program(1.3)
[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}})]
{
    func main<ios18>(tensor<fp32, [1, 256]> decoder_mask, tensor<fp32, [1, 188, 1024]> encoder_embeddings, tensor<fp32, [1, 188]> encoder_mask, tensor<int32, [1, 256]> input_ids) {
            int32 var_24 = const()[name = string("op_24"), val = int32(-1)];
            int32 token_embeddings_batch_dims_0 = const()[name = string("token_embeddings_batch_dims_0"), val = int32(0)];
            bool token_embeddings_validate_indices_0 = const()[name = string("token_embeddings_validate_indices_0"), val = bool(false)];
            tensor<fp16, [16384, 1024]> module__embedding_token_embedding_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [16384, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64))), scale = tensor<fp16, [16384, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8388736))))[name = string("module__embedding_token_embedding_weight_to_fp16_quantized")];
            string input_ids_to_int16_dtype_0 = const()[name = string("input_ids_to_int16_dtype_0"), val = string("int16")];
            string cast_132_dtype_0 = const()[name = string("cast_132_dtype_0"), val = string("int32")];
            int32 greater_equal_0_y_0 = const()[name = string("greater_equal_0_y_0"), val = int32(0)];
            tensor<int16, [1, 256]> input_ids_to_int16 = cast(dtype = input_ids_to_int16_dtype_0, x = input_ids)[name = string("cast_10")];
            tensor<int32, [1, 256]> cast_132 = cast(dtype = cast_132_dtype_0, x = input_ids_to_int16)[name = string("cast_9")];
            tensor<bool, [1, 256]> greater_equal_0 = greater_equal(x = cast_132, y = greater_equal_0_y_0)[name = string("greater_equal_0")];
            int32 slice_by_index_0 = const()[name = string("slice_by_index_0"), val = int32(16384)];
            tensor<int32, [1, 256]> add_0 = add(x = cast_132, y = slice_by_index_0)[name = string("add_0")];
            tensor<int32, [1, 256]> select_0 = select(a = cast_132, b = add_0, cond = greater_equal_0)[name = string("select_0")];
            string select_0_to_int16_dtype_0 = const()[name = string("select_0_to_int16_dtype_0"), val = string("int16")];
            string cast_0_dtype_0 = const()[name = string("cast_0_dtype_0"), val = string("int32")];
            int32 greater_equal_0_y_0_1 = const()[name = string("greater_equal_0_y_0_1"), val = int32(0)];
            tensor<int16, [1, 256]> select_0_to_int16 = cast(dtype = select_0_to_int16_dtype_0, x = select_0)[name = string("cast_8")];
            tensor<int32, [1, 256]> cast_0 = cast(dtype = cast_0_dtype_0, x = select_0_to_int16)[name = string("cast_7")];
            tensor<bool, [1, 256]> greater_equal_0_1 = greater_equal(x = cast_0, y = greater_equal_0_y_0_1)[name = string("greater_equal_0_1")];
            int32 slice_by_index_0_1 = const()[name = string("slice_by_index_0_1"), val = int32(16384)];
            tensor<int32, [1, 256]> add_0_1 = add(x = cast_0, y = slice_by_index_0_1)[name = string("add_0_1")];
            tensor<int32, [1, 256]> select_0_1 = select(a = cast_0, b = add_0_1, cond = greater_equal_0_1)[name = string("select_0_1")];
            int32 token_embeddings_cast_fp16_cast_uint16_cast_uint16_axis_0 = const()[name = string("token_embeddings_cast_fp16_cast_uint16_cast_uint16_axis_0"), val = int32(0)];
            tensor<fp16, [1, 256, 1024]> token_embeddings_cast_fp16_cast_uint16_cast_uint16 = gather(axis = token_embeddings_cast_fp16_cast_uint16_cast_uint16_axis_0, batch_dims = token_embeddings_batch_dims_0, indices = select_0_1, validate_indices = token_embeddings_validate_indices_0, x = module__embedding_token_embedding_weight_to_fp16_quantized)[name = string("token_embeddings_cast_fp16_cast_uint16_cast_uint16")];
            tensor<fp16, [1, 256, 1024]> position_embeddings_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1, 256, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9437376))), scale = tensor<fp16, [1, 8, 1]>([[[0x1.248p-8], [0x1.248p-8], [0x1.248p-8], [0x1.248p-8], [0x1.248p-8], [0x1.248p-8], [0x1.248p-8], [0x1.248p-8]]]))[name = string("position_embeddings_to_fp16_quantized")];
            tensor<fp16, [1, 256, 1024]> input_1_cast_fp16 = add(x = token_embeddings_cast_fp16_cast_uint16_cast_uint16, y = position_embeddings_to_fp16_quantized)[name = string("input_1_cast_fp16")];
            tensor<int32, [1]> input_3_axes_0 = const()[name = string("input_3_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__embedding_layer_norm_weight_to_fp16 = const()[name = string("module__embedding_layer_norm_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9568512)))];
            tensor<fp16, [1024]> module__embedding_layer_norm_bias_to_fp16 = const()[name = string("module__embedding_layer_norm_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9570624)))];
            fp16 var_26_to_fp16 = const()[name = string("op_26_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 256, 1024]> input_3_cast_fp16 = layer_norm(axes = input_3_axes_0, beta = module__embedding_layer_norm_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__embedding_layer_norm_weight_to_fp16, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string var_73_dtype_0 = const()[name = string("op_73_dtype_0"), val = string("bool")];
            tensor<int32, [1]> attn_mask_1_axes_0 = const()[name = string("attn_mask_1_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 256]> var_73 = cast(dtype = var_73_dtype_0, x = decoder_mask)[name = string("cast_6")];
            tensor<bool, [1, 1, 256]> attn_mask_1 = expand_dims(axes = attn_mask_1_axes_0, x = var_73)[name = string("attn_mask_1")];
            tensor<bool, [1, 256, 256]> band_part_0 = const()[name = string("band_part_0"), val = tensor<bool, [1, 256, 256]>([[[true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, 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            tensor<bool, [1, 256, 256]> attn_mask_3 = logical_and(x = attn_mask_1, y = band_part_0)[name = string("attn_mask_3")];
            fp16 var_18_promoted_to_fp16 = const()[name = string("op_18_promoted_to_fp16"), val = fp16(0x1p+0)];
            string var_79_to_fp16_dtype_0 = const()[name = string("op_79_to_fp16_dtype_0"), val = string("fp16")];
            tensor<fp16, [1, 256, 256]> attn_mask_3_to_fp16 = cast(dtype = var_79_to_fp16_dtype_0, x = attn_mask_3)[name = string("cast_5")];
            tensor<fp16, [1, 256, 256]> var_80_cast_fp16 = sub(x = var_18_promoted_to_fp16, y = attn_mask_3_to_fp16)[name = string("op_80_cast_fp16")];
            fp16 var_81_to_fp16 = const()[name = string("op_81_to_fp16"), val = fp16(-0x1.388p+13)];
            tensor<fp16, [1, 256, 256]> attention_mask_1_cast_fp16 = mul(x = var_80_cast_fp16, y = var_81_to_fp16)[name = string("attention_mask_1_cast_fp16")];
            tensor<int32, [1]> attention_mask_5_axes_0 = const()[name = string("attention_mask_5_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1, 1, 256, 256]> attention_mask_5_cast_fp16 = expand_dims(axes = attention_mask_5_axes_0, x = attention_mask_1_cast_fp16)[name = string("attention_mask_5_cast_fp16")];
            string var_84_dtype_0 = const()[name = string("op_84_dtype_0"), val = string("bool")];
            tensor<int32, [1]> attn_mask_axes_0 = const()[name = string("attn_mask_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 188]> var_84 = cast(dtype = var_84_dtype_0, x = encoder_mask)[name = string("cast_4")];
            tensor<bool, [1, 1, 188]> attn_mask = expand_dims(axes = attn_mask_axes_0, x = var_84)[name = string("attn_mask")];
            fp16 var_18_promoted_1_to_fp16 = const()[name = string("op_18_promoted_1_to_fp16"), val = fp16(0x1p+0)];
            string var_86_to_fp16_dtype_0 = const()[name = string("op_86_to_fp16_dtype_0"), val = string("fp16")];
            tensor<fp16, [1, 1, 188]> attn_mask_to_fp16 = cast(dtype = var_86_to_fp16_dtype_0, x = attn_mask)[name = string("cast_3")];
            tensor<fp16, [1, 1, 188]> var_87_cast_fp16 = sub(x = var_18_promoted_1_to_fp16, y = attn_mask_to_fp16)[name = string("op_87_cast_fp16")];
            fp16 var_88_to_fp16 = const()[name = string("op_88_to_fp16"), val = fp16(-0x1.388p+13)];
            tensor<fp16, [1, 1, 188]> attention_mask_3_cast_fp16 = mul(x = var_87_cast_fp16, y = var_88_to_fp16)[name = string("attention_mask_3_cast_fp16")];
            tensor<int32, [1]> attention_mask_9_axes_0 = const()[name = string("attention_mask_9_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1, 1, 1, 188]> attention_mask_9_cast_fp16 = expand_dims(axes = attention_mask_9_axes_0, x = attention_mask_3_cast_fp16)[name = string("attention_mask_9_cast_fp16")];
            tensor<int32, [1]> input_7_axes_0 = const()[name = string("input_7_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_0_layer_norm_1_weight_to_fp16 = const()[name = string("module__decoder_layers_0_layer_norm_1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9572736)))];
            tensor<fp16, [1024]> module__decoder_layers_0_layer_norm_1_bias_to_fp16 = const()[name = string("module__decoder_layers_0_layer_norm_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9574848)))];
            tensor<fp16, [1, 256, 1024]> input_7_cast_fp16 = layer_norm(axes = input_7_axes_0, beta = module__decoder_layers_0_layer_norm_1_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_0_layer_norm_1_weight_to_fp16, x = input_3_cast_fp16)[name = string("input_7_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_0_first_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9576960))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10101312))))[name = string("module__decoder_layers_0_first_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_0_first_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_0_first_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10166912)))];
            tensor<fp16, [1, 256, 1024]> linear_0_cast_fp16 = linear(bias = module__decoder_layers_0_first_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_0_first_sub_layer_query_net_weight_to_fp16_quantized, x = input_7_cast_fp16)[name = string("linear_0_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_0_first_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10169024))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10693376))))[name = string("module__decoder_layers_0_first_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_0_first_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_0_first_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10758976)))];
            tensor<fp16, [1, 256, 1024]> linear_1_cast_fp16 = linear(bias = module__decoder_layers_0_first_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_0_first_sub_layer_key_net_weight_to_fp16_quantized, x = input_7_cast_fp16)[name = string("linear_1_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_0_first_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10761088))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11285440))))[name = string("module__decoder_layers_0_first_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_0_first_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_0_first_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11351040)))];
            tensor<fp16, [1, 256, 1024]> linear_2_cast_fp16 = linear(bias = module__decoder_layers_0_first_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_0_first_sub_layer_value_net_weight_to_fp16_quantized, x = input_7_cast_fp16)[name = string("linear_2_cast_fp16")];
            tensor<int32, [4]> var_120 = const()[name = string("op_120"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_3_cast_fp16 = reshape(shape = var_120, x = linear_0_cast_fp16)[name = string("x_3_cast_fp16")];
            fp16 _inversed_query_1_y_0_to_fp16 = const()[name = string("_inversed_query_1_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_1_cast_fp16 = mul(x = x_3_cast_fp16, y = _inversed_query_1_y_0_to_fp16)[name = string("_inversed_query_1_cast_fp16")];
            tensor<int32, [4]> var_128 = const()[name = string("op_128"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_7_cast_fp16 = reshape(shape = var_128, x = linear_1_cast_fp16)[name = string("x_7_cast_fp16")];
            fp16 _inversed_key_1_y_0_to_fp16 = const()[name = string("_inversed_key_1_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_key_1_cast_fp16 = mul(x = x_7_cast_fp16, y = _inversed_key_1_y_0_to_fp16)[name = string("_inversed_key_1_cast_fp16")];
            tensor<int32, [4]> var_136 = const()[name = string("op_136"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_11_cast_fp16 = reshape(shape = var_136, x = linear_2_cast_fp16)[name = string("x_11_cast_fp16")];
            tensor<int32, [4]> var_138 = const()[name = string("op_138"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_1_transpose_x_1 = const()[name = string("attention_scores_1_transpose_x_1"), val = bool(false)];
            bool attention_scores_1_transpose_y_1 = const()[name = string("attention_scores_1_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_64_perm_0 = const()[name = string("transpose_64_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_65_perm_0 = const()[name = string("transpose_65_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 256, 128]> transpose_65 = transpose(perm = transpose_65_perm_0, x = _inversed_key_1_cast_fp16)[name = string("transpose_158")];
            tensor<fp16, [1, 8, 256, 128]> transpose_64 = transpose(perm = transpose_64_perm_0, x = _inversed_query_1_cast_fp16)[name = string("transpose_159")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_1_cast_fp16 = matmul(transpose_x = attention_scores_1_transpose_x_1, transpose_y = attention_scores_1_transpose_y_1, x = transpose_64, y = transpose_65)[name = string("attention_scores_1_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_3_cast_fp16 = add(x = attention_scores_1_cast_fp16, y = attention_mask_5_cast_fp16)[name = string("attention_scores_3_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> input_11_cast_fp16 = softmax(axis = var_24, x = attention_scores_3_cast_fp16)[name = string("input_11_cast_fp16")];
            bool context_1_transpose_x_0 = const()[name = string("context_1_transpose_x_0"), val = bool(false)];
            bool context_1_transpose_y_0 = const()[name = string("context_1_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 256, 128]> value_3_cast_fp16 = transpose(perm = var_138, x = x_11_cast_fp16)[name = string("transpose_157")];
            tensor<fp16, [1, 8, 256, 128]> context_1_cast_fp16 = matmul(transpose_x = context_1_transpose_x_0, transpose_y = context_1_transpose_y_0, x = input_11_cast_fp16, y = value_3_cast_fp16)[name = string("context_1_cast_fp16")];
            tensor<int32, [4]> var_152 = const()[name = string("op_152"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_157 = const()[name = string("op_157"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_153_cast_fp16 = transpose(perm = var_152, x = context_1_cast_fp16)[name = string("transpose_156")];
            tensor<fp16, [1, 256, 1024]> input_13_cast_fp16 = reshape(shape = var_157, x = var_153_cast_fp16)[name = string("input_13_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_0_first_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11353152))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11877504))))[name = string("module__decoder_layers_0_first_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_0_first_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_0_first_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11943104)))];
            tensor<fp16, [1, 256, 1024]> linear_3_cast_fp16 = linear(bias = module__decoder_layers_0_first_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_0_first_sub_layer_out_projection_weight_to_fp16_quantized, x = input_13_cast_fp16)[name = string("linear_3_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_17_cast_fp16 = add(x = linear_3_cast_fp16, y = input_3_cast_fp16)[name = string("input_17_cast_fp16")];
            tensor<int32, [1]> input_19_axes_0 = const()[name = string("input_19_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_0_layer_norm_2_weight_to_fp16 = const()[name = string("module__decoder_layers_0_layer_norm_2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11945216)))];
            tensor<fp16, [1024]> module__decoder_layers_0_layer_norm_2_bias_to_fp16 = const()[name = string("module__decoder_layers_0_layer_norm_2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11947328)))];
            tensor<fp16, [1, 256, 1024]> input_19_cast_fp16 = layer_norm(axes = input_19_axes_0, beta = module__decoder_layers_0_layer_norm_2_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_0_layer_norm_2_weight_to_fp16, x = input_17_cast_fp16)[name = string("input_19_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_0_second_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11949440))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12473792))))[name = string("module__decoder_layers_0_second_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_0_second_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_0_second_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12539392)))];
            tensor<fp16, [1, 256, 1024]> linear_4_cast_fp16 = linear(bias = module__decoder_layers_0_second_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_0_second_sub_layer_query_net_weight_to_fp16_quantized, x = input_19_cast_fp16)[name = string("linear_4_cast_fp16")];
            string encoder_embeddings_to_fp16_dtype_0 = const()[name = string("encoder_embeddings_to_fp16_dtype_0"), val = string("fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_0_second_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12541504))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13065856))))[name = string("module__decoder_layers_0_second_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_0_second_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_0_second_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13131456)))];
