0, end_mask = var_3336_end_mask_0, x = v_23_cast_fp16)[name = string("op_3336_cast_fp16")];
            tensor<int32, [4]> var_3340_begin_0 = const()[name = string("op_3340_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_3340_end_0 = const()[name = string("op_3340_end_0"), val = tensor<int32, [4]>([1, 320, 1, 77])];
            tensor<bool, [4]> var_3340_end_mask_0 = const()[name = string("op_3340_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3340_cast_fp16 = slice_by_index(begin = var_3340_begin_0, end = var_3340_end_0, end_mask = var_3340_end_mask_0, x = v_23_cast_fp16)[name = string("op_3340_cast_fp16")];
            tensor<int32, [4]> var_3344_begin_0 = const()[name = string("op_3344_begin_0"), val = tensor<int32, [4]>([0, 320, 0, 0])];
            tensor<int32, [4]> var_3344_end_0 = const()[name = string("op_3344_end_0"), val = tensor<int32, [4]>([1, 400, 1, 77])];
            tensor<bool, [4]> var_3344_end_mask_0 = const()[name = string("op_3344_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3344_cast_fp16 = slice_by_index(begin = var_3344_begin_0, end = var_3344_end_0, end_mask = var_3344_end_mask_0, x = v_23_cast_fp16)[name = string("op_3344_cast_fp16")];
            tensor<int32, [4]> var_3348_begin_0 = const()[name = string("op_3348_begin_0"), val = tensor<int32, [4]>([0, 400, 0, 0])];
            tensor<int32, [4]> var_3348_end_0 = const()[name = string("op_3348_end_0"), val = tensor<int32, [4]>([1, 480, 1, 77])];
            tensor<bool, [4]> var_3348_end_mask_0 = const()[name = string("op_3348_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3348_cast_fp16 = slice_by_index(begin = var_3348_begin_0, end = var_3348_end_0, end_mask = var_3348_end_mask_0, x = v_23_cast_fp16)[name = string("op_3348_cast_fp16")];
            tensor<int32, [4]> var_3352_begin_0 = const()[name = string("op_3352_begin_0"), val = tensor<int32, [4]>([0, 480, 0, 0])];
            tensor<int32, [4]> var_3352_end_0 = const()[name = string("op_3352_end_0"), val = tensor<int32, [4]>([1, 560, 1, 77])];
            tensor<bool, [4]> var_3352_end_mask_0 = const()[name = string("op_3352_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3352_cast_fp16 = slice_by_index(begin = var_3352_begin_0, end = var_3352_end_0, end_mask = var_3352_end_mask_0, x = v_23_cast_fp16)[name = string("op_3352_cast_fp16")];
            tensor<int32, [4]> var_3356_begin_0 = const()[name = string("op_3356_begin_0"), val = tensor<int32, [4]>([0, 560, 0, 0])];
            tensor<int32, [4]> var_3356_end_0 = const()[name = string("op_3356_end_0"), val = tensor<int32, [4]>([1, 1, 1, 77])];
            tensor<bool, [4]> var_3356_end_mask_0 = const()[name = string("op_3356_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3356_cast_fp16 = slice_by_index(begin = var_3356_begin_0, end = var_3356_end_0, end_mask = var_3356_end_mask_0, x = v_23_cast_fp16)[name = string("op_3356_cast_fp16")];
            string var_3360_equation_0 = const()[name = string("op_3360_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3360_cast_fp16 = einsum(equation = var_3360_equation_0, values = (var_3298_cast_fp16, var_3263_cast_fp16))[name = string("op_3360_cast_fp16")];
            fp16 var_3361_to_fp16 = const()[name = string("op_3361_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_177_cast_fp16 = mul(x = var_3360_cast_fp16, y = var_3361_to_fp16)[name = string("aw_177_cast_fp16")];
            string var_3364_equation_0 = const()[name = string("op_3364_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3364_cast_fp16 = einsum(equation = var_3364_equation_0, values = (var_3302_cast_fp16, var_3267_cast_fp16))[name = string("op_3364_cast_fp16")];
            fp16 var_3365_to_fp16 = const()[name = string("op_3365_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_179_cast_fp16 = mul(x = var_3364_cast_fp16, y = var_3365_to_fp16)[name = string("aw_179_cast_fp16")];
            string var_3368_equation_0 = const()[name = string("op_3368_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3368_cast_fp16 = einsum(equation = var_3368_equation_0, values = (var_3306_cast_fp16, var_3271_cast_fp16))[name = string("op_3368_cast_fp16")];
            fp16 var_3369_to_fp16 = const()[name = string("op_3369_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_181_cast_fp16 = mul(x = var_3368_cast_fp16, y = var_3369_to_fp16)[name = string("aw_181_cast_fp16")];
            string var_3372_equation_0 = const()[name = string("op_3372_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3372_cast_fp16 = einsum(equation = var_3372_equation_0, values = (var_3310_cast_fp16, var_3275_cast_fp16))[name = string("op_3372_cast_fp16")];
            fp16 var_3373_to_fp16 = const()[name = string("op_3373_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_183_cast_fp16 = mul(x = var_3372_cast_fp16, y = var_3373_to_fp16)[name = string("aw_183_cast_fp16")];
            string var_3376_equation_0 = const()[name = string("op_3376_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3376_cast_fp16 = einsum(equation = var_3376_equation_0, values = (var_3314_cast_fp16, var_3279_cast_fp16))[name = string("op_3376_cast_fp16")];
            fp16 var_3377_to_fp16 = const()[name = string("op_3377_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_185_cast_fp16 = mul(x = var_3376_cast_fp16, y = var_3377_to_fp16)[name = string("aw_185_cast_fp16")];
            string var_3380_equation_0 = const()[name = string("op_3380_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3380_cast_fp16 = einsum(equation = var_3380_equation_0, values = (var_3318_cast_fp16, var_3283_cast_fp16))[name = string("op_3380_cast_fp16")];
            fp16 var_3381_to_fp16 = const()[name = string("op_3381_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_187_cast_fp16 = mul(x = var_3380_cast_fp16, y = var_3381_to_fp16)[name = string("aw_187_cast_fp16")];
            string var_3384_equation_0 = const()[name = string("op_3384_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3384_cast_fp16 = einsum(equation = var_3384_equation_0, values = (var_3322_cast_fp16, var_3287_cast_fp16))[name = string("op_3384_cast_fp16")];
            fp16 var_3385_to_fp16 = const()[name = string("op_3385_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_189_cast_fp16 = mul(x = var_3384_cast_fp16, y = var_3385_to_fp16)[name = string("aw_189_cast_fp16")];
            string var_3388_equation_0 = const()[name = string("op_3388_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3388_cast_fp16 = einsum(equation = var_3388_equation_0, values = (var_3326_cast_fp16, var_3291_cast_fp16))[name = string("op_3388_cast_fp16")];
            fp16 var_3389_to_fp16 = const()[name = string("op_3389_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_191_cast_fp16 = mul(x = var_3388_cast_fp16, y = var_3389_to_fp16)[name = string("aw_191_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3391_cast_fp16 = softmax(axis = var_2929, x = aw_177_cast_fp16)[name = string("op_3391_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3392_cast_fp16 = softmax(axis = var_2929, x = aw_179_cast_fp16)[name = string("op_3392_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3393_cast_fp16 = softmax(axis = var_2929, x = aw_181_cast_fp16)[name = string("op_3393_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3394_cast_fp16 = softmax(axis = var_2929, x = aw_183_cast_fp16)[name = string("op_3394_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3395_cast_fp16 = softmax(axis = var_2929, x = aw_185_cast_fp16)[name = string("op_3395_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3396_cast_fp16 = softmax(axis = var_2929, x = aw_187_cast_fp16)[name = string("op_3396_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3397_cast_fp16 = softmax(axis = var_2929, x = aw_189_cast_fp16)[name = string("op_3397_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3398_cast_fp16 = softmax(axis = var_2929, x = aw_191_cast_fp16)[name = string("op_3398_cast_fp16")];
            string var_3400_equation_0 = const()[name = string("op_3400_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3400_cast_fp16 = einsum(equation = var_3400_equation_0, values = (var_3328_cast_fp16, var_3391_cast_fp16))[name = string("op_3400_cast_fp16")];
            string var_3402_equation_0 = const()[name = string("op_3402_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3402_cast_fp16 = einsum(equation = var_3402_equation_0, values = (var_3332_cast_fp16, var_3392_cast_fp16))[name = string("op_3402_cast_fp16")];
            string var_3404_equation_0 = const()[name = string("op_3404_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3404_cast_fp16 = einsum(equation = var_3404_equation_0, values = (var_3336_cast_fp16, var_3393_cast_fp16))[name = string("op_3404_cast_fp16")];
            string var_3406_equation_0 = const()[name = string("op_3406_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3406_cast_fp16 = einsum(equation = var_3406_equation_0, values = (var_3340_cast_fp16, var_3394_cast_fp16))[name = string("op_3406_cast_fp16")];
            string var_3408_equation_0 = const()[name = string("op_3408_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3408_cast_fp16 = einsum(equation = var_3408_equation_0, values = (var_3344_cast_fp16, var_3395_cast_fp16))[name = string("op_3408_cast_fp16")];
            string var_3410_equation_0 = const()[name = string("op_3410_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3410_cast_fp16 = einsum(equation = var_3410_equation_0, values = (var_3348_cast_fp16, var_3396_cast_fp16))[name = string("op_3410_cast_fp16")];
            string var_3412_equation_0 = const()[name = string("op_3412_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3412_cast_fp16 = einsum(equation = var_3412_equation_0, values = (var_3352_cast_fp16, var_3397_cast_fp16))[name = string("op_3412_cast_fp16")];
            string var_3414_equation_0 = const()[name = string("op_3414_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3414_cast_fp16 = einsum(equation = var_3414_equation_0, values = (var_3356_cast_fp16, var_3398_cast_fp16))[name = string("op_3414_cast_fp16")];
            bool input_165_interleave_0 = const()[name = string("input_165_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 640, 1, 1024]> input_165_cast_fp16 = concat(axis = var_2929, interleave = input_165_interleave_0, values = (var_3400_cast_fp16, var_3402_cast_fp16, var_3404_cast_fp16, var_3406_cast_fp16, var_3408_cast_fp16, var_3410_cast_fp16, var_3412_cast_fp16, var_3414_cast_fp16))[name = string("input_165_cast_fp16")];
            string var_3424_pad_type_0 = const()[name = string("op_3424_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_3424_strides_0 = const()[name = string("op_3424_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_3424_pad_0 = const()[name = string("op_3424_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_3424_dilations_0 = const()[name = string("op_3424_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3424_groups_0 = const()[name = string("op_3424_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_out_0_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_out_0_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(237863744)))];
            tensor<fp16, [640]> up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_out_0_bias_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_out_0_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(238683008)))];
            tensor<fp16, [1, 640, 1, 1024]> var_3424_cast_fp16 = conv(bias = up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_out_0_bias_to_fp16, dilations = var_3424_dilations_0, groups = var_3424_groups_0, pad = var_3424_pad_0, pad_type = var_3424_pad_type_0, strides = var_3424_strides_0, weight = up_blocks_1_attentions_0_transformer_blocks_0_attn2_to_out_0_weight_to_fp16, x = input_165_cast_fp16)[name = string("op_3424_cast_fp16")];
            tensor<fp16, [1, 640, 1, 1024]> inputs_35_cast_fp16 = add(x = var_3424_cast_fp16, y = inputs_33_cast_fp16)[name = string("inputs_35_cast_fp16")];
            tensor<int32, [1]> input_167_axes_0 = const()[name = string("input_167_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [640]> input_167_gamma_0_to_fp16 = const()[name = string("input_167_gamma_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(238684352)))];
            tensor<fp16, [640]> input_167_beta_0_to_fp16 = const()[name = string("input_167_beta_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(238685696)))];
            fp16 var_3434_to_fp16 = const()[name = string("op_3434_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 640, 1, 1024]> input_167_cast_fp16 = layer_norm(axes = input_167_axes_0, beta = input_167_beta_0_to_fp16, epsilon = var_3434_to_fp16, gamma = input_167_gamma_0_to_fp16, x = inputs_35_cast_fp16)[name = string("input_167_cast_fp16")];
            string var_3454_pad_type_0 = const()[name = string("op_3454_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_3454_strides_0 = const()[name = string("op_3454_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_3454_pad_0 = const()[name = string("op_3454_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_3454_dilations_0 = const()[name = string("op_3454_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3454_groups_0 = const()[name = string("op_3454_groups_0"), val = int32(1)];
            tensor<fp16, [5120, 640, 1, 1]> up_blocks_1_attentions_0_transformer_blocks_0_ff_net_0_proj_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_ff_net_0_proj_weight_to_fp16"), val = tensor<fp16, [5120, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(238687040)))];
            tensor<fp16, [5120]> up_blocks_1_attentions_0_transformer_blocks_0_ff_net_0_proj_bias_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_ff_net_0_proj_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(245240704)))];
            tensor<fp16, [1, 5120, 1, 1024]> var_3454_cast_fp16 = conv(bias = up_blocks_1_attentions_0_transformer_blocks_0_ff_net_0_proj_bias_to_fp16, dilations = var_3454_dilations_0, groups = var_3454_groups_0, pad = var_3454_pad_0, pad_type = var_3454_pad_type_0, strides = var_3454_strides_0, weight = up_blocks_1_attentions_0_transformer_blocks_0_ff_net_0_proj_weight_to_fp16, x = input_167_cast_fp16)[name = string("op_3454_cast_fp16")];
            tensor<int32, [2]> var_3455_split_sizes_0 = const()[name = string("op_3455_split_sizes_0"), val = tensor<int32, [2]>([2560, 2560])];
            int32 var_3455_axis_0 = const()[name = string("op_3455_axis_0"), val = int32(1)];
            tensor<fp16, [1, 2560, 1, 1024]> var_3455_cast_fp16_0, tensor<fp16, [1, 2560, 1, 1024]> var_3455_cast_fp16_1 = split(axis = var_3455_axis_0, split_sizes = var_3455_split_sizes_0, x = var_3454_cast_fp16)[name = string("op_3455_cast_fp16")];
            string var_3457_mode_0 = const()[name = string("op_3457_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2560, 1, 1024]> var_3457_cast_fp16 = gelu(mode = var_3457_mode_0, x = var_3455_cast_fp16_1)[name = string("op_3457_cast_fp16")];
            tensor<fp16, [1, 2560, 1, 1024]> input_169_cast_fp16 = mul(x = var_3455_cast_fp16_0, y = var_3457_cast_fp16)[name = string("input_169_cast_fp16")];
            string var_3465_pad_type_0 = const()[name = string("op_3465_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_3465_strides_0 = const()[name = string("op_3465_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_3465_pad_0 = const()[name = string("op_3465_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_3465_dilations_0 = const()[name = string("op_3465_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3465_groups_0 = const()[name = string("op_3465_groups_0"), val = int32(1)];
            tensor<fp16, [640, 2560, 1, 1]> up_blocks_1_attentions_0_transformer_blocks_0_ff_net_2_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_ff_net_2_weight_to_fp16"), val = tensor<fp16, [640, 2560, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(245251008)))];
            tensor<fp16, [640]> up_blocks_1_attentions_0_transformer_blocks_0_ff_net_2_bias_to_fp16 = const()[name = string("up_blocks_1_attentions_0_transformer_blocks_0_ff_net_2_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(248527872)))];
            tensor<fp16, [1, 640, 1, 1024]> var_3465_cast_fp16 = conv(bias = up_blocks_1_attentions_0_transformer_blocks_0_ff_net_2_bias_to_fp16, dilations = var_3465_dilations_0, groups = var_3465_groups_0, pad = var_3465_pad_0, pad_type = var_3465_pad_type_0, strides = var_3465_strides_0, weight = up_blocks_1_attentions_0_transformer_blocks_0_ff_net_2_weight_to_fp16, x = input_169_cast_fp16)[name = string("op_3465_cast_fp16")];
            tensor<fp16, [1, 640, 1, 1024]> hidden_states_111_cast_fp16 = add(x = var_3465_cast_fp16, y = inputs_35_cast_fp16)[name = string("hidden_states_111_cast_fp16")];
            tensor<int32, [4]> var_3467 = const()[name = string("op_3467"), val = tensor<int32, [4]>([1, 640, 32, 32])];
            tensor<fp16, [1, 640, 32, 32]> input_171_cast_fp16 = reshape(shape = var_3467, x = hidden_states_111_cast_fp16)[name = string("input_171_cast_fp16")];
            string hidden_states_113_pad_type_0 = const()[name = string("hidden_states_113_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> hidden_states_113_strides_0 = const()[name = string("hidden_states_113_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> hidden_states_113_pad_0 = const()[name = string("hidden_states_113_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> hidden_states_113_dilations_0 = const()[name = string("hidden_states_113_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_113_groups_0 = const()[name = string("hidden_states_113_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_0_proj_out_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_0_proj_out_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(248529216)))];
            tensor<fp16, [640]> up_blocks_1_attentions_0_proj_out_bias_to_fp16 = const()[name = string("up_blocks_1_attentions_0_proj_out_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(249348480)))];
            tensor<fp16, [1, 640, 32, 32]> hidden_states_113_cast_fp16 = conv(bias = up_blocks_1_attentions_0_proj_out_bias_to_fp16, dilations = hidden_states_113_dilations_0, groups = hidden_states_113_groups_0, pad = hidden_states_113_pad_0, pad_type = hidden_states_113_pad_type_0, strides = hidden_states_113_strides_0, weight = up_blocks_1_attentions_0_proj_out_weight_to_fp16, x = input_171_cast_fp16)[name = string("hidden_states_113_cast_fp16")];
            tensor<fp16, [1, 640, 32, 32]> hidden_states_115_cast_fp16 = add(x = hidden_states_113_cast_fp16, y = hidden_states_101_cast_fp16)[name = string("hidden_states_115_cast_fp16")];
            bool input_173_interleave_0 = const()[name = string("input_173_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 320, 32, 32]> cast_5 = cast(dtype = cast_5_dtype_0, x = input_37_cast_fp16)[name = string("cast_6")];
            tensor<fp16, [1, 960, 32, 32]> input_173_cast_fp16 = concat(axis = var_2929, interleave = input_173_interleave_0, values = (hidden_states_115_cast_fp16, cast_5))[name = string("input_173_cast_fp16")];
            tensor<int32, [5]> reshape_72_shape_0 = const()[name = string("reshape_72_shape_0"), val = tensor<int32, [5]>([1, 32, 30, 32, 32])];
            tensor<fp16, [1, 32, 30, 32, 32]> reshape_72_cast_fp16 = reshape(shape = reshape_72_shape_0, x = input_173_cast_fp16)[name = string("reshape_72_cast_fp16")];
            tensor<int32, [3]> reduce_mean_54_axes_0 = const()[name = string("reduce_mean_54_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_54_keep_dims_0 = const()[name = string("reduce_mean_54_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_54_cast_fp16 = reduce_mean(axes = reduce_mean_54_axes_0, keep_dims = reduce_mean_54_keep_dims_0, x = reshape_72_cast_fp16)[name = string("reduce_mean_54_cast_fp16")];
            tensor<fp16, [1, 32, 30, 32, 32]> sub_36_cast_fp16 = sub(x = reshape_72_cast_fp16, y = reduce_mean_54_cast_fp16)[name = string("sub_36_cast_fp16")];
            tensor<fp16, [1, 32, 30, 32, 32]> square_18_cast_fp16 = square(x = sub_36_cast_fp16)[name = string("square_18_cast_fp16")];
            tensor<int32, [3]> reduce_mean_56_axes_0 = const()[name = string("reduce_mean_56_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_56_keep_dims_0 = const()[name = string("reduce_mean_56_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_56_cast_fp16 = reduce_mean(axes = reduce_mean_56_axes_0, keep_dims = reduce_mean_56_keep_dims_0, x = square_18_cast_fp16)[name = string("reduce_mean_56_cast_fp16")];
            fp16 add_36_y_0_to_fp16 = const()[name = string("add_36_y_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_36_cast_fp16 = add(x = reduce_mean_56_cast_fp16, y = add_36_y_0_to_fp16)[name = string("add_36_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_18_cast_fp16 = sqrt(x = add_36_cast_fp16)[name = string("sqrt_18_cast_fp16")];
            tensor<fp16, [1, 32, 30, 32, 32]> real_div_18_cast_fp16 = real_div(x = sub_36_cast_fp16, y = sqrt_18_cast_fp16)[name = string("real_div_18_cast_fp16")];
            tensor<int32, [4]> reshape_73_shape_0 = const()[name = string("reshape_73_shape_0"), val = tensor<int32, [4]>([1, 960, 32, 32])];
            tensor<fp16, [1, 960, 32, 32]> reshape_73_cast_fp16 = reshape(shape = reshape_73_shape_0, x = real_div_18_cast_fp16)[name = string("reshape_73_cast_fp16")];
            tensor<fp16, [960]> add_37_mean_0_to_fp16 = const()[name = string("add_37_mean_0_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(249349824)))];
            tensor<fp16, [960]> add_37_variance_0_to_fp16 = const()[name = string("add_37_variance_0_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(249351808)))];
            tensor<fp16, [960]> add_37_gamma_0_to_fp16 = const()[name = string("add_37_gamma_0_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(249353792)))];
            tensor<fp16, [960]> add_37_beta_0_to_fp16 = const()[name = string("add_37_beta_0_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(249355776)))];
            fp16 add_37_epsilon_0_to_fp16 = const()[name = string("add_37_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 960, 32, 32]> add_37_cast_fp16 = batch_norm(beta = add_37_beta_0_to_fp16, epsilon = add_37_epsilon_0_to_fp16, gamma = add_37_gamma_0_to_fp16, mean = add_37_mean_0_to_fp16, variance = add_37_variance_0_to_fp16, x = reshape_73_cast_fp16)[name = string("add_37_cast_fp16")];
            tensor<fp16, [1, 960, 32, 32]> input_177_cast_fp16 = silu(x = add_37_cast_fp16)[name = string("input_177_cast_fp16")];
            string hidden_states_117_pad_type_0 = const()[name = string("hidden_states_117_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> hidden_states_117_pad_0 = const()[name = string("hidden_states_117_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> hidden_states_117_strides_0 = const()[name = string("hidden_states_117_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> hidden_states_117_dilations_0 = const()[name = string("hidden_states_117_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_117_groups_0 = const()[name = string("hidden_states_117_groups_0"), val = int32(1)];
            tensor<fp16, [640, 960, 3, 3]> up_blocks_1_resnets_1_conv1_weight_to_fp16 = const()[name = string("up_blocks_1_resnets_1_conv1_weight_to_fp16"), val = tensor<fp16, [640, 960, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(249357760)))];
            tensor<fp16, [640]> up_blocks_1_resnets_1_conv1_bias_to_fp16 = const()[name = string("up_blocks_1_resnets_1_conv1_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(260417024)))];
            tensor<fp16, [1, 640, 32, 32]> hidden_states_117_cast_fp16 = conv(bias = up_blocks_1_resnets_1_conv1_bias_to_fp16, dilations = hidden_states_117_dilations_0, groups = hidden_states_117_groups_0, pad = hidden_states_117_pad_0, pad_type = hidden_states_117_pad_type_0, strides = hidden_states_117_strides_0, weight = up_blocks_1_resnets_1_conv1_weight_to_fp16, x = input_177_cast_fp16)[name = string("hidden_states_117_cast_fp16")];
            string temb_13_pad_type_0 = const()[name = string("temb_13_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> temb_13_strides_0 = const()[name = string("temb_13_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> temb_13_pad_0 = const()[name = string("temb_13_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> temb_13_dilations_0 = const()[name = string("temb_13_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 temb_13_groups_0 = const()[name = string("temb_13_groups_0"), val = int32(1)];
            tensor<fp16, [640, 1280, 1, 1]> up_blocks_1_resnets_1_time_emb_proj_weight_to_fp16 = const()[name = string("up_blocks_1_resnets_1_time_emb_proj_weight_to_fp16"), val = tensor<fp16, [640, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(260418368)))];
            tensor<fp16, [640]> up_blocks_1_resnets_1_time_emb_proj_bias_to_fp16 = const()[name = string("up_blocks_1_resnets_1_time_emb_proj_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(262056832)))];
            tensor<fp16, [1, 640, 1, 1]> temb_13_cast_fp16 = conv(bias = up_blocks_1_resnets_1_time_emb_proj_bias_to_fp16, dilations = temb_13_dilations_0, groups = temb_13_groups_0, pad = temb_13_pad_0, pad_type = temb_13_pad_type_0, strides = temb_13_strides_0, weight = up_blocks_1_resnets_1_time_emb_proj_weight_to_fp16, x = cast_7)[name = string("temb_13_cast_fp16")];
            tensor<fp16, [1, 640, 32, 32]> input_181_cast_fp16 = add(x = hidden_states_117_cast_fp16, y = temb_13_cast_fp16)[name = string("input_181_cast_fp16")];
            tensor<int32, [5]> reshape_76_shape_0 = const()[name = string("reshape_76_shape_0"), val = tensor<int32, [5]>([1, 32, 20, 32, 32])];
            tensor<fp16, [1, 32, 20, 32, 32]> reshape_76_cast_fp16 = reshape(shape = reshape_76_shape_0, x = input_181_cast_fp16)[name = string("reshape_76_cast_fp16")];
            tensor<int32, [3]> reduce_mean_57_axes_0 = const()[name = string("reduce_mean_57_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_57_keep_dims_0 = const()[name = string("reduce_mean_57_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_57_cast_fp16 = reduce_mean(axes = reduce_mean_57_axes_0, keep_dims = reduce_mean_57_keep_dims_0, x = reshape_76_cast_fp16)[name = string("reduce_mean_57_cast_fp16")];
            tensor<fp16, [1, 32, 20, 32, 32]> sub_38_cast_fp16 = sub(x = reshape_76_cast_fp16, y = reduce_mean_57_cast_fp16)[name = string("sub_38_cast_fp16")];
            tensor<fp16, [1, 32, 20, 32, 32]> square_19_cast_fp16 = square(x = sub_38_cast_fp16)[name = string("square_19_cast_fp16")];
            tensor<int32, [3]> reduce_mean_59_axes_0 = const()[name = string("reduce_mean_59_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_59_keep_dims_0 = const()[name = string("reduce_mean_59_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_59_cast_fp16 = reduce_mean(axes = reduce_mean_59_axes_0, keep_dims = reduce_mean_59_keep_dims_0, x = square_19_cast_fp16)[name = string("reduce_mean_59_cast_fp16")];
            fp16 add_38_y_0_to_fp16 = const()[name = string("add_38_y_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_38_cast_fp16 = add(x = reduce_mean_59_cast_fp16, y = add_38_y_0_to_fp16)[name = string("add_38_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_19_cast_fp16 = sqrt(x = add_38_cast_fp16)[name = string("sqrt_19_cast_fp16")];
            tensor<fp16, [1, 32, 20, 32, 32]> real_div_19_cast_fp16 = real_div(x = sub_38_cast_fp16, y = sqrt_19_cast_fp16)[name = string("real_div_19_cast_fp16")];
            tensor<int32, [4]> reshape_77_shape_0 = const()[name = string("reshape_77_shape_0"), val = tensor<int32, [4]>([1, 640, 32, 32])];
            tensor<fp16, [1, 640, 32, 32]> reshape_77_cast_fp16 = reshape(shape = reshape_77_shape_0, x = real_div_19_cast_fp16)[name = string("reshape_77_cast_fp16")];
            tensor<fp16, [640]> add_39_gamma_0_to_fp16 = const()[name = string("add_39_gamma_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(262058176)))];
            tensor<fp16, [640]> add_39_beta_0_to_fp16 = const()[name = string("add_39_beta_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(262059520)))];
            fp16 add_39_epsilon_0_to_fp16 = const()[name = string("add_39_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 640, 32, 32]> add_39_cast_fp16 = batch_norm(beta = add_39_beta_0_to_fp16, epsilon = add_39_epsilon_0_to_fp16, gamma = add_39_gamma_0_to_fp16, mean = add_9_mean_0_to_fp16, variance = add_9_variance_0_to_fp16, x = reshape_77_cast_fp16)[name = string("add_39_cast_fp16")];
            tensor<fp16, [1, 640, 32, 32]> input_185_cast_fp16 = silu(x = add_39_cast_fp16)[name = string("input_185_cast_fp16")];
            string hidden_states_119_pad_type_0 = const()[name = string("hidden_states_119_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> hidden_states_119_pad_0 = const()[name = string("hidden_states_119_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> hidden_states_119_strides_0 = const()[name = string("hidden_states_119_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> hidden_states_119_dilations_0 = const()[name = string("hidden_states_119_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_119_groups_0 = const()[name = string("hidden_states_119_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 3, 3]> up_blocks_1_resnets_1_conv2_weight_to_fp16 = const()[name = string("up_blocks_1_resnets_1_conv2_weight_to_fp16"), val = tensor<fp16, [640, 640, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(262060864)))];
            tensor<fp16, [640]> up_blocks_1_resnets_1_conv2_bias_to_fp16 = const()[name = string("up_blocks_1_resnets_1_conv2_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(269433728)))];
            tensor<fp16, [1, 640, 32, 32]> hidden_states_119_cast_fp16 = conv(bias = up_blocks_1_resnets_1_conv2_bias_to_fp16, dilations = hidden_states_119_dilations_0, groups = hidden_states_119_groups_0, pad = hidden_states_119_pad_0, pad_type = hidden_states_119_pad_type_0, strides = hidden_states_119_strides_0, weight = up_blocks_1_resnets_1_conv2_weight_to_fp16, x = input_185_cast_fp16)[name = string("hidden_states_119_cast_fp16")];
            string x_11_pad_type_0 = const()[name = string("x_11_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_11_strides_0 = const()[name = string("x_11_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_11_pad_0 = const()[name = string("x_11_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_11_dilations_0 = const()[name = string("x_11_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_11_groups_0 = const()[name = string("x_11_groups_0"), val = int32(1)];
            tensor<fp16, [640, 960, 1, 1]> up_blocks_1_resnets_1_conv_shortcut_weight_to_fp16 = const()[name = string("up_blocks_1_resnets_1_conv_shortcut_weight_to_fp16"), val = tensor<fp16, [640, 960, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(269435072)))];
            tensor<fp16, [640]> up_blocks_1_resnets_1_conv_shortcut_bias_to_fp16 = const()[name = string("up_blocks_1_resnets_1_conv_shortcut_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270663936)))];
            tensor<fp16, [1, 640, 32, 32]> x_11_cast_fp16 = conv(bias = up_blocks_1_resnets_1_conv_shortcut_bias_to_fp16, dilations = x_11_dilations_0, groups = x_11_groups_0, pad = x_11_pad_0, pad_type = x_11_pad_type_0, strides = x_11_strides_0, weight = up_blocks_1_resnets_1_conv_shortcut_weight_to_fp16, x = input_173_cast_fp16)[name = string("x_11_cast_fp16")];
            tensor<fp16, [1, 640, 32, 32]> hidden_states_121_cast_fp16 = add(x = x_11_cast_fp16, y = hidden_states_119_cast_fp16)[name = string("hidden_states_121_cast_fp16")];
            tensor<int32, [5]> reshape_80_shape_0 = const()[name = string("reshape_80_shape_0"), val = tensor<int32, [5]>([1, 32, 20, 32, 32])];
            tensor<fp16, [1, 32, 20, 32, 32]> reshape_80_cast_fp16 = reshape(shape = reshape_80_shape_0, x = hidden_states_121_cast_fp16)[name = string("reshape_80_cast_fp16")];
            tensor<int32, [3]> reduce_mean_60_axes_0 = const()[name = string("reduce_mean_60_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_60_keep_dims_0 = const()[name = string("reduce_mean_60_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_60_cast_fp16 = reduce_mean(axes = reduce_mean_60_axes_0, keep_dims = reduce_mean_60_keep_dims_0, x = reshape_80_cast_fp16)[name = string("reduce_mean_60_cast_fp16")];