            tensor<fp16, [1, 188, 1024]> encoder_embeddings_to_fp16 = cast(dtype = encoder_embeddings_to_fp16_dtype_0, x = encoder_embeddings)[name = string("cast_2")];
            tensor<fp16, [1, 188, 1024]> linear_5_cast_fp16 = linear(bias = module__decoder_layers_0_second_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_0_second_sub_layer_key_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_5_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_0_second_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13133568))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13657920))))[name = string("module__decoder_layers_0_second_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_0_second_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_0_second_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13723520)))];
            tensor<fp16, [1, 188, 1024]> linear_6_cast_fp16 = linear(bias = module__decoder_layers_0_second_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_0_second_sub_layer_value_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_6_cast_fp16")];
            tensor<int32, [4]> var_186 = const()[name = string("op_186"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_15_cast_fp16 = reshape(shape = var_186, x = linear_4_cast_fp16)[name = string("x_15_cast_fp16")];
            fp16 _inversed_query_3_y_0_to_fp16 = const()[name = string("_inversed_query_3_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_3_cast_fp16 = mul(x = x_15_cast_fp16, y = _inversed_query_3_y_0_to_fp16)[name = string("_inversed_query_3_cast_fp16")];
            tensor<int32, [4]> var_194 = const()[name = string("op_194"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_19_cast_fp16 = reshape(shape = var_194, x = linear_5_cast_fp16)[name = string("x_19_cast_fp16")];
            fp16 _inversed_key_3_y_0_to_fp16 = const()[name = string("_inversed_key_3_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 188, 8, 128]> _inversed_key_3_cast_fp16 = mul(x = x_19_cast_fp16, y = _inversed_key_3_y_0_to_fp16)[name = string("_inversed_key_3_cast_fp16")];
            tensor<int32, [4]> var_202 = const()[name = string("op_202"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_23_cast_fp16 = reshape(shape = var_202, x = linear_6_cast_fp16)[name = string("x_23_cast_fp16")];
            tensor<int32, [4]> var_204 = const()[name = string("op_204"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_5_transpose_x_1 = const()[name = string("attention_scores_5_transpose_x_1"), val = bool(false)];
            bool attention_scores_5_transpose_y_1 = const()[name = string("attention_scores_5_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_66_perm_0 = const()[name = string("transpose_66_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_67_perm_0 = const()[name = string("transpose_67_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 188, 128]> transpose_67 = transpose(perm = transpose_67_perm_0, x = _inversed_key_3_cast_fp16)[name = string("transpose_154")];
            tensor<fp16, [1, 8, 256, 128]> transpose_66 = transpose(perm = transpose_66_perm_0, x = _inversed_query_3_cast_fp16)[name = string("transpose_155")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_5_cast_fp16 = matmul(transpose_x = attention_scores_5_transpose_x_1, transpose_y = attention_scores_5_transpose_y_1, x = transpose_66, y = transpose_67)[name = string("attention_scores_5_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_7_cast_fp16 = add(x = attention_scores_5_cast_fp16, y = attention_mask_9_cast_fp16)[name = string("attention_scores_7_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> input_21_cast_fp16 = softmax(axis = var_24, x = attention_scores_7_cast_fp16)[name = string("input_21_cast_fp16")];
            bool context_5_transpose_x_0 = const()[name = string("context_5_transpose_x_0"), val = bool(false)];
            bool context_5_transpose_y_0 = const()[name = string("context_5_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_5_cast_fp16 = transpose(perm = var_204, x = x_23_cast_fp16)[name = string("transpose_153")];
            tensor<fp16, [1, 8, 256, 128]> context_5_cast_fp16 = matmul(transpose_x = context_5_transpose_x_0, transpose_y = context_5_transpose_y_0, x = input_21_cast_fp16, y = value_5_cast_fp16)[name = string("context_5_cast_fp16")];
            tensor<int32, [4]> var_218 = const()[name = string("op_218"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_223 = const()[name = string("op_223"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_219_cast_fp16 = transpose(perm = var_218, x = context_5_cast_fp16)[name = string("transpose_152")];
            tensor<fp16, [1, 256, 1024]> input_23_cast_fp16 = reshape(shape = var_223, x = var_219_cast_fp16)[name = string("input_23_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_0_second_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13725632))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14249984))))[name = string("module__decoder_layers_0_second_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_0_second_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_0_second_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14315584)))];
            tensor<fp16, [1, 256, 1024]> linear_7_cast_fp16 = linear(bias = module__decoder_layers_0_second_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_0_second_sub_layer_out_projection_weight_to_fp16_quantized, x = input_23_cast_fp16)[name = string("linear_7_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_27_cast_fp16 = add(x = linear_7_cast_fp16, y = input_17_cast_fp16)[name = string("input_27_cast_fp16")];
            tensor<int32, [1]> input_29_axes_0 = const()[name = string("input_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_0_layer_norm_3_weight_to_fp16 = const()[name = string("module__decoder_layers_0_layer_norm_3_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14317696)))];
            tensor<fp16, [1024]> module__decoder_layers_0_layer_norm_3_bias_to_fp16 = const()[name = string("module__decoder_layers_0_layer_norm_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14319808)))];
            tensor<fp16, [1, 256, 1024]> input_29_cast_fp16 = layer_norm(axes = input_29_axes_0, beta = module__decoder_layers_0_layer_norm_3_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_0_layer_norm_3_weight_to_fp16, x = input_27_cast_fp16)[name = string("input_29_cast_fp16")];
            tensor<fp16, [4096, 1024]> module__decoder_layers_0_third_sub_layer_dense_in_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14321920))), scale = tensor<fp16, [4096, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16419136))))[name = string("module__decoder_layers_0_third_sub_layer_dense_in_weight_to_fp16_quantized")];
            tensor<fp16, [4096]> module__decoder_layers_0_third_sub_layer_dense_in_bias_to_fp16 = const()[name = string("module__decoder_layers_0_third_sub_layer_dense_in_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16681344)))];
            tensor<fp16, [1, 256, 4096]> linear_8_cast_fp16 = linear(bias = module__decoder_layers_0_third_sub_layer_dense_in_bias_to_fp16, weight = module__decoder_layers_0_third_sub_layer_dense_in_weight_to_fp16_quantized, x = input_29_cast_fp16)[name = string("linear_8_cast_fp16")];
            tensor<fp16, [1, 256, 4096]> input_31_cast_fp16 = relu(x = linear_8_cast_fp16)[name = string("input_31_cast_fp16")];
            tensor<fp16, [1024, 4096]> module__decoder_layers_0_third_sub_layer_dense_out_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16689600))), scale = tensor<fp16, [1024, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18786816))))[name = string("module__decoder_layers_0_third_sub_layer_dense_out_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_0_third_sub_layer_dense_out_bias_to_fp16 = const()[name = string("module__decoder_layers_0_third_sub_layer_dense_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19049024)))];
            tensor<fp16, [1, 256, 1024]> linear_9_cast_fp16 = linear(bias = module__decoder_layers_0_third_sub_layer_dense_out_bias_to_fp16, weight = module__decoder_layers_0_third_sub_layer_dense_out_weight_to_fp16_quantized, x = input_31_cast_fp16)[name = string("linear_9_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_35_cast_fp16 = add(x = linear_9_cast_fp16, y = input_27_cast_fp16)[name = string("input_35_cast_fp16")];
            tensor<int32, [1]> input_37_axes_0 = const()[name = string("input_37_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_1_layer_norm_1_weight_to_fp16 = const()[name = string("module__decoder_layers_1_layer_norm_1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19051136)))];
            tensor<fp16, [1024]> module__decoder_layers_1_layer_norm_1_bias_to_fp16 = const()[name = string("module__decoder_layers_1_layer_norm_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19053248)))];
            tensor<fp16, [1, 256, 1024]> input_37_cast_fp16 = layer_norm(axes = input_37_axes_0, beta = module__decoder_layers_1_layer_norm_1_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_1_layer_norm_1_weight_to_fp16, x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_1_first_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19055360))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19579712))))[name = string("module__decoder_layers_1_first_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_1_first_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_1_first_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19645312)))];
            tensor<fp16, [1, 256, 1024]> linear_10_cast_fp16 = linear(bias = module__decoder_layers_1_first_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_1_first_sub_layer_query_net_weight_to_fp16_quantized, x = input_37_cast_fp16)[name = string("linear_10_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_1_first_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19647424))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20171776))))[name = string("module__decoder_layers_1_first_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_1_first_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_1_first_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20237376)))];
            tensor<fp16, [1, 256, 1024]> linear_11_cast_fp16 = linear(bias = module__decoder_layers_1_first_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_1_first_sub_layer_key_net_weight_to_fp16_quantized, x = input_37_cast_fp16)[name = string("linear_11_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_1_first_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20239488))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20763840))))[name = string("module__decoder_layers_1_first_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_1_first_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_1_first_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20829440)))];
            tensor<fp16, [1, 256, 1024]> linear_12_cast_fp16 = linear(bias = module__decoder_layers_1_first_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_1_first_sub_layer_value_net_weight_to_fp16_quantized, x = input_37_cast_fp16)[name = string("linear_12_cast_fp16")];
            tensor<int32, [4]> var_281 = const()[name = string("op_281"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_27_cast_fp16 = reshape(shape = var_281, x = linear_10_cast_fp16)[name = string("x_27_cast_fp16")];
            fp16 _inversed_query_5_y_0_to_fp16 = const()[name = string("_inversed_query_5_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_5_cast_fp16 = mul(x = x_27_cast_fp16, y = _inversed_query_5_y_0_to_fp16)[name = string("_inversed_query_5_cast_fp16")];
            tensor<int32, [4]> var_289 = const()[name = string("op_289"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_31_cast_fp16 = reshape(shape = var_289, x = linear_11_cast_fp16)[name = string("x_31_cast_fp16")];
            fp16 _inversed_key_5_y_0_to_fp16 = const()[name = string("_inversed_key_5_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_key_5_cast_fp16 = mul(x = x_31_cast_fp16, y = _inversed_key_5_y_0_to_fp16)[name = string("_inversed_key_5_cast_fp16")];
            tensor<int32, [4]> var_297 = const()[name = string("op_297"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_35_cast_fp16 = reshape(shape = var_297, x = linear_12_cast_fp16)[name = string("x_35_cast_fp16")];
            tensor<int32, [4]> var_299 = const()[name = string("op_299"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_9_transpose_x_1 = const()[name = string("attention_scores_9_transpose_x_1"), val = bool(false)];
            bool attention_scores_9_transpose_y_1 = const()[name = string("attention_scores_9_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_68_perm_0 = const()[name = string("transpose_68_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_69_perm_0 = const()[name = string("transpose_69_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 256, 128]> transpose_69 = transpose(perm = transpose_69_perm_0, x = _inversed_key_5_cast_fp16)[name = string("transpose_150")];
            tensor<fp16, [1, 8, 256, 128]> transpose_68 = transpose(perm = transpose_68_perm_0, x = _inversed_query_5_cast_fp16)[name = string("transpose_151")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_9_cast_fp16 = matmul(transpose_x = attention_scores_9_transpose_x_1, transpose_y = attention_scores_9_transpose_y_1, x = transpose_68, y = transpose_69)[name = string("attention_scores_9_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_11_cast_fp16 = add(x = attention_scores_9_cast_fp16, y = attention_mask_5_cast_fp16)[name = string("attention_scores_11_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> input_41_cast_fp16 = softmax(axis = var_24, x = attention_scores_11_cast_fp16)[name = string("input_41_cast_fp16")];
            bool context_9_transpose_x_0 = const()[name = string("context_9_transpose_x_0"), val = bool(false)];
            bool context_9_transpose_y_0 = const()[name = string("context_9_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 256, 128]> value_7_cast_fp16 = transpose(perm = var_299, x = x_35_cast_fp16)[name = string("transpose_149")];
            tensor<fp16, [1, 8, 256, 128]> context_9_cast_fp16 = matmul(transpose_x = context_9_transpose_x_0, transpose_y = context_9_transpose_y_0, x = input_41_cast_fp16, y = value_7_cast_fp16)[name = string("context_9_cast_fp16")];
            tensor<int32, [4]> var_313 = const()[name = string("op_313"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_318 = const()[name = string("op_318"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_314_cast_fp16 = transpose(perm = var_313, x = context_9_cast_fp16)[name = string("transpose_148")];
            tensor<fp16, [1, 256, 1024]> input_43_cast_fp16 = reshape(shape = var_318, x = var_314_cast_fp16)[name = string("input_43_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_1_first_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20831552))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21355904))))[name = string("module__decoder_layers_1_first_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_1_first_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_1_first_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21421504)))];
            tensor<fp16, [1, 256, 1024]> linear_13_cast_fp16 = linear(bias = module__decoder_layers_1_first_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_1_first_sub_layer_out_projection_weight_to_fp16_quantized, x = input_43_cast_fp16)[name = string("linear_13_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_47_cast_fp16 = add(x = linear_13_cast_fp16, y = input_35_cast_fp16)[name = string("input_47_cast_fp16")];
            tensor<int32, [1]> input_49_axes_0 = const()[name = string("input_49_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_1_layer_norm_2_weight_to_fp16 = const()[name = string("module__decoder_layers_1_layer_norm_2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21423616)))];
            tensor<fp16, [1024]> module__decoder_layers_1_layer_norm_2_bias_to_fp16 = const()[name = string("module__decoder_layers_1_layer_norm_2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21425728)))];
            tensor<fp16, [1, 256, 1024]> input_49_cast_fp16 = layer_norm(axes = input_49_axes_0, beta = module__decoder_layers_1_layer_norm_2_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_1_layer_norm_2_weight_to_fp16, x = input_47_cast_fp16)[name = string("input_49_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_1_second_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21427840))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21952192))))[name = string("module__decoder_layers_1_second_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_1_second_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_1_second_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22017792)))];
            tensor<fp16, [1, 256, 1024]> linear_14_cast_fp16 = linear(bias = module__decoder_layers_1_second_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_1_second_sub_layer_query_net_weight_to_fp16_quantized, x = input_49_cast_fp16)[name = string("linear_14_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_1_second_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22019904))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22544256))))[name = string("module__decoder_layers_1_second_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_1_second_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_1_second_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22609856)))];
            tensor<fp16, [1, 188, 1024]> linear_15_cast_fp16 = linear(bias = module__decoder_layers_1_second_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_1_second_sub_layer_key_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_15_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_1_second_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22611968))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23136320))))[name = string("module__decoder_layers_1_second_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_1_second_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_1_second_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23201920)))];
            tensor<fp16, [1, 188, 1024]> linear_16_cast_fp16 = linear(bias = module__decoder_layers_1_second_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_1_second_sub_layer_value_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_16_cast_fp16")];
            tensor<int32, [4]> var_347 = const()[name = string("op_347"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_39_cast_fp16 = reshape(shape = var_347, x = linear_14_cast_fp16)[name = string("x_39_cast_fp16")];
            fp16 _inversed_query_7_y_0_to_fp16 = const()[name = string("_inversed_query_7_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_7_cast_fp16 = mul(x = x_39_cast_fp16, y = _inversed_query_7_y_0_to_fp16)[name = string("_inversed_query_7_cast_fp16")];
            tensor<int32, [4]> var_355 = const()[name = string("op_355"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_43_cast_fp16 = reshape(shape = var_355, x = linear_15_cast_fp16)[name = string("x_43_cast_fp16")];
            fp16 _inversed_key_7_y_0_to_fp16 = const()[name = string("_inversed_key_7_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 188, 8, 128]> _inversed_key_7_cast_fp16 = mul(x = x_43_cast_fp16, y = _inversed_key_7_y_0_to_fp16)[name = string("_inversed_key_7_cast_fp16")];
            tensor<int32, [4]> var_363 = const()[name = string("op_363"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_47_cast_fp16 = reshape(shape = var_363, x = linear_16_cast_fp16)[name = string("x_47_cast_fp16")];
            tensor<int32, [4]> var_365 = const()[name = string("op_365"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_13_transpose_x_1 = const()[name = string("attention_scores_13_transpose_x_1"), val = bool(false)];
            bool attention_scores_13_transpose_y_1 = const()[name = string("attention_scores_13_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_70_perm_0 = const()[name = string("transpose_70_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_71_perm_0 = const()[name = string("transpose_71_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 188, 128]> transpose_71 = transpose(perm = transpose_71_perm_0, x = _inversed_key_7_cast_fp16)[name = string("transpose_146")];
            tensor<fp16, [1, 8, 256, 128]> transpose_70 = transpose(perm = transpose_70_perm_0, x = _inversed_query_7_cast_fp16)[name = string("transpose_147")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_13_cast_fp16 = matmul(transpose_x = attention_scores_13_transpose_x_1, transpose_y = attention_scores_13_transpose_y_1, x = transpose_70, y = transpose_71)[name = string("attention_scores_13_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_15_cast_fp16 = add(x = attention_scores_13_cast_fp16, y = attention_mask_9_cast_fp16)[name = string("attention_scores_15_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> input_51_cast_fp16 = softmax(axis = var_24, x = attention_scores_15_cast_fp16)[name = string("input_51_cast_fp16")];
            bool context_13_transpose_x_0 = const()[name = string("context_13_transpose_x_0"), val = bool(false)];
            bool context_13_transpose_y_0 = const()[name = string("context_13_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_9_cast_fp16 = transpose(perm = var_365, x = x_47_cast_fp16)[name = string("transpose_145")];
            tensor<fp16, [1, 8, 256, 128]> context_13_cast_fp16 = matmul(transpose_x = context_13_transpose_x_0, transpose_y = context_13_transpose_y_0, x = input_51_cast_fp16, y = value_9_cast_fp16)[name = string("context_13_cast_fp16")];
            tensor<int32, [4]> var_379 = const()[name = string("op_379"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_384 = const()[name = string("op_384"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_380_cast_fp16 = transpose(perm = var_379, x = context_13_cast_fp16)[name = string("transpose_144")];
            tensor<fp16, [1, 256, 1024]> input_53_cast_fp16 = reshape(shape = var_384, x = var_380_cast_fp16)[name = string("input_53_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_1_second_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23204032))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23728384))))[name = string("module__decoder_layers_1_second_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_1_second_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_1_second_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23793984)))];
            tensor<fp16, [1, 256, 1024]> linear_17_cast_fp16 = linear(bias = module__decoder_layers_1_second_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_1_second_sub_layer_out_projection_weight_to_fp16_quantized, x = input_53_cast_fp16)[name = string("linear_17_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_57_cast_fp16 = add(x = linear_17_cast_fp16, y = input_47_cast_fp16)[name = string("input_57_cast_fp16")];
            tensor<int32, [1]> input_59_axes_0 = const()[name = string("input_59_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_1_layer_norm_3_weight_to_fp16 = const()[name = string("module__decoder_layers_1_layer_norm_3_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23796096)))];
            tensor<fp16, [1024]> module__decoder_layers_1_layer_norm_3_bias_to_fp16 = const()[name = string("module__decoder_layers_1_layer_norm_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23798208)))];
            tensor<fp16, [1, 256, 1024]> input_59_cast_fp16 = layer_norm(axes = input_59_axes_0, beta = module__decoder_layers_1_layer_norm_3_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_1_layer_norm_3_weight_to_fp16, x = input_57_cast_fp16)[name = string("input_59_cast_fp16")];
            tensor<fp16, [4096, 1024]> module__decoder_layers_1_third_sub_layer_dense_in_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23800320))), scale = tensor<fp16, [4096, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25897536))))[name = string("module__decoder_layers_1_third_sub_layer_dense_in_weight_to_fp16_quantized")];
            tensor<fp16, [4096]> module__decoder_layers_1_third_sub_layer_dense_in_bias_to_fp16 = const()[name = string("module__decoder_layers_1_third_sub_layer_dense_in_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26159744)))];
            tensor<fp16, [1, 256, 4096]> linear_18_cast_fp16 = linear(bias = module__decoder_layers_1_third_sub_layer_dense_in_bias_to_fp16, weight = module__decoder_layers_1_third_sub_layer_dense_in_weight_to_fp16_quantized, x = input_59_cast_fp16)[name = string("linear_18_cast_fp16")];
            tensor<fp16, [1, 256, 4096]> input_61_cast_fp16 = relu(x = linear_18_cast_fp16)[name = string("input_61_cast_fp16")];
            tensor<fp16, [1024, 4096]> module__decoder_layers_1_third_sub_layer_dense_out_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26168000))), scale = tensor<fp16, [1024, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28265216))))[name = string("module__decoder_layers_1_third_sub_layer_dense_out_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_1_third_sub_layer_dense_out_bias_to_fp16 = const()[name = string("module__decoder_layers_1_third_sub_layer_dense_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28527424)))];
            tensor<fp16, [1, 256, 1024]> linear_19_cast_fp16 = linear(bias = module__decoder_layers_1_third_sub_layer_dense_out_bias_to_fp16, weight = module__decoder_layers_1_third_sub_layer_dense_out_weight_to_fp16_quantized, x = input_61_cast_fp16)[name = string("linear_19_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_65_cast_fp16 = add(x = linear_19_cast_fp16, y = input_57_cast_fp16)[name = string("input_65_cast_fp16")];
            tensor<int32, [1]> input_67_axes_0 = const()[name = string("input_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_2_layer_norm_1_weight_to_fp16 = const()[name = string("module__decoder_layers_2_layer_norm_1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28529536)))];
            tensor<fp16, [1024]> module__decoder_layers_2_layer_norm_1_bias_to_fp16 = const()[name = string("module__decoder_layers_2_layer_norm_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28531648)))];
            tensor<fp16, [1, 256, 1024]> input_67_cast_fp16 = layer_norm(axes = input_67_axes_0, beta = module__decoder_layers_2_layer_norm_1_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_2_layer_norm_1_weight_to_fp16, x = input_65_cast_fp16)[name = string("input_67_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_2_first_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28533760))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29058112))))[name = string("module__decoder_layers_2_first_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_2_first_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_2_first_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29123712)))];
            tensor<fp16, [1, 256, 1024]> linear_20_cast_fp16 = linear(bias = module__decoder_layers_2_first_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_2_first_sub_layer_query_net_weight_to_fp16_quantized, x = input_67_cast_fp16)[name = string("linear_20_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_2_first_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29125824))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29650176))))[name = string("module__decoder_layers_2_first_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_2_first_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_2_first_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29715776)))];
            tensor<fp16, [1, 256, 1024]> linear_21_cast_fp16 = linear(bias = module__decoder_layers_2_first_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_2_first_sub_layer_key_net_weight_to_fp16_quantized, x = input_67_cast_fp16)[name = string("linear_21_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_2_first_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29717888))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30242240))))[name = string("module__decoder_layers_2_first_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_2_first_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_2_first_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30307840)))];
            tensor<fp16, [1, 256, 1024]> linear_22_cast_fp16 = linear(bias = module__decoder_layers_2_first_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_2_first_sub_layer_value_net_weight_to_fp16_quantized, x = input_67_cast_fp16)[name = string("linear_22_cast_fp16")];
            tensor<int32, [4]> var_442 = const()[name = string("op_442"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_51_cast_fp16 = reshape(shape = var_442, x = linear_20_cast_fp16)[name = string("x_51_cast_fp16")];
            fp16 _inversed_query_9_y_0_to_fp16 = const()[name = string("_inversed_query_9_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_9_cast_fp16 = mul(x = x_51_cast_fp16, y = _inversed_query_9_y_0_to_fp16)[name = string("_inversed_query_9_cast_fp16")];
            tensor<int32, [4]> var_450 = const()[name = string("op_450"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_55_cast_fp16 = reshape(shape = var_450, x = linear_21_cast_fp16)[name = string("x_55_cast_fp16")];
            fp16 _inversed_key_9_y_0_to_fp16 = const()[name = string("_inversed_key_9_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_key_9_cast_fp16 = mul(x = x_55_cast_fp16, y = _inversed_key_9_y_0_to_fp16)[name = string("_inversed_key_9_cast_fp16")];
            tensor<int32, [4]> var_458 = const()[name = string("op_458"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_59_cast_fp16 = reshape(shape = var_458, x = linear_22_cast_fp16)[name = string("x_59_cast_fp16")];
            tensor<int32, [4]> var_460 = const()[name = string("op_460"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_17_transpose_x_1 = const()[name = string("attention_scores_17_transpose_x_1"), val = bool(false)];
            bool attention_scores_17_transpose_y_1 = const()[name = string("attention_scores_17_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_72_perm_0 = const()[name = string("transpose_72_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_73_perm_0 = const()[name = string("transpose_73_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 256, 128]> transpose_73 = transpose(perm = transpose_73_perm_0, x = _inversed_key_9_cast_fp16)[name = string("transpose_142")];
            tensor<fp16, [1, 8, 256, 128]> transpose_72 = transpose(perm = transpose_72_perm_0, x = _inversed_query_9_cast_fp16)[name = string("transpose_143")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_17_cast_fp16 = matmul(transpose_x = attention_scores_17_transpose_x_1, transpose_y = attention_scores_17_transpose_y_1, x = transpose_72, y = transpose_73)[name = string("attention_scores_17_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_19_cast_fp16 = add(x = attention_scores_17_cast_fp16, y = attention_mask_5_cast_fp16)[name = string("attention_scores_19_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> input_71_cast_fp16 = softmax(axis = var_24, x = attention_scores_19_cast_fp16)[name = string("input_71_cast_fp16")];
            bool context_17_transpose_x_0 = const()[name = string("context_17_transpose_x_0"), val = bool(false)];
            bool context_17_transpose_y_0 = const()[name = string("context_17_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 256, 128]> value_11_cast_fp16 = transpose(perm = var_460, x = x_59_cast_fp16)[name = string("transpose_141")];
            tensor<fp16, [1, 8, 256, 128]> context_17_cast_fp16 = matmul(transpose_x = context_17_transpose_x_0, transpose_y = context_17_transpose_y_0, x = input_71_cast_fp16, y = value_11_cast_fp16)[name = string("context_17_cast_fp16")];
            tensor<int32, [4]> var_474 = const()[name = string("op_474"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_479 = const()[name = string("op_479"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_475_cast_fp16 = transpose(perm = var_474, x = context_17_cast_fp16)[name = string("transpose_140")];
            tensor<fp16, [1, 256, 1024]> input_73_cast_fp16 = reshape(shape = var_479, x = var_475_cast_fp16)[name = string("input_73_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_2_first_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30309952))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30834304))))[name = string("module__decoder_layers_2_first_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_2_first_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_2_first_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30899904)))];
            tensor<fp16, [1, 256, 1024]> linear_23_cast_fp16 = linear(bias = module__decoder_layers_2_first_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_2_first_sub_layer_out_projection_weight_to_fp16_quantized, x = input_73_cast_fp16)[name = string("linear_23_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_77_cast_fp16 = add(x = linear_23_cast_fp16, y = input_65_cast_fp16)[name = string("input_77_cast_fp16")];
            tensor<int32, [1]> input_79_axes_0 = const()[name = string("input_79_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_2_layer_norm_2_weight_to_fp16 = const()[name = string("module__decoder_layers_2_layer_norm_2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30902016)))];
            tensor<fp16, [1024]> module__decoder_layers_2_layer_norm_2_bias_to_fp16 = const()[name = string("module__decoder_layers_2_layer_norm_2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30904128)))];
            tensor<fp16, [1, 256, 1024]> input_79_cast_fp16 = layer_norm(axes = input_79_axes_0, beta = module__decoder_layers_2_layer_norm_2_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_2_layer_norm_2_weight_to_fp16, x = input_77_cast_fp16)[name = string("input_79_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_2_second_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30906240))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31430592))))[name = string("module__decoder_layers_2_second_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_2_second_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_2_second_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31496192)))];
            tensor<fp16, [1, 256, 1024]> linear_24_cast_fp16 = linear(bias = module__decoder_layers_2_second_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_2_second_sub_layer_query_net_weight_to_fp16_quantized, x = input_79_cast_fp16)[name = string("linear_24_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_2_second_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31498304))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32022656))))[name = string("module__decoder_layers_2_second_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_2_second_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_2_second_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32088256)))];
            tensor<fp16, [1, 188, 1024]> linear_25_cast_fp16 = linear(bias = module__decoder_layers_2_second_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_2_second_sub_layer_key_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_25_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_2_second_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32090368))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32614720))))[name = string("module__decoder_layers_2_second_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_2_second_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_2_second_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32680320)))];
            tensor<fp16, [1, 188, 1024]> linear_26_cast_fp16 = linear(bias = module__decoder_layers_2_second_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_2_second_sub_layer_value_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_26_cast_fp16")];