            tensor<fp16, [1, 32, 20, 32, 32]> sub_40_cast_fp16 = sub(x = reshape_80_cast_fp16, y = reduce_mean_60_cast_fp16)[name = string("sub_40_cast_fp16")];
            tensor<fp16, [1, 32, 20, 32, 32]> square_20_cast_fp16 = square(x = sub_40_cast_fp16)[name = string("square_20_cast_fp16")];
            tensor<int32, [3]> reduce_mean_62_axes_0 = const()[name = string("reduce_mean_62_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_62_keep_dims_0 = const()[name = string("reduce_mean_62_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_62_cast_fp16 = reduce_mean(axes = reduce_mean_62_axes_0, keep_dims = reduce_mean_62_keep_dims_0, x = square_20_cast_fp16)[name = string("reduce_mean_62_cast_fp16")];
            fp16 add_40_y_0_to_fp16 = const()[name = string("add_40_y_0_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_40_cast_fp16 = add(x = reduce_mean_62_cast_fp16, y = add_40_y_0_to_fp16)[name = string("add_40_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_20_cast_fp16 = sqrt(x = add_40_cast_fp16)[name = string("sqrt_20_cast_fp16")];
            tensor<fp16, [1, 32, 20, 32, 32]> real_div_20_cast_fp16 = real_div(x = sub_40_cast_fp16, y = sqrt_20_cast_fp16)[name = string("real_div_20_cast_fp16")];
            tensor<int32, [4]> reshape_81_shape_0 = const()[name = string("reshape_81_shape_0"), val = tensor<int32, [4]>([1, 640, 32, 32])];
            tensor<fp16, [1, 640, 32, 32]> reshape_81_cast_fp16 = reshape(shape = reshape_81_shape_0, x = real_div_20_cast_fp16)[name = string("reshape_81_cast_fp16")];
            tensor<fp16, [640]> add_41_gamma_0_to_fp16 = const()[name = string("add_41_gamma_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270665280)))];
            tensor<fp16, [640]> add_41_beta_0_to_fp16 = const()[name = string("add_41_beta_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270666624)))];
            fp16 add_41_epsilon_0_to_fp16 = const()[name = string("add_41_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 640, 32, 32]> add_41_cast_fp16 = batch_norm(beta = add_41_beta_0_to_fp16, epsilon = add_41_epsilon_0_to_fp16, gamma = add_41_gamma_0_to_fp16, mean = add_9_mean_0_to_fp16, variance = add_9_variance_0_to_fp16, x = reshape_81_cast_fp16)[name = string("add_41_cast_fp16")];
            string hidden_states_123_pad_type_0 = const()[name = string("hidden_states_123_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> hidden_states_123_strides_0 = const()[name = string("hidden_states_123_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> hidden_states_123_pad_0 = const()[name = string("hidden_states_123_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> hidden_states_123_dilations_0 = const()[name = string("hidden_states_123_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_123_groups_0 = const()[name = string("hidden_states_123_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_1_proj_in_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_1_proj_in_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(270667968)))];
            tensor<fp16, [640]> up_blocks_1_attentions_1_proj_in_bias_to_fp16 = const()[name = string("up_blocks_1_attentions_1_proj_in_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(271487232)))];
            tensor<fp16, [1, 640, 32, 32]> hidden_states_123_cast_fp16 = conv(bias = up_blocks_1_attentions_1_proj_in_bias_to_fp16, dilations = hidden_states_123_dilations_0, groups = hidden_states_123_groups_0, pad = hidden_states_123_pad_0, pad_type = hidden_states_123_pad_type_0, strides = hidden_states_123_strides_0, weight = up_blocks_1_attentions_1_proj_in_weight_to_fp16, x = add_41_cast_fp16)[name = string("hidden_states_123_cast_fp16")];
            tensor<int32, [4]> var_3547 = const()[name = string("op_3547"), val = tensor<int32, [4]>([1, 640, 1, 1024])];
            tensor<fp16, [1, 640, 1, 1024]> inputs_37_cast_fp16 = reshape(shape = var_3547, x = hidden_states_123_cast_fp16)[name = string("inputs_37_cast_fp16")];
            tensor<int32, [1]> hidden_states_125_axes_0 = const()[name = string("hidden_states_125_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [640]> hidden_states_125_gamma_0_to_fp16 = const()[name = string("hidden_states_125_gamma_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(271488576)))];
            tensor<fp16, [640]> hidden_states_125_beta_0_to_fp16 = const()[name = string("hidden_states_125_beta_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(271489920)))];
            fp16 var_3563_to_fp16 = const()[name = string("op_3563_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 640, 1, 1024]> hidden_states_125_cast_fp16 = layer_norm(axes = hidden_states_125_axes_0, beta = hidden_states_125_beta_0_to_fp16, epsilon = var_3563_to_fp16, gamma = hidden_states_125_gamma_0_to_fp16, x = inputs_37_cast_fp16)[name = string("hidden_states_125_cast_fp16")];
            string q_25_pad_type_0 = const()[name = string("q_25_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> q_25_strides_0 = const()[name = string("q_25_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> q_25_pad_0 = const()[name = string("q_25_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> q_25_dilations_0 = const()[name = string("q_25_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 q_25_groups_0 = const()[name = string("q_25_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_q_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_q_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(271491264)))];
            tensor<fp16, [1, 640, 1, 1024]> q_25_cast_fp16 = conv(dilations = q_25_dilations_0, groups = q_25_groups_0, pad = q_25_pad_0, pad_type = q_25_pad_type_0, strides = q_25_strides_0, weight = up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_q_weight_to_fp16, x = hidden_states_125_cast_fp16)[name = string("q_25_cast_fp16")];
            string k_49_pad_type_0 = const()[name = string("k_49_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> k_49_strides_0 = const()[name = string("k_49_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> k_49_pad_0 = const()[name = string("k_49_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> k_49_dilations_0 = const()[name = string("k_49_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 k_49_groups_0 = const()[name = string("k_49_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_k_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_k_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(272310528)))];
            tensor<fp16, [1, 640, 1, 1024]> k_49_cast_fp16 = conv(dilations = k_49_dilations_0, groups = k_49_groups_0, pad = k_49_pad_0, pad_type = k_49_pad_type_0, strides = k_49_strides_0, weight = up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_k_weight_to_fp16, x = hidden_states_125_cast_fp16)[name = string("k_49_cast_fp16")];
            string v_25_pad_type_0 = const()[name = string("v_25_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> v_25_strides_0 = const()[name = string("v_25_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> v_25_pad_0 = const()[name = string("v_25_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> v_25_dilations_0 = const()[name = string("v_25_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 v_25_groups_0 = const()[name = string("v_25_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_v_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_v_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(273129792)))];
            tensor<fp16, [1, 640, 1, 1024]> v_25_cast_fp16 = conv(dilations = v_25_dilations_0, groups = v_25_groups_0, pad = v_25_pad_0, pad_type = v_25_pad_type_0, strides = v_25_strides_0, weight = up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_v_weight_to_fp16, x = hidden_states_125_cast_fp16)[name = string("v_25_cast_fp16")];
            tensor<int32, [4]> var_3596_begin_0 = const()[name = string("op_3596_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_3596_end_0 = const()[name = string("op_3596_end_0"), val = tensor<int32, [4]>([1, 80, 1, 1024])];
            tensor<bool, [4]> var_3596_end_mask_0 = const()[name = string("op_3596_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3596_cast_fp16 = slice_by_index(begin = var_3596_begin_0, end = var_3596_end_0, end_mask = var_3596_end_mask_0, x = q_25_cast_fp16)[name = string("op_3596_cast_fp16")];
            tensor<int32, [4]> var_3600_begin_0 = const()[name = string("op_3600_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_3600_end_0 = const()[name = string("op_3600_end_0"), val = tensor<int32, [4]>([1, 160, 1, 1024])];
            tensor<bool, [4]> var_3600_end_mask_0 = const()[name = string("op_3600_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3600_cast_fp16 = slice_by_index(begin = var_3600_begin_0, end = var_3600_end_0, end_mask = var_3600_end_mask_0, x = q_25_cast_fp16)[name = string("op_3600_cast_fp16")];
            tensor<int32, [4]> var_3604_begin_0 = const()[name = string("op_3604_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_3604_end_0 = const()[name = string("op_3604_end_0"), val = tensor<int32, [4]>([1, 240, 1, 1024])];
            tensor<bool, [4]> var_3604_end_mask_0 = const()[name = string("op_3604_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3604_cast_fp16 = slice_by_index(begin = var_3604_begin_0, end = var_3604_end_0, end_mask = var_3604_end_mask_0, x = q_25_cast_fp16)[name = string("op_3604_cast_fp16")];
            tensor<int32, [4]> var_3608_begin_0 = const()[name = string("op_3608_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_3608_end_0 = const()[name = string("op_3608_end_0"), val = tensor<int32, [4]>([1, 320, 1, 1024])];
            tensor<bool, [4]> var_3608_end_mask_0 = const()[name = string("op_3608_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3608_cast_fp16 = slice_by_index(begin = var_3608_begin_0, end = var_3608_end_0, end_mask = var_3608_end_mask_0, x = q_25_cast_fp16)[name = string("op_3608_cast_fp16")];
            tensor<int32, [4]> var_3612_begin_0 = const()[name = string("op_3612_begin_0"), val = tensor<int32, [4]>([0, 320, 0, 0])];
            tensor<int32, [4]> var_3612_end_0 = const()[name = string("op_3612_end_0"), val = tensor<int32, [4]>([1, 400, 1, 1024])];
            tensor<bool, [4]> var_3612_end_mask_0 = const()[name = string("op_3612_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3612_cast_fp16 = slice_by_index(begin = var_3612_begin_0, end = var_3612_end_0, end_mask = var_3612_end_mask_0, x = q_25_cast_fp16)[name = string("op_3612_cast_fp16")];
            tensor<int32, [4]> var_3616_begin_0 = const()[name = string("op_3616_begin_0"), val = tensor<int32, [4]>([0, 400, 0, 0])];
            tensor<int32, [4]> var_3616_end_0 = const()[name = string("op_3616_end_0"), val = tensor<int32, [4]>([1, 480, 1, 1024])];
            tensor<bool, [4]> var_3616_end_mask_0 = const()[name = string("op_3616_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3616_cast_fp16 = slice_by_index(begin = var_3616_begin_0, end = var_3616_end_0, end_mask = var_3616_end_mask_0, x = q_25_cast_fp16)[name = string("op_3616_cast_fp16")];
            tensor<int32, [4]> var_3620_begin_0 = const()[name = string("op_3620_begin_0"), val = tensor<int32, [4]>([0, 480, 0, 0])];
            tensor<int32, [4]> var_3620_end_0 = const()[name = string("op_3620_end_0"), val = tensor<int32, [4]>([1, 560, 1, 1024])];
            tensor<bool, [4]> var_3620_end_mask_0 = const()[name = string("op_3620_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3620_cast_fp16 = slice_by_index(begin = var_3620_begin_0, end = var_3620_end_0, end_mask = var_3620_end_mask_0, x = q_25_cast_fp16)[name = string("op_3620_cast_fp16")];
            tensor<int32, [4]> var_3624_begin_0 = const()[name = string("op_3624_begin_0"), val = tensor<int32, [4]>([0, 560, 0, 0])];
            tensor<int32, [4]> var_3624_end_0 = const()[name = string("op_3624_end_0"), val = tensor<int32, [4]>([1, 1, 1, 1024])];
            tensor<bool, [4]> var_3624_end_mask_0 = const()[name = string("op_3624_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3624_cast_fp16 = slice_by_index(begin = var_3624_begin_0, end = var_3624_end_0, end_mask = var_3624_end_mask_0, x = q_25_cast_fp16)[name = string("op_3624_cast_fp16")];
            tensor<int32, [4]> k_51_perm_0 = const()[name = string("k_51_perm_0"), val = tensor<int32, [4]>([0, 3, 2, 1])];
            tensor<int32, [4]> var_3631_begin_0 = const()[name = string("op_3631_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_3631_end_0 = const()[name = string("op_3631_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 80])];
            tensor<bool, [4]> var_3631_end_mask_0 = const()[name = string("op_3631_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 640]> k_51_cast_fp16 = transpose(perm = k_51_perm_0, x = k_49_cast_fp16)[name = string("transpose_5")];
            tensor<fp16, [1, 1024, 1, 80]> var_3631_cast_fp16 = slice_by_index(begin = var_3631_begin_0, end = var_3631_end_0, end_mask = var_3631_end_mask_0, x = k_51_cast_fp16)[name = string("op_3631_cast_fp16")];
            tensor<int32, [4]> var_3635_begin_0 = const()[name = string("op_3635_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 80])];
            tensor<int32, [4]> var_3635_end_0 = const()[name = string("op_3635_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 160])];
            tensor<bool, [4]> var_3635_end_mask_0 = const()[name = string("op_3635_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 80]> var_3635_cast_fp16 = slice_by_index(begin = var_3635_begin_0, end = var_3635_end_0, end_mask = var_3635_end_mask_0, x = k_51_cast_fp16)[name = string("op_3635_cast_fp16")];
            tensor<int32, [4]> var_3639_begin_0 = const()[name = string("op_3639_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 160])];
            tensor<int32, [4]> var_3639_end_0 = const()[name = string("op_3639_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 240])];
            tensor<bool, [4]> var_3639_end_mask_0 = const()[name = string("op_3639_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 80]> var_3639_cast_fp16 = slice_by_index(begin = var_3639_begin_0, end = var_3639_end_0, end_mask = var_3639_end_mask_0, x = k_51_cast_fp16)[name = string("op_3639_cast_fp16")];
            tensor<int32, [4]> var_3643_begin_0 = const()[name = string("op_3643_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 240])];
            tensor<int32, [4]> var_3643_end_0 = const()[name = string("op_3643_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 320])];
            tensor<bool, [4]> var_3643_end_mask_0 = const()[name = string("op_3643_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 80]> var_3643_cast_fp16 = slice_by_index(begin = var_3643_begin_0, end = var_3643_end_0, end_mask = var_3643_end_mask_0, x = k_51_cast_fp16)[name = string("op_3643_cast_fp16")];
            tensor<int32, [4]> var_3647_begin_0 = const()[name = string("op_3647_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 320])];
            tensor<int32, [4]> var_3647_end_0 = const()[name = string("op_3647_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 400])];
            tensor<bool, [4]> var_3647_end_mask_0 = const()[name = string("op_3647_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 80]> var_3647_cast_fp16 = slice_by_index(begin = var_3647_begin_0, end = var_3647_end_0, end_mask = var_3647_end_mask_0, x = k_51_cast_fp16)[name = string("op_3647_cast_fp16")];
            tensor<int32, [4]> var_3651_begin_0 = const()[name = string("op_3651_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 400])];
            tensor<int32, [4]> var_3651_end_0 = const()[name = string("op_3651_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 480])];
            tensor<bool, [4]> var_3651_end_mask_0 = const()[name = string("op_3651_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 80]> var_3651_cast_fp16 = slice_by_index(begin = var_3651_begin_0, end = var_3651_end_0, end_mask = var_3651_end_mask_0, x = k_51_cast_fp16)[name = string("op_3651_cast_fp16")];
            tensor<int32, [4]> var_3655_begin_0 = const()[name = string("op_3655_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 480])];
            tensor<int32, [4]> var_3655_end_0 = const()[name = string("op_3655_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 560])];
            tensor<bool, [4]> var_3655_end_mask_0 = const()[name = string("op_3655_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 1024, 1, 80]> var_3655_cast_fp16 = slice_by_index(begin = var_3655_begin_0, end = var_3655_end_0, end_mask = var_3655_end_mask_0, x = k_51_cast_fp16)[name = string("op_3655_cast_fp16")];
            tensor<int32, [4]> var_3659_begin_0 = const()[name = string("op_3659_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 560])];
            tensor<int32, [4]> var_3659_end_0 = const()[name = string("op_3659_end_0"), val = tensor<int32, [4]>([1, 1024, 1, 1])];
            tensor<bool, [4]> var_3659_end_mask_0 = const()[name = string("op_3659_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 1024, 1, 80]> var_3659_cast_fp16 = slice_by_index(begin = var_3659_begin_0, end = var_3659_end_0, end_mask = var_3659_end_mask_0, x = k_51_cast_fp16)[name = string("op_3659_cast_fp16")];
            tensor<int32, [4]> var_3661_begin_0 = const()[name = string("op_3661_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_3661_end_0 = const()[name = string("op_3661_end_0"), val = tensor<int32, [4]>([1, 80, 1, 1024])];
            tensor<bool, [4]> var_3661_end_mask_0 = const()[name = string("op_3661_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3661_cast_fp16 = slice_by_index(begin = var_3661_begin_0, end = var_3661_end_0, end_mask = var_3661_end_mask_0, x = v_25_cast_fp16)[name = string("op_3661_cast_fp16")];
            tensor<int32, [4]> var_3665_begin_0 = const()[name = string("op_3665_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_3665_end_0 = const()[name = string("op_3665_end_0"), val = tensor<int32, [4]>([1, 160, 1, 1024])];
            tensor<bool, [4]> var_3665_end_mask_0 = const()[name = string("op_3665_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3665_cast_fp16 = slice_by_index(begin = var_3665_begin_0, end = var_3665_end_0, end_mask = var_3665_end_mask_0, x = v_25_cast_fp16)[name = string("op_3665_cast_fp16")];
            tensor<int32, [4]> var_3669_begin_0 = const()[name = string("op_3669_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_3669_end_0 = const()[name = string("op_3669_end_0"), val = tensor<int32, [4]>([1, 240, 1, 1024])];
            tensor<bool, [4]> var_3669_end_mask_0 = const()[name = string("op_3669_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3669_cast_fp16 = slice_by_index(begin = var_3669_begin_0, end = var_3669_end_0, end_mask = var_3669_end_mask_0, x = v_25_cast_fp16)[name = string("op_3669_cast_fp16")];
            tensor<int32, [4]> var_3673_begin_0 = const()[name = string("op_3673_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_3673_end_0 = const()[name = string("op_3673_end_0"), val = tensor<int32, [4]>([1, 320, 1, 1024])];
            tensor<bool, [4]> var_3673_end_mask_0 = const()[name = string("op_3673_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3673_cast_fp16 = slice_by_index(begin = var_3673_begin_0, end = var_3673_end_0, end_mask = var_3673_end_mask_0, x = v_25_cast_fp16)[name = string("op_3673_cast_fp16")];
            tensor<int32, [4]> var_3677_begin_0 = const()[name = string("op_3677_begin_0"), val = tensor<int32, [4]>([0, 320, 0, 0])];
            tensor<int32, [4]> var_3677_end_0 = const()[name = string("op_3677_end_0"), val = tensor<int32, [4]>([1, 400, 1, 1024])];
            tensor<bool, [4]> var_3677_end_mask_0 = const()[name = string("op_3677_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3677_cast_fp16 = slice_by_index(begin = var_3677_begin_0, end = var_3677_end_0, end_mask = var_3677_end_mask_0, x = v_25_cast_fp16)[name = string("op_3677_cast_fp16")];
            tensor<int32, [4]> var_3681_begin_0 = const()[name = string("op_3681_begin_0"), val = tensor<int32, [4]>([0, 400, 0, 0])];
            tensor<int32, [4]> var_3681_end_0 = const()[name = string("op_3681_end_0"), val = tensor<int32, [4]>([1, 480, 1, 1024])];
            tensor<bool, [4]> var_3681_end_mask_0 = const()[name = string("op_3681_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3681_cast_fp16 = slice_by_index(begin = var_3681_begin_0, end = var_3681_end_0, end_mask = var_3681_end_mask_0, x = v_25_cast_fp16)[name = string("op_3681_cast_fp16")];
            tensor<int32, [4]> var_3685_begin_0 = const()[name = string("op_3685_begin_0"), val = tensor<int32, [4]>([0, 480, 0, 0])];
            tensor<int32, [4]> var_3685_end_0 = const()[name = string("op_3685_end_0"), val = tensor<int32, [4]>([1, 560, 1, 1024])];
            tensor<bool, [4]> var_3685_end_mask_0 = const()[name = string("op_3685_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3685_cast_fp16 = slice_by_index(begin = var_3685_begin_0, end = var_3685_end_0, end_mask = var_3685_end_mask_0, x = v_25_cast_fp16)[name = string("op_3685_cast_fp16")];
            tensor<int32, [4]> var_3689_begin_0 = const()[name = string("op_3689_begin_0"), val = tensor<int32, [4]>([0, 560, 0, 0])];
            tensor<int32, [4]> var_3689_end_0 = const()[name = string("op_3689_end_0"), val = tensor<int32, [4]>([1, 1, 1, 1024])];
            tensor<bool, [4]> var_3689_end_mask_0 = const()[name = string("op_3689_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3689_cast_fp16 = slice_by_index(begin = var_3689_begin_0, end = var_3689_end_0, end_mask = var_3689_end_mask_0, x = v_25_cast_fp16)[name = string("op_3689_cast_fp16")];
            string var_3693_equation_0 = const()[name = string("op_3693_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3693_cast_fp16 = einsum(equation = var_3693_equation_0, values = (var_3631_cast_fp16, var_3596_cast_fp16))[name = string("op_3693_cast_fp16")];
            fp16 var_3694_to_fp16 = const()[name = string("op_3694_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_193_cast_fp16 = mul(x = var_3693_cast_fp16, y = var_3694_to_fp16)[name = string("aw_193_cast_fp16")];
            string var_3697_equation_0 = const()[name = string("op_3697_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3697_cast_fp16 = einsum(equation = var_3697_equation_0, values = (var_3635_cast_fp16, var_3600_cast_fp16))[name = string("op_3697_cast_fp16")];
            fp16 var_3698_to_fp16 = const()[name = string("op_3698_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_195_cast_fp16 = mul(x = var_3697_cast_fp16, y = var_3698_to_fp16)[name = string("aw_195_cast_fp16")];
            string var_3701_equation_0 = const()[name = string("op_3701_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3701_cast_fp16 = einsum(equation = var_3701_equation_0, values = (var_3639_cast_fp16, var_3604_cast_fp16))[name = string("op_3701_cast_fp16")];
            fp16 var_3702_to_fp16 = const()[name = string("op_3702_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_197_cast_fp16 = mul(x = var_3701_cast_fp16, y = var_3702_to_fp16)[name = string("aw_197_cast_fp16")];
            string var_3705_equation_0 = const()[name = string("op_3705_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3705_cast_fp16 = einsum(equation = var_3705_equation_0, values = (var_3643_cast_fp16, var_3608_cast_fp16))[name = string("op_3705_cast_fp16")];
            fp16 var_3706_to_fp16 = const()[name = string("op_3706_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_199_cast_fp16 = mul(x = var_3705_cast_fp16, y = var_3706_to_fp16)[name = string("aw_199_cast_fp16")];
            string var_3709_equation_0 = const()[name = string("op_3709_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3709_cast_fp16 = einsum(equation = var_3709_equation_0, values = (var_3647_cast_fp16, var_3612_cast_fp16))[name = string("op_3709_cast_fp16")];
            fp16 var_3710_to_fp16 = const()[name = string("op_3710_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_201_cast_fp16 = mul(x = var_3709_cast_fp16, y = var_3710_to_fp16)[name = string("aw_201_cast_fp16")];
            string var_3713_equation_0 = const()[name = string("op_3713_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3713_cast_fp16 = einsum(equation = var_3713_equation_0, values = (var_3651_cast_fp16, var_3616_cast_fp16))[name = string("op_3713_cast_fp16")];
            fp16 var_3714_to_fp16 = const()[name = string("op_3714_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_203_cast_fp16 = mul(x = var_3713_cast_fp16, y = var_3714_to_fp16)[name = string("aw_203_cast_fp16")];
            string var_3717_equation_0 = const()[name = string("op_3717_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3717_cast_fp16 = einsum(equation = var_3717_equation_0, values = (var_3655_cast_fp16, var_3620_cast_fp16))[name = string("op_3717_cast_fp16")];
            fp16 var_3718_to_fp16 = const()[name = string("op_3718_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_205_cast_fp16 = mul(x = var_3717_cast_fp16, y = var_3718_to_fp16)[name = string("aw_205_cast_fp16")];
            string var_3721_equation_0 = const()[name = string("op_3721_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3721_cast_fp16 = einsum(equation = var_3721_equation_0, values = (var_3659_cast_fp16, var_3624_cast_fp16))[name = string("op_3721_cast_fp16")];
            fp16 var_3722_to_fp16 = const()[name = string("op_3722_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 1024, 1, 1024]> aw_207_cast_fp16 = mul(x = var_3721_cast_fp16, y = var_3722_to_fp16)[name = string("aw_207_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3724_cast_fp16 = softmax(axis = var_2929, x = aw_193_cast_fp16)[name = string("op_3724_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3725_cast_fp16 = softmax(axis = var_2929, x = aw_195_cast_fp16)[name = string("op_3725_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3726_cast_fp16 = softmax(axis = var_2929, x = aw_197_cast_fp16)[name = string("op_3726_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3727_cast_fp16 = softmax(axis = var_2929, x = aw_199_cast_fp16)[name = string("op_3727_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3728_cast_fp16 = softmax(axis = var_2929, x = aw_201_cast_fp16)[name = string("op_3728_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3729_cast_fp16 = softmax(axis = var_2929, x = aw_203_cast_fp16)[name = string("op_3729_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3730_cast_fp16 = softmax(axis = var_2929, x = aw_205_cast_fp16)[name = string("op_3730_cast_fp16")];
            tensor<fp16, [1, 1024, 1, 1024]> var_3731_cast_fp16 = softmax(axis = var_2929, x = aw_207_cast_fp16)[name = string("op_3731_cast_fp16")];
            string var_3733_equation_0 = const()[name = string("op_3733_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3733_cast_fp16 = einsum(equation = var_3733_equation_0, values = (var_3661_cast_fp16, var_3724_cast_fp16))[name = string("op_3733_cast_fp16")];
            string var_3735_equation_0 = const()[name = string("op_3735_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3735_cast_fp16 = einsum(equation = var_3735_equation_0, values = (var_3665_cast_fp16, var_3725_cast_fp16))[name = string("op_3735_cast_fp16")];
            string var_3737_equation_0 = const()[name = string("op_3737_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3737_cast_fp16 = einsum(equation = var_3737_equation_0, values = (var_3669_cast_fp16, var_3726_cast_fp16))[name = string("op_3737_cast_fp16")];
            string var_3739_equation_0 = const()[name = string("op_3739_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3739_cast_fp16 = einsum(equation = var_3739_equation_0, values = (var_3673_cast_fp16, var_3727_cast_fp16))[name = string("op_3739_cast_fp16")];
            string var_3741_equation_0 = const()[name = string("op_3741_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3741_cast_fp16 = einsum(equation = var_3741_equation_0, values = (var_3677_cast_fp16, var_3728_cast_fp16))[name = string("op_3741_cast_fp16")];
            string var_3743_equation_0 = const()[name = string("op_3743_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3743_cast_fp16 = einsum(equation = var_3743_equation_0, values = (var_3681_cast_fp16, var_3729_cast_fp16))[name = string("op_3743_cast_fp16")];
            string var_3745_equation_0 = const()[name = string("op_3745_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3745_cast_fp16 = einsum(equation = var_3745_equation_0, values = (var_3685_cast_fp16, var_3730_cast_fp16))[name = string("op_3745_cast_fp16")];
            string var_3747_equation_0 = const()[name = string("op_3747_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3747_cast_fp16 = einsum(equation = var_3747_equation_0, values = (var_3689_cast_fp16, var_3731_cast_fp16))[name = string("op_3747_cast_fp16")];
            bool input_189_interleave_0 = const()[name = string("input_189_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 640, 1, 1024]> input_189_cast_fp16 = concat(axis = var_2929, interleave = input_189_interleave_0, values = (var_3733_cast_fp16, var_3735_cast_fp16, var_3737_cast_fp16, var_3739_cast_fp16, var_3741_cast_fp16, var_3743_cast_fp16, var_3745_cast_fp16, var_3747_cast_fp16))[name = string("input_189_cast_fp16")];
            string var_3757_pad_type_0 = const()[name = string("op_3757_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_3757_strides_0 = const()[name = string("op_3757_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_3757_pad_0 = const()[name = string("op_3757_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_3757_dilations_0 = const()[name = string("op_3757_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3757_groups_0 = const()[name = string("op_3757_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_out_0_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_out_0_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(273949056)))];
            tensor<fp16, [640]> up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_out_0_bias_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_out_0_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(274768320)))];
            tensor<fp16, [1, 640, 1, 1024]> var_3757_cast_fp16 = conv(bias = up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_out_0_bias_to_fp16, dilations = var_3757_dilations_0, groups = var_3757_groups_0, pad = var_3757_pad_0, pad_type = var_3757_pad_type_0, strides = var_3757_strides_0, weight = up_blocks_1_attentions_1_transformer_blocks_0_attn1_to_out_0_weight_to_fp16, x = input_189_cast_fp16)[name = string("op_3757_cast_fp16")];
            tensor<fp16, [1, 640, 1, 1024]> inputs_39_cast_fp16 = add(x = var_3757_cast_fp16, y = inputs_37_cast_fp16)[name = string("inputs_39_cast_fp16")];
            tensor<int32, [1]> hidden_states_127_axes_0 = const()[name = string("hidden_states_127_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [640]> hidden_states_127_gamma_0_to_fp16 = const()[name = string("hidden_states_127_gamma_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(274769664)))];
            tensor<fp16, [640]> hidden_states_127_beta_0_to_fp16 = const()[name = string("hidden_states_127_beta_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(274771008)))];
            fp16 var_3767_to_fp16 = const()[name = string("op_3767_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 640, 1, 1024]> hidden_states_127_cast_fp16 = layer_norm(axes = hidden_states_127_axes_0, beta = hidden_states_127_beta_0_to_fp16, epsilon = var_3767_to_fp16, gamma = hidden_states_127_gamma_0_to_fp16, x = inputs_39_cast_fp16)[name = string("hidden_states_127_cast_fp16")];
            string q_27_pad_type_0 = const()[name = string("q_27_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> q_27_strides_0 = const()[name = string("q_27_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> q_27_pad_0 = const()[name = string("q_27_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> q_27_dilations_0 = const()[name = string("q_27_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 q_27_groups_0 = const()[name = string("q_27_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_q_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_q_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(274772352)))];