            tensor<int32, [4]> var_508 = const()[name = string("op_508"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_63_cast_fp16 = reshape(shape = var_508, x = linear_24_cast_fp16)[name = string("x_63_cast_fp16")];
            fp16 _inversed_query_11_y_0_to_fp16 = const()[name = string("_inversed_query_11_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_11_cast_fp16 = mul(x = x_63_cast_fp16, y = _inversed_query_11_y_0_to_fp16)[name = string("_inversed_query_11_cast_fp16")];
            tensor<int32, [4]> var_516 = const()[name = string("op_516"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_67_cast_fp16 = reshape(shape = var_516, x = linear_25_cast_fp16)[name = string("x_67_cast_fp16")];
            fp16 _inversed_key_11_y_0_to_fp16 = const()[name = string("_inversed_key_11_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 188, 8, 128]> _inversed_key_11_cast_fp16 = mul(x = x_67_cast_fp16, y = _inversed_key_11_y_0_to_fp16)[name = string("_inversed_key_11_cast_fp16")];
            tensor<int32, [4]> var_524 = const()[name = string("op_524"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_71_cast_fp16 = reshape(shape = var_524, x = linear_26_cast_fp16)[name = string("x_71_cast_fp16")];
            tensor<int32, [4]> var_526 = const()[name = string("op_526"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_21_transpose_x_1 = const()[name = string("attention_scores_21_transpose_x_1"), val = bool(false)];
            bool attention_scores_21_transpose_y_1 = const()[name = string("attention_scores_21_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_74_perm_0 = const()[name = string("transpose_74_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_75_perm_0 = const()[name = string("transpose_75_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 188, 128]> transpose_75 = transpose(perm = transpose_75_perm_0, x = _inversed_key_11_cast_fp16)[name = string("transpose_138")];
            tensor<fp16, [1, 8, 256, 128]> transpose_74 = transpose(perm = transpose_74_perm_0, x = _inversed_query_11_cast_fp16)[name = string("transpose_139")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_21_cast_fp16 = matmul(transpose_x = attention_scores_21_transpose_x_1, transpose_y = attention_scores_21_transpose_y_1, x = transpose_74, y = transpose_75)[name = string("attention_scores_21_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_23_cast_fp16 = add(x = attention_scores_21_cast_fp16, y = attention_mask_9_cast_fp16)[name = string("attention_scores_23_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> input_81_cast_fp16 = softmax(axis = var_24, x = attention_scores_23_cast_fp16)[name = string("input_81_cast_fp16")];
            bool context_21_transpose_x_0 = const()[name = string("context_21_transpose_x_0"), val = bool(false)];
            bool context_21_transpose_y_0 = const()[name = string("context_21_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_13_cast_fp16 = transpose(perm = var_526, x = x_71_cast_fp16)[name = string("transpose_137")];
            tensor<fp16, [1, 8, 256, 128]> context_21_cast_fp16 = matmul(transpose_x = context_21_transpose_x_0, transpose_y = context_21_transpose_y_0, x = input_81_cast_fp16, y = value_13_cast_fp16)[name = string("context_21_cast_fp16")];
            tensor<int32, [4]> var_540 = const()[name = string("op_540"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_545 = const()[name = string("op_545"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_541_cast_fp16 = transpose(perm = var_540, x = context_21_cast_fp16)[name = string("transpose_136")];
            tensor<fp16, [1, 256, 1024]> input_83_cast_fp16 = reshape(shape = var_545, x = var_541_cast_fp16)[name = string("input_83_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_2_second_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32682432))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33206784))))[name = string("module__decoder_layers_2_second_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_2_second_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_2_second_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33272384)))];
            tensor<fp16, [1, 256, 1024]> linear_27_cast_fp16 = linear(bias = module__decoder_layers_2_second_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_2_second_sub_layer_out_projection_weight_to_fp16_quantized, x = input_83_cast_fp16)[name = string("linear_27_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_87_cast_fp16 = add(x = linear_27_cast_fp16, y = input_77_cast_fp16)[name = string("input_87_cast_fp16")];
            tensor<int32, [1]> input_89_axes_0 = const()[name = string("input_89_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_2_layer_norm_3_weight_to_fp16 = const()[name = string("module__decoder_layers_2_layer_norm_3_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33274496)))];
            tensor<fp16, [1024]> module__decoder_layers_2_layer_norm_3_bias_to_fp16 = const()[name = string("module__decoder_layers_2_layer_norm_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33276608)))];
            tensor<fp16, [1, 256, 1024]> input_89_cast_fp16 = layer_norm(axes = input_89_axes_0, beta = module__decoder_layers_2_layer_norm_3_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_2_layer_norm_3_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_89_cast_fp16")];
            tensor<fp16, [4096, 1024]> module__decoder_layers_2_third_sub_layer_dense_in_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33278720))), scale = tensor<fp16, [4096, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35375936))))[name = string("module__decoder_layers_2_third_sub_layer_dense_in_weight_to_fp16_quantized")];
            tensor<fp16, [4096]> module__decoder_layers_2_third_sub_layer_dense_in_bias_to_fp16 = const()[name = string("module__decoder_layers_2_third_sub_layer_dense_in_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35638144)))];
            tensor<fp16, [1, 256, 4096]> linear_28_cast_fp16 = linear(bias = module__decoder_layers_2_third_sub_layer_dense_in_bias_to_fp16, weight = module__decoder_layers_2_third_sub_layer_dense_in_weight_to_fp16_quantized, x = input_89_cast_fp16)[name = string("linear_28_cast_fp16")];
            tensor<fp16, [1, 256, 4096]> input_91_cast_fp16 = relu(x = linear_28_cast_fp16)[name = string("input_91_cast_fp16")];
            tensor<fp16, [1024, 4096]> module__decoder_layers_2_third_sub_layer_dense_out_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35646400))), scale = tensor<fp16, [1024, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37743616))))[name = string("module__decoder_layers_2_third_sub_layer_dense_out_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_2_third_sub_layer_dense_out_bias_to_fp16 = const()[name = string("module__decoder_layers_2_third_sub_layer_dense_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38005824)))];
            tensor<fp16, [1, 256, 1024]> linear_29_cast_fp16 = linear(bias = module__decoder_layers_2_third_sub_layer_dense_out_bias_to_fp16, weight = module__decoder_layers_2_third_sub_layer_dense_out_weight_to_fp16_quantized, x = input_91_cast_fp16)[name = string("linear_29_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_95_cast_fp16 = add(x = linear_29_cast_fp16, y = input_87_cast_fp16)[name = string("input_95_cast_fp16")];
            tensor<int32, [1]> input_97_axes_0 = const()[name = string("input_97_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_3_layer_norm_1_weight_to_fp16 = const()[name = string("module__decoder_layers_3_layer_norm_1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38007936)))];
            tensor<fp16, [1024]> module__decoder_layers_3_layer_norm_1_bias_to_fp16 = const()[name = string("module__decoder_layers_3_layer_norm_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38010048)))];
            tensor<fp16, [1, 256, 1024]> input_97_cast_fp16 = layer_norm(axes = input_97_axes_0, beta = module__decoder_layers_3_layer_norm_1_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_3_layer_norm_1_weight_to_fp16, x = input_95_cast_fp16)[name = string("input_97_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_3_first_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38012160))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38536512))))[name = string("module__decoder_layers_3_first_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_3_first_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_3_first_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38602112)))];
            tensor<fp16, [1, 256, 1024]> linear_30_cast_fp16 = linear(bias = module__decoder_layers_3_first_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_3_first_sub_layer_query_net_weight_to_fp16_quantized, x = input_97_cast_fp16)[name = string("linear_30_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_3_first_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38604224))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39128576))))[name = string("module__decoder_layers_3_first_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_3_first_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_3_first_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39194176)))];
            tensor<fp16, [1, 256, 1024]> linear_31_cast_fp16 = linear(bias = module__decoder_layers_3_first_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_3_first_sub_layer_key_net_weight_to_fp16_quantized, x = input_97_cast_fp16)[name = string("linear_31_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_3_first_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39196288))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39720640))))[name = string("module__decoder_layers_3_first_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_3_first_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_3_first_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39786240)))];
            tensor<fp16, [1, 256, 1024]> linear_32_cast_fp16 = linear(bias = module__decoder_layers_3_first_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_3_first_sub_layer_value_net_weight_to_fp16_quantized, x = input_97_cast_fp16)[name = string("linear_32_cast_fp16")];
            tensor<int32, [4]> var_603 = const()[name = string("op_603"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_75_cast_fp16 = reshape(shape = var_603, x = linear_30_cast_fp16)[name = string("x_75_cast_fp16")];
            fp16 _inversed_query_13_y_0_to_fp16 = const()[name = string("_inversed_query_13_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_13_cast_fp16 = mul(x = x_75_cast_fp16, y = _inversed_query_13_y_0_to_fp16)[name = string("_inversed_query_13_cast_fp16")];
            tensor<int32, [4]> var_611 = const()[name = string("op_611"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_79_cast_fp16 = reshape(shape = var_611, x = linear_31_cast_fp16)[name = string("x_79_cast_fp16")];
            fp16 _inversed_key_13_y_0_to_fp16 = const()[name = string("_inversed_key_13_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_key_13_cast_fp16 = mul(x = x_79_cast_fp16, y = _inversed_key_13_y_0_to_fp16)[name = string("_inversed_key_13_cast_fp16")];
            tensor<int32, [4]> var_619 = const()[name = string("op_619"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_83_cast_fp16 = reshape(shape = var_619, x = linear_32_cast_fp16)[name = string("x_83_cast_fp16")];
            tensor<int32, [4]> var_621 = const()[name = string("op_621"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_25_transpose_x_1 = const()[name = string("attention_scores_25_transpose_x_1"), val = bool(false)];
            bool attention_scores_25_transpose_y_1 = const()[name = string("attention_scores_25_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_76_perm_0 = const()[name = string("transpose_76_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_77_perm_0 = const()[name = string("transpose_77_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 256, 128]> transpose_77 = transpose(perm = transpose_77_perm_0, x = _inversed_key_13_cast_fp16)[name = string("transpose_134")];
            tensor<fp16, [1, 8, 256, 128]> transpose_76 = transpose(perm = transpose_76_perm_0, x = _inversed_query_13_cast_fp16)[name = string("transpose_135")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_25_cast_fp16 = matmul(transpose_x = attention_scores_25_transpose_x_1, transpose_y = attention_scores_25_transpose_y_1, x = transpose_76, y = transpose_77)[name = string("attention_scores_25_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_27_cast_fp16 = add(x = attention_scores_25_cast_fp16, y = attention_mask_5_cast_fp16)[name = string("attention_scores_27_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> input_101_cast_fp16 = softmax(axis = var_24, x = attention_scores_27_cast_fp16)[name = string("input_101_cast_fp16")];
            bool context_25_transpose_x_0 = const()[name = string("context_25_transpose_x_0"), val = bool(false)];
            bool context_25_transpose_y_0 = const()[name = string("context_25_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 256, 128]> value_15_cast_fp16 = transpose(perm = var_621, x = x_83_cast_fp16)[name = string("transpose_133")];
            tensor<fp16, [1, 8, 256, 128]> context_25_cast_fp16 = matmul(transpose_x = context_25_transpose_x_0, transpose_y = context_25_transpose_y_0, x = input_101_cast_fp16, y = value_15_cast_fp16)[name = string("context_25_cast_fp16")];
            tensor<int32, [4]> var_635 = const()[name = string("op_635"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_640 = const()[name = string("op_640"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_636_cast_fp16 = transpose(perm = var_635, x = context_25_cast_fp16)[name = string("transpose_132")];
            tensor<fp16, [1, 256, 1024]> input_103_cast_fp16 = reshape(shape = var_640, x = var_636_cast_fp16)[name = string("input_103_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_3_first_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39788352))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40312704))))[name = string("module__decoder_layers_3_first_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_3_first_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_3_first_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40378304)))];
            tensor<fp16, [1, 256, 1024]> linear_33_cast_fp16 = linear(bias = module__decoder_layers_3_first_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_3_first_sub_layer_out_projection_weight_to_fp16_quantized, x = input_103_cast_fp16)[name = string("linear_33_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_107_cast_fp16 = add(x = linear_33_cast_fp16, y = input_95_cast_fp16)[name = string("input_107_cast_fp16")];
            tensor<int32, [1]> input_109_axes_0 = const()[name = string("input_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_3_layer_norm_2_weight_to_fp16 = const()[name = string("module__decoder_layers_3_layer_norm_2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40380416)))];
            tensor<fp16, [1024]> module__decoder_layers_3_layer_norm_2_bias_to_fp16 = const()[name = string("module__decoder_layers_3_layer_norm_2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40382528)))];
            tensor<fp16, [1, 256, 1024]> input_109_cast_fp16 = layer_norm(axes = input_109_axes_0, beta = module__decoder_layers_3_layer_norm_2_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_3_layer_norm_2_weight_to_fp16, x = input_107_cast_fp16)[name = string("input_109_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_3_second_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40384640))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40908992))))[name = string("module__decoder_layers_3_second_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_3_second_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_3_second_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40974592)))];
            tensor<fp16, [1, 256, 1024]> linear_34_cast_fp16 = linear(bias = module__decoder_layers_3_second_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_3_second_sub_layer_query_net_weight_to_fp16_quantized, x = input_109_cast_fp16)[name = string("linear_34_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_3_second_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40976704))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41501056))))[name = string("module__decoder_layers_3_second_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_3_second_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_3_second_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41566656)))];
            tensor<fp16, [1, 188, 1024]> linear_35_cast_fp16 = linear(bias = module__decoder_layers_3_second_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_3_second_sub_layer_key_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_35_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_3_second_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41568768))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42093120))))[name = string("module__decoder_layers_3_second_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_3_second_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_3_second_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42158720)))];
            tensor<fp16, [1, 188, 1024]> linear_36_cast_fp16 = linear(bias = module__decoder_layers_3_second_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_3_second_sub_layer_value_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_36_cast_fp16")];
            tensor<int32, [4]> var_669 = const()[name = string("op_669"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_87_cast_fp16 = reshape(shape = var_669, x = linear_34_cast_fp16)[name = string("x_87_cast_fp16")];
            fp16 _inversed_query_15_y_0_to_fp16 = const()[name = string("_inversed_query_15_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_15_cast_fp16 = mul(x = x_87_cast_fp16, y = _inversed_query_15_y_0_to_fp16)[name = string("_inversed_query_15_cast_fp16")];
            tensor<int32, [4]> var_677 = const()[name = string("op_677"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_91_cast_fp16 = reshape(shape = var_677, x = linear_35_cast_fp16)[name = string("x_91_cast_fp16")];
            fp16 _inversed_key_15_y_0_to_fp16 = const()[name = string("_inversed_key_15_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 188, 8, 128]> _inversed_key_15_cast_fp16 = mul(x = x_91_cast_fp16, y = _inversed_key_15_y_0_to_fp16)[name = string("_inversed_key_15_cast_fp16")];
            tensor<int32, [4]> var_685 = const()[name = string("op_685"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_95_cast_fp16 = reshape(shape = var_685, x = linear_36_cast_fp16)[name = string("x_95_cast_fp16")];
            tensor<int32, [4]> var_687 = const()[name = string("op_687"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_29_transpose_x_1 = const()[name = string("attention_scores_29_transpose_x_1"), val = bool(false)];
            bool attention_scores_29_transpose_y_1 = const()[name = string("attention_scores_29_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_78_perm_0 = const()[name = string("transpose_78_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_79_perm_0 = const()[name = string("transpose_79_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 188, 128]> transpose_79 = transpose(perm = transpose_79_perm_0, x = _inversed_key_15_cast_fp16)[name = string("transpose_130")];
            tensor<fp16, [1, 8, 256, 128]> transpose_78 = transpose(perm = transpose_78_perm_0, x = _inversed_query_15_cast_fp16)[name = string("transpose_131")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_29_cast_fp16 = matmul(transpose_x = attention_scores_29_transpose_x_1, transpose_y = attention_scores_29_transpose_y_1, x = transpose_78, y = transpose_79)[name = string("attention_scores_29_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_31_cast_fp16 = add(x = attention_scores_29_cast_fp16, y = attention_mask_9_cast_fp16)[name = string("attention_scores_31_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> input_111_cast_fp16 = softmax(axis = var_24, x = attention_scores_31_cast_fp16)[name = string("input_111_cast_fp16")];
            bool context_29_transpose_x_0 = const()[name = string("context_29_transpose_x_0"), val = bool(false)];
            bool context_29_transpose_y_0 = const()[name = string("context_29_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_17_cast_fp16 = transpose(perm = var_687, x = x_95_cast_fp16)[name = string("transpose_129")];
            tensor<fp16, [1, 8, 256, 128]> context_29_cast_fp16 = matmul(transpose_x = context_29_transpose_x_0, transpose_y = context_29_transpose_y_0, x = input_111_cast_fp16, y = value_17_cast_fp16)[name = string("context_29_cast_fp16")];
            tensor<int32, [4]> var_701 = const()[name = string("op_701"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_706 = const()[name = string("op_706"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_702_cast_fp16 = transpose(perm = var_701, x = context_29_cast_fp16)[name = string("transpose_128")];
            tensor<fp16, [1, 256, 1024]> input_113_cast_fp16 = reshape(shape = var_706, x = var_702_cast_fp16)[name = string("input_113_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_3_second_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42160832))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42685184))))[name = string("module__decoder_layers_3_second_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_3_second_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_3_second_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42750784)))];
            tensor<fp16, [1, 256, 1024]> linear_37_cast_fp16 = linear(bias = module__decoder_layers_3_second_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_3_second_sub_layer_out_projection_weight_to_fp16_quantized, x = input_113_cast_fp16)[name = string("linear_37_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_117_cast_fp16 = add(x = linear_37_cast_fp16, y = input_107_cast_fp16)[name = string("input_117_cast_fp16")];
            tensor<int32, [1]> input_119_axes_0 = const()[name = string("input_119_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_3_layer_norm_3_weight_to_fp16 = const()[name = string("module__decoder_layers_3_layer_norm_3_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42752896)))];
            tensor<fp16, [1024]> module__decoder_layers_3_layer_norm_3_bias_to_fp16 = const()[name = string("module__decoder_layers_3_layer_norm_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42755008)))];
            tensor<fp16, [1, 256, 1024]> input_119_cast_fp16 = layer_norm(axes = input_119_axes_0, beta = module__decoder_layers_3_layer_norm_3_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_3_layer_norm_3_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_119_cast_fp16")];
            tensor<fp16, [4096, 1024]> module__decoder_layers_3_third_sub_layer_dense_in_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42757120))), scale = tensor<fp16, [4096, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(44854336))))[name = string("module__decoder_layers_3_third_sub_layer_dense_in_weight_to_fp16_quantized")];
            tensor<fp16, [4096]> module__decoder_layers_3_third_sub_layer_dense_in_bias_to_fp16 = const()[name = string("module__decoder_layers_3_third_sub_layer_dense_in_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45116544)))];
            tensor<fp16, [1, 256, 4096]> linear_38_cast_fp16 = linear(bias = module__decoder_layers_3_third_sub_layer_dense_in_bias_to_fp16, weight = module__decoder_layers_3_third_sub_layer_dense_in_weight_to_fp16_quantized, x = input_119_cast_fp16)[name = string("linear_38_cast_fp16")];
            tensor<fp16, [1, 256, 4096]> input_121_cast_fp16 = relu(x = linear_38_cast_fp16)[name = string("input_121_cast_fp16")];
            tensor<fp16, [1024, 4096]> module__decoder_layers_3_third_sub_layer_dense_out_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45124800))), scale = tensor<fp16, [1024, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(47222016))))[name = string("module__decoder_layers_3_third_sub_layer_dense_out_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_3_third_sub_layer_dense_out_bias_to_fp16 = const()[name = string("module__decoder_layers_3_third_sub_layer_dense_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(47484224)))];
            tensor<fp16, [1, 256, 1024]> linear_39_cast_fp16 = linear(bias = module__decoder_layers_3_third_sub_layer_dense_out_bias_to_fp16, weight = module__decoder_layers_3_third_sub_layer_dense_out_weight_to_fp16_quantized, x = input_121_cast_fp16)[name = string("linear_39_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_125_cast_fp16 = add(x = linear_39_cast_fp16, y = input_117_cast_fp16)[name = string("input_125_cast_fp16")];
            tensor<int32, [1]> input_127_axes_0 = const()[name = string("input_127_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_4_layer_norm_1_weight_to_fp16 = const()[name = string("module__decoder_layers_4_layer_norm_1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(47486336)))];
            tensor<fp16, [1024]> module__decoder_layers_4_layer_norm_1_bias_to_fp16 = const()[name = string("module__decoder_layers_4_layer_norm_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(47488448)))];
            tensor<fp16, [1, 256, 1024]> input_127_cast_fp16 = layer_norm(axes = input_127_axes_0, beta = module__decoder_layers_4_layer_norm_1_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_4_layer_norm_1_weight_to_fp16, x = input_125_cast_fp16)[name = string("input_127_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_4_first_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(47490560))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48014912))))[name = string("module__decoder_layers_4_first_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_4_first_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_4_first_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48080512)))];
            tensor<fp16, [1, 256, 1024]> linear_40_cast_fp16 = linear(bias = module__decoder_layers_4_first_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_4_first_sub_layer_query_net_weight_to_fp16_quantized, x = input_127_cast_fp16)[name = string("linear_40_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_4_first_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48082624))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48606976))))[name = string("module__decoder_layers_4_first_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_4_first_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_4_first_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48672576)))];
            tensor<fp16, [1, 256, 1024]> linear_41_cast_fp16 = linear(bias = module__decoder_layers_4_first_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_4_first_sub_layer_key_net_weight_to_fp16_quantized, x = input_127_cast_fp16)[name = string("linear_41_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_4_first_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(48674688))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(49199040))))[name = string("module__decoder_layers_4_first_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_4_first_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_4_first_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(49264640)))];
            tensor<fp16, [1, 256, 1024]> linear_42_cast_fp16 = linear(bias = module__decoder_layers_4_first_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_4_first_sub_layer_value_net_weight_to_fp16_quantized, x = input_127_cast_fp16)[name = string("linear_42_cast_fp16")];
            tensor<int32, [4]> var_764 = const()[name = string("op_764"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_99_cast_fp16 = reshape(shape = var_764, x = linear_40_cast_fp16)[name = string("x_99_cast_fp16")];
            fp16 _inversed_query_17_y_0_to_fp16 = const()[name = string("_inversed_query_17_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_17_cast_fp16 = mul(x = x_99_cast_fp16, y = _inversed_query_17_y_0_to_fp16)[name = string("_inversed_query_17_cast_fp16")];
            tensor<int32, [4]> var_772 = const()[name = string("op_772"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_103_cast_fp16 = reshape(shape = var_772, x = linear_41_cast_fp16)[name = string("x_103_cast_fp16")];
            fp16 _inversed_key_17_y_0_to_fp16 = const()[name = string("_inversed_key_17_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_key_17_cast_fp16 = mul(x = x_103_cast_fp16, y = _inversed_key_17_y_0_to_fp16)[name = string("_inversed_key_17_cast_fp16")];
            tensor<int32, [4]> var_780 = const()[name = string("op_780"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_107_cast_fp16 = reshape(shape = var_780, x = linear_42_cast_fp16)[name = string("x_107_cast_fp16")];
            tensor<int32, [4]> var_782 = const()[name = string("op_782"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_33_transpose_x_1 = const()[name = string("attention_scores_33_transpose_x_1"), val = bool(false)];
            bool attention_scores_33_transpose_y_1 = const()[name = string("attention_scores_33_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_80_perm_0 = const()[name = string("transpose_80_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_81_perm_0 = const()[name = string("transpose_81_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 256, 128]> transpose_81 = transpose(perm = transpose_81_perm_0, x = _inversed_key_17_cast_fp16)[name = string("transpose_126")];
            tensor<fp16, [1, 8, 256, 128]> transpose_80 = transpose(perm = transpose_80_perm_0, x = _inversed_query_17_cast_fp16)[name = string("transpose_127")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_33_cast_fp16 = matmul(transpose_x = attention_scores_33_transpose_x_1, transpose_y = attention_scores_33_transpose_y_1, x = transpose_80, y = transpose_81)[name = string("attention_scores_33_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_35_cast_fp16 = add(x = attention_scores_33_cast_fp16, y = attention_mask_5_cast_fp16)[name = string("attention_scores_35_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> input_131_cast_fp16 = softmax(axis = var_24, x = attention_scores_35_cast_fp16)[name = string("input_131_cast_fp16")];
            bool context_33_transpose_x_0 = const()[name = string("context_33_transpose_x_0"), val = bool(false)];
            bool context_33_transpose_y_0 = const()[name = string("context_33_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 256, 128]> value_19_cast_fp16 = transpose(perm = var_782, x = x_107_cast_fp16)[name = string("transpose_125")];
            tensor<fp16, [1, 8, 256, 128]> context_33_cast_fp16 = matmul(transpose_x = context_33_transpose_x_0, transpose_y = context_33_transpose_y_0, x = input_131_cast_fp16, y = value_19_cast_fp16)[name = string("context_33_cast_fp16")];
            tensor<int32, [4]> var_796 = const()[name = string("op_796"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_801 = const()[name = string("op_801"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_797_cast_fp16 = transpose(perm = var_796, x = context_33_cast_fp16)[name = string("transpose_124")];
            tensor<fp16, [1, 256, 1024]> input_133_cast_fp16 = reshape(shape = var_801, x = var_797_cast_fp16)[name = string("input_133_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_4_first_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(49266752))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(49791104))))[name = string("module__decoder_layers_4_first_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_4_first_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_4_first_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(49856704)))];
            tensor<fp16, [1, 256, 1024]> linear_43_cast_fp16 = linear(bias = module__decoder_layers_4_first_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_4_first_sub_layer_out_projection_weight_to_fp16_quantized, x = input_133_cast_fp16)[name = string("linear_43_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_137_cast_fp16 = add(x = linear_43_cast_fp16, y = input_125_cast_fp16)[name = string("input_137_cast_fp16")];
            tensor<int32, [1]> input_139_axes_0 = const()[name = string("input_139_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_4_layer_norm_2_weight_to_fp16 = const()[name = string("module__decoder_layers_4_layer_norm_2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(49858816)))];
            tensor<fp16, [1024]> module__decoder_layers_4_layer_norm_2_bias_to_fp16 = const()[name = string("module__decoder_layers_4_layer_norm_2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(49860928)))];
            tensor<fp16, [1, 256, 1024]> input_139_cast_fp16 = layer_norm(axes = input_139_axes_0, beta = module__decoder_layers_4_layer_norm_2_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_4_layer_norm_2_weight_to_fp16, x = input_137_cast_fp16)[name = string("input_139_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_4_second_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(49863040))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(50387392))))[name = string("module__decoder_layers_4_second_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_4_second_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_4_second_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(50452992)))];
            tensor<fp16, [1, 256, 1024]> linear_44_cast_fp16 = linear(bias = module__decoder_layers_4_second_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_4_second_sub_layer_query_net_weight_to_fp16_quantized, x = input_139_cast_fp16)[name = string("linear_44_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_4_second_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(50455104))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(50979456))))[name = string("module__decoder_layers_4_second_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_4_second_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_4_second_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51045056)))];
            tensor<fp16, [1, 188, 1024]> linear_45_cast_fp16 = linear(bias = module__decoder_layers_4_second_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_4_second_sub_layer_key_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_45_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_4_second_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51047168))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51571520))))[name = string("module__decoder_layers_4_second_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_4_second_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_4_second_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51637120)))];
            tensor<fp16, [1, 188, 1024]> linear_46_cast_fp16 = linear(bias = module__decoder_layers_4_second_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_4_second_sub_layer_value_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_46_cast_fp16")];
            tensor<int32, [4]> var_830 = const()[name = string("op_830"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_111_cast_fp16 = reshape(shape = var_830, x = linear_44_cast_fp16)[name = string("x_111_cast_fp16")];
            fp16 _inversed_query_19_y_0_to_fp16 = const()[name = string("_inversed_query_19_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_19_cast_fp16 = mul(x = x_111_cast_fp16, y = _inversed_query_19_y_0_to_fp16)[name = string("_inversed_query_19_cast_fp16")];
            tensor<int32, [4]> var_838 = const()[name = string("op_838"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_115_cast_fp16 = reshape(shape = var_838, x = linear_45_cast_fp16)[name = string("x_115_cast_fp16")];
            fp16 _inversed_key_19_y_0_to_fp16 = const()[name = string("_inversed_key_19_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 188, 8, 128]> _inversed_key_19_cast_fp16 = mul(x = x_115_cast_fp16, y = _inversed_key_19_y_0_to_fp16)[name = string("_inversed_key_19_cast_fp16")];