            tensor<fp16, [1, 640, 1, 1024]> q_27_cast_fp16 = conv(dilations = q_27_dilations_0, groups = q_27_groups_0, pad = q_27_pad_0, pad_type = q_27_pad_type_0, strides = q_27_strides_0, weight = up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_q_weight_to_fp16, x = hidden_states_127_cast_fp16)[name = string("q_27_cast_fp16")];
            string k_53_pad_type_0 = const()[name = string("k_53_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> k_53_strides_0 = const()[name = string("k_53_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> k_53_pad_0 = const()[name = string("k_53_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> k_53_dilations_0 = const()[name = string("k_53_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 k_53_groups_0 = const()[name = string("k_53_groups_0"), val = int32(1)];
            tensor<fp16, [640, 768, 1, 1]> up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_k_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_k_weight_to_fp16"), val = tensor<fp16, [640, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(275591616)))];
            tensor<fp16, [1, 640, 1, 77]> k_53_cast_fp16 = conv(dilations = k_53_dilations_0, groups = k_53_groups_0, pad = k_53_pad_0, pad_type = k_53_pad_type_0, strides = k_53_strides_0, weight = up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_k_weight_to_fp16, x = encoder_hidden_states)[name = string("k_53_cast_fp16")];
            string v_27_pad_type_0 = const()[name = string("v_27_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> v_27_strides_0 = const()[name = string("v_27_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> v_27_pad_0 = const()[name = string("v_27_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> v_27_dilations_0 = const()[name = string("v_27_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 v_27_groups_0 = const()[name = string("v_27_groups_0"), val = int32(1)];
            tensor<fp16, [640, 768, 1, 1]> up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_v_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_v_weight_to_fp16"), val = tensor<fp16, [640, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(276574720)))];
            tensor<fp16, [1, 640, 1, 77]> v_27_cast_fp16 = conv(dilations = v_27_dilations_0, groups = v_27_groups_0, pad = v_27_pad_0, pad_type = v_27_pad_type_0, strides = v_27_strides_0, weight = up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_v_weight_to_fp16, x = encoder_hidden_states)[name = string("v_27_cast_fp16")];
            tensor<int32, [4]> var_3800_begin_0 = const()[name = string("op_3800_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_3800_end_0 = const()[name = string("op_3800_end_0"), val = tensor<int32, [4]>([1, 80, 1, 1024])];
            tensor<bool, [4]> var_3800_end_mask_0 = const()[name = string("op_3800_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3800_cast_fp16 = slice_by_index(begin = var_3800_begin_0, end = var_3800_end_0, end_mask = var_3800_end_mask_0, x = q_27_cast_fp16)[name = string("op_3800_cast_fp16")];
            tensor<int32, [4]> var_3804_begin_0 = const()[name = string("op_3804_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_3804_end_0 = const()[name = string("op_3804_end_0"), val = tensor<int32, [4]>([1, 160, 1, 1024])];
            tensor<bool, [4]> var_3804_end_mask_0 = const()[name = string("op_3804_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3804_cast_fp16 = slice_by_index(begin = var_3804_begin_0, end = var_3804_end_0, end_mask = var_3804_end_mask_0, x = q_27_cast_fp16)[name = string("op_3804_cast_fp16")];
            tensor<int32, [4]> var_3808_begin_0 = const()[name = string("op_3808_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_3808_end_0 = const()[name = string("op_3808_end_0"), val = tensor<int32, [4]>([1, 240, 1, 1024])];
            tensor<bool, [4]> var_3808_end_mask_0 = const()[name = string("op_3808_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3808_cast_fp16 = slice_by_index(begin = var_3808_begin_0, end = var_3808_end_0, end_mask = var_3808_end_mask_0, x = q_27_cast_fp16)[name = string("op_3808_cast_fp16")];
            tensor<int32, [4]> var_3812_begin_0 = const()[name = string("op_3812_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_3812_end_0 = const()[name = string("op_3812_end_0"), val = tensor<int32, [4]>([1, 320, 1, 1024])];
            tensor<bool, [4]> var_3812_end_mask_0 = const()[name = string("op_3812_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3812_cast_fp16 = slice_by_index(begin = var_3812_begin_0, end = var_3812_end_0, end_mask = var_3812_end_mask_0, x = q_27_cast_fp16)[name = string("op_3812_cast_fp16")];
            tensor<int32, [4]> var_3816_begin_0 = const()[name = string("op_3816_begin_0"), val = tensor<int32, [4]>([0, 320, 0, 0])];
            tensor<int32, [4]> var_3816_end_0 = const()[name = string("op_3816_end_0"), val = tensor<int32, [4]>([1, 400, 1, 1024])];
            tensor<bool, [4]> var_3816_end_mask_0 = const()[name = string("op_3816_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3816_cast_fp16 = slice_by_index(begin = var_3816_begin_0, end = var_3816_end_0, end_mask = var_3816_end_mask_0, x = q_27_cast_fp16)[name = string("op_3816_cast_fp16")];
            tensor<int32, [4]> var_3820_begin_0 = const()[name = string("op_3820_begin_0"), val = tensor<int32, [4]>([0, 400, 0, 0])];
            tensor<int32, [4]> var_3820_end_0 = const()[name = string("op_3820_end_0"), val = tensor<int32, [4]>([1, 480, 1, 1024])];
            tensor<bool, [4]> var_3820_end_mask_0 = const()[name = string("op_3820_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3820_cast_fp16 = slice_by_index(begin = var_3820_begin_0, end = var_3820_end_0, end_mask = var_3820_end_mask_0, x = q_27_cast_fp16)[name = string("op_3820_cast_fp16")];
            tensor<int32, [4]> var_3824_begin_0 = const()[name = string("op_3824_begin_0"), val = tensor<int32, [4]>([0, 480, 0, 0])];
            tensor<int32, [4]> var_3824_end_0 = const()[name = string("op_3824_end_0"), val = tensor<int32, [4]>([1, 560, 1, 1024])];
            tensor<bool, [4]> var_3824_end_mask_0 = const()[name = string("op_3824_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3824_cast_fp16 = slice_by_index(begin = var_3824_begin_0, end = var_3824_end_0, end_mask = var_3824_end_mask_0, x = q_27_cast_fp16)[name = string("op_3824_cast_fp16")];
            tensor<int32, [4]> var_3828_begin_0 = const()[name = string("op_3828_begin_0"), val = tensor<int32, [4]>([0, 560, 0, 0])];
            tensor<int32, [4]> var_3828_end_0 = const()[name = string("op_3828_end_0"), val = tensor<int32, [4]>([1, 1, 1, 1024])];
            tensor<bool, [4]> var_3828_end_mask_0 = const()[name = string("op_3828_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 80, 1, 1024]> var_3828_cast_fp16 = slice_by_index(begin = var_3828_begin_0, end = var_3828_end_0, end_mask = var_3828_end_mask_0, x = q_27_cast_fp16)[name = string("op_3828_cast_fp16")];
            tensor<int32, [4]> k_55_perm_0 = const()[name = string("k_55_perm_0"), val = tensor<int32, [4]>([0, 3, 2, 1])];
            tensor<int32, [4]> var_3835_begin_0 = const()[name = string("op_3835_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_3835_end_0 = const()[name = string("op_3835_end_0"), val = tensor<int32, [4]>([1, 77, 1, 80])];
            tensor<bool, [4]> var_3835_end_mask_0 = const()[name = string("op_3835_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 640]> k_55_cast_fp16 = transpose(perm = k_55_perm_0, x = k_53_cast_fp16)[name = string("transpose_4")];
            tensor<fp16, [1, 77, 1, 80]> var_3835_cast_fp16 = slice_by_index(begin = var_3835_begin_0, end = var_3835_end_0, end_mask = var_3835_end_mask_0, x = k_55_cast_fp16)[name = string("op_3835_cast_fp16")];
            tensor<int32, [4]> var_3839_begin_0 = const()[name = string("op_3839_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 80])];
            tensor<int32, [4]> var_3839_end_0 = const()[name = string("op_3839_end_0"), val = tensor<int32, [4]>([1, 77, 1, 160])];
            tensor<bool, [4]> var_3839_end_mask_0 = const()[name = string("op_3839_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 80]> var_3839_cast_fp16 = slice_by_index(begin = var_3839_begin_0, end = var_3839_end_0, end_mask = var_3839_end_mask_0, x = k_55_cast_fp16)[name = string("op_3839_cast_fp16")];
            tensor<int32, [4]> var_3843_begin_0 = const()[name = string("op_3843_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 160])];
            tensor<int32, [4]> var_3843_end_0 = const()[name = string("op_3843_end_0"), val = tensor<int32, [4]>([1, 77, 1, 240])];
            tensor<bool, [4]> var_3843_end_mask_0 = const()[name = string("op_3843_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 80]> var_3843_cast_fp16 = slice_by_index(begin = var_3843_begin_0, end = var_3843_end_0, end_mask = var_3843_end_mask_0, x = k_55_cast_fp16)[name = string("op_3843_cast_fp16")];
            tensor<int32, [4]> var_3847_begin_0 = const()[name = string("op_3847_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 240])];
            tensor<int32, [4]> var_3847_end_0 = const()[name = string("op_3847_end_0"), val = tensor<int32, [4]>([1, 77, 1, 320])];
            tensor<bool, [4]> var_3847_end_mask_0 = const()[name = string("op_3847_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 80]> var_3847_cast_fp16 = slice_by_index(begin = var_3847_begin_0, end = var_3847_end_0, end_mask = var_3847_end_mask_0, x = k_55_cast_fp16)[name = string("op_3847_cast_fp16")];
            tensor<int32, [4]> var_3851_begin_0 = const()[name = string("op_3851_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 320])];
            tensor<int32, [4]> var_3851_end_0 = const()[name = string("op_3851_end_0"), val = tensor<int32, [4]>([1, 77, 1, 400])];
            tensor<bool, [4]> var_3851_end_mask_0 = const()[name = string("op_3851_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 80]> var_3851_cast_fp16 = slice_by_index(begin = var_3851_begin_0, end = var_3851_end_0, end_mask = var_3851_end_mask_0, x = k_55_cast_fp16)[name = string("op_3851_cast_fp16")];
            tensor<int32, [4]> var_3855_begin_0 = const()[name = string("op_3855_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 400])];
            tensor<int32, [4]> var_3855_end_0 = const()[name = string("op_3855_end_0"), val = tensor<int32, [4]>([1, 77, 1, 480])];
            tensor<bool, [4]> var_3855_end_mask_0 = const()[name = string("op_3855_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 80]> var_3855_cast_fp16 = slice_by_index(begin = var_3855_begin_0, end = var_3855_end_0, end_mask = var_3855_end_mask_0, x = k_55_cast_fp16)[name = string("op_3855_cast_fp16")];
            tensor<int32, [4]> var_3859_begin_0 = const()[name = string("op_3859_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 480])];
            tensor<int32, [4]> var_3859_end_0 = const()[name = string("op_3859_end_0"), val = tensor<int32, [4]>([1, 77, 1, 560])];
            tensor<bool, [4]> var_3859_end_mask_0 = const()[name = string("op_3859_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 80]> var_3859_cast_fp16 = slice_by_index(begin = var_3859_begin_0, end = var_3859_end_0, end_mask = var_3859_end_mask_0, x = k_55_cast_fp16)[name = string("op_3859_cast_fp16")];
            tensor<int32, [4]> var_3863_begin_0 = const()[name = string("op_3863_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 560])];
            tensor<int32, [4]> var_3863_end_0 = const()[name = string("op_3863_end_0"), val = tensor<int32, [4]>([1, 77, 1, 1])];
            tensor<bool, [4]> var_3863_end_mask_0 = const()[name = string("op_3863_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 77, 1, 80]> var_3863_cast_fp16 = slice_by_index(begin = var_3863_begin_0, end = var_3863_end_0, end_mask = var_3863_end_mask_0, x = k_55_cast_fp16)[name = string("op_3863_cast_fp16")];
            tensor<int32, [4]> var_3865_begin_0 = const()[name = string("op_3865_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_3865_end_0 = const()[name = string("op_3865_end_0"), val = tensor<int32, [4]>([1, 80, 1, 77])];
            tensor<bool, [4]> var_3865_end_mask_0 = const()[name = string("op_3865_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3865_cast_fp16 = slice_by_index(begin = var_3865_begin_0, end = var_3865_end_0, end_mask = var_3865_end_mask_0, x = v_27_cast_fp16)[name = string("op_3865_cast_fp16")];
            tensor<int32, [4]> var_3869_begin_0 = const()[name = string("op_3869_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_3869_end_0 = const()[name = string("op_3869_end_0"), val = tensor<int32, [4]>([1, 160, 1, 77])];
            tensor<bool, [4]> var_3869_end_mask_0 = const()[name = string("op_3869_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3869_cast_fp16 = slice_by_index(begin = var_3869_begin_0, end = var_3869_end_0, end_mask = var_3869_end_mask_0, x = v_27_cast_fp16)[name = string("op_3869_cast_fp16")];
            tensor<int32, [4]> var_3873_begin_0 = const()[name = string("op_3873_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_3873_end_0 = const()[name = string("op_3873_end_0"), val = tensor<int32, [4]>([1, 240, 1, 77])];
            tensor<bool, [4]> var_3873_end_mask_0 = const()[name = string("op_3873_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3873_cast_fp16 = slice_by_index(begin = var_3873_begin_0, end = var_3873_end_0, end_mask = var_3873_end_mask_0, x = v_27_cast_fp16)[name = string("op_3873_cast_fp16")];
            tensor<int32, [4]> var_3877_begin_0 = const()[name = string("op_3877_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_3877_end_0 = const()[name = string("op_3877_end_0"), val = tensor<int32, [4]>([1, 320, 1, 77])];
            tensor<bool, [4]> var_3877_end_mask_0 = const()[name = string("op_3877_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3877_cast_fp16 = slice_by_index(begin = var_3877_begin_0, end = var_3877_end_0, end_mask = var_3877_end_mask_0, x = v_27_cast_fp16)[name = string("op_3877_cast_fp16")];
            tensor<int32, [4]> var_3881_begin_0 = const()[name = string("op_3881_begin_0"), val = tensor<int32, [4]>([0, 320, 0, 0])];
            tensor<int32, [4]> var_3881_end_0 = const()[name = string("op_3881_end_0"), val = tensor<int32, [4]>([1, 400, 1, 77])];
            tensor<bool, [4]> var_3881_end_mask_0 = const()[name = string("op_3881_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3881_cast_fp16 = slice_by_index(begin = var_3881_begin_0, end = var_3881_end_0, end_mask = var_3881_end_mask_0, x = v_27_cast_fp16)[name = string("op_3881_cast_fp16")];
            tensor<int32, [4]> var_3885_begin_0 = const()[name = string("op_3885_begin_0"), val = tensor<int32, [4]>([0, 400, 0, 0])];
            tensor<int32, [4]> var_3885_end_0 = const()[name = string("op_3885_end_0"), val = tensor<int32, [4]>([1, 480, 1, 77])];
            tensor<bool, [4]> var_3885_end_mask_0 = const()[name = string("op_3885_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3885_cast_fp16 = slice_by_index(begin = var_3885_begin_0, end = var_3885_end_0, end_mask = var_3885_end_mask_0, x = v_27_cast_fp16)[name = string("op_3885_cast_fp16")];
            tensor<int32, [4]> var_3889_begin_0 = const()[name = string("op_3889_begin_0"), val = tensor<int32, [4]>([0, 480, 0, 0])];
            tensor<int32, [4]> var_3889_end_0 = const()[name = string("op_3889_end_0"), val = tensor<int32, [4]>([1, 560, 1, 77])];
            tensor<bool, [4]> var_3889_end_mask_0 = const()[name = string("op_3889_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3889_cast_fp16 = slice_by_index(begin = var_3889_begin_0, end = var_3889_end_0, end_mask = var_3889_end_mask_0, x = v_27_cast_fp16)[name = string("op_3889_cast_fp16")];
            tensor<int32, [4]> var_3893_begin_0 = const()[name = string("op_3893_begin_0"), val = tensor<int32, [4]>([0, 560, 0, 0])];
            tensor<int32, [4]> var_3893_end_0 = const()[name = string("op_3893_end_0"), val = tensor<int32, [4]>([1, 1, 1, 77])];
            tensor<bool, [4]> var_3893_end_mask_0 = const()[name = string("op_3893_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 80, 1, 77]> var_3893_cast_fp16 = slice_by_index(begin = var_3893_begin_0, end = var_3893_end_0, end_mask = var_3893_end_mask_0, x = v_27_cast_fp16)[name = string("op_3893_cast_fp16")];
            string var_3897_equation_0 = const()[name = string("op_3897_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3897_cast_fp16 = einsum(equation = var_3897_equation_0, values = (var_3835_cast_fp16, var_3800_cast_fp16))[name = string("op_3897_cast_fp16")];
            fp16 var_3898_to_fp16 = const()[name = string("op_3898_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_209_cast_fp16 = mul(x = var_3897_cast_fp16, y = var_3898_to_fp16)[name = string("aw_209_cast_fp16")];
            string var_3901_equation_0 = const()[name = string("op_3901_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3901_cast_fp16 = einsum(equation = var_3901_equation_0, values = (var_3839_cast_fp16, var_3804_cast_fp16))[name = string("op_3901_cast_fp16")];
            fp16 var_3902_to_fp16 = const()[name = string("op_3902_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_211_cast_fp16 = mul(x = var_3901_cast_fp16, y = var_3902_to_fp16)[name = string("aw_211_cast_fp16")];
            string var_3905_equation_0 = const()[name = string("op_3905_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3905_cast_fp16 = einsum(equation = var_3905_equation_0, values = (var_3843_cast_fp16, var_3808_cast_fp16))[name = string("op_3905_cast_fp16")];
            fp16 var_3906_to_fp16 = const()[name = string("op_3906_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_213_cast_fp16 = mul(x = var_3905_cast_fp16, y = var_3906_to_fp16)[name = string("aw_213_cast_fp16")];
            string var_3909_equation_0 = const()[name = string("op_3909_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3909_cast_fp16 = einsum(equation = var_3909_equation_0, values = (var_3847_cast_fp16, var_3812_cast_fp16))[name = string("op_3909_cast_fp16")];
            fp16 var_3910_to_fp16 = const()[name = string("op_3910_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_215_cast_fp16 = mul(x = var_3909_cast_fp16, y = var_3910_to_fp16)[name = string("aw_215_cast_fp16")];
            string var_3913_equation_0 = const()[name = string("op_3913_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3913_cast_fp16 = einsum(equation = var_3913_equation_0, values = (var_3851_cast_fp16, var_3816_cast_fp16))[name = string("op_3913_cast_fp16")];
            fp16 var_3914_to_fp16 = const()[name = string("op_3914_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_217_cast_fp16 = mul(x = var_3913_cast_fp16, y = var_3914_to_fp16)[name = string("aw_217_cast_fp16")];
            string var_3917_equation_0 = const()[name = string("op_3917_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3917_cast_fp16 = einsum(equation = var_3917_equation_0, values = (var_3855_cast_fp16, var_3820_cast_fp16))[name = string("op_3917_cast_fp16")];
            fp16 var_3918_to_fp16 = const()[name = string("op_3918_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_219_cast_fp16 = mul(x = var_3917_cast_fp16, y = var_3918_to_fp16)[name = string("aw_219_cast_fp16")];
            string var_3921_equation_0 = const()[name = string("op_3921_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3921_cast_fp16 = einsum(equation = var_3921_equation_0, values = (var_3859_cast_fp16, var_3824_cast_fp16))[name = string("op_3921_cast_fp16")];
            fp16 var_3922_to_fp16 = const()[name = string("op_3922_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_221_cast_fp16 = mul(x = var_3921_cast_fp16, y = var_3922_to_fp16)[name = string("aw_221_cast_fp16")];
            string var_3925_equation_0 = const()[name = string("op_3925_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 1024]> var_3925_cast_fp16 = einsum(equation = var_3925_equation_0, values = (var_3863_cast_fp16, var_3828_cast_fp16))[name = string("op_3925_cast_fp16")];
            fp16 var_3926_to_fp16 = const()[name = string("op_3926_to_fp16"), val = fp16(0x1.cap-4)];
            tensor<fp16, [1, 77, 1, 1024]> aw_223_cast_fp16 = mul(x = var_3925_cast_fp16, y = var_3926_to_fp16)[name = string("aw_223_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3928_cast_fp16 = softmax(axis = var_2929, x = aw_209_cast_fp16)[name = string("op_3928_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3929_cast_fp16 = softmax(axis = var_2929, x = aw_211_cast_fp16)[name = string("op_3929_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3930_cast_fp16 = softmax(axis = var_2929, x = aw_213_cast_fp16)[name = string("op_3930_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3931_cast_fp16 = softmax(axis = var_2929, x = aw_215_cast_fp16)[name = string("op_3931_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3932_cast_fp16 = softmax(axis = var_2929, x = aw_217_cast_fp16)[name = string("op_3932_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3933_cast_fp16 = softmax(axis = var_2929, x = aw_219_cast_fp16)[name = string("op_3933_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3934_cast_fp16 = softmax(axis = var_2929, x = aw_221_cast_fp16)[name = string("op_3934_cast_fp16")];
            tensor<fp16, [1, 77, 1, 1024]> var_3935_cast_fp16 = softmax(axis = var_2929, x = aw_223_cast_fp16)[name = string("op_3935_cast_fp16")];
            string var_3937_equation_0 = const()[name = string("op_3937_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3937_cast_fp16 = einsum(equation = var_3937_equation_0, values = (var_3865_cast_fp16, var_3928_cast_fp16))[name = string("op_3937_cast_fp16")];
            string var_3939_equation_0 = const()[name = string("op_3939_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3939_cast_fp16 = einsum(equation = var_3939_equation_0, values = (var_3869_cast_fp16, var_3929_cast_fp16))[name = string("op_3939_cast_fp16")];
            string var_3941_equation_0 = const()[name = string("op_3941_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3941_cast_fp16 = einsum(equation = var_3941_equation_0, values = (var_3873_cast_fp16, var_3930_cast_fp16))[name = string("op_3941_cast_fp16")];
            string var_3943_equation_0 = const()[name = string("op_3943_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3943_cast_fp16 = einsum(equation = var_3943_equation_0, values = (var_3877_cast_fp16, var_3931_cast_fp16))[name = string("op_3943_cast_fp16")];
            string var_3945_equation_0 = const()[name = string("op_3945_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3945_cast_fp16 = einsum(equation = var_3945_equation_0, values = (var_3881_cast_fp16, var_3932_cast_fp16))[name = string("op_3945_cast_fp16")];
            string var_3947_equation_0 = const()[name = string("op_3947_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3947_cast_fp16 = einsum(equation = var_3947_equation_0, values = (var_3885_cast_fp16, var_3933_cast_fp16))[name = string("op_3947_cast_fp16")];
            string var_3949_equation_0 = const()[name = string("op_3949_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3949_cast_fp16 = einsum(equation = var_3949_equation_0, values = (var_3889_cast_fp16, var_3934_cast_fp16))[name = string("op_3949_cast_fp16")];
            string var_3951_equation_0 = const()[name = string("op_3951_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 80, 1, 1024]> var_3951_cast_fp16 = einsum(equation = var_3951_equation_0, values = (var_3893_cast_fp16, var_3935_cast_fp16))[name = string("op_3951_cast_fp16")];
            bool input_191_interleave_0 = const()[name = string("input_191_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 640, 1, 1024]> input_191_cast_fp16 = concat(axis = var_2929, interleave = input_191_interleave_0, values = (var_3937_cast_fp16, var_3939_cast_fp16, var_3941_cast_fp16, var_3943_cast_fp16, var_3945_cast_fp16, var_3947_cast_fp16, var_3949_cast_fp16, var_3951_cast_fp16))[name = string("input_191_cast_fp16")];
            string var_3961_pad_type_0 = const()[name = string("op_3961_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_3961_strides_0 = const()[name = string("op_3961_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_3961_pad_0 = const()[name = string("op_3961_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_3961_dilations_0 = const()[name = string("op_3961_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3961_groups_0 = const()[name = string("op_3961_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_out_0_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_out_0_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(277557824)))];
            tensor<fp16, [640]> up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_out_0_bias_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_out_0_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(278377088)))];
            tensor<fp16, [1, 640, 1, 1024]> var_3961_cast_fp16 = conv(bias = up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_out_0_bias_to_fp16, dilations = var_3961_dilations_0, groups = var_3961_groups_0, pad = var_3961_pad_0, pad_type = var_3961_pad_type_0, strides = var_3961_strides_0, weight = up_blocks_1_attentions_1_transformer_blocks_0_attn2_to_out_0_weight_to_fp16, x = input_191_cast_fp16)[name = string("op_3961_cast_fp16")];
            tensor<fp16, [1, 640, 1, 1024]> inputs_41_cast_fp16 = add(x = var_3961_cast_fp16, y = inputs_39_cast_fp16)[name = string("inputs_41_cast_fp16")];
            tensor<int32, [1]> input_193_axes_0 = const()[name = string("input_193_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [640]> input_193_gamma_0_to_fp16 = const()[name = string("input_193_gamma_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(278378432)))];
            tensor<fp16, [640]> input_193_beta_0_to_fp16 = const()[name = string("input_193_beta_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(278379776)))];
            fp16 var_3971_to_fp16 = const()[name = string("op_3971_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 640, 1, 1024]> input_193_cast_fp16 = layer_norm(axes = input_193_axes_0, beta = input_193_beta_0_to_fp16, epsilon = var_3971_to_fp16, gamma = input_193_gamma_0_to_fp16, x = inputs_41_cast_fp16)[name = string("input_193_cast_fp16")];
            string var_3991_pad_type_0 = const()[name = string("op_3991_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_3991_strides_0 = const()[name = string("op_3991_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_3991_pad_0 = const()[name = string("op_3991_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_3991_dilations_0 = const()[name = string("op_3991_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3991_groups_0 = const()[name = string("op_3991_groups_0"), val = int32(1)];
            tensor<fp16, [5120, 640, 1, 1]> up_blocks_1_attentions_1_transformer_blocks_0_ff_net_0_proj_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_ff_net_0_proj_weight_to_fp16"), val = tensor<fp16, [5120, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(278381120)))];
            tensor<fp16, [5120]> up_blocks_1_attentions_1_transformer_blocks_0_ff_net_0_proj_bias_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_ff_net_0_proj_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(284934784)))];
            tensor<fp16, [1, 5120, 1, 1024]> var_3991_cast_fp16 = conv(bias = up_blocks_1_attentions_1_transformer_blocks_0_ff_net_0_proj_bias_to_fp16, dilations = var_3991_dilations_0, groups = var_3991_groups_0, pad = var_3991_pad_0, pad_type = var_3991_pad_type_0, strides = var_3991_strides_0, weight = up_blocks_1_attentions_1_transformer_blocks_0_ff_net_0_proj_weight_to_fp16, x = input_193_cast_fp16)[name = string("op_3991_cast_fp16")];
            tensor<int32, [2]> var_3992_split_sizes_0 = const()[name = string("op_3992_split_sizes_0"), val = tensor<int32, [2]>([2560, 2560])];
            int32 var_3992_axis_0 = const()[name = string("op_3992_axis_0"), val = int32(1)];
            tensor<fp16, [1, 2560, 1, 1024]> var_3992_cast_fp16_0, tensor<fp16, [1, 2560, 1, 1024]> var_3992_cast_fp16_1 = split(axis = var_3992_axis_0, split_sizes = var_3992_split_sizes_0, x = var_3991_cast_fp16)[name = string("op_3992_cast_fp16")];
            string var_3994_mode_0 = const()[name = string("op_3994_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 2560, 1, 1024]> var_3994_cast_fp16 = gelu(mode = var_3994_mode_0, x = var_3992_cast_fp16_1)[name = string("op_3994_cast_fp16")];
            tensor<fp16, [1, 2560, 1, 1024]> input_195_cast_fp16 = mul(x = var_3992_cast_fp16_0, y = var_3994_cast_fp16)[name = string("input_195_cast_fp16")];
            string var_4002_pad_type_0 = const()[name = string("op_4002_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_4002_strides_0 = const()[name = string("op_4002_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_4002_pad_0 = const()[name = string("op_4002_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_4002_dilations_0 = const()[name = string("op_4002_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_4002_groups_0 = const()[name = string("op_4002_groups_0"), val = int32(1)];
            tensor<fp16, [640, 2560, 1, 1]> up_blocks_1_attentions_1_transformer_blocks_0_ff_net_2_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_ff_net_2_weight_to_fp16"), val = tensor<fp16, [640, 2560, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(284945088)))];
            tensor<fp16, [640]> up_blocks_1_attentions_1_transformer_blocks_0_ff_net_2_bias_to_fp16 = const()[name = string("up_blocks_1_attentions_1_transformer_blocks_0_ff_net_2_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288221952)))];
            tensor<fp16, [1, 640, 1, 1024]> var_4002_cast_fp16 = conv(bias = up_blocks_1_attentions_1_transformer_blocks_0_ff_net_2_bias_to_fp16, dilations = var_4002_dilations_0, groups = var_4002_groups_0, pad = var_4002_pad_0, pad_type = var_4002_pad_type_0, strides = var_4002_strides_0, weight = up_blocks_1_attentions_1_transformer_blocks_0_ff_net_2_weight_to_fp16, x = input_195_cast_fp16)[name = string("op_4002_cast_fp16")];
            tensor<fp16, [1, 640, 1, 1024]> hidden_states_131_cast_fp16 = add(x = var_4002_cast_fp16, y = inputs_41_cast_fp16)[name = string("hidden_states_131_cast_fp16")];
            tensor<int32, [4]> var_4004 = const()[name = string("op_4004"), val = tensor<int32, [4]>([1, 640, 32, 32])];
            tensor<fp16, [1, 640, 32, 32]> input_197_cast_fp16 = reshape(shape = var_4004, x = hidden_states_131_cast_fp16)[name = string("input_197_cast_fp16")];
            string hidden_states_133_pad_type_0 = const()[name = string("hidden_states_133_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> hidden_states_133_strides_0 = const()[name = string("hidden_states_133_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> hidden_states_133_pad_0 = const()[name = string("hidden_states_133_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> hidden_states_133_dilations_0 = const()[name = string("hidden_states_133_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_133_groups_0 = const()[name = string("hidden_states_133_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 1, 1]> up_blocks_1_attentions_1_proj_out_weight_to_fp16 = const()[name = string("up_blocks_1_attentions_1_proj_out_weight_to_fp16"), val = tensor<fp16, [640, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288223296)))];
            tensor<fp16, [640]> up_blocks_1_attentions_1_proj_out_bias_to_fp16 = const()[name = string("up_blocks_1_attentions_1_proj_out_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(289042560)))];
            tensor<fp16, [1, 640, 32, 32]> hidden_states_133_cast_fp16 = conv(bias = up_blocks_1_attentions_1_proj_out_bias_to_fp16, dilations = hidden_states_133_dilations_0, groups = hidden_states_133_groups_0, pad = hidden_states_133_pad_0, pad_type = hidden_states_133_pad_type_0, strides = hidden_states_133_strides_0, weight = up_blocks_1_attentions_1_proj_out_weight_to_fp16, x = input_197_cast_fp16)[name = string("hidden_states_133_cast_fp16")];
            tensor<fp16, [1, 640, 32, 32]> input_199_cast_fp16 = add(x = hidden_states_133_cast_fp16, y = hidden_states_121_cast_fp16)[name = string("input_199_cast_fp16")];
            fp32 input_201_scale_factor_height_0 = const()[name = string("input_201_scale_factor_height_0"), val = fp32(0x1p+1)];
            fp32 input_201_scale_factor_width_0 = const()[name = string("input_201_scale_factor_width_0"), val = fp32(0x1p+1)];
            tensor<fp16, [1, 640, 64, 64]> input_201_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = input_201_scale_factor_height_0, scale_factor_width = input_201_scale_factor_width_0, x = input_199_cast_fp16)[name = string("input_201_cast_fp16")];
            string hidden_states_135_pad_type_0 = const()[name = string("hidden_states_135_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> hidden_states_135_pad_0 = const()[name = string("hidden_states_135_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> hidden_states_135_strides_0 = const()[name = string("hidden_states_135_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> hidden_states_135_dilations_0 = const()[name = string("hidden_states_135_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_135_groups_0 = const()[name = string("hidden_states_135_groups_0"), val = int32(1)];
            tensor<fp16, [640, 640, 3, 3]> up_blocks_1_upsamplers_0_conv_weight_to_fp16 = const()[name = string("up_blocks_1_upsamplers_0_conv_weight_to_fp16"), val = tensor<fp16, [640, 640, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(289043904)))];
            tensor<fp16, [640]> up_blocks_1_upsamplers_0_conv_bias_to_fp16 = const()[name = string("up_blocks_1_upsamplers_0_conv_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296416768)))];
            tensor<fp16, [1, 640, 64, 64]> hidden_states_135_cast_fp16 = conv(bias = up_blocks_1_upsamplers_0_conv_bias_to_fp16, dilations = hidden_states_135_dilations_0, groups = hidden_states_135_groups_0, pad = hidden_states_135_pad_0, pad_type = hidden_states_135_pad_type_0, strides = hidden_states_135_strides_0, weight = up_blocks_1_upsamplers_0_conv_weight_to_fp16, x = input_201_cast_fp16)[name = string("hidden_states_135_cast_fp16")];
            int32 var_4045 = const()[name = string("op_4045"), val = int32(1)];
            bool input_203_interleave_0 = const()[name = string("input_203_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 320, 64, 64]> cast_2 = cast(dtype = cast_2_dtype_0, x = input_35_cast_fp16)[name = string("cast_7")];
            tensor<fp16, [1, 960, 64, 64]> input_203_cast_fp16 = concat(axis = var_4045, interleave = input_203_interleave_0, values = (hidden_states_135_cast_fp16, cast_2))[name = string("input_203_cast_fp16")];
            tensor<int32, [5]> reshape_84_shape_0 = const()[name = string("reshape_84_shape_0"), val = tensor<int32, [5]>([1, 32, 30, 64, 64])];
            tensor<fp16, [1, 32, 30, 64, 64]> reshape_84_cast_fp16 = reshape(shape = reshape_84_shape_0, x = input_203_cast_fp16)[name = string("reshape_84_cast_fp16")];
            tensor<int32, [3]> reduce_mean_63_axes_0 = const()[name = string("reduce_mean_63_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_63_keep_dims_0 = const()[name = string("reduce_mean_63_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_63_cast_fp16 = reduce_mean(axes = reduce_mean_63_axes_0, keep_dims = reduce_mean_63_keep_dims_0, x = reshape_84_cast_fp16)[name = string("reduce_mean_63_cast_fp16")];
            tensor<fp16, [1, 32, 30, 64, 64]> sub_42_cast_fp16 = sub(x = reshape_84_cast_fp16, y = reduce_mean_63_cast_fp16)[name = string("sub_42_cast_fp16")];
            tensor<fp16, [1, 32, 30, 64, 64]> square_21_cast_fp16 = square(x = sub_42_cast_fp16)[name = string("square_21_cast_fp16")];
            tensor<int32, [3]> reduce_mean_65_axes_0 = const()[name = string("reduce_mean_65_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_65_keep_dims_0 = const()[name = string("reduce_mean_65_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_65_cast_fp16 = reduce_mean(axes = reduce_mean_65_axes_0, keep_dims = reduce_mean_65_keep_dims_0, x = square_21_cast_fp16)[name = string("reduce_mean_65_cast_fp16")];
            fp16 add_42_y_0_to_fp16 = const()[name = string("add_42_y_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_42_cast_fp16 = add(x = reduce_mean_65_cast_fp16, y = add_42_y_0_to_fp16)[name = string("add_42_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_21_cast_fp16 = sqrt(x = add_42_cast_fp16)[name = string("sqrt_21_cast_fp16")];
            tensor<fp16, [1, 32, 30, 64, 64]> real_div_21_cast_fp16 = real_div(x = sub_42_cast_fp16, y = sqrt_21_cast_fp16)[name = string("real_div_21_cast_fp16")];
            tensor<int32, [4]> reshape_85_shape_0 = const()[name = string("reshape_85_shape_0"), val = tensor<int32, [4]>([1, 960, 64, 64])];
            tensor<fp16, [1, 960, 64, 64]> reshape_85_cast_fp16 = reshape(shape = reshape_85_shape_0, x = real_div_21_cast_fp16)[name = string("reshape_85_cast_fp16")];
            tensor<fp16, [960]> add_43_gamma_0_to_fp16 = const()[name = string("add_43_gamma_0_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296418112)))];
            tensor<fp16, [960]> add_43_beta_0_to_fp16 = const()[name = string("add_43_beta_0_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296420096)))];
            fp16 add_43_epsilon_0_to_fp16 = const()[name = string("add_43_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 960, 64, 64]> add_43_cast_fp16 = batch_norm(beta = add_43_beta_0_to_fp16, epsilon = add_43_epsilon_0_to_fp16, gamma = add_43_gamma_0_to_fp16, mean = add_37_mean_0_to_fp16, variance = add_37_variance_0_to_fp16, x = reshape_85_cast_fp16)[name = string("add_43_cast_fp16")];
            tensor<fp16, [1, 960, 64, 64]> input_207_cast_fp16 = silu(x = add_43_cast_fp16)[name = string("input_207_cast_fp16")];
            string hidden_states_137_pad_type_0 = const()[name = string("hidden_states_137_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> hidden_states_137_pad_0 = const()[name = string("hidden_states_137_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> hidden_states_137_strides_0 = const()[name = string("hidden_states_137_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> hidden_states_137_dilations_0 = const()[name = string("hidden_states_137_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_137_groups_0 = const()[name = string("hidden_states_137_groups_0"), val = int32(1)];
            tensor<fp16, [320, 960, 3, 3]> up_blocks_2_resnets_0_conv1_weight_to_fp16 = const()[name = string("up_blocks_2_resnets_0_conv1_weight_to_fp16"), val = tensor<fp16, [320, 960, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(296422080)))];
            tensor<fp16, [320]> up_blocks_2_resnets_0_conv1_bias_to_fp16 = const()[name = string("up_blocks_2_resnets_0_conv1_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(301951744)))];
            tensor<fp16, [1, 320, 64, 64]> hidden_states_137_cast_fp16 = conv(bias = up_blocks_2_resnets_0_conv1_bias_to_fp16, dilations = hidden_states_137_dilations_0, groups = hidden_states_137_groups_0, pad = hidden_states_137_pad_0, pad_type = hidden_states_137_pad_type_0, strides = hidden_states_137_strides_0, weight = up_blocks_2_resnets_0_conv1_weight_to_fp16, x = input_207_cast_fp16)[name = string("hidden_states_137_cast_fp16")];
            string temb_15_pad_type_0 = const()[name = string("temb_15_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> temb_15_strides_0 = const()[name = string("temb_15_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> temb_15_pad_0 = const()[name = string("temb_15_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> temb_15_dilations_0 = const()[name = string("temb_15_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 temb_15_groups_0 = const()[name = string("temb_15_groups_0"), val = int32(1)];
            tensor<fp16, [320, 1280, 1, 1]> up_blocks_2_resnets_0_time_emb_proj_weight_to_fp16 = const()[name = string("up_blocks_2_resnets_0_time_emb_proj_weight_to_fp16"), val = tensor<fp16, [320, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(301952448)))];
            tensor<fp16, [320]> up_blocks_2_resnets_0_time_emb_proj_bias_to_fp16 = const()[name = string("up_blocks_2_resnets_0_time_emb_proj_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(302771712)))];
            tensor<fp16, [1, 320, 1, 1]> temb_15_cast_fp16 = conv(bias = up_blocks_2_resnets_0_time_emb_proj_bias_to_fp16, dilations = temb_15_dilations_0, groups = temb_15_groups_0, pad = temb_15_pad_0, pad_type = temb_15_pad_type_0, strides = temb_15_strides_0, weight = up_blocks_2_resnets_0_time_emb_proj_weight_to_fp16, x = cast_7)[name = string("temb_15_cast_fp16")];
            tensor<fp16, [1, 320, 64, 64]> input_211_cast_fp16 = add(x = hidden_states_137_cast_fp16, y = temb_15_cast_fp16)[name = string("input_211_cast_fp16")];
            tensor<int32, [5]> reshape_88_shape_0 = const()[name = string("reshape_88_shape_0"), val = tensor<int32, [5]>([1, 32, 10, 64, 64])];
            tensor<fp16, [1, 32, 10, 64, 64]> reshape_88_cast_fp16 = reshape(shape = reshape_88_shape_0, x = input_211_cast_fp16)[name = string("reshape_88_cast_fp16")];
            tensor<int32, [3]> reduce_mean_66_axes_0 = const()[name = string("reduce_mean_66_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_66_keep_dims_0 = const()[name = string("reduce_mean_66_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_66_cast_fp16 = reduce_mean(axes = reduce_mean_66_axes_0, keep_dims = reduce_mean_66_keep_dims_0, x = reshape_88_cast_fp16)[name = string("reduce_mean_66_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> sub_44_cast_fp16 = sub(x = reshape_88_cast_fp16, y = reduce_mean_66_cast_fp16)[name = string("sub_44_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> square_22_cast_fp16 = square(x = sub_44_cast_fp16)[name = string("square_22_cast_fp16")];
            tensor<int32, [3]> reduce_mean_68_axes_0 = const()[name = string("reduce_mean_68_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_68_keep_dims_0 = const()[name = string("reduce_mean_68_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_68_cast_fp16 = reduce_mean(axes = reduce_mean_68_axes_0, keep_dims = reduce_mean_68_keep_dims_0, x = square_22_cast_fp16)[name = string("reduce_mean_68_cast_fp16")];
            fp16 add_44_y_0_to_fp16 = const()[name = string("add_44_y_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_44_cast_fp16 = add(x = reduce_mean_68_cast_fp16, y = add_44_y_0_to_fp16)[name = string("add_44_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_22_cast_fp16 = sqrt(x = add_44_cast_fp16)[name = string("sqrt_22_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> real_div_22_cast_fp16 = real_div(x = sub_44_cast_fp16, y = sqrt_22_cast_fp16)[name = string("real_div_22_cast_fp16")];
            tensor<int32, [4]> reshape_89_shape_0 = const()[name = string("reshape_89_shape_0"), val = tensor<int32, [4]>([1, 320, 64, 64])];
            tensor<fp16, [1, 320, 64, 64]> reshape_89_cast_fp16 = reshape(shape = reshape_89_shape_0, x = real_div_22_cast_fp16)[name = string("reshape_89_cast_fp16")];
            tensor<fp16, [320]> add_45_gamma_0_to_fp16 = const()[name = string("add_45_gamma_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(302772416)))];
            tensor<fp16, [320]> add_45_beta_0_to_fp16 = const()[name = string("add_45_beta_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(302773120)))];
            fp16 add_45_epsilon_0_to_fp16 = const()[name = string("add_45_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 320, 64, 64]> add_45_cast_fp16 = batch_norm(beta = add_45_beta_0_to_fp16, epsilon = add_45_epsilon_0_to_fp16, gamma = add_45_gamma_0_to_fp16, mean = add_1_mean_0_to_fp16, variance = add_1_variance_0_to_fp16, x = reshape_89_cast_fp16)[name = string("add_45_cast_fp16")];
            tensor<fp16, [1, 320, 64, 64]> input_215_cast_fp16 = silu(x = add_45_cast_fp16)[name = string("input_215_cast_fp16")];
            string hidden_states_139_pad_type_0 = const()[name = string("hidden_states_139_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> hidden_states_139_pad_0 = const()[name = string("hidden_states_139_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> hidden_states_139_strides_0 = const()[name = string("hidden_states_139_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> hidden_states_139_dilations_0 = const()[name = string("hidden_states_139_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_139_groups_0 = const()[name = string("hidden_states_139_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 3, 3]> up_blocks_2_resnets_0_conv2_weight_to_fp16 = const()[name = string("up_blocks_2_resnets_0_conv2_weight_to_fp16"), val = tensor<fp16, [320, 320, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(302773824)))];
            tensor<fp16, [320]> up_blocks_2_resnets_0_conv2_bias_to_fp16 = const()[name = string("up_blocks_2_resnets_0_conv2_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(304617088)))];
            tensor<fp16, [1, 320, 64, 64]> hidden_states_139_cast_fp16 = conv(bias = up_blocks_2_resnets_0_conv2_bias_to_fp16, dilations = hidden_states_139_dilations_0, groups = hidden_states_139_groups_0, pad = hidden_states_139_pad_0, pad_type = hidden_states_139_pad_type_0, strides = hidden_states_139_strides_0, weight = up_blocks_2_resnets_0_conv2_weight_to_fp16, x = input_215_cast_fp16)[name = string("hidden_states_139_cast_fp16")];
            string x_13_pad_type_0 = const()[name = string("x_13_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_13_strides_0 = const()[name = string("x_13_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_13_pad_0 = const()[name = string("x_13_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_13_dilations_0 = const()[name = string("x_13_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_13_groups_0 = const()[name = string("x_13_groups_0"), val = int32(1)];
            tensor<fp16, [320, 960, 1, 1]> up_blocks_2_resnets_0_conv_shortcut_weight_to_fp16 = const()[name = string("up_blocks_2_resnets_0_conv_shortcut_weight_to_fp16"), val = tensor<fp16, [320, 960, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(304617792)))];
            tensor<fp16, [320]> up_blocks_2_resnets_0_conv_shortcut_bias_to_fp16 = const()[name = string("up_blocks_2_resnets_0_conv_shortcut_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(305232256)))];
            tensor<fp16, [1, 320, 64, 64]> x_13_cast_fp16 = conv(bias = up_blocks_2_resnets_0_conv_shortcut_bias_to_fp16, dilations = x_13_dilations_0, groups = x_13_groups_0, pad = x_13_pad_0, pad_type = x_13_pad_type_0, strides = x_13_strides_0, weight = up_blocks_2_resnets_0_conv_shortcut_weight_to_fp16, x = input_203_cast_fp16)[name = string("x_13_cast_fp16")];
            tensor<fp16, [1, 320, 64, 64]> hidden_states_141_cast_fp16 = add(x = x_13_cast_fp16, y = hidden_states_139_cast_fp16)[name = string("hidden_states_141_cast_fp16")];
            tensor<int32, [5]> reshape_92_shape_0 = const()[name = string("reshape_92_shape_0"), val = tensor<int32, [5]>([1, 32, 10, 64, 64])];
            tensor<fp16, [1, 32, 10, 64, 64]> reshape_92_cast_fp16 = reshape(shape = reshape_92_shape_0, x = hidden_states_141_cast_fp16)[name = string("reshape_92_cast_fp16")];
            tensor<int32, [3]> reduce_mean_69_axes_0 = const()[name = string("reduce_mean_69_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_69_keep_dims_0 = const()[name = string("reduce_mean_69_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_69_cast_fp16 = reduce_mean(axes = reduce_mean_69_axes_0, keep_dims = reduce_mean_69_keep_dims_0, x = reshape_92_cast_fp16)[name = string("reduce_mean_69_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> sub_46_cast_fp16 = sub(x = reshape_92_cast_fp16, y = reduce_mean_69_cast_fp16)[name = string("sub_46_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> square_23_cast_fp16 = square(x = sub_46_cast_fp16)[name = string("square_23_cast_fp16")];
            tensor<int32, [3]> reduce_mean_71_axes_0 = const()[name = string("reduce_mean_71_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_71_keep_dims_0 = const()[name = string("reduce_mean_71_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_71_cast_fp16 = reduce_mean(axes = reduce_mean_71_axes_0, keep_dims = reduce_mean_71_keep_dims_0, x = square_23_cast_fp16)[name = string("reduce_mean_71_cast_fp16")];
            fp16 add_46_y_0_to_fp16 = const()[name = string("add_46_y_0_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_46_cast_fp16 = add(x = reduce_mean_71_cast_fp16, y = add_46_y_0_to_fp16)[name = string("add_46_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_23_cast_fp16 = sqrt(x = add_46_cast_fp16)[name = string("sqrt_23_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> real_div_23_cast_fp16 = real_div(x = sub_46_cast_fp16, y = sqrt_23_cast_fp16)[name = string("real_div_23_cast_fp16")];
            tensor<int32, [4]> reshape_93_shape_0 = const()[name = string("reshape_93_shape_0"), val = tensor<int32, [4]>([1, 320, 64, 64])];
            tensor<fp16, [1, 320, 64, 64]> reshape_93_cast_fp16 = reshape(shape = reshape_93_shape_0, x = real_div_23_cast_fp16)[name = string("reshape_93_cast_fp16")];
            tensor<fp16, [320]> add_47_gamma_0_to_fp16 = const()[name = string("add_47_gamma_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(305232960)))];
            tensor<fp16, [320]> add_47_beta_0_to_fp16 = const()[name = string("add_47_beta_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(305233664)))];
            fp16 add_47_epsilon_0_to_fp16 = const()[name = string("add_47_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 320, 64, 64]> add_47_cast_fp16 = batch_norm(beta = add_47_beta_0_to_fp16, epsilon = add_47_epsilon_0_to_fp16, gamma = add_47_gamma_0_to_fp16, mean = add_1_mean_0_to_fp16, variance = add_1_variance_0_to_fp16, x = reshape_93_cast_fp16)[name = string("add_47_cast_fp16")];
            string hidden_states_143_pad_type_0 = const()[name = string("hidden_states_143_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> hidden_states_143_strides_0 = const()[name = string("hidden_states_143_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> hidden_states_143_pad_0 = const()[name = string("hidden_states_143_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> hidden_states_143_dilations_0 = const()[name = string("hidden_states_143_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_143_groups_0 = const()[name = string("hidden_states_143_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_0_proj_in_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_0_proj_in_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(305234368)))];
            tensor<fp16, [320]> up_blocks_2_attentions_0_proj_in_bias_to_fp16 = const()[name = string("up_blocks_2_attentions_0_proj_in_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(305439232)))];
            tensor<fp16, [1, 320, 64, 64]> hidden_states_143_cast_fp16 = conv(bias = up_blocks_2_attentions_0_proj_in_bias_to_fp16, dilations = hidden_states_143_dilations_0, groups = hidden_states_143_groups_0, pad = hidden_states_143_pad_0, pad_type = hidden_states_143_pad_type_0, strides = hidden_states_143_strides_0, weight = up_blocks_2_attentions_0_proj_in_weight_to_fp16, x = add_47_cast_fp16)[name = string("hidden_states_143_cast_fp16")];
            tensor<int32, [4]> var_4124 = const()[name = string("op_4124"), val = tensor<int32, [4]>([1, 320, 1, 4096])];
            tensor<fp16, [1, 320, 1, 4096]> inputs_43_cast_fp16 = reshape(shape = var_4124, x = hidden_states_143_cast_fp16)[name = string("inputs_43_cast_fp16")];
            tensor<int32, [1]> hidden_states_145_axes_0 = const()[name = string("hidden_states_145_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [320]> hidden_states_145_gamma_0_to_fp16 = const()[name = string("hidden_states_145_gamma_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(305439936)))];
            tensor<fp16, [320]> hidden_states_145_beta_0_to_fp16 = const()[name = string("hidden_states_145_beta_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(305440640)))];
            fp16 var_4140_to_fp16 = const()[name = string("op_4140_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 320, 1, 4096]> hidden_states_145_cast_fp16 = layer_norm(axes = hidden_states_145_axes_0, beta = hidden_states_145_beta_0_to_fp16, epsilon = var_4140_to_fp16, gamma = hidden_states_145_gamma_0_to_fp16, x = inputs_43_cast_fp16)[name = string("hidden_states_145_cast_fp16")];
            string q_29_pad_type_0 = const()[name = string("q_29_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> q_29_strides_0 = const()[name = string("q_29_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> q_29_pad_0 = const()[name = string("q_29_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> q_29_dilations_0 = const()[name = string("q_29_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 q_29_groups_0 = const()[name = string("q_29_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_q_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_q_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(305441344)))];
            tensor<fp16, [1, 320, 1, 4096]> q_29_cast_fp16 = conv(dilations = q_29_dilations_0, groups = q_29_groups_0, pad = q_29_pad_0, pad_type = q_29_pad_type_0, strides = q_29_strides_0, weight = up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_q_weight_to_fp16, x = hidden_states_145_cast_fp16)[name = string("q_29_cast_fp16")];
            string k_57_pad_type_0 = const()[name = string("k_57_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> k_57_strides_0 = const()[name = string("k_57_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> k_57_pad_0 = const()[name = string("k_57_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> k_57_dilations_0 = const()[name = string("k_57_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 k_57_groups_0 = const()[name = string("k_57_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_k_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_k_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(305646208)))];
            tensor<fp16, [1, 320, 1, 4096]> k_57_cast_fp16 = conv(dilations = k_57_dilations_0, groups = k_57_groups_0, pad = k_57_pad_0, pad_type = k_57_pad_type_0, strides = k_57_strides_0, weight = up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_k_weight_to_fp16, x = hidden_states_145_cast_fp16)[name = string("k_57_cast_fp16")];
            string v_29_pad_type_0 = const()[name = string("v_29_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> v_29_strides_0 = const()[name = string("v_29_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> v_29_pad_0 = const()[name = string("v_29_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> v_29_dilations_0 = const()[name = string("v_29_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 v_29_groups_0 = const()[name = string("v_29_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_v_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_v_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(305851072)))];
            tensor<fp16, [1, 320, 1, 4096]> v_29_cast_fp16 = conv(dilations = v_29_dilations_0, groups = v_29_groups_0, pad = v_29_pad_0, pad_type = v_29_pad_type_0, strides = v_29_strides_0, weight = up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_v_weight_to_fp16, x = hidden_states_145_cast_fp16)[name = string("v_29_cast_fp16")];
            tensor<int32, [4]> var_4173_begin_0 = const()[name = string("op_4173_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_4173_end_0 = const()[name = string("op_4173_end_0"), val = tensor<int32, [4]>([1, 40, 1, 4096])];
            tensor<bool, [4]> var_4173_end_mask_0 = const()[name = string("op_4173_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4173_cast_fp16 = slice_by_index(begin = var_4173_begin_0, end = var_4173_end_0, end_mask = var_4173_end_mask_0, x = q_29_cast_fp16)[name = string("op_4173_cast_fp16")];
            tensor<int32, [4]> var_4177_begin_0 = const()[name = string("op_4177_begin_0"), val = tensor<int32, [4]>([0, 40, 0, 0])];
            tensor<int32, [4]> var_4177_end_0 = const()[name = string("op_4177_end_0"), val = tensor<int32, [4]>([1, 80, 1, 4096])];
            tensor<bool, [4]> var_4177_end_mask_0 = const()[name = string("op_4177_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4177_cast_fp16 = slice_by_index(begin = var_4177_begin_0, end = var_4177_end_0, end_mask = var_4177_end_mask_0, x = q_29_cast_fp16)[name = string("op_4177_cast_fp16")];
            tensor<int32, [4]> var_4181_begin_0 = const()[name = string("op_4181_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_4181_end_0 = const()[name = string("op_4181_end_0"), val = tensor<int32, [4]>([1, 120, 1, 4096])];
            tensor<bool, [4]> var_4181_end_mask_0 = const()[name = string("op_4181_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4181_cast_fp16 = slice_by_index(begin = var_4181_begin_0, end = var_4181_end_0, end_mask = var_4181_end_mask_0, x = q_29_cast_fp16)[name = string("op_4181_cast_fp16")];
            tensor<int32, [4]> var_4185_begin_0 = const()[name = string("op_4185_begin_0"), val = tensor<int32, [4]>([0, 120, 0, 0])];
            tensor<int32, [4]> var_4185_end_0 = const()[name = string("op_4185_end_0"), val = tensor<int32, [4]>([1, 160, 1, 4096])];
            tensor<bool, [4]> var_4185_end_mask_0 = const()[name = string("op_4185_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4185_cast_fp16 = slice_by_index(begin = var_4185_begin_0, end = var_4185_end_0, end_mask = var_4185_end_mask_0, x = q_29_cast_fp16)[name = string("op_4185_cast_fp16")];
            tensor<int32, [4]> var_4189_begin_0 = const()[name = string("op_4189_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_4189_end_0 = const()[name = string("op_4189_end_0"), val = tensor<int32, [4]>([1, 200, 1, 4096])];
            tensor<bool, [4]> var_4189_end_mask_0 = const()[name = string("op_4189_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4189_cast_fp16 = slice_by_index(begin = var_4189_begin_0, end = var_4189_end_0, end_mask = var_4189_end_mask_0, x = q_29_cast_fp16)[name = string("op_4189_cast_fp16")];
            tensor<int32, [4]> var_4193_begin_0 = const()[name = string("op_4193_begin_0"), val = tensor<int32, [4]>([0, 200, 0, 0])];
            tensor<int32, [4]> var_4193_end_0 = const()[name = string("op_4193_end_0"), val = tensor<int32, [4]>([1, 240, 1, 4096])];
            tensor<bool, [4]> var_4193_end_mask_0 = const()[name = string("op_4193_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4193_cast_fp16 = slice_by_index(begin = var_4193_begin_0, end = var_4193_end_0, end_mask = var_4193_end_mask_0, x = q_29_cast_fp16)[name = string("op_4193_cast_fp16")];
            tensor<int32, [4]> var_4197_begin_0 = const()[name = string("op_4197_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_4197_end_0 = const()[name = string("op_4197_end_0"), val = tensor<int32, [4]>([1, 280, 1, 4096])];
            tensor<bool, [4]> var_4197_end_mask_0 = const()[name = string("op_4197_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4197_cast_fp16 = slice_by_index(begin = var_4197_begin_0, end = var_4197_end_0, end_mask = var_4197_end_mask_0, x = q_29_cast_fp16)[name = string("op_4197_cast_fp16")];
            tensor<int32, [4]> var_4201_begin_0 = const()[name = string("op_4201_begin_0"), val = tensor<int32, [4]>([0, 280, 0, 0])];
            tensor<int32, [4]> var_4201_end_0 = const()[name = string("op_4201_end_0"), val = tensor<int32, [4]>([1, 1, 1, 4096])];
            tensor<bool, [4]> var_4201_end_mask_0 = const()[name = string("op_4201_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4201_cast_fp16 = slice_by_index(begin = var_4201_begin_0, end = var_4201_end_0, end_mask = var_4201_end_mask_0, x = q_29_cast_fp16)[name = string("op_4201_cast_fp16")];
            tensor<int32, [4]> k_59_perm_0 = const()[name = string("k_59_perm_0"), val = tensor<int32, [4]>([0, 3, 2, 1])];
            tensor<int32, [4]> var_4208_begin_0 = const()[name = string("op_4208_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_4208_end_0 = const()[name = string("op_4208_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 40])];
            tensor<bool, [4]> var_4208_end_mask_0 = const()[name = string("op_4208_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 320]> k_59_cast_fp16 = transpose(perm = k_59_perm_0, x = k_57_cast_fp16)[name = string("transpose_3")];
            tensor<fp16, [1, 4096, 1, 40]> var_4208_cast_fp16 = slice_by_index(begin = var_4208_begin_0, end = var_4208_end_0, end_mask = var_4208_end_mask_0, x = k_59_cast_fp16)[name = string("op_4208_cast_fp16")];
            tensor<int32, [4]> var_4212_begin_0 = const()[name = string("op_4212_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 40])];
            tensor<int32, [4]> var_4212_end_0 = const()[name = string("op_4212_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 80])];
            tensor<bool, [4]> var_4212_end_mask_0 = const()[name = string("op_4212_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 40]> var_4212_cast_fp16 = slice_by_index(begin = var_4212_begin_0, end = var_4212_end_0, end_mask = var_4212_end_mask_0, x = k_59_cast_fp16)[name = string("op_4212_cast_fp16")];
            tensor<int32, [4]> var_4216_begin_0 = const()[name = string("op_4216_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 80])];
            tensor<int32, [4]> var_4216_end_0 = const()[name = string("op_4216_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 120])];
            tensor<bool, [4]> var_4216_end_mask_0 = const()[name = string("op_4216_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 40]> var_4216_cast_fp16 = slice_by_index(begin = var_4216_begin_0, end = var_4216_end_0, end_mask = var_4216_end_mask_0, x = k_59_cast_fp16)[name = string("op_4216_cast_fp16")];
            tensor<int32, [4]> var_4220_begin_0 = const()[name = string("op_4220_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 120])];
            tensor<int32, [4]> var_4220_end_0 = const()[name = string("op_4220_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 160])];
            tensor<bool, [4]> var_4220_end_mask_0 = const()[name = string("op_4220_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 40]> var_4220_cast_fp16 = slice_by_index(begin = var_4220_begin_0, end = var_4220_end_0, end_mask = var_4220_end_mask_0, x = k_59_cast_fp16)[name = string("op_4220_cast_fp16")];
            tensor<int32, [4]> var_4224_begin_0 = const()[name = string("op_4224_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 160])];
            tensor<int32, [4]> var_4224_end_0 = const()[name = string("op_4224_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 200])];
            tensor<bool, [4]> var_4224_end_mask_0 = const()[name = string("op_4224_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 40]> var_4224_cast_fp16 = slice_by_index(begin = var_4224_begin_0, end = var_4224_end_0, end_mask = var_4224_end_mask_0, x = k_59_cast_fp16)[name = string("op_4224_cast_fp16")];
            tensor<int32, [4]> var_4228_begin_0 = const()[name = string("op_4228_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 200])];
            tensor<int32, [4]> var_4228_end_0 = const()[name = string("op_4228_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 240])];
            tensor<bool, [4]> var_4228_end_mask_0 = const()[name = string("op_4228_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 40]> var_4228_cast_fp16 = slice_by_index(begin = var_4228_begin_0, end = var_4228_end_0, end_mask = var_4228_end_mask_0, x = k_59_cast_fp16)[name = string("op_4228_cast_fp16")];
            tensor<int32, [4]> var_4232_begin_0 = const()[name = string("op_4232_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 240])];
            tensor<int32, [4]> var_4232_end_0 = const()[name = string("op_4232_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 280])];
            tensor<bool, [4]> var_4232_end_mask_0 = const()[name = string("op_4232_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 40]> var_4232_cast_fp16 = slice_by_index(begin = var_4232_begin_0, end = var_4232_end_0, end_mask = var_4232_end_mask_0, x = k_59_cast_fp16)[name = string("op_4232_cast_fp16")];
            tensor<int32, [4]> var_4236_begin_0 = const()[name = string("op_4236_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 280])];
            tensor<int32, [4]> var_4236_end_0 = const()[name = string("op_4236_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 1])];
            tensor<bool, [4]> var_4236_end_mask_0 = const()[name = string("op_4236_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4096, 1, 40]> var_4236_cast_fp16 = slice_by_index(begin = var_4236_begin_0, end = var_4236_end_0, end_mask = var_4236_end_mask_0, x = k_59_cast_fp16)[name = string("op_4236_cast_fp16")];