            tensor<int32, [4]> var_846 = const()[name = string("op_846"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_119_cast_fp16 = reshape(shape = var_846, x = linear_46_cast_fp16)[name = string("x_119_cast_fp16")];
            tensor<int32, [4]> var_848 = const()[name = string("op_848"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_37_transpose_x_1 = const()[name = string("attention_scores_37_transpose_x_1"), val = bool(false)];
            bool attention_scores_37_transpose_y_1 = const()[name = string("attention_scores_37_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_82_perm_0 = const()[name = string("transpose_82_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_83_perm_0 = const()[name = string("transpose_83_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 188, 128]> transpose_83 = transpose(perm = transpose_83_perm_0, x = _inversed_key_19_cast_fp16)[name = string("transpose_122")];
            tensor<fp16, [1, 8, 256, 128]> transpose_82 = transpose(perm = transpose_82_perm_0, x = _inversed_query_19_cast_fp16)[name = string("transpose_123")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_37_cast_fp16 = matmul(transpose_x = attention_scores_37_transpose_x_1, transpose_y = attention_scores_37_transpose_y_1, x = transpose_82, y = transpose_83)[name = string("attention_scores_37_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_39_cast_fp16 = add(x = attention_scores_37_cast_fp16, y = attention_mask_9_cast_fp16)[name = string("attention_scores_39_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> input_141_cast_fp16 = softmax(axis = var_24, x = attention_scores_39_cast_fp16)[name = string("input_141_cast_fp16")];
            bool context_37_transpose_x_0 = const()[name = string("context_37_transpose_x_0"), val = bool(false)];
            bool context_37_transpose_y_0 = const()[name = string("context_37_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_21_cast_fp16 = transpose(perm = var_848, x = x_119_cast_fp16)[name = string("transpose_121")];
            tensor<fp16, [1, 8, 256, 128]> context_37_cast_fp16 = matmul(transpose_x = context_37_transpose_x_0, transpose_y = context_37_transpose_y_0, x = input_141_cast_fp16, y = value_21_cast_fp16)[name = string("context_37_cast_fp16")];
            tensor<int32, [4]> var_862 = const()[name = string("op_862"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_867 = const()[name = string("op_867"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_863_cast_fp16 = transpose(perm = var_862, x = context_37_cast_fp16)[name = string("transpose_120")];
            tensor<fp16, [1, 256, 1024]> input_143_cast_fp16 = reshape(shape = var_867, x = var_863_cast_fp16)[name = string("input_143_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_4_second_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51639232))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(52163584))))[name = string("module__decoder_layers_4_second_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_4_second_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_4_second_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(52229184)))];
            tensor<fp16, [1, 256, 1024]> linear_47_cast_fp16 = linear(bias = module__decoder_layers_4_second_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_4_second_sub_layer_out_projection_weight_to_fp16_quantized, x = input_143_cast_fp16)[name = string("linear_47_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_147_cast_fp16 = add(x = linear_47_cast_fp16, y = input_137_cast_fp16)[name = string("input_147_cast_fp16")];
            tensor<int32, [1]> input_149_axes_0 = const()[name = string("input_149_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_4_layer_norm_3_weight_to_fp16 = const()[name = string("module__decoder_layers_4_layer_norm_3_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(52231296)))];
            tensor<fp16, [1024]> module__decoder_layers_4_layer_norm_3_bias_to_fp16 = const()[name = string("module__decoder_layers_4_layer_norm_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(52233408)))];
            tensor<fp16, [1, 256, 1024]> input_149_cast_fp16 = layer_norm(axes = input_149_axes_0, beta = module__decoder_layers_4_layer_norm_3_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_4_layer_norm_3_weight_to_fp16, x = input_147_cast_fp16)[name = string("input_149_cast_fp16")];
            tensor<fp16, [4096, 1024]> module__decoder_layers_4_third_sub_layer_dense_in_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(52235520))), scale = tensor<fp16, [4096, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(54332736))))[name = string("module__decoder_layers_4_third_sub_layer_dense_in_weight_to_fp16_quantized")];
            tensor<fp16, [4096]> module__decoder_layers_4_third_sub_layer_dense_in_bias_to_fp16 = const()[name = string("module__decoder_layers_4_third_sub_layer_dense_in_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(54594944)))];
            tensor<fp16, [1, 256, 4096]> linear_48_cast_fp16 = linear(bias = module__decoder_layers_4_third_sub_layer_dense_in_bias_to_fp16, weight = module__decoder_layers_4_third_sub_layer_dense_in_weight_to_fp16_quantized, x = input_149_cast_fp16)[name = string("linear_48_cast_fp16")];
            tensor<fp16, [1, 256, 4096]> input_151_cast_fp16 = relu(x = linear_48_cast_fp16)[name = string("input_151_cast_fp16")];
            tensor<fp16, [1024, 4096]> module__decoder_layers_4_third_sub_layer_dense_out_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(54603200))), scale = tensor<fp16, [1024, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56700416))))[name = string("module__decoder_layers_4_third_sub_layer_dense_out_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_4_third_sub_layer_dense_out_bias_to_fp16 = const()[name = string("module__decoder_layers_4_third_sub_layer_dense_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56962624)))];
            tensor<fp16, [1, 256, 1024]> linear_49_cast_fp16 = linear(bias = module__decoder_layers_4_third_sub_layer_dense_out_bias_to_fp16, weight = module__decoder_layers_4_third_sub_layer_dense_out_weight_to_fp16_quantized, x = input_151_cast_fp16)[name = string("linear_49_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_155_cast_fp16 = add(x = linear_49_cast_fp16, y = input_147_cast_fp16)[name = string("input_155_cast_fp16")];
            tensor<int32, [1]> input_157_axes_0 = const()[name = string("input_157_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_5_layer_norm_1_weight_to_fp16 = const()[name = string("module__decoder_layers_5_layer_norm_1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56964736)))];
            tensor<fp16, [1024]> module__decoder_layers_5_layer_norm_1_bias_to_fp16 = const()[name = string("module__decoder_layers_5_layer_norm_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56966848)))];
            tensor<fp16, [1, 256, 1024]> input_157_cast_fp16 = layer_norm(axes = input_157_axes_0, beta = module__decoder_layers_5_layer_norm_1_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_5_layer_norm_1_weight_to_fp16, x = input_155_cast_fp16)[name = string("input_157_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_5_first_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(56968960))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(57493312))))[name = string("module__decoder_layers_5_first_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_5_first_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_5_first_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(57558912)))];
            tensor<fp16, [1, 256, 1024]> linear_50_cast_fp16 = linear(bias = module__decoder_layers_5_first_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_5_first_sub_layer_query_net_weight_to_fp16_quantized, x = input_157_cast_fp16)[name = string("linear_50_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_5_first_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(57561024))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(58085376))))[name = string("module__decoder_layers_5_first_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_5_first_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_5_first_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(58150976)))];
            tensor<fp16, [1, 256, 1024]> linear_51_cast_fp16 = linear(bias = module__decoder_layers_5_first_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_5_first_sub_layer_key_net_weight_to_fp16_quantized, x = input_157_cast_fp16)[name = string("linear_51_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_5_first_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(58153088))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(58677440))))[name = string("module__decoder_layers_5_first_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_5_first_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_5_first_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(58743040)))];
            tensor<fp16, [1, 256, 1024]> linear_52_cast_fp16 = linear(bias = module__decoder_layers_5_first_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_5_first_sub_layer_value_net_weight_to_fp16_quantized, x = input_157_cast_fp16)[name = string("linear_52_cast_fp16")];
            tensor<int32, [4]> var_925 = const()[name = string("op_925"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_123_cast_fp16 = reshape(shape = var_925, x = linear_50_cast_fp16)[name = string("x_123_cast_fp16")];
            fp16 _inversed_query_21_y_0_to_fp16 = const()[name = string("_inversed_query_21_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_21_cast_fp16 = mul(x = x_123_cast_fp16, y = _inversed_query_21_y_0_to_fp16)[name = string("_inversed_query_21_cast_fp16")];
            tensor<int32, [4]> var_933 = const()[name = string("op_933"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_127_cast_fp16 = reshape(shape = var_933, x = linear_51_cast_fp16)[name = string("x_127_cast_fp16")];
            fp16 _inversed_key_21_y_0_to_fp16 = const()[name = string("_inversed_key_21_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_key_21_cast_fp16 = mul(x = x_127_cast_fp16, y = _inversed_key_21_y_0_to_fp16)[name = string("_inversed_key_21_cast_fp16")];
            tensor<int32, [4]> var_941 = const()[name = string("op_941"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_131_cast_fp16 = reshape(shape = var_941, x = linear_52_cast_fp16)[name = string("x_131_cast_fp16")];
            tensor<int32, [4]> var_943 = const()[name = string("op_943"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_41_transpose_x_1 = const()[name = string("attention_scores_41_transpose_x_1"), val = bool(false)];
            bool attention_scores_41_transpose_y_1 = const()[name = string("attention_scores_41_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_84_perm_0 = const()[name = string("transpose_84_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_85_perm_0 = const()[name = string("transpose_85_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 256, 128]> transpose_85 = transpose(perm = transpose_85_perm_0, x = _inversed_key_21_cast_fp16)[name = string("transpose_118")];
            tensor<fp16, [1, 8, 256, 128]> transpose_84 = transpose(perm = transpose_84_perm_0, x = _inversed_query_21_cast_fp16)[name = string("transpose_119")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_41_cast_fp16 = matmul(transpose_x = attention_scores_41_transpose_x_1, transpose_y = attention_scores_41_transpose_y_1, x = transpose_84, y = transpose_85)[name = string("attention_scores_41_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_43_cast_fp16 = add(x = attention_scores_41_cast_fp16, y = attention_mask_5_cast_fp16)[name = string("attention_scores_43_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> input_161_cast_fp16 = softmax(axis = var_24, x = attention_scores_43_cast_fp16)[name = string("input_161_cast_fp16")];
            bool context_41_transpose_x_0 = const()[name = string("context_41_transpose_x_0"), val = bool(false)];
            bool context_41_transpose_y_0 = const()[name = string("context_41_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 256, 128]> value_23_cast_fp16 = transpose(perm = var_943, x = x_131_cast_fp16)[name = string("transpose_117")];
            tensor<fp16, [1, 8, 256, 128]> context_41_cast_fp16 = matmul(transpose_x = context_41_transpose_x_0, transpose_y = context_41_transpose_y_0, x = input_161_cast_fp16, y = value_23_cast_fp16)[name = string("context_41_cast_fp16")];
            tensor<int32, [4]> var_957 = const()[name = string("op_957"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_962 = const()[name = string("op_962"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_958_cast_fp16 = transpose(perm = var_957, x = context_41_cast_fp16)[name = string("transpose_116")];
            tensor<fp16, [1, 256, 1024]> input_163_cast_fp16 = reshape(shape = var_962, x = var_958_cast_fp16)[name = string("input_163_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_5_first_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(58745152))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59269504))))[name = string("module__decoder_layers_5_first_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_5_first_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_5_first_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59335104)))];
            tensor<fp16, [1, 256, 1024]> linear_53_cast_fp16 = linear(bias = module__decoder_layers_5_first_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_5_first_sub_layer_out_projection_weight_to_fp16_quantized, x = input_163_cast_fp16)[name = string("linear_53_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_167_cast_fp16 = add(x = linear_53_cast_fp16, y = input_155_cast_fp16)[name = string("input_167_cast_fp16")];
            tensor<int32, [1]> input_169_axes_0 = const()[name = string("input_169_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_5_layer_norm_2_weight_to_fp16 = const()[name = string("module__decoder_layers_5_layer_norm_2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59337216)))];
            tensor<fp16, [1024]> module__decoder_layers_5_layer_norm_2_bias_to_fp16 = const()[name = string("module__decoder_layers_5_layer_norm_2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59339328)))];
            tensor<fp16, [1, 256, 1024]> input_169_cast_fp16 = layer_norm(axes = input_169_axes_0, beta = module__decoder_layers_5_layer_norm_2_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_5_layer_norm_2_weight_to_fp16, x = input_167_cast_fp16)[name = string("input_169_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_5_second_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59341440))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59865792))))[name = string("module__decoder_layers_5_second_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_5_second_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_5_second_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59931392)))];
            tensor<fp16, [1, 256, 1024]> linear_54_cast_fp16 = linear(bias = module__decoder_layers_5_second_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_5_second_sub_layer_query_net_weight_to_fp16_quantized, x = input_169_cast_fp16)[name = string("linear_54_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_5_second_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59933504))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(60457856))))[name = string("module__decoder_layers_5_second_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_5_second_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_5_second_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(60523456)))];
            tensor<fp16, [1, 188, 1024]> linear_55_cast_fp16 = linear(bias = module__decoder_layers_5_second_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_5_second_sub_layer_key_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_55_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_5_second_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(60525568))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61049920))))[name = string("module__decoder_layers_5_second_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_5_second_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_5_second_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61115520)))];
            tensor<fp16, [1, 188, 1024]> linear_56_cast_fp16 = linear(bias = module__decoder_layers_5_second_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_5_second_sub_layer_value_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_56_cast_fp16")];
            tensor<int32, [4]> var_991 = const()[name = string("op_991"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_135_cast_fp16 = reshape(shape = var_991, x = linear_54_cast_fp16)[name = string("x_135_cast_fp16")];
            fp16 _inversed_query_23_y_0_to_fp16 = const()[name = string("_inversed_query_23_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_23_cast_fp16 = mul(x = x_135_cast_fp16, y = _inversed_query_23_y_0_to_fp16)[name = string("_inversed_query_23_cast_fp16")];
            tensor<int32, [4]> var_999 = const()[name = string("op_999"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_139_cast_fp16 = reshape(shape = var_999, x = linear_55_cast_fp16)[name = string("x_139_cast_fp16")];
            fp16 _inversed_key_23_y_0_to_fp16 = const()[name = string("_inversed_key_23_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 188, 8, 128]> _inversed_key_23_cast_fp16 = mul(x = x_139_cast_fp16, y = _inversed_key_23_y_0_to_fp16)[name = string("_inversed_key_23_cast_fp16")];
            tensor<int32, [4]> var_1007 = const()[name = string("op_1007"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_143_cast_fp16 = reshape(shape = var_1007, x = linear_56_cast_fp16)[name = string("x_143_cast_fp16")];