            tensor<int32, [4]> var_4238_begin_0 = const()[name = string("op_4238_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_4238_end_0 = const()[name = string("op_4238_end_0"), val = tensor<int32, [4]>([1, 40, 1, 4096])];
            tensor<bool, [4]> var_4238_end_mask_0 = const()[name = string("op_4238_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4238_cast_fp16 = slice_by_index(begin = var_4238_begin_0, end = var_4238_end_0, end_mask = var_4238_end_mask_0, x = v_29_cast_fp16)[name = string("op_4238_cast_fp16")];
            tensor<int32, [4]> var_4242_begin_0 = const()[name = string("op_4242_begin_0"), val = tensor<int32, [4]>([0, 40, 0, 0])];
            tensor<int32, [4]> var_4242_end_0 = const()[name = string("op_4242_end_0"), val = tensor<int32, [4]>([1, 80, 1, 4096])];
            tensor<bool, [4]> var_4242_end_mask_0 = const()[name = string("op_4242_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4242_cast_fp16 = slice_by_index(begin = var_4242_begin_0, end = var_4242_end_0, end_mask = var_4242_end_mask_0, x = v_29_cast_fp16)[name = string("op_4242_cast_fp16")];
            tensor<int32, [4]> var_4246_begin_0 = const()[name = string("op_4246_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_4246_end_0 = const()[name = string("op_4246_end_0"), val = tensor<int32, [4]>([1, 120, 1, 4096])];
            tensor<bool, [4]> var_4246_end_mask_0 = const()[name = string("op_4246_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4246_cast_fp16 = slice_by_index(begin = var_4246_begin_0, end = var_4246_end_0, end_mask = var_4246_end_mask_0, x = v_29_cast_fp16)[name = string("op_4246_cast_fp16")];
            tensor<int32, [4]> var_4250_begin_0 = const()[name = string("op_4250_begin_0"), val = tensor<int32, [4]>([0, 120, 0, 0])];
            tensor<int32, [4]> var_4250_end_0 = const()[name = string("op_4250_end_0"), val = tensor<int32, [4]>([1, 160, 1, 4096])];
            tensor<bool, [4]> var_4250_end_mask_0 = const()[name = string("op_4250_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4250_cast_fp16 = slice_by_index(begin = var_4250_begin_0, end = var_4250_end_0, end_mask = var_4250_end_mask_0, x = v_29_cast_fp16)[name = string("op_4250_cast_fp16")];
            tensor<int32, [4]> var_4254_begin_0 = const()[name = string("op_4254_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_4254_end_0 = const()[name = string("op_4254_end_0"), val = tensor<int32, [4]>([1, 200, 1, 4096])];
            tensor<bool, [4]> var_4254_end_mask_0 = const()[name = string("op_4254_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4254_cast_fp16 = slice_by_index(begin = var_4254_begin_0, end = var_4254_end_0, end_mask = var_4254_end_mask_0, x = v_29_cast_fp16)[name = string("op_4254_cast_fp16")];
            tensor<int32, [4]> var_4258_begin_0 = const()[name = string("op_4258_begin_0"), val = tensor<int32, [4]>([0, 200, 0, 0])];
            tensor<int32, [4]> var_4258_end_0 = const()[name = string("op_4258_end_0"), val = tensor<int32, [4]>([1, 240, 1, 4096])];
            tensor<bool, [4]> var_4258_end_mask_0 = const()[name = string("op_4258_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4258_cast_fp16 = slice_by_index(begin = var_4258_begin_0, end = var_4258_end_0, end_mask = var_4258_end_mask_0, x = v_29_cast_fp16)[name = string("op_4258_cast_fp16")];
            tensor<int32, [4]> var_4262_begin_0 = const()[name = string("op_4262_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_4262_end_0 = const()[name = string("op_4262_end_0"), val = tensor<int32, [4]>([1, 280, 1, 4096])];
            tensor<bool, [4]> var_4262_end_mask_0 = const()[name = string("op_4262_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4262_cast_fp16 = slice_by_index(begin = var_4262_begin_0, end = var_4262_end_0, end_mask = var_4262_end_mask_0, x = v_29_cast_fp16)[name = string("op_4262_cast_fp16")];
            tensor<int32, [4]> var_4266_begin_0 = const()[name = string("op_4266_begin_0"), val = tensor<int32, [4]>([0, 280, 0, 0])];
            tensor<int32, [4]> var_4266_end_0 = const()[name = string("op_4266_end_0"), val = tensor<int32, [4]>([1, 1, 1, 4096])];
            tensor<bool, [4]> var_4266_end_mask_0 = const()[name = string("op_4266_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4266_cast_fp16 = slice_by_index(begin = var_4266_begin_0, end = var_4266_end_0, end_mask = var_4266_end_mask_0, x = v_29_cast_fp16)[name = string("op_4266_cast_fp16")];
            string var_4270_equation_0 = const()[name = string("op_4270_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4270_cast_fp16 = einsum(equation = var_4270_equation_0, values = (var_4208_cast_fp16, var_4173_cast_fp16))[name = string("op_4270_cast_fp16")];
            fp16 var_4271_to_fp16 = const()[name = string("op_4271_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_225_cast_fp16 = mul(x = var_4270_cast_fp16, y = var_4271_to_fp16)[name = string("aw_225_cast_fp16")];
            string var_4274_equation_0 = const()[name = string("op_4274_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4274_cast_fp16 = einsum(equation = var_4274_equation_0, values = (var_4212_cast_fp16, var_4177_cast_fp16))[name = string("op_4274_cast_fp16")];
            fp16 var_4275_to_fp16 = const()[name = string("op_4275_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_227_cast_fp16 = mul(x = var_4274_cast_fp16, y = var_4275_to_fp16)[name = string("aw_227_cast_fp16")];
            string var_4278_equation_0 = const()[name = string("op_4278_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4278_cast_fp16 = einsum(equation = var_4278_equation_0, values = (var_4216_cast_fp16, var_4181_cast_fp16))[name = string("op_4278_cast_fp16")];
            fp16 var_4279_to_fp16 = const()[name = string("op_4279_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_229_cast_fp16 = mul(x = var_4278_cast_fp16, y = var_4279_to_fp16)[name = string("aw_229_cast_fp16")];
            string var_4282_equation_0 = const()[name = string("op_4282_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4282_cast_fp16 = einsum(equation = var_4282_equation_0, values = (var_4220_cast_fp16, var_4185_cast_fp16))[name = string("op_4282_cast_fp16")];
            fp16 var_4283_to_fp16 = const()[name = string("op_4283_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_231_cast_fp16 = mul(x = var_4282_cast_fp16, y = var_4283_to_fp16)[name = string("aw_231_cast_fp16")];
            string var_4286_equation_0 = const()[name = string("op_4286_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4286_cast_fp16 = einsum(equation = var_4286_equation_0, values = (var_4224_cast_fp16, var_4189_cast_fp16))[name = string("op_4286_cast_fp16")];
            fp16 var_4287_to_fp16 = const()[name = string("op_4287_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_233_cast_fp16 = mul(x = var_4286_cast_fp16, y = var_4287_to_fp16)[name = string("aw_233_cast_fp16")];
            string var_4290_equation_0 = const()[name = string("op_4290_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4290_cast_fp16 = einsum(equation = var_4290_equation_0, values = (var_4228_cast_fp16, var_4193_cast_fp16))[name = string("op_4290_cast_fp16")];
            fp16 var_4291_to_fp16 = const()[name = string("op_4291_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_235_cast_fp16 = mul(x = var_4290_cast_fp16, y = var_4291_to_fp16)[name = string("aw_235_cast_fp16")];
            string var_4294_equation_0 = const()[name = string("op_4294_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4294_cast_fp16 = einsum(equation = var_4294_equation_0, values = (var_4232_cast_fp16, var_4197_cast_fp16))[name = string("op_4294_cast_fp16")];
            fp16 var_4295_to_fp16 = const()[name = string("op_4295_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_237_cast_fp16 = mul(x = var_4294_cast_fp16, y = var_4295_to_fp16)[name = string("aw_237_cast_fp16")];
            string var_4298_equation_0 = const()[name = string("op_4298_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4298_cast_fp16 = einsum(equation = var_4298_equation_0, values = (var_4236_cast_fp16, var_4201_cast_fp16))[name = string("op_4298_cast_fp16")];
            fp16 var_4299_to_fp16 = const()[name = string("op_4299_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_239_cast_fp16 = mul(x = var_4298_cast_fp16, y = var_4299_to_fp16)[name = string("aw_239_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4301_cast_fp16 = softmax(axis = var_4045, x = aw_225_cast_fp16)[name = string("op_4301_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4302_cast_fp16 = softmax(axis = var_4045, x = aw_227_cast_fp16)[name = string("op_4302_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4303_cast_fp16 = softmax(axis = var_4045, x = aw_229_cast_fp16)[name = string("op_4303_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4304_cast_fp16 = softmax(axis = var_4045, x = aw_231_cast_fp16)[name = string("op_4304_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4305_cast_fp16 = softmax(axis = var_4045, x = aw_233_cast_fp16)[name = string("op_4305_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4306_cast_fp16 = softmax(axis = var_4045, x = aw_235_cast_fp16)[name = string("op_4306_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4307_cast_fp16 = softmax(axis = var_4045, x = aw_237_cast_fp16)[name = string("op_4307_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4308_cast_fp16 = softmax(axis = var_4045, x = aw_239_cast_fp16)[name = string("op_4308_cast_fp16")];
            string var_4310_equation_0 = const()[name = string("op_4310_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4310_cast_fp16 = einsum(equation = var_4310_equation_0, values = (var_4238_cast_fp16, var_4301_cast_fp16))[name = string("op_4310_cast_fp16")];
            string var_4312_equation_0 = const()[name = string("op_4312_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4312_cast_fp16 = einsum(equation = var_4312_equation_0, values = (var_4242_cast_fp16, var_4302_cast_fp16))[name = string("op_4312_cast_fp16")];
            string var_4314_equation_0 = const()[name = string("op_4314_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4314_cast_fp16 = einsum(equation = var_4314_equation_0, values = (var_4246_cast_fp16, var_4303_cast_fp16))[name = string("op_4314_cast_fp16")];
            string var_4316_equation_0 = const()[name = string("op_4316_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4316_cast_fp16 = einsum(equation = var_4316_equation_0, values = (var_4250_cast_fp16, var_4304_cast_fp16))[name = string("op_4316_cast_fp16")];
            string var_4318_equation_0 = const()[name = string("op_4318_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4318_cast_fp16 = einsum(equation = var_4318_equation_0, values = (var_4254_cast_fp16, var_4305_cast_fp16))[name = string("op_4318_cast_fp16")];
            string var_4320_equation_0 = const()[name = string("op_4320_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4320_cast_fp16 = einsum(equation = var_4320_equation_0, values = (var_4258_cast_fp16, var_4306_cast_fp16))[name = string("op_4320_cast_fp16")];
            string var_4322_equation_0 = const()[name = string("op_4322_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4322_cast_fp16 = einsum(equation = var_4322_equation_0, values = (var_4262_cast_fp16, var_4307_cast_fp16))[name = string("op_4322_cast_fp16")];
            string var_4324_equation_0 = const()[name = string("op_4324_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4324_cast_fp16 = einsum(equation = var_4324_equation_0, values = (var_4266_cast_fp16, var_4308_cast_fp16))[name = string("op_4324_cast_fp16")];
            bool input_219_interleave_0 = const()[name = string("input_219_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 320, 1, 4096]> input_219_cast_fp16 = concat(axis = var_4045, interleave = input_219_interleave_0, values = (var_4310_cast_fp16, var_4312_cast_fp16, var_4314_cast_fp16, var_4316_cast_fp16, var_4318_cast_fp16, var_4320_cast_fp16, var_4322_cast_fp16, var_4324_cast_fp16))[name = string("input_219_cast_fp16")];
            string var_4334_pad_type_0 = const()[name = string("op_4334_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_4334_strides_0 = const()[name = string("op_4334_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_4334_pad_0 = const()[name = string("op_4334_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_4334_dilations_0 = const()[name = string("op_4334_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_4334_groups_0 = const()[name = string("op_4334_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_out_0_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_out_0_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(306055936)))];
            tensor<fp16, [320]> up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_out_0_bias_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_out_0_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(306260800)))];
            tensor<fp16, [1, 320, 1, 4096]> var_4334_cast_fp16 = conv(bias = up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_out_0_bias_to_fp16, dilations = var_4334_dilations_0, groups = var_4334_groups_0, pad = var_4334_pad_0, pad_type = var_4334_pad_type_0, strides = var_4334_strides_0, weight = up_blocks_2_attentions_0_transformer_blocks_0_attn1_to_out_0_weight_to_fp16, x = input_219_cast_fp16)[name = string("op_4334_cast_fp16")];
            tensor<fp16, [1, 320, 1, 4096]> inputs_45_cast_fp16 = add(x = var_4334_cast_fp16, y = inputs_43_cast_fp16)[name = string("inputs_45_cast_fp16")];
            tensor<int32, [1]> hidden_states_147_axes_0 = const()[name = string("hidden_states_147_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [320]> hidden_states_147_gamma_0_to_fp16 = const()[name = string("hidden_states_147_gamma_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(306261504)))];
            tensor<fp16, [320]> hidden_states_147_beta_0_to_fp16 = const()[name = string("hidden_states_147_beta_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(306262208)))];
            fp16 var_4344_to_fp16 = const()[name = string("op_4344_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 320, 1, 4096]> hidden_states_147_cast_fp16 = layer_norm(axes = hidden_states_147_axes_0, beta = hidden_states_147_beta_0_to_fp16, epsilon = var_4344_to_fp16, gamma = hidden_states_147_gamma_0_to_fp16, x = inputs_45_cast_fp16)[name = string("hidden_states_147_cast_fp16")];
            string q_31_pad_type_0 = const()[name = string("q_31_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> q_31_strides_0 = const()[name = string("q_31_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> q_31_pad_0 = const()[name = string("q_31_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> q_31_dilations_0 = const()[name = string("q_31_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 q_31_groups_0 = const()[name = string("q_31_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_q_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_q_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(306262912)))];
            tensor<fp16, [1, 320, 1, 4096]> q_31_cast_fp16 = conv(dilations = q_31_dilations_0, groups = q_31_groups_0, pad = q_31_pad_0, pad_type = q_31_pad_type_0, strides = q_31_strides_0, weight = up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_q_weight_to_fp16, x = hidden_states_147_cast_fp16)[name = string("q_31_cast_fp16")];
            string k_61_pad_type_0 = const()[name = string("k_61_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> k_61_strides_0 = const()[name = string("k_61_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> k_61_pad_0 = const()[name = string("k_61_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> k_61_dilations_0 = const()[name = string("k_61_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 k_61_groups_0 = const()[name = string("k_61_groups_0"), val = int32(1)];
            tensor<fp16, [320, 768, 1, 1]> up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_k_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_k_weight_to_fp16"), val = tensor<fp16, [320, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(306467776)))];
            tensor<fp16, [1, 320, 1, 77]> k_61_cast_fp16 = conv(dilations = k_61_dilations_0, groups = k_61_groups_0, pad = k_61_pad_0, pad_type = k_61_pad_type_0, strides = k_61_strides_0, weight = up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_k_weight_to_fp16, x = encoder_hidden_states)[name = string("k_61_cast_fp16")];
            string v_31_pad_type_0 = const()[name = string("v_31_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> v_31_strides_0 = const()[name = string("v_31_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> v_31_pad_0 = const()[name = string("v_31_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> v_31_dilations_0 = const()[name = string("v_31_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 v_31_groups_0 = const()[name = string("v_31_groups_0"), val = int32(1)];
            tensor<fp16, [320, 768, 1, 1]> up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_v_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_v_weight_to_fp16"), val = tensor<fp16, [320, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(306959360)))];
            tensor<fp16, [1, 320, 1, 77]> v_31_cast_fp16 = conv(dilations = v_31_dilations_0, groups = v_31_groups_0, pad = v_31_pad_0, pad_type = v_31_pad_type_0, strides = v_31_strides_0, weight = up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_v_weight_to_fp16, x = encoder_hidden_states)[name = string("v_31_cast_fp16")];
            tensor<int32, [4]> var_4377_begin_0 = const()[name = string("op_4377_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_4377_end_0 = const()[name = string("op_4377_end_0"), val = tensor<int32, [4]>([1, 40, 1, 4096])];
            tensor<bool, [4]> var_4377_end_mask_0 = const()[name = string("op_4377_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4377_cast_fp16 = slice_by_index(begin = var_4377_begin_0, end = var_4377_end_0, end_mask = var_4377_end_mask_0, x = q_31_cast_fp16)[name = string("op_4377_cast_fp16")];
            tensor<int32, [4]> var_4381_begin_0 = const()[name = string("op_4381_begin_0"), val = tensor<int32, [4]>([0, 40, 0, 0])];
            tensor<int32, [4]> var_4381_end_0 = const()[name = string("op_4381_end_0"), val = tensor<int32, [4]>([1, 80, 1, 4096])];
            tensor<bool, [4]> var_4381_end_mask_0 = const()[name = string("op_4381_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4381_cast_fp16 = slice_by_index(begin = var_4381_begin_0, end = var_4381_end_0, end_mask = var_4381_end_mask_0, x = q_31_cast_fp16)[name = string("op_4381_cast_fp16")];
            tensor<int32, [4]> var_4385_begin_0 = const()[name = string("op_4385_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_4385_end_0 = const()[name = string("op_4385_end_0"), val = tensor<int32, [4]>([1, 120, 1, 4096])];
            tensor<bool, [4]> var_4385_end_mask_0 = const()[name = string("op_4385_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4385_cast_fp16 = slice_by_index(begin = var_4385_begin_0, end = var_4385_end_0, end_mask = var_4385_end_mask_0, x = q_31_cast_fp16)[name = string("op_4385_cast_fp16")];
            tensor<int32, [4]> var_4389_begin_0 = const()[name = string("op_4389_begin_0"), val = tensor<int32, [4]>([0, 120, 0, 0])];
            tensor<int32, [4]> var_4389_end_0 = const()[name = string("op_4389_end_0"), val = tensor<int32, [4]>([1, 160, 1, 4096])];
            tensor<bool, [4]> var_4389_end_mask_0 = const()[name = string("op_4389_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4389_cast_fp16 = slice_by_index(begin = var_4389_begin_0, end = var_4389_end_0, end_mask = var_4389_end_mask_0, x = q_31_cast_fp16)[name = string("op_4389_cast_fp16")];
            tensor<int32, [4]> var_4393_begin_0 = const()[name = string("op_4393_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_4393_end_0 = const()[name = string("op_4393_end_0"), val = tensor<int32, [4]>([1, 200, 1, 4096])];
            tensor<bool, [4]> var_4393_end_mask_0 = const()[name = string("op_4393_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4393_cast_fp16 = slice_by_index(begin = var_4393_begin_0, end = var_4393_end_0, end_mask = var_4393_end_mask_0, x = q_31_cast_fp16)[name = string("op_4393_cast_fp16")];
            tensor<int32, [4]> var_4397_begin_0 = const()[name = string("op_4397_begin_0"), val = tensor<int32, [4]>([0, 200, 0, 0])];
            tensor<int32, [4]> var_4397_end_0 = const()[name = string("op_4397_end_0"), val = tensor<int32, [4]>([1, 240, 1, 4096])];
            tensor<bool, [4]> var_4397_end_mask_0 = const()[name = string("op_4397_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4397_cast_fp16 = slice_by_index(begin = var_4397_begin_0, end = var_4397_end_0, end_mask = var_4397_end_mask_0, x = q_31_cast_fp16)[name = string("op_4397_cast_fp16")];
            tensor<int32, [4]> var_4401_begin_0 = const()[name = string("op_4401_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_4401_end_0 = const()[name = string("op_4401_end_0"), val = tensor<int32, [4]>([1, 280, 1, 4096])];
            tensor<bool, [4]> var_4401_end_mask_0 = const()[name = string("op_4401_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4401_cast_fp16 = slice_by_index(begin = var_4401_begin_0, end = var_4401_end_0, end_mask = var_4401_end_mask_0, x = q_31_cast_fp16)[name = string("op_4401_cast_fp16")];
            tensor<int32, [4]> var_4405_begin_0 = const()[name = string("op_4405_begin_0"), val = tensor<int32, [4]>([0, 280, 0, 0])];
            tensor<int32, [4]> var_4405_end_0 = const()[name = string("op_4405_end_0"), val = tensor<int32, [4]>([1, 1, 1, 4096])];
            tensor<bool, [4]> var_4405_end_mask_0 = const()[name = string("op_4405_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4405_cast_fp16 = slice_by_index(begin = var_4405_begin_0, end = var_4405_end_0, end_mask = var_4405_end_mask_0, x = q_31_cast_fp16)[name = string("op_4405_cast_fp16")];
            tensor<int32, [4]> k_63_perm_0 = const()[name = string("k_63_perm_0"), val = tensor<int32, [4]>([0, 3, 2, 1])];
            tensor<int32, [4]> var_4412_begin_0 = const()[name = string("op_4412_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_4412_end_0 = const()[name = string("op_4412_end_0"), val = tensor<int32, [4]>([1, 77, 1, 40])];
            tensor<bool, [4]> var_4412_end_mask_0 = const()[name = string("op_4412_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 320]> k_63_cast_fp16 = transpose(perm = k_63_perm_0, x = k_61_cast_fp16)[name = string("transpose_2")];
            tensor<fp16, [1, 77, 1, 40]> var_4412_cast_fp16 = slice_by_index(begin = var_4412_begin_0, end = var_4412_end_0, end_mask = var_4412_end_mask_0, x = k_63_cast_fp16)[name = string("op_4412_cast_fp16")];
            tensor<int32, [4]> var_4416_begin_0 = const()[name = string("op_4416_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 40])];
            tensor<int32, [4]> var_4416_end_0 = const()[name = string("op_4416_end_0"), val = tensor<int32, [4]>([1, 77, 1, 80])];
            tensor<bool, [4]> var_4416_end_mask_0 = const()[name = string("op_4416_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 40]> var_4416_cast_fp16 = slice_by_index(begin = var_4416_begin_0, end = var_4416_end_0, end_mask = var_4416_end_mask_0, x = k_63_cast_fp16)[name = string("op_4416_cast_fp16")];
            tensor<int32, [4]> var_4420_begin_0 = const()[name = string("op_4420_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 80])];
            tensor<int32, [4]> var_4420_end_0 = const()[name = string("op_4420_end_0"), val = tensor<int32, [4]>([1, 77, 1, 120])];
            tensor<bool, [4]> var_4420_end_mask_0 = const()[name = string("op_4420_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 40]> var_4420_cast_fp16 = slice_by_index(begin = var_4420_begin_0, end = var_4420_end_0, end_mask = var_4420_end_mask_0, x = k_63_cast_fp16)[name = string("op_4420_cast_fp16")];
            tensor<int32, [4]> var_4424_begin_0 = const()[name = string("op_4424_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 120])];
            tensor<int32, [4]> var_4424_end_0 = const()[name = string("op_4424_end_0"), val = tensor<int32, [4]>([1, 77, 1, 160])];
            tensor<bool, [4]> var_4424_end_mask_0 = const()[name = string("op_4424_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 40]> var_4424_cast_fp16 = slice_by_index(begin = var_4424_begin_0, end = var_4424_end_0, end_mask = var_4424_end_mask_0, x = k_63_cast_fp16)[name = string("op_4424_cast_fp16")];
            tensor<int32, [4]> var_4428_begin_0 = const()[name = string("op_4428_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 160])];
            tensor<int32, [4]> var_4428_end_0 = const()[name = string("op_4428_end_0"), val = tensor<int32, [4]>([1, 77, 1, 200])];
            tensor<bool, [4]> var_4428_end_mask_0 = const()[name = string("op_4428_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 40]> var_4428_cast_fp16 = slice_by_index(begin = var_4428_begin_0, end = var_4428_end_0, end_mask = var_4428_end_mask_0, x = k_63_cast_fp16)[name = string("op_4428_cast_fp16")];
            tensor<int32, [4]> var_4432_begin_0 = const()[name = string("op_4432_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 200])];
            tensor<int32, [4]> var_4432_end_0 = const()[name = string("op_4432_end_0"), val = tensor<int32, [4]>([1, 77, 1, 240])];
            tensor<bool, [4]> var_4432_end_mask_0 = const()[name = string("op_4432_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 40]> var_4432_cast_fp16 = slice_by_index(begin = var_4432_begin_0, end = var_4432_end_0, end_mask = var_4432_end_mask_0, x = k_63_cast_fp16)[name = string("op_4432_cast_fp16")];
            tensor<int32, [4]> var_4436_begin_0 = const()[name = string("op_4436_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 240])];
            tensor<int32, [4]> var_4436_end_0 = const()[name = string("op_4436_end_0"), val = tensor<int32, [4]>([1, 77, 1, 280])];
            tensor<bool, [4]> var_4436_end_mask_0 = const()[name = string("op_4436_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 40]> var_4436_cast_fp16 = slice_by_index(begin = var_4436_begin_0, end = var_4436_end_0, end_mask = var_4436_end_mask_0, x = k_63_cast_fp16)[name = string("op_4436_cast_fp16")];
            tensor<int32, [4]> var_4440_begin_0 = const()[name = string("op_4440_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 280])];
            tensor<int32, [4]> var_4440_end_0 = const()[name = string("op_4440_end_0"), val = tensor<int32, [4]>([1, 77, 1, 1])];
            tensor<bool, [4]> var_4440_end_mask_0 = const()[name = string("op_4440_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 77, 1, 40]> var_4440_cast_fp16 = slice_by_index(begin = var_4440_begin_0, end = var_4440_end_0, end_mask = var_4440_end_mask_0, x = k_63_cast_fp16)[name = string("op_4440_cast_fp16")];
            tensor<int32, [4]> var_4442_begin_0 = const()[name = string("op_4442_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_4442_end_0 = const()[name = string("op_4442_end_0"), val = tensor<int32, [4]>([1, 40, 1, 77])];
            tensor<bool, [4]> var_4442_end_mask_0 = const()[name = string("op_4442_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4442_cast_fp16 = slice_by_index(begin = var_4442_begin_0, end = var_4442_end_0, end_mask = var_4442_end_mask_0, x = v_31_cast_fp16)[name = string("op_4442_cast_fp16")];
            tensor<int32, [4]> var_4446_begin_0 = const()[name = string("op_4446_begin_0"), val = tensor<int32, [4]>([0, 40, 0, 0])];
            tensor<int32, [4]> var_4446_end_0 = const()[name = string("op_4446_end_0"), val = tensor<int32, [4]>([1, 80, 1, 77])];
            tensor<bool, [4]> var_4446_end_mask_0 = const()[name = string("op_4446_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4446_cast_fp16 = slice_by_index(begin = var_4446_begin_0, end = var_4446_end_0, end_mask = var_4446_end_mask_0, x = v_31_cast_fp16)[name = string("op_4446_cast_fp16")];
            tensor<int32, [4]> var_4450_begin_0 = const()[name = string("op_4450_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_4450_end_0 = const()[name = string("op_4450_end_0"), val = tensor<int32, [4]>([1, 120, 1, 77])];
            tensor<bool, [4]> var_4450_end_mask_0 = const()[name = string("op_4450_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4450_cast_fp16 = slice_by_index(begin = var_4450_begin_0, end = var_4450_end_0, end_mask = var_4450_end_mask_0, x = v_31_cast_fp16)[name = string("op_4450_cast_fp16")];
            tensor<int32, [4]> var_4454_begin_0 = const()[name = string("op_4454_begin_0"), val = tensor<int32, [4]>([0, 120, 0, 0])];
            tensor<int32, [4]> var_4454_end_0 = const()[name = string("op_4454_end_0"), val = tensor<int32, [4]>([1, 160, 1, 77])];
            tensor<bool, [4]> var_4454_end_mask_0 = const()[name = string("op_4454_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4454_cast_fp16 = slice_by_index(begin = var_4454_begin_0, end = var_4454_end_0, end_mask = var_4454_end_mask_0, x = v_31_cast_fp16)[name = string("op_4454_cast_fp16")];
            tensor<int32, [4]> var_4458_begin_0 = const()[name = string("op_4458_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_4458_end_0 = const()[name = string("op_4458_end_0"), val = tensor<int32, [4]>([1, 200, 1, 77])];
            tensor<bool, [4]> var_4458_end_mask_0 = const()[name = string("op_4458_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4458_cast_fp16 = slice_by_index(begin = var_4458_begin_0, end = var_4458_end_0, end_mask = var_4458_end_mask_0, x = v_31_cast_fp16)[name = string("op_4458_cast_fp16")];
            tensor<int32, [4]> var_4462_begin_0 = const()[name = string("op_4462_begin_0"), val = tensor<int32, [4]>([0, 200, 0, 0])];
            tensor<int32, [4]> var_4462_end_0 = const()[name = string("op_4462_end_0"), val = tensor<int32, [4]>([1, 240, 1, 77])];
            tensor<bool, [4]> var_4462_end_mask_0 = const()[name = string("op_4462_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4462_cast_fp16 = slice_by_index(begin = var_4462_begin_0, end = var_4462_end_0, end_mask = var_4462_end_mask_0, x = v_31_cast_fp16)[name = string("op_4462_cast_fp16")];
            tensor<int32, [4]> var_4466_begin_0 = const()[name = string("op_4466_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_4466_end_0 = const()[name = string("op_4466_end_0"), val = tensor<int32, [4]>([1, 280, 1, 77])];
            tensor<bool, [4]> var_4466_end_mask_0 = const()[name = string("op_4466_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4466_cast_fp16 = slice_by_index(begin = var_4466_begin_0, end = var_4466_end_0, end_mask = var_4466_end_mask_0, x = v_31_cast_fp16)[name = string("op_4466_cast_fp16")];
            tensor<int32, [4]> var_4470_begin_0 = const()[name = string("op_4470_begin_0"), val = tensor<int32, [4]>([0, 280, 0, 0])];
            tensor<int32, [4]> var_4470_end_0 = const()[name = string("op_4470_end_0"), val = tensor<int32, [4]>([1, 1, 1, 77])];
            tensor<bool, [4]> var_4470_end_mask_0 = const()[name = string("op_4470_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4470_cast_fp16 = slice_by_index(begin = var_4470_begin_0, end = var_4470_end_0, end_mask = var_4470_end_mask_0, x = v_31_cast_fp16)[name = string("op_4470_cast_fp16")];
            string var_4474_equation_0 = const()[name = string("op_4474_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_4474_cast_fp16 = einsum(equation = var_4474_equation_0, values = (var_4412_cast_fp16, var_4377_cast_fp16))[name = string("op_4474_cast_fp16")];
            fp16 var_4475_to_fp16 = const()[name = string("op_4475_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_241_cast_fp16 = mul(x = var_4474_cast_fp16, y = var_4475_to_fp16)[name = string("aw_241_cast_fp16")];
            string var_4478_equation_0 = const()[name = string("op_4478_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_4478_cast_fp16 = einsum(equation = var_4478_equation_0, values = (var_4416_cast_fp16, var_4381_cast_fp16))[name = string("op_4478_cast_fp16")];
            fp16 var_4479_to_fp16 = const()[name = string("op_4479_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_243_cast_fp16 = mul(x = var_4478_cast_fp16, y = var_4479_to_fp16)[name = string("aw_243_cast_fp16")];
            string var_4482_equation_0 = const()[name = string("op_4482_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_4482_cast_fp16 = einsum(equation = var_4482_equation_0, values = (var_4420_cast_fp16, var_4385_cast_fp16))[name = string("op_4482_cast_fp16")];
            fp16 var_4483_to_fp16 = const()[name = string("op_4483_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_245_cast_fp16 = mul(x = var_4482_cast_fp16, y = var_4483_to_fp16)[name = string("aw_245_cast_fp16")];
            string var_4486_equation_0 = const()[name = string("op_4486_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_4486_cast_fp16 = einsum(equation = var_4486_equation_0, values = (var_4424_cast_fp16, var_4389_cast_fp16))[name = string("op_4486_cast_fp16")];
            fp16 var_4487_to_fp16 = const()[name = string("op_4487_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_247_cast_fp16 = mul(x = var_4486_cast_fp16, y = var_4487_to_fp16)[name = string("aw_247_cast_fp16")];
            string var_4490_equation_0 = const()[name = string("op_4490_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_4490_cast_fp16 = einsum(equation = var_4490_equation_0, values = (var_4428_cast_fp16, var_4393_cast_fp16))[name = string("op_4490_cast_fp16")];
            fp16 var_4491_to_fp16 = const()[name = string("op_4491_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_249_cast_fp16 = mul(x = var_4490_cast_fp16, y = var_4491_to_fp16)[name = string("aw_249_cast_fp16")];
            string var_4494_equation_0 = const()[name = string("op_4494_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_4494_cast_fp16 = einsum(equation = var_4494_equation_0, values = (var_4432_cast_fp16, var_4397_cast_fp16))[name = string("op_4494_cast_fp16")];
            fp16 var_4495_to_fp16 = const()[name = string("op_4495_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_251_cast_fp16 = mul(x = var_4494_cast_fp16, y = var_4495_to_fp16)[name = string("aw_251_cast_fp16")];
            string var_4498_equation_0 = const()[name = string("op_4498_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_4498_cast_fp16 = einsum(equation = var_4498_equation_0, values = (var_4436_cast_fp16, var_4401_cast_fp16))[name = string("op_4498_cast_fp16")];
            fp16 var_4499_to_fp16 = const()[name = string("op_4499_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_253_cast_fp16 = mul(x = var_4498_cast_fp16, y = var_4499_to_fp16)[name = string("aw_253_cast_fp16")];
            string var_4502_equation_0 = const()[name = string("op_4502_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_4502_cast_fp16 = einsum(equation = var_4502_equation_0, values = (var_4440_cast_fp16, var_4405_cast_fp16))[name = string("op_4502_cast_fp16")];
            fp16 var_4503_to_fp16 = const()[name = string("op_4503_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_255_cast_fp16 = mul(x = var_4502_cast_fp16, y = var_4503_to_fp16)[name = string("aw_255_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_4505_cast_fp16 = softmax(axis = var_4045, x = aw_241_cast_fp16)[name = string("op_4505_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_4506_cast_fp16 = softmax(axis = var_4045, x = aw_243_cast_fp16)[name = string("op_4506_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_4507_cast_fp16 = softmax(axis = var_4045, x = aw_245_cast_fp16)[name = string("op_4507_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_4508_cast_fp16 = softmax(axis = var_4045, x = aw_247_cast_fp16)[name = string("op_4508_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_4509_cast_fp16 = softmax(axis = var_4045, x = aw_249_cast_fp16)[name = string("op_4509_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_4510_cast_fp16 = softmax(axis = var_4045, x = aw_251_cast_fp16)[name = string("op_4510_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_4511_cast_fp16 = softmax(axis = var_4045, x = aw_253_cast_fp16)[name = string("op_4511_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_4512_cast_fp16 = softmax(axis = var_4045, x = aw_255_cast_fp16)[name = string("op_4512_cast_fp16")];
            string var_4514_equation_0 = const()[name = string("op_4514_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4514_cast_fp16 = einsum(equation = var_4514_equation_0, values = (var_4442_cast_fp16, var_4505_cast_fp16))[name = string("op_4514_cast_fp16")];
            string var_4516_equation_0 = const()[name = string("op_4516_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4516_cast_fp16 = einsum(equation = var_4516_equation_0, values = (var_4446_cast_fp16, var_4506_cast_fp16))[name = string("op_4516_cast_fp16")];
            string var_4518_equation_0 = const()[name = string("op_4518_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4518_cast_fp16 = einsum(equation = var_4518_equation_0, values = (var_4450_cast_fp16, var_4507_cast_fp16))[name = string("op_4518_cast_fp16")];
            string var_4520_equation_0 = const()[name = string("op_4520_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4520_cast_fp16 = einsum(equation = var_4520_equation_0, values = (var_4454_cast_fp16, var_4508_cast_fp16))[name = string("op_4520_cast_fp16")];
            string var_4522_equation_0 = const()[name = string("op_4522_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4522_cast_fp16 = einsum(equation = var_4522_equation_0, values = (var_4458_cast_fp16, var_4509_cast_fp16))[name = string("op_4522_cast_fp16")];
            string var_4524_equation_0 = const()[name = string("op_4524_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4524_cast_fp16 = einsum(equation = var_4524_equation_0, values = (var_4462_cast_fp16, var_4510_cast_fp16))[name = string("op_4524_cast_fp16")];
            string var_4526_equation_0 = const()[name = string("op_4526_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4526_cast_fp16 = einsum(equation = var_4526_equation_0, values = (var_4466_cast_fp16, var_4511_cast_fp16))[name = string("op_4526_cast_fp16")];
            string var_4528_equation_0 = const()[name = string("op_4528_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4528_cast_fp16 = einsum(equation = var_4528_equation_0, values = (var_4470_cast_fp16, var_4512_cast_fp16))[name = string("op_4528_cast_fp16")];
            bool input_221_interleave_0 = const()[name = string("input_221_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 320, 1, 4096]> input_221_cast_fp16 = concat(axis = var_4045, interleave = input_221_interleave_0, values = (var_4514_cast_fp16, var_4516_cast_fp16, var_4518_cast_fp16, var_4520_cast_fp16, var_4522_cast_fp16, var_4524_cast_fp16, var_4526_cast_fp16, var_4528_cast_fp16))[name = string("input_221_cast_fp16")];
            string var_4538_pad_type_0 = const()[name = string("op_4538_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_4538_strides_0 = const()[name = string("op_4538_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_4538_pad_0 = const()[name = string("op_4538_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_4538_dilations_0 = const()[name = string("op_4538_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_4538_groups_0 = const()[name = string("op_4538_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_out_0_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_out_0_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(307450944)))];
            tensor<fp16, [320]> up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_out_0_bias_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_out_0_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(307655808)))];
            tensor<fp16, [1, 320, 1, 4096]> var_4538_cast_fp16 = conv(bias = up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_out_0_bias_to_fp16, dilations = var_4538_dilations_0, groups = var_4538_groups_0, pad = var_4538_pad_0, pad_type = var_4538_pad_type_0, strides = var_4538_strides_0, weight = up_blocks_2_attentions_0_transformer_blocks_0_attn2_to_out_0_weight_to_fp16, x = input_221_cast_fp16)[name = string("op_4538_cast_fp16")];
            tensor<fp16, [1, 320, 1, 4096]> inputs_47_cast_fp16 = add(x = var_4538_cast_fp16, y = inputs_45_cast_fp16)[name = string("inputs_47_cast_fp16")];
            tensor<int32, [1]> input_223_axes_0 = const()[name = string("input_223_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [320]> input_223_gamma_0_to_fp16 = const()[name = string("input_223_gamma_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(307656512)))];
            tensor<fp16, [320]> input_223_beta_0_to_fp16 = const()[name = string("input_223_beta_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(307657216)))];
            fp16 var_4548_to_fp16 = const()[name = string("op_4548_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 320, 1, 4096]> input_223_cast_fp16 = layer_norm(axes = input_223_axes_0, beta = input_223_beta_0_to_fp16, epsilon = var_4548_to_fp16, gamma = input_223_gamma_0_to_fp16, x = inputs_47_cast_fp16)[name = string("input_223_cast_fp16")];
            string var_4568_pad_type_0 = const()[name = string("op_4568_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_4568_strides_0 = const()[name = string("op_4568_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_4568_pad_0 = const()[name = string("op_4568_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_4568_dilations_0 = const()[name = string("op_4568_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_4568_groups_0 = const()[name = string("op_4568_groups_0"), val = int32(1)];
            tensor<fp16, [2560, 320, 1, 1]> up_blocks_2_attentions_0_transformer_blocks_0_ff_net_0_proj_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_ff_net_0_proj_weight_to_fp16"), val = tensor<fp16, [2560, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(307657920)))];
            tensor<fp16, [2560]> up_blocks_2_attentions_0_transformer_blocks_0_ff_net_0_proj_bias_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_ff_net_0_proj_bias_to_fp16"), val = tensor<fp16, [2560]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(309296384)))];
            tensor<fp16, [1, 2560, 1, 4096]> var_4568_cast_fp16 = conv(bias = up_blocks_2_attentions_0_transformer_blocks_0_ff_net_0_proj_bias_to_fp16, dilations = var_4568_dilations_0, groups = var_4568_groups_0, pad = var_4568_pad_0, pad_type = var_4568_pad_type_0, strides = var_4568_strides_0, weight = up_blocks_2_attentions_0_transformer_blocks_0_ff_net_0_proj_weight_to_fp16, x = input_223_cast_fp16)[name = string("op_4568_cast_fp16")];
            tensor<int32, [2]> var_4569_split_sizes_0 = const()[name = string("op_4569_split_sizes_0"), val = tensor<int32, [2]>([1280, 1280])];
            int32 var_4569_axis_0 = const()[name = string("op_4569_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1280, 1, 4096]> var_4569_cast_fp16_0, tensor<fp16, [1, 1280, 1, 4096]> var_4569_cast_fp16_1 = split(axis = var_4569_axis_0, split_sizes = var_4569_split_sizes_0, x = var_4568_cast_fp16)[name = string("op_4569_cast_fp16")];
            string var_4571_mode_0 = const()[name = string("op_4571_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1280, 1, 4096]> var_4571_cast_fp16 = gelu(mode = var_4571_mode_0, x = var_4569_cast_fp16_1)[name = string("op_4571_cast_fp16")];
            tensor<fp16, [1, 1280, 1, 4096]> input_225_cast_fp16 = mul(x = var_4569_cast_fp16_0, y = var_4571_cast_fp16)[name = string("input_225_cast_fp16")];
            string var_4579_pad_type_0 = const()[name = string("op_4579_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_4579_strides_0 = const()[name = string("op_4579_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_4579_pad_0 = const()[name = string("op_4579_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_4579_dilations_0 = const()[name = string("op_4579_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_4579_groups_0 = const()[name = string("op_4579_groups_0"), val = int32(1)];
            tensor<fp16, [320, 1280, 1, 1]> up_blocks_2_attentions_0_transformer_blocks_0_ff_net_2_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_ff_net_2_weight_to_fp16"), val = tensor<fp16, [320, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(309301568)))];
            tensor<fp16, [320]> up_blocks_2_attentions_0_transformer_blocks_0_ff_net_2_bias_to_fp16 = const()[name = string("up_blocks_2_attentions_0_transformer_blocks_0_ff_net_2_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(310120832)))];
            tensor<fp16, [1, 320, 1, 4096]> var_4579_cast_fp16 = conv(bias = up_blocks_2_attentions_0_transformer_blocks_0_ff_net_2_bias_to_fp16, dilations = var_4579_dilations_0, groups = var_4579_groups_0, pad = var_4579_pad_0, pad_type = var_4579_pad_type_0, strides = var_4579_strides_0, weight = up_blocks_2_attentions_0_transformer_blocks_0_ff_net_2_weight_to_fp16, x = input_225_cast_fp16)[name = string("op_4579_cast_fp16")];
            tensor<fp16, [1, 320, 1, 4096]> hidden_states_151_cast_fp16 = add(x = var_4579_cast_fp16, y = inputs_47_cast_fp16)[name = string("hidden_states_151_cast_fp16")];
            tensor<int32, [4]> var_4581 = const()[name = string("op_4581"), val = tensor<int32, [4]>([1, 320, 64, 64])];
            tensor<fp16, [1, 320, 64, 64]> input_227_cast_fp16 = reshape(shape = var_4581, x = hidden_states_151_cast_fp16)[name = string("input_227_cast_fp16")];
            string hidden_states_153_pad_type_0 = const()[name = string("hidden_states_153_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> hidden_states_153_strides_0 = const()[name = string("hidden_states_153_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> hidden_states_153_pad_0 = const()[name = string("hidden_states_153_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> hidden_states_153_dilations_0 = const()[name = string("hidden_states_153_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_153_groups_0 = const()[name = string("hidden_states_153_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_0_proj_out_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_0_proj_out_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(310121536)))];
            tensor<fp16, [320]> up_blocks_2_attentions_0_proj_out_bias_to_fp16 = const()[name = string("up_blocks_2_attentions_0_proj_out_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(310326400)))];
            tensor<fp16, [1, 320, 64, 64]> hidden_states_153_cast_fp16 = conv(bias = up_blocks_2_attentions_0_proj_out_bias_to_fp16, dilations = hidden_states_153_dilations_0, groups = hidden_states_153_groups_0, pad = hidden_states_153_pad_0, pad_type = hidden_states_153_pad_type_0, strides = hidden_states_153_strides_0, weight = up_blocks_2_attentions_0_proj_out_weight_to_fp16, x = input_227_cast_fp16)[name = string("hidden_states_153_cast_fp16")];
            tensor<fp16, [1, 320, 64, 64]> hidden_states_155_cast_fp16 = add(x = hidden_states_153_cast_fp16, y = hidden_states_141_cast_fp16)[name = string("hidden_states_155_cast_fp16")];
            bool input_229_interleave_0 = const()[name = string("input_229_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 320, 64, 64]> cast_8 = cast(dtype = cast_8_dtype_0, x = input_7_cast_fp16)[name = string("cast_9")];
            tensor<fp16, [1, 640, 64, 64]> input_229_cast_fp16 = concat(axis = var_4045, interleave = input_229_interleave_0, values = (hidden_states_155_cast_fp16, cast_8))[name = string("input_229_cast_fp16")];
            tensor<int32, [5]> reshape_96_shape_0 = const()[name = string("reshape_96_shape_0"), val = tensor<int32, [5]>([1, 32, 20, 64, 64])];
            tensor<fp16, [1, 32, 20, 64, 64]> reshape_96_cast_fp16 = reshape(shape = reshape_96_shape_0, x = input_229_cast_fp16)[name = string("reshape_96_cast_fp16")];
            tensor<int32, [3]> reduce_mean_72_axes_0 = const()[name = string("reduce_mean_72_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_72_keep_dims_0 = const()[name = string("reduce_mean_72_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_72_cast_fp16 = reduce_mean(axes = reduce_mean_72_axes_0, keep_dims = reduce_mean_72_keep_dims_0, x = reshape_96_cast_fp16)[name = string("reduce_mean_72_cast_fp16")];
            tensor<fp16, [1, 32, 20, 64, 64]> sub_48_cast_fp16 = sub(x = reshape_96_cast_fp16, y = reduce_mean_72_cast_fp16)[name = string("sub_48_cast_fp16")];
            tensor<fp16, [1, 32, 20, 64, 64]> square_24_cast_fp16 = square(x = sub_48_cast_fp16)[name = string("square_24_cast_fp16")];
            tensor<int32, [3]> reduce_mean_74_axes_0 = const()[name = string("reduce_mean_74_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_74_keep_dims_0 = const()[name = string("reduce_mean_74_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_74_cast_fp16 = reduce_mean(axes = reduce_mean_74_axes_0, keep_dims = reduce_mean_74_keep_dims_0, x = square_24_cast_fp16)[name = string("reduce_mean_74_cast_fp16")];
            fp16 add_48_y_0_to_fp16 = const()[name = string("add_48_y_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_48_cast_fp16 = add(x = reduce_mean_74_cast_fp16, y = add_48_y_0_to_fp16)[name = string("add_48_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_24_cast_fp16 = sqrt(x = add_48_cast_fp16)[name = string("sqrt_24_cast_fp16")];
            tensor<fp16, [1, 32, 20, 64, 64]> real_div_24_cast_fp16 = real_div(x = sub_48_cast_fp16, y = sqrt_24_cast_fp16)[name = string("real_div_24_cast_fp16")];
            tensor<int32, [4]> reshape_97_shape_0 = const()[name = string("reshape_97_shape_0"), val = tensor<int32, [4]>([1, 640, 64, 64])];
            tensor<fp16, [1, 640, 64, 64]> reshape_97_cast_fp16 = reshape(shape = reshape_97_shape_0, x = real_div_24_cast_fp16)[name = string("reshape_97_cast_fp16")];
            tensor<fp16, [640]> add_49_gamma_0_to_fp16 = const()[name = string("add_49_gamma_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(310327104)))];
            tensor<fp16, [640]> add_49_beta_0_to_fp16 = const()[name = string("add_49_beta_0_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(310328448)))];
            fp16 add_49_epsilon_0_to_fp16 = const()[name = string("add_49_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 640, 64, 64]> add_49_cast_fp16 = batch_norm(beta = add_49_beta_0_to_fp16, epsilon = add_49_epsilon_0_to_fp16, gamma = add_49_gamma_0_to_fp16, mean = add_9_mean_0_to_fp16, variance = add_9_variance_0_to_fp16, x = reshape_97_cast_fp16)[name = string("add_49_cast_fp16")];
            tensor<fp16, [1, 640, 64, 64]> input_233_cast_fp16 = silu(x = add_49_cast_fp16)[name = string("input_233_cast_fp16")];
            string hidden_states_157_pad_type_0 = const()[name = string("hidden_states_157_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> hidden_states_157_pad_0 = const()[name = string("hidden_states_157_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> hidden_states_157_strides_0 = const()[name = string("hidden_states_157_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> hidden_states_157_dilations_0 = const()[name = string("hidden_states_157_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_157_groups_0 = const()[name = string("hidden_states_157_groups_0"), val = int32(1)];
            tensor<fp16, [320, 640, 3, 3]> up_blocks_2_resnets_1_conv1_weight_to_fp16 = const()[name = string("up_blocks_2_resnets_1_conv1_weight_to_fp16"), val = tensor<fp16, [320, 640, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(310329792)))];
            tensor<fp16, [320]> up_blocks_2_resnets_1_conv1_bias_to_fp16 = const()[name = string("up_blocks_2_resnets_1_conv1_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(314016256)))];
            tensor<fp16, [1, 320, 64, 64]> hidden_states_157_cast_fp16 = conv(bias = up_blocks_2_resnets_1_conv1_bias_to_fp16, dilations = hidden_states_157_dilations_0, groups = hidden_states_157_groups_0, pad = hidden_states_157_pad_0, pad_type = hidden_states_157_pad_type_0, strides = hidden_states_157_strides_0, weight = up_blocks_2_resnets_1_conv1_weight_to_fp16, x = input_233_cast_fp16)[name = string("hidden_states_157_cast_fp16")];
            string temb_pad_type_0 = const()[name = string("temb_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> temb_strides_0 = const()[name = string("temb_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> temb_pad_0 = const()[name = string("temb_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> temb_dilations_0 = const()[name = string("temb_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 temb_groups_0 = const()[name = string("temb_groups_0"), val = int32(1)];
            tensor<fp16, [320, 1280, 1, 1]> up_blocks_2_resnets_1_time_emb_proj_weight_to_fp16 = const()[name = string("up_blocks_2_resnets_1_time_emb_proj_weight_to_fp16"), val = tensor<fp16, [320, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(314016960)))];
            tensor<fp16, [320]> up_blocks_2_resnets_1_time_emb_proj_bias_to_fp16 = const()[name = string("up_blocks_2_resnets_1_time_emb_proj_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(314836224)))];
            tensor<fp16, [1, 320, 1, 1]> temb_cast_fp16 = conv(bias = up_blocks_2_resnets_1_time_emb_proj_bias_to_fp16, dilations = temb_dilations_0, groups = temb_groups_0, pad = temb_pad_0, pad_type = temb_pad_type_0, strides = temb_strides_0, weight = up_blocks_2_resnets_1_time_emb_proj_weight_to_fp16, x = cast_7)[name = string("temb_cast_fp16")];
            tensor<fp16, [1, 320, 64, 64]> input_237_cast_fp16 = add(x = hidden_states_157_cast_fp16, y = temb_cast_fp16)[name = string("input_237_cast_fp16")];
            tensor<int32, [5]> reshape_100_shape_0 = const()[name = string("reshape_100_shape_0"), val = tensor<int32, [5]>([1, 32, 10, 64, 64])];
            tensor<fp16, [1, 32, 10, 64, 64]> reshape_100_cast_fp16 = reshape(shape = reshape_100_shape_0, x = input_237_cast_fp16)[name = string("reshape_100_cast_fp16")];
            tensor<int32, [3]> reduce_mean_75_axes_0 = const()[name = string("reduce_mean_75_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_75_keep_dims_0 = const()[name = string("reduce_mean_75_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_75_cast_fp16 = reduce_mean(axes = reduce_mean_75_axes_0, keep_dims = reduce_mean_75_keep_dims_0, x = reshape_100_cast_fp16)[name = string("reduce_mean_75_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> sub_50_cast_fp16 = sub(x = reshape_100_cast_fp16, y = reduce_mean_75_cast_fp16)[name = string("sub_50_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> square_25_cast_fp16 = square(x = sub_50_cast_fp16)[name = string("square_25_cast_fp16")];
            tensor<int32, [3]> reduce_mean_77_axes_0 = const()[name = string("reduce_mean_77_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_77_keep_dims_0 = const()[name = string("reduce_mean_77_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_77_cast_fp16 = reduce_mean(axes = reduce_mean_77_axes_0, keep_dims = reduce_mean_77_keep_dims_0, x = square_25_cast_fp16)[name = string("reduce_mean_77_cast_fp16")];
            fp16 add_50_y_0_to_fp16 = const()[name = string("add_50_y_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_50_cast_fp16 = add(x = reduce_mean_77_cast_fp16, y = add_50_y_0_to_fp16)[name = string("add_50_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_25_cast_fp16 = sqrt(x = add_50_cast_fp16)[name = string("sqrt_25_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> real_div_25_cast_fp16 = real_div(x = sub_50_cast_fp16, y = sqrt_25_cast_fp16)[name = string("real_div_25_cast_fp16")];
            tensor<int32, [4]> reshape_101_shape_0 = const()[name = string("reshape_101_shape_0"), val = tensor<int32, [4]>([1, 320, 64, 64])];
            tensor<fp16, [1, 320, 64, 64]> reshape_101_cast_fp16 = reshape(shape = reshape_101_shape_0, x = real_div_25_cast_fp16)[name = string("reshape_101_cast_fp16")];
            tensor<fp16, [320]> add_51_gamma_0_to_fp16 = const()[name = string("add_51_gamma_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(314836928)))];
            tensor<fp16, [320]> add_51_beta_0_to_fp16 = const()[name = string("add_51_beta_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(314837632)))];
            fp16 add_51_epsilon_0_to_fp16 = const()[name = string("add_51_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 320, 64, 64]> add_51_cast_fp16 = batch_norm(beta = add_51_beta_0_to_fp16, epsilon = add_51_epsilon_0_to_fp16, gamma = add_51_gamma_0_to_fp16, mean = add_1_mean_0_to_fp16, variance = add_1_variance_0_to_fp16, x = reshape_101_cast_fp16)[name = string("add_51_cast_fp16")];
            tensor<fp16, [1, 320, 64, 64]> input_241_cast_fp16 = silu(x = add_51_cast_fp16)[name = string("input_241_cast_fp16")];
            string hidden_states_159_pad_type_0 = const()[name = string("hidden_states_159_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> hidden_states_159_pad_0 = const()[name = string("hidden_states_159_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> hidden_states_159_strides_0 = const()[name = string("hidden_states_159_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> hidden_states_159_dilations_0 = const()[name = string("hidden_states_159_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_159_groups_0 = const()[name = string("hidden_states_159_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 3, 3]> up_blocks_2_resnets_1_conv2_weight_to_fp16 = const()[name = string("up_blocks_2_resnets_1_conv2_weight_to_fp16"), val = tensor<fp16, [320, 320, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(314838336)))];
            tensor<fp16, [320]> up_blocks_2_resnets_1_conv2_bias_to_fp16 = const()[name = string("up_blocks_2_resnets_1_conv2_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(316681600)))];
            tensor<fp16, [1, 320, 64, 64]> hidden_states_159_cast_fp16 = conv(bias = up_blocks_2_resnets_1_conv2_bias_to_fp16, dilations = hidden_states_159_dilations_0, groups = hidden_states_159_groups_0, pad = hidden_states_159_pad_0, pad_type = hidden_states_159_pad_type_0, strides = hidden_states_159_strides_0, weight = up_blocks_2_resnets_1_conv2_weight_to_fp16, x = input_241_cast_fp16)[name = string("hidden_states_159_cast_fp16")];
            string x_pad_type_0 = const()[name = string("x_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> x_strides_0 = const()[name = string("x_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> x_pad_0 = const()[name = string("x_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> x_dilations_0 = const()[name = string("x_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 x_groups_0 = const()[name = string("x_groups_0"), val = int32(1)];
            tensor<fp16, [320, 640, 1, 1]> up_blocks_2_resnets_1_conv_shortcut_weight_to_fp16 = const()[name = string("up_blocks_2_resnets_1_conv_shortcut_weight_to_fp16"), val = tensor<fp16, [320, 640, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(316682304)))];
            tensor<fp16, [320]> up_blocks_2_resnets_1_conv_shortcut_bias_to_fp16 = const()[name = string("up_blocks_2_resnets_1_conv_shortcut_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(317091968)))];
            tensor<fp16, [1, 320, 64, 64]> x_cast_fp16 = conv(bias = up_blocks_2_resnets_1_conv_shortcut_bias_to_fp16, dilations = x_dilations_0, groups = x_groups_0, pad = x_pad_0, pad_type = x_pad_type_0, strides = x_strides_0, weight = up_blocks_2_resnets_1_conv_shortcut_weight_to_fp16, x = input_229_cast_fp16)[name = string("x_cast_fp16")];
            tensor<fp16, [1, 320, 64, 64]> hidden_states_161_cast_fp16 = add(x = x_cast_fp16, y = hidden_states_159_cast_fp16)[name = string("hidden_states_161_cast_fp16")];
            tensor<int32, [5]> reshape_104_shape_0 = const()[name = string("reshape_104_shape_0"), val = tensor<int32, [5]>([1, 32, 10, 64, 64])];
            tensor<fp16, [1, 32, 10, 64, 64]> reshape_104_cast_fp16 = reshape(shape = reshape_104_shape_0, x = hidden_states_161_cast_fp16)[name = string("reshape_104_cast_fp16")];
            tensor<int32, [3]> reduce_mean_78_axes_0 = const()[name = string("reduce_mean_78_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_78_keep_dims_0 = const()[name = string("reduce_mean_78_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_78_cast_fp16 = reduce_mean(axes = reduce_mean_78_axes_0, keep_dims = reduce_mean_78_keep_dims_0, x = reshape_104_cast_fp16)[name = string("reduce_mean_78_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> sub_52_cast_fp16 = sub(x = reshape_104_cast_fp16, y = reduce_mean_78_cast_fp16)[name = string("sub_52_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> square_26_cast_fp16 = square(x = sub_52_cast_fp16)[name = string("square_26_cast_fp16")];
            tensor<int32, [3]> reduce_mean_80_axes_0 = const()[name = string("reduce_mean_80_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_80_keep_dims_0 = const()[name = string("reduce_mean_80_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_80_cast_fp16 = reduce_mean(axes = reduce_mean_80_axes_0, keep_dims = reduce_mean_80_keep_dims_0, x = square_26_cast_fp16)[name = string("reduce_mean_80_cast_fp16")];
            fp16 add_52_y_0_to_fp16 = const()[name = string("add_52_y_0_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_52_cast_fp16 = add(x = reduce_mean_80_cast_fp16, y = add_52_y_0_to_fp16)[name = string("add_52_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_26_cast_fp16 = sqrt(x = add_52_cast_fp16)[name = string("sqrt_26_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> real_div_26_cast_fp16 = real_div(x = sub_52_cast_fp16, y = sqrt_26_cast_fp16)[name = string("real_div_26_cast_fp16")];
            tensor<int32, [4]> reshape_105_shape_0 = const()[name = string("reshape_105_shape_0"), val = tensor<int32, [4]>([1, 320, 64, 64])];
            tensor<fp16, [1, 320, 64, 64]> reshape_105_cast_fp16 = reshape(shape = reshape_105_shape_0, x = real_div_26_cast_fp16)[name = string("reshape_105_cast_fp16")];
            tensor<fp16, [320]> add_53_gamma_0_to_fp16 = const()[name = string("add_53_gamma_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(317092672)))];
            tensor<fp16, [320]> add_53_beta_0_to_fp16 = const()[name = string("add_53_beta_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(317093376)))];
            fp16 add_53_epsilon_0_to_fp16 = const()[name = string("add_53_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 320, 64, 64]> add_53_cast_fp16 = batch_norm(beta = add_53_beta_0_to_fp16, epsilon = add_53_epsilon_0_to_fp16, gamma = add_53_gamma_0_to_fp16, mean = add_1_mean_0_to_fp16, variance = add_1_variance_0_to_fp16, x = reshape_105_cast_fp16)[name = string("add_53_cast_fp16")];
            string hidden_states_163_pad_type_0 = const()[name = string("hidden_states_163_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> hidden_states_163_strides_0 = const()[name = string("hidden_states_163_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> hidden_states_163_pad_0 = const()[name = string("hidden_states_163_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> hidden_states_163_dilations_0 = const()[name = string("hidden_states_163_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_163_groups_0 = const()[name = string("hidden_states_163_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_1_proj_in_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_1_proj_in_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(317094080)))];
            tensor<fp16, [320]> up_blocks_2_attentions_1_proj_in_bias_to_fp16 = const()[name = string("up_blocks_2_attentions_1_proj_in_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(317298944)))];
            tensor<fp16, [1, 320, 64, 64]> hidden_states_163_cast_fp16 = conv(bias = up_blocks_2_attentions_1_proj_in_bias_to_fp16, dilations = hidden_states_163_dilations_0, groups = hidden_states_163_groups_0, pad = hidden_states_163_pad_0, pad_type = hidden_states_163_pad_type_0, strides = hidden_states_163_strides_0, weight = up_blocks_2_attentions_1_proj_in_weight_to_fp16, x = add_53_cast_fp16)[name = string("hidden_states_163_cast_fp16")];
            tensor<int32, [4]> var_4661 = const()[name = string("op_4661"), val = tensor<int32, [4]>([1, 320, 1, 4096])];
            tensor<fp16, [1, 320, 1, 4096]> inputs_49_cast_fp16 = reshape(shape = var_4661, x = hidden_states_163_cast_fp16)[name = string("inputs_49_cast_fp16")];
            tensor<int32, [1]> hidden_states_165_axes_0 = const()[name = string("hidden_states_165_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [320]> hidden_states_165_gamma_0_to_fp16 = const()[name = string("hidden_states_165_gamma_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(317299648)))];
            tensor<fp16, [320]> hidden_states_165_beta_0_to_fp16 = const()[name = string("hidden_states_165_beta_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(317300352)))];