            tensor<int32, [4]> var_1009 = const()[name = string("op_1009"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_45_transpose_x_1 = const()[name = string("attention_scores_45_transpose_x_1"), val = bool(false)];
            bool attention_scores_45_transpose_y_1 = const()[name = string("attention_scores_45_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_86_perm_0 = const()[name = string("transpose_86_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_87_perm_0 = const()[name = string("transpose_87_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 188, 128]> transpose_87 = transpose(perm = transpose_87_perm_0, x = _inversed_key_23_cast_fp16)[name = string("transpose_114")];
            tensor<fp16, [1, 8, 256, 128]> transpose_86 = transpose(perm = transpose_86_perm_0, x = _inversed_query_23_cast_fp16)[name = string("transpose_115")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_45_cast_fp16 = matmul(transpose_x = attention_scores_45_transpose_x_1, transpose_y = attention_scores_45_transpose_y_1, x = transpose_86, y = transpose_87)[name = string("attention_scores_45_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_47_cast_fp16 = add(x = attention_scores_45_cast_fp16, y = attention_mask_9_cast_fp16)[name = string("attention_scores_47_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> input_171_cast_fp16 = softmax(axis = var_24, x = attention_scores_47_cast_fp16)[name = string("input_171_cast_fp16")];
            bool context_45_transpose_x_0 = const()[name = string("context_45_transpose_x_0"), val = bool(false)];
            bool context_45_transpose_y_0 = const()[name = string("context_45_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_25_cast_fp16 = transpose(perm = var_1009, x = x_143_cast_fp16)[name = string("transpose_113")];
            tensor<fp16, [1, 8, 256, 128]> context_45_cast_fp16 = matmul(transpose_x = context_45_transpose_x_0, transpose_y = context_45_transpose_y_0, x = input_171_cast_fp16, y = value_25_cast_fp16)[name = string("context_45_cast_fp16")];
            tensor<int32, [4]> var_1023 = const()[name = string("op_1023"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1028 = const()[name = string("op_1028"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_1024_cast_fp16 = transpose(perm = var_1023, x = context_45_cast_fp16)[name = string("transpose_112")];
            tensor<fp16, [1, 256, 1024]> input_173_cast_fp16 = reshape(shape = var_1028, x = var_1024_cast_fp16)[name = string("input_173_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_5_second_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61117632))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61641984))))[name = string("module__decoder_layers_5_second_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_5_second_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_5_second_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61707584)))];
            tensor<fp16, [1, 256, 1024]> linear_57_cast_fp16 = linear(bias = module__decoder_layers_5_second_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_5_second_sub_layer_out_projection_weight_to_fp16_quantized, x = input_173_cast_fp16)[name = string("linear_57_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_177_cast_fp16 = add(x = linear_57_cast_fp16, y = input_167_cast_fp16)[name = string("input_177_cast_fp16")];
            tensor<int32, [1]> input_179_axes_0 = const()[name = string("input_179_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_5_layer_norm_3_weight_to_fp16 = const()[name = string("module__decoder_layers_5_layer_norm_3_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61709696)))];
            tensor<fp16, [1024]> module__decoder_layers_5_layer_norm_3_bias_to_fp16 = const()[name = string("module__decoder_layers_5_layer_norm_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61711808)))];
            tensor<fp16, [1, 256, 1024]> input_179_cast_fp16 = layer_norm(axes = input_179_axes_0, beta = module__decoder_layers_5_layer_norm_3_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_5_layer_norm_3_weight_to_fp16, x = input_177_cast_fp16)[name = string("input_179_cast_fp16")];
            tensor<fp16, [4096, 1024]> module__decoder_layers_5_third_sub_layer_dense_in_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61713920))), scale = tensor<fp16, [4096, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(63811136))))[name = string("module__decoder_layers_5_third_sub_layer_dense_in_weight_to_fp16_quantized")];
            tensor<fp16, [4096]> module__decoder_layers_5_third_sub_layer_dense_in_bias_to_fp16 = const()[name = string("module__decoder_layers_5_third_sub_layer_dense_in_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64073344)))];
            tensor<fp16, [1, 256, 4096]> linear_58_cast_fp16 = linear(bias = module__decoder_layers_5_third_sub_layer_dense_in_bias_to_fp16, weight = module__decoder_layers_5_third_sub_layer_dense_in_weight_to_fp16_quantized, x = input_179_cast_fp16)[name = string("linear_58_cast_fp16")];
            tensor<fp16, [1, 256, 4096]> input_181_cast_fp16 = relu(x = linear_58_cast_fp16)[name = string("input_181_cast_fp16")];
            tensor<fp16, [1024, 4096]> module__decoder_layers_5_third_sub_layer_dense_out_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64081600))), scale = tensor<fp16, [1024, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(66178816))))[name = string("module__decoder_layers_5_third_sub_layer_dense_out_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_5_third_sub_layer_dense_out_bias_to_fp16 = const()[name = string("module__decoder_layers_5_third_sub_layer_dense_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(66441024)))];
            tensor<fp16, [1, 256, 1024]> linear_59_cast_fp16 = linear(bias = module__decoder_layers_5_third_sub_layer_dense_out_bias_to_fp16, weight = module__decoder_layers_5_third_sub_layer_dense_out_weight_to_fp16_quantized, x = input_181_cast_fp16)[name = string("linear_59_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_185_cast_fp16 = add(x = linear_59_cast_fp16, y = input_177_cast_fp16)[name = string("input_185_cast_fp16")];
            tensor<int32, [1]> input_187_axes_0 = const()[name = string("input_187_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_6_layer_norm_1_weight_to_fp16 = const()[name = string("module__decoder_layers_6_layer_norm_1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(66443136)))];
            tensor<fp16, [1024]> module__decoder_layers_6_layer_norm_1_bias_to_fp16 = const()[name = string("module__decoder_layers_6_layer_norm_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(66445248)))];
            tensor<fp16, [1, 256, 1024]> input_187_cast_fp16 = layer_norm(axes = input_187_axes_0, beta = module__decoder_layers_6_layer_norm_1_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_6_layer_norm_1_weight_to_fp16, x = input_185_cast_fp16)[name = string("input_187_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_6_first_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(66447360))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(66971712))))[name = string("module__decoder_layers_6_first_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_6_first_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_6_first_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(67037312)))];
            tensor<fp16, [1, 256, 1024]> linear_60_cast_fp16 = linear(bias = module__decoder_layers_6_first_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_6_first_sub_layer_query_net_weight_to_fp16_quantized, x = input_187_cast_fp16)[name = string("linear_60_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_6_first_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(67039424))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(67563776))))[name = string("module__decoder_layers_6_first_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_6_first_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_6_first_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(67629376)))];
            tensor<fp16, [1, 256, 1024]> linear_61_cast_fp16 = linear(bias = module__decoder_layers_6_first_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_6_first_sub_layer_key_net_weight_to_fp16_quantized, x = input_187_cast_fp16)[name = string("linear_61_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_6_first_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(67631488))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(68155840))))[name = string("module__decoder_layers_6_first_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_6_first_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_6_first_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(68221440)))];
            tensor<fp16, [1, 256, 1024]> linear_62_cast_fp16 = linear(bias = module__decoder_layers_6_first_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_6_first_sub_layer_value_net_weight_to_fp16_quantized, x = input_187_cast_fp16)[name = string("linear_62_cast_fp16")];
            tensor<int32, [4]> var_1086 = const()[name = string("op_1086"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_147_cast_fp16 = reshape(shape = var_1086, x = linear_60_cast_fp16)[name = string("x_147_cast_fp16")];
            fp16 _inversed_query_25_y_0_to_fp16 = const()[name = string("_inversed_query_25_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_25_cast_fp16 = mul(x = x_147_cast_fp16, y = _inversed_query_25_y_0_to_fp16)[name = string("_inversed_query_25_cast_fp16")];
            tensor<int32, [4]> var_1094 = const()[name = string("op_1094"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_151_cast_fp16 = reshape(shape = var_1094, x = linear_61_cast_fp16)[name = string("x_151_cast_fp16")];
            fp16 _inversed_key_25_y_0_to_fp16 = const()[name = string("_inversed_key_25_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_key_25_cast_fp16 = mul(x = x_151_cast_fp16, y = _inversed_key_25_y_0_to_fp16)[name = string("_inversed_key_25_cast_fp16")];
            tensor<int32, [4]> var_1102 = const()[name = string("op_1102"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_155_cast_fp16 = reshape(shape = var_1102, x = linear_62_cast_fp16)[name = string("x_155_cast_fp16")];
            tensor<int32, [4]> var_1104 = const()[name = string("op_1104"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_49_transpose_x_1 = const()[name = string("attention_scores_49_transpose_x_1"), val = bool(false)];
            bool attention_scores_49_transpose_y_1 = const()[name = string("attention_scores_49_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_88_perm_0 = const()[name = string("transpose_88_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_89_perm_0 = const()[name = string("transpose_89_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 256, 128]> transpose_89 = transpose(perm = transpose_89_perm_0, x = _inversed_key_25_cast_fp16)[name = string("transpose_110")];
            tensor<fp16, [1, 8, 256, 128]> transpose_88 = transpose(perm = transpose_88_perm_0, x = _inversed_query_25_cast_fp16)[name = string("transpose_111")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_49_cast_fp16 = matmul(transpose_x = attention_scores_49_transpose_x_1, transpose_y = attention_scores_49_transpose_y_1, x = transpose_88, y = transpose_89)[name = string("attention_scores_49_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_51_cast_fp16 = add(x = attention_scores_49_cast_fp16, y = attention_mask_5_cast_fp16)[name = string("attention_scores_51_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> input_191_cast_fp16 = softmax(axis = var_24, x = attention_scores_51_cast_fp16)[name = string("input_191_cast_fp16")];
            bool context_49_transpose_x_0 = const()[name = string("context_49_transpose_x_0"), val = bool(false)];
            bool context_49_transpose_y_0 = const()[name = string("context_49_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 256, 128]> value_27_cast_fp16 = transpose(perm = var_1104, x = x_155_cast_fp16)[name = string("transpose_109")];
            tensor<fp16, [1, 8, 256, 128]> context_49_cast_fp16 = matmul(transpose_x = context_49_transpose_x_0, transpose_y = context_49_transpose_y_0, x = input_191_cast_fp16, y = value_27_cast_fp16)[name = string("context_49_cast_fp16")];
            tensor<int32, [4]> var_1118 = const()[name = string("op_1118"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1123 = const()[name = string("op_1123"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_1119_cast_fp16 = transpose(perm = var_1118, x = context_49_cast_fp16)[name = string("transpose_108")];
            tensor<fp16, [1, 256, 1024]> input_193_cast_fp16 = reshape(shape = var_1123, x = var_1119_cast_fp16)[name = string("input_193_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_6_first_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(68223552))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(68747904))))[name = string("module__decoder_layers_6_first_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_6_first_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_6_first_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(68813504)))];
            tensor<fp16, [1, 256, 1024]> linear_63_cast_fp16 = linear(bias = module__decoder_layers_6_first_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_6_first_sub_layer_out_projection_weight_to_fp16_quantized, x = input_193_cast_fp16)[name = string("linear_63_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_197_cast_fp16 = add(x = linear_63_cast_fp16, y = input_185_cast_fp16)[name = string("input_197_cast_fp16")];
            tensor<int32, [1]> input_199_axes_0 = const()[name = string("input_199_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_6_layer_norm_2_weight_to_fp16 = const()[name = string("module__decoder_layers_6_layer_norm_2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(68815616)))];
            tensor<fp16, [1024]> module__decoder_layers_6_layer_norm_2_bias_to_fp16 = const()[name = string("module__decoder_layers_6_layer_norm_2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(68817728)))];
            tensor<fp16, [1, 256, 1024]> input_199_cast_fp16 = layer_norm(axes = input_199_axes_0, beta = module__decoder_layers_6_layer_norm_2_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_6_layer_norm_2_weight_to_fp16, x = input_197_cast_fp16)[name = string("input_199_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_6_second_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(68819840))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(69344192))))[name = string("module__decoder_layers_6_second_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_6_second_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_6_second_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(69409792)))];
            tensor<fp16, [1, 256, 1024]> linear_64_cast_fp16 = linear(bias = module__decoder_layers_6_second_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_6_second_sub_layer_query_net_weight_to_fp16_quantized, x = input_199_cast_fp16)[name = string("linear_64_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_6_second_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(69411904))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(69936256))))[name = string("module__decoder_layers_6_second_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_6_second_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_6_second_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(70001856)))];
            tensor<fp16, [1, 188, 1024]> linear_65_cast_fp16 = linear(bias = module__decoder_layers_6_second_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_6_second_sub_layer_key_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_65_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_6_second_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(70003968))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(70528320))))[name = string("module__decoder_layers_6_second_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_6_second_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_6_second_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(70593920)))];
            tensor<fp16, [1, 188, 1024]> linear_66_cast_fp16 = linear(bias = module__decoder_layers_6_second_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_6_second_sub_layer_value_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_66_cast_fp16")];
            tensor<int32, [4]> var_1152 = const()[name = string("op_1152"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_159_cast_fp16 = reshape(shape = var_1152, x = linear_64_cast_fp16)[name = string("x_159_cast_fp16")];
            fp16 _inversed_query_27_y_0_to_fp16 = const()[name = string("_inversed_query_27_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_27_cast_fp16 = mul(x = x_159_cast_fp16, y = _inversed_query_27_y_0_to_fp16)[name = string("_inversed_query_27_cast_fp16")];
            tensor<int32, [4]> var_1160 = const()[name = string("op_1160"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_163_cast_fp16 = reshape(shape = var_1160, x = linear_65_cast_fp16)[name = string("x_163_cast_fp16")];
            fp16 _inversed_key_27_y_0_to_fp16 = const()[name = string("_inversed_key_27_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 188, 8, 128]> _inversed_key_27_cast_fp16 = mul(x = x_163_cast_fp16, y = _inversed_key_27_y_0_to_fp16)[name = string("_inversed_key_27_cast_fp16")];
            tensor<int32, [4]> var_1168 = const()[name = string("op_1168"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_167_cast_fp16 = reshape(shape = var_1168, x = linear_66_cast_fp16)[name = string("x_167_cast_fp16")];
            tensor<int32, [4]> var_1170 = const()[name = string("op_1170"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_53_transpose_x_1 = const()[name = string("attention_scores_53_transpose_x_1"), val = bool(false)];