            fp16 var_4677_to_fp16 = const()[name = string("op_4677_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 320, 1, 4096]> hidden_states_165_cast_fp16 = layer_norm(axes = hidden_states_165_axes_0, beta = hidden_states_165_beta_0_to_fp16, epsilon = var_4677_to_fp16, gamma = hidden_states_165_gamma_0_to_fp16, x = inputs_49_cast_fp16)[name = string("hidden_states_165_cast_fp16")];
            string q_33_pad_type_0 = const()[name = string("q_33_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> q_33_strides_0 = const()[name = string("q_33_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> q_33_pad_0 = const()[name = string("q_33_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> q_33_dilations_0 = const()[name = string("q_33_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 q_33_groups_0 = const()[name = string("q_33_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_q_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_q_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(317301056)))];
            tensor<fp16, [1, 320, 1, 4096]> q_33_cast_fp16 = conv(dilations = q_33_dilations_0, groups = q_33_groups_0, pad = q_33_pad_0, pad_type = q_33_pad_type_0, strides = q_33_strides_0, weight = up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_q_weight_to_fp16, x = hidden_states_165_cast_fp16)[name = string("q_33_cast_fp16")];
            string k_65_pad_type_0 = const()[name = string("k_65_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> k_65_strides_0 = const()[name = string("k_65_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> k_65_pad_0 = const()[name = string("k_65_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> k_65_dilations_0 = const()[name = string("k_65_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 k_65_groups_0 = const()[name = string("k_65_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_k_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_k_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(317505920)))];
            tensor<fp16, [1, 320, 1, 4096]> k_65_cast_fp16 = conv(dilations = k_65_dilations_0, groups = k_65_groups_0, pad = k_65_pad_0, pad_type = k_65_pad_type_0, strides = k_65_strides_0, weight = up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_k_weight_to_fp16, x = hidden_states_165_cast_fp16)[name = string("k_65_cast_fp16")];
            string v_33_pad_type_0 = const()[name = string("v_33_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> v_33_strides_0 = const()[name = string("v_33_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> v_33_pad_0 = const()[name = string("v_33_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> v_33_dilations_0 = const()[name = string("v_33_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 v_33_groups_0 = const()[name = string("v_33_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_v_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_v_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(317710784)))];
            tensor<fp16, [1, 320, 1, 4096]> v_33_cast_fp16 = conv(dilations = v_33_dilations_0, groups = v_33_groups_0, pad = v_33_pad_0, pad_type = v_33_pad_type_0, strides = v_33_strides_0, weight = up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_v_weight_to_fp16, x = hidden_states_165_cast_fp16)[name = string("v_33_cast_fp16")];
            tensor<int32, [4]> var_4710_begin_0 = const()[name = string("op_4710_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_4710_end_0 = const()[name = string("op_4710_end_0"), val = tensor<int32, [4]>([1, 40, 1, 4096])];
            tensor<bool, [4]> var_4710_end_mask_0 = const()[name = string("op_4710_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4710_cast_fp16 = slice_by_index(begin = var_4710_begin_0, end = var_4710_end_0, end_mask = var_4710_end_mask_0, x = q_33_cast_fp16)[name = string("op_4710_cast_fp16")];
            tensor<int32, [4]> var_4714_begin_0 = const()[name = string("op_4714_begin_0"), val = tensor<int32, [4]>([0, 40, 0, 0])];
            tensor<int32, [4]> var_4714_end_0 = const()[name = string("op_4714_end_0"), val = tensor<int32, [4]>([1, 80, 1, 4096])];
            tensor<bool, [4]> var_4714_end_mask_0 = const()[name = string("op_4714_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4714_cast_fp16 = slice_by_index(begin = var_4714_begin_0, end = var_4714_end_0, end_mask = var_4714_end_mask_0, x = q_33_cast_fp16)[name = string("op_4714_cast_fp16")];
            tensor<int32, [4]> var_4718_begin_0 = const()[name = string("op_4718_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_4718_end_0 = const()[name = string("op_4718_end_0"), val = tensor<int32, [4]>([1, 120, 1, 4096])];
            tensor<bool, [4]> var_4718_end_mask_0 = const()[name = string("op_4718_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4718_cast_fp16 = slice_by_index(begin = var_4718_begin_0, end = var_4718_end_0, end_mask = var_4718_end_mask_0, x = q_33_cast_fp16)[name = string("op_4718_cast_fp16")];
            tensor<int32, [4]> var_4722_begin_0 = const()[name = string("op_4722_begin_0"), val = tensor<int32, [4]>([0, 120, 0, 0])];
            tensor<int32, [4]> var_4722_end_0 = const()[name = string("op_4722_end_0"), val = tensor<int32, [4]>([1, 160, 1, 4096])];
            tensor<bool, [4]> var_4722_end_mask_0 = const()[name = string("op_4722_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4722_cast_fp16 = slice_by_index(begin = var_4722_begin_0, end = var_4722_end_0, end_mask = var_4722_end_mask_0, x = q_33_cast_fp16)[name = string("op_4722_cast_fp16")];
            tensor<int32, [4]> var_4726_begin_0 = const()[name = string("op_4726_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_4726_end_0 = const()[name = string("op_4726_end_0"), val = tensor<int32, [4]>([1, 200, 1, 4096])];
            tensor<bool, [4]> var_4726_end_mask_0 = const()[name = string("op_4726_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4726_cast_fp16 = slice_by_index(begin = var_4726_begin_0, end = var_4726_end_0, end_mask = var_4726_end_mask_0, x = q_33_cast_fp16)[name = string("op_4726_cast_fp16")];
            tensor<int32, [4]> var_4730_begin_0 = const()[name = string("op_4730_begin_0"), val = tensor<int32, [4]>([0, 200, 0, 0])];
            tensor<int32, [4]> var_4730_end_0 = const()[name = string("op_4730_end_0"), val = tensor<int32, [4]>([1, 240, 1, 4096])];
            tensor<bool, [4]> var_4730_end_mask_0 = const()[name = string("op_4730_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4730_cast_fp16 = slice_by_index(begin = var_4730_begin_0, end = var_4730_end_0, end_mask = var_4730_end_mask_0, x = q_33_cast_fp16)[name = string("op_4730_cast_fp16")];
            tensor<int32, [4]> var_4734_begin_0 = const()[name = string("op_4734_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_4734_end_0 = const()[name = string("op_4734_end_0"), val = tensor<int32, [4]>([1, 280, 1, 4096])];
            tensor<bool, [4]> var_4734_end_mask_0 = const()[name = string("op_4734_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4734_cast_fp16 = slice_by_index(begin = var_4734_begin_0, end = var_4734_end_0, end_mask = var_4734_end_mask_0, x = q_33_cast_fp16)[name = string("op_4734_cast_fp16")];
            tensor<int32, [4]> var_4738_begin_0 = const()[name = string("op_4738_begin_0"), val = tensor<int32, [4]>([0, 280, 0, 0])];
            tensor<int32, [4]> var_4738_end_0 = const()[name = string("op_4738_end_0"), val = tensor<int32, [4]>([1, 1, 1, 4096])];
            tensor<bool, [4]> var_4738_end_mask_0 = const()[name = string("op_4738_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4738_cast_fp16 = slice_by_index(begin = var_4738_begin_0, end = var_4738_end_0, end_mask = var_4738_end_mask_0, x = q_33_cast_fp16)[name = string("op_4738_cast_fp16")];
            tensor<int32, [4]> k_67_perm_0 = const()[name = string("k_67_perm_0"), val = tensor<int32, [4]>([0, 3, 2, 1])];
            tensor<int32, [4]> var_4745_begin_0 = const()[name = string("op_4745_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_4745_end_0 = const()[name = string("op_4745_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 40])];
            tensor<bool, [4]> var_4745_end_mask_0 = const()[name = string("op_4745_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 320]> k_67_cast_fp16 = transpose(perm = k_67_perm_0, x = k_65_cast_fp16)[name = string("transpose_1")];
            tensor<fp16, [1, 4096, 1, 40]> var_4745_cast_fp16 = slice_by_index(begin = var_4745_begin_0, end = var_4745_end_0, end_mask = var_4745_end_mask_0, x = k_67_cast_fp16)[name = string("op_4745_cast_fp16")];
            tensor<int32, [4]> var_4749_begin_0 = const()[name = string("op_4749_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 40])];
            tensor<int32, [4]> var_4749_end_0 = const()[name = string("op_4749_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 80])];
            tensor<bool, [4]> var_4749_end_mask_0 = const()[name = string("op_4749_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 40]> var_4749_cast_fp16 = slice_by_index(begin = var_4749_begin_0, end = var_4749_end_0, end_mask = var_4749_end_mask_0, x = k_67_cast_fp16)[name = string("op_4749_cast_fp16")];
            tensor<int32, [4]> var_4753_begin_0 = const()[name = string("op_4753_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 80])];
            tensor<int32, [4]> var_4753_end_0 = const()[name = string("op_4753_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 120])];
            tensor<bool, [4]> var_4753_end_mask_0 = const()[name = string("op_4753_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 40]> var_4753_cast_fp16 = slice_by_index(begin = var_4753_begin_0, end = var_4753_end_0, end_mask = var_4753_end_mask_0, x = k_67_cast_fp16)[name = string("op_4753_cast_fp16")];
            tensor<int32, [4]> var_4757_begin_0 = const()[name = string("op_4757_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 120])];
            tensor<int32, [4]> var_4757_end_0 = const()[name = string("op_4757_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 160])];
            tensor<bool, [4]> var_4757_end_mask_0 = const()[name = string("op_4757_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 40]> var_4757_cast_fp16 = slice_by_index(begin = var_4757_begin_0, end = var_4757_end_0, end_mask = var_4757_end_mask_0, x = k_67_cast_fp16)[name = string("op_4757_cast_fp16")];
            tensor<int32, [4]> var_4761_begin_0 = const()[name = string("op_4761_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 160])];
            tensor<int32, [4]> var_4761_end_0 = const()[name = string("op_4761_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 200])];
            tensor<bool, [4]> var_4761_end_mask_0 = const()[name = string("op_4761_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 40]> var_4761_cast_fp16 = slice_by_index(begin = var_4761_begin_0, end = var_4761_end_0, end_mask = var_4761_end_mask_0, x = k_67_cast_fp16)[name = string("op_4761_cast_fp16")];
            tensor<int32, [4]> var_4765_begin_0 = const()[name = string("op_4765_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 200])];
            tensor<int32, [4]> var_4765_end_0 = const()[name = string("op_4765_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 240])];
            tensor<bool, [4]> var_4765_end_mask_0 = const()[name = string("op_4765_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 40]> var_4765_cast_fp16 = slice_by_index(begin = var_4765_begin_0, end = var_4765_end_0, end_mask = var_4765_end_mask_0, x = k_67_cast_fp16)[name = string("op_4765_cast_fp16")];
            tensor<int32, [4]> var_4769_begin_0 = const()[name = string("op_4769_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 240])];
            tensor<int32, [4]> var_4769_end_0 = const()[name = string("op_4769_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 280])];
            tensor<bool, [4]> var_4769_end_mask_0 = const()[name = string("op_4769_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 4096, 1, 40]> var_4769_cast_fp16 = slice_by_index(begin = var_4769_begin_0, end = var_4769_end_0, end_mask = var_4769_end_mask_0, x = k_67_cast_fp16)[name = string("op_4769_cast_fp16")];
            tensor<int32, [4]> var_4773_begin_0 = const()[name = string("op_4773_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 280])];
            tensor<int32, [4]> var_4773_end_0 = const()[name = string("op_4773_end_0"), val = tensor<int32, [4]>([1, 4096, 1, 1])];
            tensor<bool, [4]> var_4773_end_mask_0 = const()[name = string("op_4773_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4096, 1, 40]> var_4773_cast_fp16 = slice_by_index(begin = var_4773_begin_0, end = var_4773_end_0, end_mask = var_4773_end_mask_0, x = k_67_cast_fp16)[name = string("op_4773_cast_fp16")];
            tensor<int32, [4]> var_4775_begin_0 = const()[name = string("op_4775_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_4775_end_0 = const()[name = string("op_4775_end_0"), val = tensor<int32, [4]>([1, 40, 1, 4096])];
            tensor<bool, [4]> var_4775_end_mask_0 = const()[name = string("op_4775_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4775_cast_fp16 = slice_by_index(begin = var_4775_begin_0, end = var_4775_end_0, end_mask = var_4775_end_mask_0, x = v_33_cast_fp16)[name = string("op_4775_cast_fp16")];
            tensor<int32, [4]> var_4779_begin_0 = const()[name = string("op_4779_begin_0"), val = tensor<int32, [4]>([0, 40, 0, 0])];
            tensor<int32, [4]> var_4779_end_0 = const()[name = string("op_4779_end_0"), val = tensor<int32, [4]>([1, 80, 1, 4096])];
            tensor<bool, [4]> var_4779_end_mask_0 = const()[name = string("op_4779_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4779_cast_fp16 = slice_by_index(begin = var_4779_begin_0, end = var_4779_end_0, end_mask = var_4779_end_mask_0, x = v_33_cast_fp16)[name = string("op_4779_cast_fp16")];
            tensor<int32, [4]> var_4783_begin_0 = const()[name = string("op_4783_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_4783_end_0 = const()[name = string("op_4783_end_0"), val = tensor<int32, [4]>([1, 120, 1, 4096])];
            tensor<bool, [4]> var_4783_end_mask_0 = const()[name = string("op_4783_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4783_cast_fp16 = slice_by_index(begin = var_4783_begin_0, end = var_4783_end_0, end_mask = var_4783_end_mask_0, x = v_33_cast_fp16)[name = string("op_4783_cast_fp16")];
            tensor<int32, [4]> var_4787_begin_0 = const()[name = string("op_4787_begin_0"), val = tensor<int32, [4]>([0, 120, 0, 0])];
            tensor<int32, [4]> var_4787_end_0 = const()[name = string("op_4787_end_0"), val = tensor<int32, [4]>([1, 160, 1, 4096])];
            tensor<bool, [4]> var_4787_end_mask_0 = const()[name = string("op_4787_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4787_cast_fp16 = slice_by_index(begin = var_4787_begin_0, end = var_4787_end_0, end_mask = var_4787_end_mask_0, x = v_33_cast_fp16)[name = string("op_4787_cast_fp16")];
            tensor<int32, [4]> var_4791_begin_0 = const()[name = string("op_4791_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_4791_end_0 = const()[name = string("op_4791_end_0"), val = tensor<int32, [4]>([1, 200, 1, 4096])];
            tensor<bool, [4]> var_4791_end_mask_0 = const()[name = string("op_4791_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4791_cast_fp16 = slice_by_index(begin = var_4791_begin_0, end = var_4791_end_0, end_mask = var_4791_end_mask_0, x = v_33_cast_fp16)[name = string("op_4791_cast_fp16")];
            tensor<int32, [4]> var_4795_begin_0 = const()[name = string("op_4795_begin_0"), val = tensor<int32, [4]>([0, 200, 0, 0])];
            tensor<int32, [4]> var_4795_end_0 = const()[name = string("op_4795_end_0"), val = tensor<int32, [4]>([1, 240, 1, 4096])];
            tensor<bool, [4]> var_4795_end_mask_0 = const()[name = string("op_4795_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4795_cast_fp16 = slice_by_index(begin = var_4795_begin_0, end = var_4795_end_0, end_mask = var_4795_end_mask_0, x = v_33_cast_fp16)[name = string("op_4795_cast_fp16")];
            tensor<int32, [4]> var_4799_begin_0 = const()[name = string("op_4799_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_4799_end_0 = const()[name = string("op_4799_end_0"), val = tensor<int32, [4]>([1, 280, 1, 4096])];
            tensor<bool, [4]> var_4799_end_mask_0 = const()[name = string("op_4799_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4799_cast_fp16 = slice_by_index(begin = var_4799_begin_0, end = var_4799_end_0, end_mask = var_4799_end_mask_0, x = v_33_cast_fp16)[name = string("op_4799_cast_fp16")];
            tensor<int32, [4]> var_4803_begin_0 = const()[name = string("op_4803_begin_0"), val = tensor<int32, [4]>([0, 280, 0, 0])];
            tensor<int32, [4]> var_4803_end_0 = const()[name = string("op_4803_end_0"), val = tensor<int32, [4]>([1, 1, 1, 4096])];
            tensor<bool, [4]> var_4803_end_mask_0 = const()[name = string("op_4803_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4803_cast_fp16 = slice_by_index(begin = var_4803_begin_0, end = var_4803_end_0, end_mask = var_4803_end_mask_0, x = v_33_cast_fp16)[name = string("op_4803_cast_fp16")];
            string var_4807_equation_0 = const()[name = string("op_4807_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4807_cast_fp16 = einsum(equation = var_4807_equation_0, values = (var_4745_cast_fp16, var_4710_cast_fp16))[name = string("op_4807_cast_fp16")];
            fp16 var_4808_to_fp16 = const()[name = string("op_4808_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_257_cast_fp16 = mul(x = var_4807_cast_fp16, y = var_4808_to_fp16)[name = string("aw_257_cast_fp16")];
            string var_4811_equation_0 = const()[name = string("op_4811_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4811_cast_fp16 = einsum(equation = var_4811_equation_0, values = (var_4749_cast_fp16, var_4714_cast_fp16))[name = string("op_4811_cast_fp16")];
            fp16 var_4812_to_fp16 = const()[name = string("op_4812_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_259_cast_fp16 = mul(x = var_4811_cast_fp16, y = var_4812_to_fp16)[name = string("aw_259_cast_fp16")];
            string var_4815_equation_0 = const()[name = string("op_4815_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4815_cast_fp16 = einsum(equation = var_4815_equation_0, values = (var_4753_cast_fp16, var_4718_cast_fp16))[name = string("op_4815_cast_fp16")];
            fp16 var_4816_to_fp16 = const()[name = string("op_4816_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_261_cast_fp16 = mul(x = var_4815_cast_fp16, y = var_4816_to_fp16)[name = string("aw_261_cast_fp16")];
            string var_4819_equation_0 = const()[name = string("op_4819_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4819_cast_fp16 = einsum(equation = var_4819_equation_0, values = (var_4757_cast_fp16, var_4722_cast_fp16))[name = string("op_4819_cast_fp16")];
            fp16 var_4820_to_fp16 = const()[name = string("op_4820_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_263_cast_fp16 = mul(x = var_4819_cast_fp16, y = var_4820_to_fp16)[name = string("aw_263_cast_fp16")];
            string var_4823_equation_0 = const()[name = string("op_4823_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4823_cast_fp16 = einsum(equation = var_4823_equation_0, values = (var_4761_cast_fp16, var_4726_cast_fp16))[name = string("op_4823_cast_fp16")];
            fp16 var_4824_to_fp16 = const()[name = string("op_4824_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_265_cast_fp16 = mul(x = var_4823_cast_fp16, y = var_4824_to_fp16)[name = string("aw_265_cast_fp16")];
            string var_4827_equation_0 = const()[name = string("op_4827_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4827_cast_fp16 = einsum(equation = var_4827_equation_0, values = (var_4765_cast_fp16, var_4730_cast_fp16))[name = string("op_4827_cast_fp16")];
            fp16 var_4828_to_fp16 = const()[name = string("op_4828_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_267_cast_fp16 = mul(x = var_4827_cast_fp16, y = var_4828_to_fp16)[name = string("aw_267_cast_fp16")];
            string var_4831_equation_0 = const()[name = string("op_4831_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4831_cast_fp16 = einsum(equation = var_4831_equation_0, values = (var_4769_cast_fp16, var_4734_cast_fp16))[name = string("op_4831_cast_fp16")];
            fp16 var_4832_to_fp16 = const()[name = string("op_4832_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_269_cast_fp16 = mul(x = var_4831_cast_fp16, y = var_4832_to_fp16)[name = string("aw_269_cast_fp16")];
            string var_4835_equation_0 = const()[name = string("op_4835_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4835_cast_fp16 = einsum(equation = var_4835_equation_0, values = (var_4773_cast_fp16, var_4738_cast_fp16))[name = string("op_4835_cast_fp16")];
            fp16 var_4836_to_fp16 = const()[name = string("op_4836_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 4096, 1, 4096]> aw_271_cast_fp16 = mul(x = var_4835_cast_fp16, y = var_4836_to_fp16)[name = string("aw_271_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4838_cast_fp16 = softmax(axis = var_4045, x = aw_257_cast_fp16)[name = string("op_4838_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4839_cast_fp16 = softmax(axis = var_4045, x = aw_259_cast_fp16)[name = string("op_4839_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4840_cast_fp16 = softmax(axis = var_4045, x = aw_261_cast_fp16)[name = string("op_4840_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4841_cast_fp16 = softmax(axis = var_4045, x = aw_263_cast_fp16)[name = string("op_4841_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4842_cast_fp16 = softmax(axis = var_4045, x = aw_265_cast_fp16)[name = string("op_4842_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4843_cast_fp16 = softmax(axis = var_4045, x = aw_267_cast_fp16)[name = string("op_4843_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4844_cast_fp16 = softmax(axis = var_4045, x = aw_269_cast_fp16)[name = string("op_4844_cast_fp16")];
            tensor<fp16, [1, 4096, 1, 4096]> var_4845_cast_fp16 = softmax(axis = var_4045, x = aw_271_cast_fp16)[name = string("op_4845_cast_fp16")];
            string var_4847_equation_0 = const()[name = string("op_4847_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4847_cast_fp16 = einsum(equation = var_4847_equation_0, values = (var_4775_cast_fp16, var_4838_cast_fp16))[name = string("op_4847_cast_fp16")];
            string var_4849_equation_0 = const()[name = string("op_4849_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4849_cast_fp16 = einsum(equation = var_4849_equation_0, values = (var_4779_cast_fp16, var_4839_cast_fp16))[name = string("op_4849_cast_fp16")];
            string var_4851_equation_0 = const()[name = string("op_4851_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4851_cast_fp16 = einsum(equation = var_4851_equation_0, values = (var_4783_cast_fp16, var_4840_cast_fp16))[name = string("op_4851_cast_fp16")];
            string var_4853_equation_0 = const()[name = string("op_4853_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4853_cast_fp16 = einsum(equation = var_4853_equation_0, values = (var_4787_cast_fp16, var_4841_cast_fp16))[name = string("op_4853_cast_fp16")];
            string var_4855_equation_0 = const()[name = string("op_4855_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4855_cast_fp16 = einsum(equation = var_4855_equation_0, values = (var_4791_cast_fp16, var_4842_cast_fp16))[name = string("op_4855_cast_fp16")];
            string var_4857_equation_0 = const()[name = string("op_4857_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4857_cast_fp16 = einsum(equation = var_4857_equation_0, values = (var_4795_cast_fp16, var_4843_cast_fp16))[name = string("op_4857_cast_fp16")];
            string var_4859_equation_0 = const()[name = string("op_4859_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4859_cast_fp16 = einsum(equation = var_4859_equation_0, values = (var_4799_cast_fp16, var_4844_cast_fp16))[name = string("op_4859_cast_fp16")];
            string var_4861_equation_0 = const()[name = string("op_4861_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_4861_cast_fp16 = einsum(equation = var_4861_equation_0, values = (var_4803_cast_fp16, var_4845_cast_fp16))[name = string("op_4861_cast_fp16")];
            bool input_245_interleave_0 = const()[name = string("input_245_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 320, 1, 4096]> input_245_cast_fp16 = concat(axis = var_4045, interleave = input_245_interleave_0, values = (var_4847_cast_fp16, var_4849_cast_fp16, var_4851_cast_fp16, var_4853_cast_fp16, var_4855_cast_fp16, var_4857_cast_fp16, var_4859_cast_fp16, var_4861_cast_fp16))[name = string("input_245_cast_fp16")];
            string var_4871_pad_type_0 = const()[name = string("op_4871_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_4871_strides_0 = const()[name = string("op_4871_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_4871_pad_0 = const()[name = string("op_4871_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_4871_dilations_0 = const()[name = string("op_4871_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_4871_groups_0 = const()[name = string("op_4871_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_out_0_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_out_0_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(317915648)))];
            tensor<fp16, [320]> up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_out_0_bias_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_out_0_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(318120512)))];
            tensor<fp16, [1, 320, 1, 4096]> var_4871_cast_fp16 = conv(bias = up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_out_0_bias_to_fp16, dilations = var_4871_dilations_0, groups = var_4871_groups_0, pad = var_4871_pad_0, pad_type = var_4871_pad_type_0, strides = var_4871_strides_0, weight = up_blocks_2_attentions_1_transformer_blocks_0_attn1_to_out_0_weight_to_fp16, x = input_245_cast_fp16)[name = string("op_4871_cast_fp16")];
            tensor<fp16, [1, 320, 1, 4096]> inputs_51_cast_fp16 = add(x = var_4871_cast_fp16, y = inputs_49_cast_fp16)[name = string("inputs_51_cast_fp16")];
            tensor<int32, [1]> hidden_states_167_axes_0 = const()[name = string("hidden_states_167_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [320]> hidden_states_167_gamma_0_to_fp16 = const()[name = string("hidden_states_167_gamma_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(318121216)))];
            tensor<fp16, [320]> hidden_states_167_beta_0_to_fp16 = const()[name = string("hidden_states_167_beta_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(318121920)))];
            fp16 var_4881_to_fp16 = const()[name = string("op_4881_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 320, 1, 4096]> hidden_states_167_cast_fp16 = layer_norm(axes = hidden_states_167_axes_0, beta = hidden_states_167_beta_0_to_fp16, epsilon = var_4881_to_fp16, gamma = hidden_states_167_gamma_0_to_fp16, x = inputs_51_cast_fp16)[name = string("hidden_states_167_cast_fp16")];
            string q_pad_type_0 = const()[name = string("q_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> q_strides_0 = const()[name = string("q_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> q_pad_0 = const()[name = string("q_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> q_dilations_0 = const()[name = string("q_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 q_groups_0 = const()[name = string("q_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_q_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_q_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(318122624)))];
            tensor<fp16, [1, 320, 1, 4096]> q_cast_fp16 = conv(dilations = q_dilations_0, groups = q_groups_0, pad = q_pad_0, pad_type = q_pad_type_0, strides = q_strides_0, weight = up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_q_weight_to_fp16, x = hidden_states_167_cast_fp16)[name = string("q_cast_fp16")];
            string k_69_pad_type_0 = const()[name = string("k_69_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> k_69_strides_0 = const()[name = string("k_69_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> k_69_pad_0 = const()[name = string("k_69_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> k_69_dilations_0 = const()[name = string("k_69_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 k_69_groups_0 = const()[name = string("k_69_groups_0"), val = int32(1)];
            tensor<fp16, [320, 768, 1, 1]> up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_k_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_k_weight_to_fp16"), val = tensor<fp16, [320, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(318327488)))];
            tensor<fp16, [1, 320, 1, 77]> k_69_cast_fp16 = conv(dilations = k_69_dilations_0, groups = k_69_groups_0, pad = k_69_pad_0, pad_type = k_69_pad_type_0, strides = k_69_strides_0, weight = up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_k_weight_to_fp16, x = encoder_hidden_states)[name = string("k_69_cast_fp16")];
            string v_pad_type_0 = const()[name = string("v_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> v_strides_0 = const()[name = string("v_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> v_pad_0 = const()[name = string("v_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> v_dilations_0 = const()[name = string("v_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 v_groups_0 = const()[name = string("v_groups_0"), val = int32(1)];
            tensor<fp16, [320, 768, 1, 1]> up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_v_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_v_weight_to_fp16"), val = tensor<fp16, [320, 768, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(318819072)))];
            tensor<fp16, [1, 320, 1, 77]> v_cast_fp16 = conv(dilations = v_dilations_0, groups = v_groups_0, pad = v_pad_0, pad_type = v_pad_type_0, strides = v_strides_0, weight = up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_v_weight_to_fp16, x = encoder_hidden_states)[name = string("v_cast_fp16")];
            tensor<int32, [4]> var_4914_begin_0 = const()[name = string("op_4914_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_4914_end_0 = const()[name = string("op_4914_end_0"), val = tensor<int32, [4]>([1, 40, 1, 4096])];
            tensor<bool, [4]> var_4914_end_mask_0 = const()[name = string("op_4914_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4914_cast_fp16 = slice_by_index(begin = var_4914_begin_0, end = var_4914_end_0, end_mask = var_4914_end_mask_0, x = q_cast_fp16)[name = string("op_4914_cast_fp16")];
            tensor<int32, [4]> var_4918_begin_0 = const()[name = string("op_4918_begin_0"), val = tensor<int32, [4]>([0, 40, 0, 0])];
            tensor<int32, [4]> var_4918_end_0 = const()[name = string("op_4918_end_0"), val = tensor<int32, [4]>([1, 80, 1, 4096])];
            tensor<bool, [4]> var_4918_end_mask_0 = const()[name = string("op_4918_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4918_cast_fp16 = slice_by_index(begin = var_4918_begin_0, end = var_4918_end_0, end_mask = var_4918_end_mask_0, x = q_cast_fp16)[name = string("op_4918_cast_fp16")];
            tensor<int32, [4]> var_4922_begin_0 = const()[name = string("op_4922_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_4922_end_0 = const()[name = string("op_4922_end_0"), val = tensor<int32, [4]>([1, 120, 1, 4096])];
            tensor<bool, [4]> var_4922_end_mask_0 = const()[name = string("op_4922_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4922_cast_fp16 = slice_by_index(begin = var_4922_begin_0, end = var_4922_end_0, end_mask = var_4922_end_mask_0, x = q_cast_fp16)[name = string("op_4922_cast_fp16")];
            tensor<int32, [4]> var_4926_begin_0 = const()[name = string("op_4926_begin_0"), val = tensor<int32, [4]>([0, 120, 0, 0])];
            tensor<int32, [4]> var_4926_end_0 = const()[name = string("op_4926_end_0"), val = tensor<int32, [4]>([1, 160, 1, 4096])];
            tensor<bool, [4]> var_4926_end_mask_0 = const()[name = string("op_4926_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4926_cast_fp16 = slice_by_index(begin = var_4926_begin_0, end = var_4926_end_0, end_mask = var_4926_end_mask_0, x = q_cast_fp16)[name = string("op_4926_cast_fp16")];
            tensor<int32, [4]> var_4930_begin_0 = const()[name = string("op_4930_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_4930_end_0 = const()[name = string("op_4930_end_0"), val = tensor<int32, [4]>([1, 200, 1, 4096])];
            tensor<bool, [4]> var_4930_end_mask_0 = const()[name = string("op_4930_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4930_cast_fp16 = slice_by_index(begin = var_4930_begin_0, end = var_4930_end_0, end_mask = var_4930_end_mask_0, x = q_cast_fp16)[name = string("op_4930_cast_fp16")];
            tensor<int32, [4]> var_4934_begin_0 = const()[name = string("op_4934_begin_0"), val = tensor<int32, [4]>([0, 200, 0, 0])];
            tensor<int32, [4]> var_4934_end_0 = const()[name = string("op_4934_end_0"), val = tensor<int32, [4]>([1, 240, 1, 4096])];
            tensor<bool, [4]> var_4934_end_mask_0 = const()[name = string("op_4934_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4934_cast_fp16 = slice_by_index(begin = var_4934_begin_0, end = var_4934_end_0, end_mask = var_4934_end_mask_0, x = q_cast_fp16)[name = string("op_4934_cast_fp16")];
            tensor<int32, [4]> var_4938_begin_0 = const()[name = string("op_4938_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_4938_end_0 = const()[name = string("op_4938_end_0"), val = tensor<int32, [4]>([1, 280, 1, 4096])];
            tensor<bool, [4]> var_4938_end_mask_0 = const()[name = string("op_4938_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4938_cast_fp16 = slice_by_index(begin = var_4938_begin_0, end = var_4938_end_0, end_mask = var_4938_end_mask_0, x = q_cast_fp16)[name = string("op_4938_cast_fp16")];
            tensor<int32, [4]> var_4942_begin_0 = const()[name = string("op_4942_begin_0"), val = tensor<int32, [4]>([0, 280, 0, 0])];
            tensor<int32, [4]> var_4942_end_0 = const()[name = string("op_4942_end_0"), val = tensor<int32, [4]>([1, 1, 1, 4096])];
            tensor<bool, [4]> var_4942_end_mask_0 = const()[name = string("op_4942_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 40, 1, 4096]> var_4942_cast_fp16 = slice_by_index(begin = var_4942_begin_0, end = var_4942_end_0, end_mask = var_4942_end_mask_0, x = q_cast_fp16)[name = string("op_4942_cast_fp16")];
            tensor<int32, [4]> k_perm_0 = const()[name = string("k_perm_0"), val = tensor<int32, [4]>([0, 3, 2, 1])];
            tensor<int32, [4]> var_4949_begin_0 = const()[name = string("op_4949_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_4949_end_0 = const()[name = string("op_4949_end_0"), val = tensor<int32, [4]>([1, 77, 1, 40])];
            tensor<bool, [4]> var_4949_end_mask_0 = const()[name = string("op_4949_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 320]> k_cast_fp16 = transpose(perm = k_perm_0, x = k_69_cast_fp16)[name = string("transpose_0")];
            tensor<fp16, [1, 77, 1, 40]> var_4949_cast_fp16 = slice_by_index(begin = var_4949_begin_0, end = var_4949_end_0, end_mask = var_4949_end_mask_0, x = k_cast_fp16)[name = string("op_4949_cast_fp16")];
            tensor<int32, [4]> var_4953_begin_0 = const()[name = string("op_4953_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 40])];
            tensor<int32, [4]> var_4953_end_0 = const()[name = string("op_4953_end_0"), val = tensor<int32, [4]>([1, 77, 1, 80])];
            tensor<bool, [4]> var_4953_end_mask_0 = const()[name = string("op_4953_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 40]> var_4953_cast_fp16 = slice_by_index(begin = var_4953_begin_0, end = var_4953_end_0, end_mask = var_4953_end_mask_0, x = k_cast_fp16)[name = string("op_4953_cast_fp16")];
            tensor<int32, [4]> var_4957_begin_0 = const()[name = string("op_4957_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 80])];
            tensor<int32, [4]> var_4957_end_0 = const()[name = string("op_4957_end_0"), val = tensor<int32, [4]>([1, 77, 1, 120])];
            tensor<bool, [4]> var_4957_end_mask_0 = const()[name = string("op_4957_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 40]> var_4957_cast_fp16 = slice_by_index(begin = var_4957_begin_0, end = var_4957_end_0, end_mask = var_4957_end_mask_0, x = k_cast_fp16)[name = string("op_4957_cast_fp16")];
            tensor<int32, [4]> var_4961_begin_0 = const()[name = string("op_4961_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 120])];
            tensor<int32, [4]> var_4961_end_0 = const()[name = string("op_4961_end_0"), val = tensor<int32, [4]>([1, 77, 1, 160])];
            tensor<bool, [4]> var_4961_end_mask_0 = const()[name = string("op_4961_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 40]> var_4961_cast_fp16 = slice_by_index(begin = var_4961_begin_0, end = var_4961_end_0, end_mask = var_4961_end_mask_0, x = k_cast_fp16)[name = string("op_4961_cast_fp16")];
            tensor<int32, [4]> var_4965_begin_0 = const()[name = string("op_4965_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 160])];
            tensor<int32, [4]> var_4965_end_0 = const()[name = string("op_4965_end_0"), val = tensor<int32, [4]>([1, 77, 1, 200])];
            tensor<bool, [4]> var_4965_end_mask_0 = const()[name = string("op_4965_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 40]> var_4965_cast_fp16 = slice_by_index(begin = var_4965_begin_0, end = var_4965_end_0, end_mask = var_4965_end_mask_0, x = k_cast_fp16)[name = string("op_4965_cast_fp16")];
            tensor<int32, [4]> var_4969_begin_0 = const()[name = string("op_4969_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 200])];
            tensor<int32, [4]> var_4969_end_0 = const()[name = string("op_4969_end_0"), val = tensor<int32, [4]>([1, 77, 1, 240])];
            tensor<bool, [4]> var_4969_end_mask_0 = const()[name = string("op_4969_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 40]> var_4969_cast_fp16 = slice_by_index(begin = var_4969_begin_0, end = var_4969_end_0, end_mask = var_4969_end_mask_0, x = k_cast_fp16)[name = string("op_4969_cast_fp16")];
            tensor<int32, [4]> var_4973_begin_0 = const()[name = string("op_4973_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 240])];
            tensor<int32, [4]> var_4973_end_0 = const()[name = string("op_4973_end_0"), val = tensor<int32, [4]>([1, 77, 1, 280])];
            tensor<bool, [4]> var_4973_end_mask_0 = const()[name = string("op_4973_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 77, 1, 40]> var_4973_cast_fp16 = slice_by_index(begin = var_4973_begin_0, end = var_4973_end_0, end_mask = var_4973_end_mask_0, x = k_cast_fp16)[name = string("op_4973_cast_fp16")];
            tensor<int32, [4]> var_4977_begin_0 = const()[name = string("op_4977_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 280])];
            tensor<int32, [4]> var_4977_end_0 = const()[name = string("op_4977_end_0"), val = tensor<int32, [4]>([1, 77, 1, 1])];
            tensor<bool, [4]> var_4977_end_mask_0 = const()[name = string("op_4977_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 77, 1, 40]> var_4977_cast_fp16 = slice_by_index(begin = var_4977_begin_0, end = var_4977_end_0, end_mask = var_4977_end_mask_0, x = k_cast_fp16)[name = string("op_4977_cast_fp16")];
            tensor<int32, [4]> var_4979_begin_0 = const()[name = string("op_4979_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> var_4979_end_0 = const()[name = string("op_4979_end_0"), val = tensor<int32, [4]>([1, 40, 1, 77])];
            tensor<bool, [4]> var_4979_end_mask_0 = const()[name = string("op_4979_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4979_cast_fp16 = slice_by_index(begin = var_4979_begin_0, end = var_4979_end_0, end_mask = var_4979_end_mask_0, x = v_cast_fp16)[name = string("op_4979_cast_fp16")];
            tensor<int32, [4]> var_4983_begin_0 = const()[name = string("op_4983_begin_0"), val = tensor<int32, [4]>([0, 40, 0, 0])];
            tensor<int32, [4]> var_4983_end_0 = const()[name = string("op_4983_end_0"), val = tensor<int32, [4]>([1, 80, 1, 77])];
            tensor<bool, [4]> var_4983_end_mask_0 = const()[name = string("op_4983_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4983_cast_fp16 = slice_by_index(begin = var_4983_begin_0, end = var_4983_end_0, end_mask = var_4983_end_mask_0, x = v_cast_fp16)[name = string("op_4983_cast_fp16")];
            tensor<int32, [4]> var_4987_begin_0 = const()[name = string("op_4987_begin_0"), val = tensor<int32, [4]>([0, 80, 0, 0])];
            tensor<int32, [4]> var_4987_end_0 = const()[name = string("op_4987_end_0"), val = tensor<int32, [4]>([1, 120, 1, 77])];
            tensor<bool, [4]> var_4987_end_mask_0 = const()[name = string("op_4987_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4987_cast_fp16 = slice_by_index(begin = var_4987_begin_0, end = var_4987_end_0, end_mask = var_4987_end_mask_0, x = v_cast_fp16)[name = string("op_4987_cast_fp16")];
            tensor<int32, [4]> var_4991_begin_0 = const()[name = string("op_4991_begin_0"), val = tensor<int32, [4]>([0, 120, 0, 0])];
            tensor<int32, [4]> var_4991_end_0 = const()[name = string("op_4991_end_0"), val = tensor<int32, [4]>([1, 160, 1, 77])];
            tensor<bool, [4]> var_4991_end_mask_0 = const()[name = string("op_4991_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4991_cast_fp16 = slice_by_index(begin = var_4991_begin_0, end = var_4991_end_0, end_mask = var_4991_end_mask_0, x = v_cast_fp16)[name = string("op_4991_cast_fp16")];
            tensor<int32, [4]> var_4995_begin_0 = const()[name = string("op_4995_begin_0"), val = tensor<int32, [4]>([0, 160, 0, 0])];
            tensor<int32, [4]> var_4995_end_0 = const()[name = string("op_4995_end_0"), val = tensor<int32, [4]>([1, 200, 1, 77])];
            tensor<bool, [4]> var_4995_end_mask_0 = const()[name = string("op_4995_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4995_cast_fp16 = slice_by_index(begin = var_4995_begin_0, end = var_4995_end_0, end_mask = var_4995_end_mask_0, x = v_cast_fp16)[name = string("op_4995_cast_fp16")];
            tensor<int32, [4]> var_4999_begin_0 = const()[name = string("op_4999_begin_0"), val = tensor<int32, [4]>([0, 200, 0, 0])];
            tensor<int32, [4]> var_4999_end_0 = const()[name = string("op_4999_end_0"), val = tensor<int32, [4]>([1, 240, 1, 77])];
            tensor<bool, [4]> var_4999_end_mask_0 = const()[name = string("op_4999_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_4999_cast_fp16 = slice_by_index(begin = var_4999_begin_0, end = var_4999_end_0, end_mask = var_4999_end_mask_0, x = v_cast_fp16)[name = string("op_4999_cast_fp16")];
            tensor<int32, [4]> var_5003_begin_0 = const()[name = string("op_5003_begin_0"), val = tensor<int32, [4]>([0, 240, 0, 0])];
            tensor<int32, [4]> var_5003_end_0 = const()[name = string("op_5003_end_0"), val = tensor<int32, [4]>([1, 280, 1, 77])];
            tensor<bool, [4]> var_5003_end_mask_0 = const()[name = string("op_5003_end_mask_0"), val = tensor<bool, [4]>([true, false, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_5003_cast_fp16 = slice_by_index(begin = var_5003_begin_0, end = var_5003_end_0, end_mask = var_5003_end_mask_0, x = v_cast_fp16)[name = string("op_5003_cast_fp16")];
            tensor<int32, [4]> var_5007_begin_0 = const()[name = string("op_5007_begin_0"), val = tensor<int32, [4]>([0, 280, 0, 0])];
            tensor<int32, [4]> var_5007_end_0 = const()[name = string("op_5007_end_0"), val = tensor<int32, [4]>([1, 1, 1, 77])];
            tensor<bool, [4]> var_5007_end_mask_0 = const()[name = string("op_5007_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 40, 1, 77]> var_5007_cast_fp16 = slice_by_index(begin = var_5007_begin_0, end = var_5007_end_0, end_mask = var_5007_end_mask_0, x = v_cast_fp16)[name = string("op_5007_cast_fp16")];
            string var_5011_equation_0 = const()[name = string("op_5011_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_5011_cast_fp16 = einsum(equation = var_5011_equation_0, values = (var_4949_cast_fp16, var_4914_cast_fp16))[name = string("op_5011_cast_fp16")];
            fp16 var_5012_to_fp16 = const()[name = string("op_5012_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_273_cast_fp16 = mul(x = var_5011_cast_fp16, y = var_5012_to_fp16)[name = string("aw_273_cast_fp16")];
            string var_5015_equation_0 = const()[name = string("op_5015_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_5015_cast_fp16 = einsum(equation = var_5015_equation_0, values = (var_4953_cast_fp16, var_4918_cast_fp16))[name = string("op_5015_cast_fp16")];
            fp16 var_5016_to_fp16 = const()[name = string("op_5016_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_275_cast_fp16 = mul(x = var_5015_cast_fp16, y = var_5016_to_fp16)[name = string("aw_275_cast_fp16")];
            string var_5019_equation_0 = const()[name = string("op_5019_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_5019_cast_fp16 = einsum(equation = var_5019_equation_0, values = (var_4957_cast_fp16, var_4922_cast_fp16))[name = string("op_5019_cast_fp16")];
            fp16 var_5020_to_fp16 = const()[name = string("op_5020_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_277_cast_fp16 = mul(x = var_5019_cast_fp16, y = var_5020_to_fp16)[name = string("aw_277_cast_fp16")];
            string var_5023_equation_0 = const()[name = string("op_5023_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_5023_cast_fp16 = einsum(equation = var_5023_equation_0, values = (var_4961_cast_fp16, var_4926_cast_fp16))[name = string("op_5023_cast_fp16")];
            fp16 var_5024_to_fp16 = const()[name = string("op_5024_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_279_cast_fp16 = mul(x = var_5023_cast_fp16, y = var_5024_to_fp16)[name = string("aw_279_cast_fp16")];
            string var_5027_equation_0 = const()[name = string("op_5027_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_5027_cast_fp16 = einsum(equation = var_5027_equation_0, values = (var_4965_cast_fp16, var_4930_cast_fp16))[name = string("op_5027_cast_fp16")];
            fp16 var_5028_to_fp16 = const()[name = string("op_5028_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_281_cast_fp16 = mul(x = var_5027_cast_fp16, y = var_5028_to_fp16)[name = string("aw_281_cast_fp16")];
            string var_5031_equation_0 = const()[name = string("op_5031_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_5031_cast_fp16 = einsum(equation = var_5031_equation_0, values = (var_4969_cast_fp16, var_4934_cast_fp16))[name = string("op_5031_cast_fp16")];
            fp16 var_5032_to_fp16 = const()[name = string("op_5032_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_283_cast_fp16 = mul(x = var_5031_cast_fp16, y = var_5032_to_fp16)[name = string("aw_283_cast_fp16")];
            string var_5035_equation_0 = const()[name = string("op_5035_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_5035_cast_fp16 = einsum(equation = var_5035_equation_0, values = (var_4973_cast_fp16, var_4938_cast_fp16))[name = string("op_5035_cast_fp16")];
            fp16 var_5036_to_fp16 = const()[name = string("op_5036_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_285_cast_fp16 = mul(x = var_5035_cast_fp16, y = var_5036_to_fp16)[name = string("aw_285_cast_fp16")];
            string var_5039_equation_0 = const()[name = string("op_5039_equation_0"), val = string("bkhc,bchq->bkhq")];
            tensor<fp16, [1, 77, 1, 4096]> var_5039_cast_fp16 = einsum(equation = var_5039_equation_0, values = (var_4977_cast_fp16, var_4942_cast_fp16))[name = string("op_5039_cast_fp16")];
            fp16 var_5040_to_fp16 = const()[name = string("op_5040_to_fp16"), val = fp16(0x1.43cp-3)];
            tensor<fp16, [1, 77, 1, 4096]> aw_cast_fp16 = mul(x = var_5039_cast_fp16, y = var_5040_to_fp16)[name = string("aw_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_5042_cast_fp16 = softmax(axis = var_4045, x = aw_273_cast_fp16)[name = string("op_5042_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_5043_cast_fp16 = softmax(axis = var_4045, x = aw_275_cast_fp16)[name = string("op_5043_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_5044_cast_fp16 = softmax(axis = var_4045, x = aw_277_cast_fp16)[name = string("op_5044_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_5045_cast_fp16 = softmax(axis = var_4045, x = aw_279_cast_fp16)[name = string("op_5045_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_5046_cast_fp16 = softmax(axis = var_4045, x = aw_281_cast_fp16)[name = string("op_5046_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_5047_cast_fp16 = softmax(axis = var_4045, x = aw_283_cast_fp16)[name = string("op_5047_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_5048_cast_fp16 = softmax(axis = var_4045, x = aw_285_cast_fp16)[name = string("op_5048_cast_fp16")];
            tensor<fp16, [1, 77, 1, 4096]> var_5049_cast_fp16 = softmax(axis = var_4045, x = aw_cast_fp16)[name = string("op_5049_cast_fp16")];
            string var_5051_equation_0 = const()[name = string("op_5051_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_5051_cast_fp16 = einsum(equation = var_5051_equation_0, values = (var_4979_cast_fp16, var_5042_cast_fp16))[name = string("op_5051_cast_fp16")];
            string var_5053_equation_0 = const()[name = string("op_5053_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_5053_cast_fp16 = einsum(equation = var_5053_equation_0, values = (var_4983_cast_fp16, var_5043_cast_fp16))[name = string("op_5053_cast_fp16")];
            string var_5055_equation_0 = const()[name = string("op_5055_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_5055_cast_fp16 = einsum(equation = var_5055_equation_0, values = (var_4987_cast_fp16, var_5044_cast_fp16))[name = string("op_5055_cast_fp16")];
            string var_5057_equation_0 = const()[name = string("op_5057_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_5057_cast_fp16 = einsum(equation = var_5057_equation_0, values = (var_4991_cast_fp16, var_5045_cast_fp16))[name = string("op_5057_cast_fp16")];
            string var_5059_equation_0 = const()[name = string("op_5059_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_5059_cast_fp16 = einsum(equation = var_5059_equation_0, values = (var_4995_cast_fp16, var_5046_cast_fp16))[name = string("op_5059_cast_fp16")];
            string var_5061_equation_0 = const()[name = string("op_5061_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_5061_cast_fp16 = einsum(equation = var_5061_equation_0, values = (var_4999_cast_fp16, var_5047_cast_fp16))[name = string("op_5061_cast_fp16")];
            string var_5063_equation_0 = const()[name = string("op_5063_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_5063_cast_fp16 = einsum(equation = var_5063_equation_0, values = (var_5003_cast_fp16, var_5048_cast_fp16))[name = string("op_5063_cast_fp16")];
            string var_5065_equation_0 = const()[name = string("op_5065_equation_0"), val = string("bchk,bkhq->bchq")];
            tensor<fp16, [1, 40, 1, 4096]> var_5065_cast_fp16 = einsum(equation = var_5065_equation_0, values = (var_5007_cast_fp16, var_5049_cast_fp16))[name = string("op_5065_cast_fp16")];
            bool input_247_interleave_0 = const()[name = string("input_247_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 320, 1, 4096]> input_247_cast_fp16 = concat(axis = var_4045, interleave = input_247_interleave_0, values = (var_5051_cast_fp16, var_5053_cast_fp16, var_5055_cast_fp16, var_5057_cast_fp16, var_5059_cast_fp16, var_5061_cast_fp16, var_5063_cast_fp16, var_5065_cast_fp16))[name = string("input_247_cast_fp16")];
            string var_5075_pad_type_0 = const()[name = string("op_5075_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_5075_strides_0 = const()[name = string("op_5075_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_5075_pad_0 = const()[name = string("op_5075_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_5075_dilations_0 = const()[name = string("op_5075_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_5075_groups_0 = const()[name = string("op_5075_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_out_0_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_out_0_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(319310656)))];
            tensor<fp16, [320]> up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_out_0_bias_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_out_0_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(319515520)))];
            tensor<fp16, [1, 320, 1, 4096]> var_5075_cast_fp16 = conv(bias = up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_out_0_bias_to_fp16, dilations = var_5075_dilations_0, groups = var_5075_groups_0, pad = var_5075_pad_0, pad_type = var_5075_pad_type_0, strides = var_5075_strides_0, weight = up_blocks_2_attentions_1_transformer_blocks_0_attn2_to_out_0_weight_to_fp16, x = input_247_cast_fp16)[name = string("op_5075_cast_fp16")];
            tensor<fp16, [1, 320, 1, 4096]> inputs_cast_fp16 = add(x = var_5075_cast_fp16, y = inputs_51_cast_fp16)[name = string("inputs_cast_fp16")];
            tensor<int32, [1]> input_249_axes_0 = const()[name = string("input_249_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [320]> input_249_gamma_0_to_fp16 = const()[name = string("input_249_gamma_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(319516224)))];
            tensor<fp16, [320]> input_249_beta_0_to_fp16 = const()[name = string("input_249_beta_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(319516928)))];
            fp16 var_5085_to_fp16 = const()[name = string("op_5085_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 320, 1, 4096]> input_249_cast_fp16 = layer_norm(axes = input_249_axes_0, beta = input_249_beta_0_to_fp16, epsilon = var_5085_to_fp16, gamma = input_249_gamma_0_to_fp16, x = inputs_cast_fp16)[name = string("input_249_cast_fp16")];
            string var_5105_pad_type_0 = const()[name = string("op_5105_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_5105_strides_0 = const()[name = string("op_5105_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_5105_pad_0 = const()[name = string("op_5105_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_5105_dilations_0 = const()[name = string("op_5105_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_5105_groups_0 = const()[name = string("op_5105_groups_0"), val = int32(1)];
            tensor<fp16, [2560, 320, 1, 1]> up_blocks_2_attentions_1_transformer_blocks_0_ff_net_0_proj_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_ff_net_0_proj_weight_to_fp16"), val = tensor<fp16, [2560, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(319517632)))];
            tensor<fp16, [2560]> up_blocks_2_attentions_1_transformer_blocks_0_ff_net_0_proj_bias_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_ff_net_0_proj_bias_to_fp16"), val = tensor<fp16, [2560]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(321156096)))];
            tensor<fp16, [1, 2560, 1, 4096]> var_5105_cast_fp16 = conv(bias = up_blocks_2_attentions_1_transformer_blocks_0_ff_net_0_proj_bias_to_fp16, dilations = var_5105_dilations_0, groups = var_5105_groups_0, pad = var_5105_pad_0, pad_type = var_5105_pad_type_0, strides = var_5105_strides_0, weight = up_blocks_2_attentions_1_transformer_blocks_0_ff_net_0_proj_weight_to_fp16, x = input_249_cast_fp16)[name = string("op_5105_cast_fp16")];
            tensor<int32, [2]> var_5106_split_sizes_0 = const()[name = string("op_5106_split_sizes_0"), val = tensor<int32, [2]>([1280, 1280])];
            int32 var_5106_axis_0 = const()[name = string("op_5106_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1280, 1, 4096]> var_5106_cast_fp16_0, tensor<fp16, [1, 1280, 1, 4096]> var_5106_cast_fp16_1 = split(axis = var_5106_axis_0, split_sizes = var_5106_split_sizes_0, x = var_5105_cast_fp16)[name = string("op_5106_cast_fp16")];
            string var_5108_mode_0 = const()[name = string("op_5108_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1280, 1, 4096]> var_5108_cast_fp16 = gelu(mode = var_5108_mode_0, x = var_5106_cast_fp16_1)[name = string("op_5108_cast_fp16")];
            tensor<fp16, [1, 1280, 1, 4096]> input_251_cast_fp16 = mul(x = var_5106_cast_fp16_0, y = var_5108_cast_fp16)[name = string("input_251_cast_fp16")];
            string var_5116_pad_type_0 = const()[name = string("op_5116_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> var_5116_strides_0 = const()[name = string("op_5116_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> var_5116_pad_0 = const()[name = string("op_5116_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> var_5116_dilations_0 = const()[name = string("op_5116_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_5116_groups_0 = const()[name = string("op_5116_groups_0"), val = int32(1)];
            tensor<fp16, [320, 1280, 1, 1]> up_blocks_2_attentions_1_transformer_blocks_0_ff_net_2_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_ff_net_2_weight_to_fp16"), val = tensor<fp16, [320, 1280, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(321161280)))];
            tensor<fp16, [320]> up_blocks_2_attentions_1_transformer_blocks_0_ff_net_2_bias_to_fp16 = const()[name = string("up_blocks_2_attentions_1_transformer_blocks_0_ff_net_2_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(321980544)))];
            tensor<fp16, [1, 320, 1, 4096]> var_5116_cast_fp16 = conv(bias = up_blocks_2_attentions_1_transformer_blocks_0_ff_net_2_bias_to_fp16, dilations = var_5116_dilations_0, groups = var_5116_groups_0, pad = var_5116_pad_0, pad_type = var_5116_pad_type_0, strides = var_5116_strides_0, weight = up_blocks_2_attentions_1_transformer_blocks_0_ff_net_2_weight_to_fp16, x = input_251_cast_fp16)[name = string("op_5116_cast_fp16")];
            tensor<fp16, [1, 320, 1, 4096]> hidden_states_171_cast_fp16 = add(x = var_5116_cast_fp16, y = inputs_cast_fp16)[name = string("hidden_states_171_cast_fp16")];
            tensor<int32, [4]> var_5118 = const()[name = string("op_5118"), val = tensor<int32, [4]>([1, 320, 64, 64])];
            tensor<fp16, [1, 320, 64, 64]> input_253_cast_fp16 = reshape(shape = var_5118, x = hidden_states_171_cast_fp16)[name = string("input_253_cast_fp16")];
            string hidden_states_pad_type_0 = const()[name = string("hidden_states_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> hidden_states_strides_0 = const()[name = string("hidden_states_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> hidden_states_pad_0 = const()[name = string("hidden_states_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> hidden_states_dilations_0 = const()[name = string("hidden_states_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 hidden_states_groups_0 = const()[name = string("hidden_states_groups_0"), val = int32(1)];
            tensor<fp16, [320, 320, 1, 1]> up_blocks_2_attentions_1_proj_out_weight_to_fp16 = const()[name = string("up_blocks_2_attentions_1_proj_out_weight_to_fp16"), val = tensor<fp16, [320, 320, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(321981248)))];
            tensor<fp16, [320]> up_blocks_2_attentions_1_proj_out_bias_to_fp16 = const()[name = string("up_blocks_2_attentions_1_proj_out_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(322186112)))];
            tensor<fp16, [1, 320, 64, 64]> hidden_states_cast_fp16 = conv(bias = up_blocks_2_attentions_1_proj_out_bias_to_fp16, dilations = hidden_states_dilations_0, groups = hidden_states_groups_0, pad = hidden_states_pad_0, pad_type = hidden_states_pad_type_0, strides = hidden_states_strides_0, weight = up_blocks_2_attentions_1_proj_out_weight_to_fp16, x = input_253_cast_fp16)[name = string("hidden_states_cast_fp16")];
            tensor<fp16, [1, 320, 64, 64]> input_255_cast_fp16 = add(x = hidden_states_cast_fp16, y = hidden_states_161_cast_fp16)[name = string("input_255_cast_fp16")];
            tensor<int32, [5]> reshape_108_shape_0 = const()[name = string("reshape_108_shape_0"), val = tensor<int32, [5]>([1, 32, 10, 64, 64])];
            tensor<fp16, [1, 32, 10, 64, 64]> reshape_108_cast_fp16 = reshape(shape = reshape_108_shape_0, x = input_255_cast_fp16)[name = string("reshape_108_cast_fp16")];
            tensor<int32, [3]> reduce_mean_81_axes_0 = const()[name = string("reduce_mean_81_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_81_keep_dims_0 = const()[name = string("reduce_mean_81_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_81_cast_fp16 = reduce_mean(axes = reduce_mean_81_axes_0, keep_dims = reduce_mean_81_keep_dims_0, x = reshape_108_cast_fp16)[name = string("reduce_mean_81_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> sub_54_cast_fp16 = sub(x = reshape_108_cast_fp16, y = reduce_mean_81_cast_fp16)[name = string("sub_54_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> square_27_cast_fp16 = square(x = sub_54_cast_fp16)[name = string("square_27_cast_fp16")];
            tensor<int32, [3]> reduce_mean_83_axes_0 = const()[name = string("reduce_mean_83_axes_0"), val = tensor<int32, [3]>([2, 3, 4])];
            bool reduce_mean_83_keep_dims_0 = const()[name = string("reduce_mean_83_keep_dims_0"), val = bool(true)];
            tensor<fp16, [1, 32, 1, 1, 1]> reduce_mean_83_cast_fp16 = reduce_mean(axes = reduce_mean_83_axes_0, keep_dims = reduce_mean_83_keep_dims_0, x = square_27_cast_fp16)[name = string("reduce_mean_83_cast_fp16")];
            fp16 add_54_y_0_to_fp16 = const()[name = string("add_54_y_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 32, 1, 1, 1]> add_54_cast_fp16 = add(x = reduce_mean_83_cast_fp16, y = add_54_y_0_to_fp16)[name = string("add_54_cast_fp16")];
            tensor<fp16, [1, 32, 1, 1, 1]> sqrt_27_cast_fp16 = sqrt(x = add_54_cast_fp16)[name = string("sqrt_27_cast_fp16")];
            tensor<fp16, [1, 32, 10, 64, 64]> real_div_27_cast_fp16 = real_div(x = sub_54_cast_fp16, y = sqrt_27_cast_fp16)[name = string("real_div_27_cast_fp16")];
            tensor<int32, [4]> reshape_109_shape_0 = const()[name = string("reshape_109_shape_0"), val = tensor<int32, [4]>([1, 320, 64, 64])];
            tensor<fp16, [1, 320, 64, 64]> reshape_109_cast_fp16 = reshape(shape = reshape_109_shape_0, x = real_div_27_cast_fp16)[name = string("reshape_109_cast_fp16")];
            tensor<fp16, [320]> add_55_gamma_0_to_fp16 = const()[name = string("add_55_gamma_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(322186816)))];
            tensor<fp16, [320]> add_55_beta_0_to_fp16 = const()[name = string("add_55_beta_0_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(322187520)))];
            fp16 add_55_epsilon_0_to_fp16 = const()[name = string("add_55_epsilon_0_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 320, 64, 64]> add_55_cast_fp16 = batch_norm(beta = add_55_beta_0_to_fp16, epsilon = add_55_epsilon_0_to_fp16, gamma = add_55_gamma_0_to_fp16, mean = add_1_mean_0_to_fp16, variance = add_1_variance_0_to_fp16, x = reshape_109_cast_fp16)[name = string("add_55_cast_fp16")];
            tensor<fp16, [1, 320, 64, 64]> input_cast_fp16 = silu(x = add_55_cast_fp16)[name = string("input_cast_fp16")];
            string var_5145_pad_type_0 = const()[name = string("op_5145_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> var_5145_pad_0 = const()[name = string("op_5145_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> var_5145_strides_0 = const()[name = string("op_5145_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> var_5145_dilations_0 = const()[name = string("op_5145_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 var_5145_groups_0 = const()[name = string("op_5145_groups_0"), val = int32(1)];
            tensor<fp16, [4, 320, 3, 3]> conv_out_weight_to_fp16 = const()[name = string("conv_out_weight_to_fp16"), val = tensor<fp16, [4, 320, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(322188224)))];
            tensor<fp16, [4]> conv_out_bias_to_fp16 = const()[name = string("conv_out_bias_to_fp16"), val = tensor<fp16, [4]>([0x1.d64p-10, -0x1.31cp-11, 0x1.548p-12, -0x1.674p-10])];
            tensor<fp16, [1, 4, 64, 64]> var_5145_cast_fp16 = conv(bias = conv_out_bias_to_fp16, dilations = var_5145_dilations_0, groups = var_5145_groups_0, pad = var_5145_pad_0, pad_type = var_5145_pad_type_0, strides = var_5145_strides_0, weight = conv_out_weight_to_fp16, x = input_cast_fp16)[name = string("op_5145_cast_fp16")];
            string var_5145_cast_fp16_to_fp32_dtype_0 = const()[name = string("op_5145_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
            tensor<fp32, [1, 4, 64, 64]> noise_pred = cast(dtype = var_5145_cast_fp16_to_fp32_dtype_0, x = var_5145_cast_fp16)[name = string("cast_0")];
        } -> (noise_pred);
}