            bool attention_scores_53_transpose_y_1 = const()[name = string("attention_scores_53_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_90_perm_0 = const()[name = string("transpose_90_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_91_perm_0 = const()[name = string("transpose_91_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 188, 128]> transpose_91 = transpose(perm = transpose_91_perm_0, x = _inversed_key_27_cast_fp16)[name = string("transpose_106")];
            tensor<fp16, [1, 8, 256, 128]> transpose_90 = transpose(perm = transpose_90_perm_0, x = _inversed_query_27_cast_fp16)[name = string("transpose_107")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_53_cast_fp16 = matmul(transpose_x = attention_scores_53_transpose_x_1, transpose_y = attention_scores_53_transpose_y_1, x = transpose_90, y = transpose_91)[name = string("attention_scores_53_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_55_cast_fp16 = add(x = attention_scores_53_cast_fp16, y = attention_mask_9_cast_fp16)[name = string("attention_scores_55_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> input_201_cast_fp16 = softmax(axis = var_24, x = attention_scores_55_cast_fp16)[name = string("input_201_cast_fp16")];
            bool context_53_transpose_x_0 = const()[name = string("context_53_transpose_x_0"), val = bool(false)];
            bool context_53_transpose_y_0 = const()[name = string("context_53_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_29_cast_fp16 = transpose(perm = var_1170, x = x_167_cast_fp16)[name = string("transpose_105")];
            tensor<fp16, [1, 8, 256, 128]> context_53_cast_fp16 = matmul(transpose_x = context_53_transpose_x_0, transpose_y = context_53_transpose_y_0, x = input_201_cast_fp16, y = value_29_cast_fp16)[name = string("context_53_cast_fp16")];
            tensor<int32, [4]> var_1184 = const()[name = string("op_1184"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1189 = const()[name = string("op_1189"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_1185_cast_fp16 = transpose(perm = var_1184, x = context_53_cast_fp16)[name = string("transpose_104")];
            tensor<fp16, [1, 256, 1024]> input_203_cast_fp16 = reshape(shape = var_1189, x = var_1185_cast_fp16)[name = string("input_203_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_6_second_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(70596032))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(71120384))))[name = string("module__decoder_layers_6_second_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_6_second_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_6_second_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(71185984)))];
            tensor<fp16, [1, 256, 1024]> linear_67_cast_fp16 = linear(bias = module__decoder_layers_6_second_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_6_second_sub_layer_out_projection_weight_to_fp16_quantized, x = input_203_cast_fp16)[name = string("linear_67_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_207_cast_fp16 = add(x = linear_67_cast_fp16, y = input_197_cast_fp16)[name = string("input_207_cast_fp16")];
            tensor<int32, [1]> input_209_axes_0 = const()[name = string("input_209_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_6_layer_norm_3_weight_to_fp16 = const()[name = string("module__decoder_layers_6_layer_norm_3_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(71188096)))];
            tensor<fp16, [1024]> module__decoder_layers_6_layer_norm_3_bias_to_fp16 = const()[name = string("module__decoder_layers_6_layer_norm_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(71190208)))];
            tensor<fp16, [1, 256, 1024]> input_209_cast_fp16 = layer_norm(axes = input_209_axes_0, beta = module__decoder_layers_6_layer_norm_3_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_6_layer_norm_3_weight_to_fp16, x = input_207_cast_fp16)[name = string("input_209_cast_fp16")];
            tensor<fp16, [4096, 1024]> module__decoder_layers_6_third_sub_layer_dense_in_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(71192320))), scale = tensor<fp16, [4096, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(73289536))))[name = string("module__decoder_layers_6_third_sub_layer_dense_in_weight_to_fp16_quantized")];
            tensor<fp16, [4096]> module__decoder_layers_6_third_sub_layer_dense_in_bias_to_fp16 = const()[name = string("module__decoder_layers_6_third_sub_layer_dense_in_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(73551744)))];
            tensor<fp16, [1, 256, 4096]> linear_68_cast_fp16 = linear(bias = module__decoder_layers_6_third_sub_layer_dense_in_bias_to_fp16, weight = module__decoder_layers_6_third_sub_layer_dense_in_weight_to_fp16_quantized, x = input_209_cast_fp16)[name = string("linear_68_cast_fp16")];
            tensor<fp16, [1, 256, 4096]> input_211_cast_fp16 = relu(x = linear_68_cast_fp16)[name = string("input_211_cast_fp16")];
            tensor<fp16, [1024, 4096]> module__decoder_layers_6_third_sub_layer_dense_out_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(73560000))), scale = tensor<fp16, [1024, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(75657216))))[name = string("module__decoder_layers_6_third_sub_layer_dense_out_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_6_third_sub_layer_dense_out_bias_to_fp16 = const()[name = string("module__decoder_layers_6_third_sub_layer_dense_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(75919424)))];
            tensor<fp16, [1, 256, 1024]> linear_69_cast_fp16 = linear(bias = module__decoder_layers_6_third_sub_layer_dense_out_bias_to_fp16, weight = module__decoder_layers_6_third_sub_layer_dense_out_weight_to_fp16_quantized, x = input_211_cast_fp16)[name = string("linear_69_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_215_cast_fp16 = add(x = linear_69_cast_fp16, y = input_207_cast_fp16)[name = string("input_215_cast_fp16")];
            tensor<int32, [1]> input_217_axes_0 = const()[name = string("input_217_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_7_layer_norm_1_weight_to_fp16 = const()[name = string("module__decoder_layers_7_layer_norm_1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(75921536)))];
            tensor<fp16, [1024]> module__decoder_layers_7_layer_norm_1_bias_to_fp16 = const()[name = string("module__decoder_layers_7_layer_norm_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(75923648)))];
            tensor<fp16, [1, 256, 1024]> input_217_cast_fp16 = layer_norm(axes = input_217_axes_0, beta = module__decoder_layers_7_layer_norm_1_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_7_layer_norm_1_weight_to_fp16, x = input_215_cast_fp16)[name = string("input_217_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_7_first_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(75925760))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(76450112))))[name = string("module__decoder_layers_7_first_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_7_first_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_7_first_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(76515712)))];
            tensor<fp16, [1, 256, 1024]> linear_70_cast_fp16 = linear(bias = module__decoder_layers_7_first_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_7_first_sub_layer_query_net_weight_to_fp16_quantized, x = input_217_cast_fp16)[name = string("linear_70_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_7_first_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(76517824))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(77042176))))[name = string("module__decoder_layers_7_first_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_7_first_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_7_first_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(77107776)))];
            tensor<fp16, [1, 256, 1024]> linear_71_cast_fp16 = linear(bias = module__decoder_layers_7_first_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_7_first_sub_layer_key_net_weight_to_fp16_quantized, x = input_217_cast_fp16)[name = string("linear_71_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_7_first_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(77109888))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(77634240))))[name = string("module__decoder_layers_7_first_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_7_first_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_7_first_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(77699840)))];
            tensor<fp16, [1, 256, 1024]> linear_72_cast_fp16 = linear(bias = module__decoder_layers_7_first_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_7_first_sub_layer_value_net_weight_to_fp16_quantized, x = input_217_cast_fp16)[name = string("linear_72_cast_fp16")];
            tensor<int32, [4]> var_1247 = const()[name = string("op_1247"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_171_cast_fp16 = reshape(shape = var_1247, x = linear_70_cast_fp16)[name = string("x_171_cast_fp16")];
            fp16 _inversed_query_29_y_0_to_fp16 = const()[name = string("_inversed_query_29_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_29_cast_fp16 = mul(x = x_171_cast_fp16, y = _inversed_query_29_y_0_to_fp16)[name = string("_inversed_query_29_cast_fp16")];
            tensor<int32, [4]> var_1255 = const()[name = string("op_1255"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_175_cast_fp16 = reshape(shape = var_1255, x = linear_71_cast_fp16)[name = string("x_175_cast_fp16")];
            fp16 _inversed_key_29_y_0_to_fp16 = const()[name = string("_inversed_key_29_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_key_29_cast_fp16 = mul(x = x_175_cast_fp16, y = _inversed_key_29_y_0_to_fp16)[name = string("_inversed_key_29_cast_fp16")];
            tensor<int32, [4]> var_1263 = const()[name = string("op_1263"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_179_cast_fp16 = reshape(shape = var_1263, x = linear_72_cast_fp16)[name = string("x_179_cast_fp16")];
            tensor<int32, [4]> var_1265 = const()[name = string("op_1265"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_57_transpose_x_1 = const()[name = string("attention_scores_57_transpose_x_1"), val = bool(false)];
            bool attention_scores_57_transpose_y_1 = const()[name = string("attention_scores_57_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_92_perm_0 = const()[name = string("transpose_92_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_93_perm_0 = const()[name = string("transpose_93_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 256, 128]> transpose_93 = transpose(perm = transpose_93_perm_0, x = _inversed_key_29_cast_fp16)[name = string("transpose_102")];
            tensor<fp16, [1, 8, 256, 128]> transpose_92 = transpose(perm = transpose_92_perm_0, x = _inversed_query_29_cast_fp16)[name = string("transpose_103")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_57_cast_fp16 = matmul(transpose_x = attention_scores_57_transpose_x_1, transpose_y = attention_scores_57_transpose_y_1, x = transpose_92, y = transpose_93)[name = string("attention_scores_57_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> attention_scores_59_cast_fp16 = add(x = attention_scores_57_cast_fp16, y = attention_mask_5_cast_fp16)[name = string("attention_scores_59_cast_fp16")];
            tensor<fp16, [1, 8, 256, 256]> input_221_cast_fp16 = softmax(axis = var_24, x = attention_scores_59_cast_fp16)[name = string("input_221_cast_fp16")];
            bool context_57_transpose_x_0 = const()[name = string("context_57_transpose_x_0"), val = bool(false)];
            bool context_57_transpose_y_0 = const()[name = string("context_57_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 256, 128]> value_31_cast_fp16 = transpose(perm = var_1265, x = x_179_cast_fp16)[name = string("transpose_101")];
            tensor<fp16, [1, 8, 256, 128]> context_57_cast_fp16 = matmul(transpose_x = context_57_transpose_x_0, transpose_y = context_57_transpose_y_0, x = input_221_cast_fp16, y = value_31_cast_fp16)[name = string("context_57_cast_fp16")];
            tensor<int32, [4]> var_1279 = const()[name = string("op_1279"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1284 = const()[name = string("op_1284"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_1280_cast_fp16 = transpose(perm = var_1279, x = context_57_cast_fp16)[name = string("transpose_100")];
            tensor<fp16, [1, 256, 1024]> input_223_cast_fp16 = reshape(shape = var_1284, x = var_1280_cast_fp16)[name = string("input_223_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_7_first_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(77701952))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78226304))))[name = string("module__decoder_layers_7_first_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_7_first_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_7_first_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78291904)))];
            tensor<fp16, [1, 256, 1024]> linear_73_cast_fp16 = linear(bias = module__decoder_layers_7_first_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_7_first_sub_layer_out_projection_weight_to_fp16_quantized, x = input_223_cast_fp16)[name = string("linear_73_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_227_cast_fp16 = add(x = linear_73_cast_fp16, y = input_215_cast_fp16)[name = string("input_227_cast_fp16")];
            tensor<int32, [1]> input_229_axes_0 = const()[name = string("input_229_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_7_layer_norm_2_weight_to_fp16 = const()[name = string("module__decoder_layers_7_layer_norm_2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78294016)))];
            tensor<fp16, [1024]> module__decoder_layers_7_layer_norm_2_bias_to_fp16 = const()[name = string("module__decoder_layers_7_layer_norm_2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78296128)))];
            tensor<fp16, [1, 256, 1024]> input_229_cast_fp16 = layer_norm(axes = input_229_axes_0, beta = module__decoder_layers_7_layer_norm_2_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_7_layer_norm_2_weight_to_fp16, x = input_227_cast_fp16)[name = string("input_229_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_7_second_sub_layer_query_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78298240))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78822592))))[name = string("module__decoder_layers_7_second_sub_layer_query_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_7_second_sub_layer_query_net_bias_to_fp16 = const()[name = string("module__decoder_layers_7_second_sub_layer_query_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78888192)))];
            tensor<fp16, [1, 256, 1024]> linear_74_cast_fp16 = linear(bias = module__decoder_layers_7_second_sub_layer_query_net_bias_to_fp16, weight = module__decoder_layers_7_second_sub_layer_query_net_weight_to_fp16_quantized, x = input_229_cast_fp16)[name = string("linear_74_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_7_second_sub_layer_key_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78890304))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(79414656))))[name = string("module__decoder_layers_7_second_sub_layer_key_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_7_second_sub_layer_key_net_bias_to_fp16 = const()[name = string("module__decoder_layers_7_second_sub_layer_key_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(79480256)))];
            tensor<fp16, [1, 188, 1024]> linear_75_cast_fp16 = linear(bias = module__decoder_layers_7_second_sub_layer_key_net_bias_to_fp16, weight = module__decoder_layers_7_second_sub_layer_key_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_75_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_7_second_sub_layer_value_net_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(79482368))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80006720))))[name = string("module__decoder_layers_7_second_sub_layer_value_net_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_7_second_sub_layer_value_net_bias_to_fp16 = const()[name = string("module__decoder_layers_7_second_sub_layer_value_net_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80072320)))];
            tensor<fp16, [1, 188, 1024]> linear_76_cast_fp16 = linear(bias = module__decoder_layers_7_second_sub_layer_value_net_bias_to_fp16, weight = module__decoder_layers_7_second_sub_layer_value_net_weight_to_fp16_quantized, x = encoder_embeddings_to_fp16)[name = string("linear_76_cast_fp16")];
            tensor<int32, [4]> var_1310 = const()[name = string("op_1310"), val = tensor<int32, [4]>([1, 256, 8, 128])];
            tensor<fp16, [1, 256, 8, 128]> x_183_cast_fp16 = reshape(shape = var_1310, x = linear_74_cast_fp16)[name = string("x_183_cast_fp16")];
            fp16 _inversed_query_y_0_to_fp16 = const()[name = string("_inversed_query_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 256, 8, 128]> _inversed_query_cast_fp16 = mul(x = x_183_cast_fp16, y = _inversed_query_y_0_to_fp16)[name = string("_inversed_query_cast_fp16")];
            tensor<int32, [4]> var_1318 = const()[name = string("op_1318"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_187_cast_fp16 = reshape(shape = var_1318, x = linear_75_cast_fp16)[name = string("x_187_cast_fp16")];
            fp16 _inversed_key_y_0_to_fp16 = const()[name = string("_inversed_key_y_0_to_fp16"), val = fp16(0x1.308p-2)];
            tensor<fp16, [1, 188, 8, 128]> _inversed_key_cast_fp16 = mul(x = x_187_cast_fp16, y = _inversed_key_y_0_to_fp16)[name = string("_inversed_key_cast_fp16")];
            tensor<int32, [4]> var_1326 = const()[name = string("op_1326"), val = tensor<int32, [4]>([1, 188, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> x_cast_fp16 = reshape(shape = var_1326, x = linear_76_cast_fp16)[name = string("x_cast_fp16")];
            tensor<int32, [4]> var_1328 = const()[name = string("op_1328"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            bool attention_scores_61_transpose_x_1 = const()[name = string("attention_scores_61_transpose_x_1"), val = bool(false)];
            bool attention_scores_61_transpose_y_1 = const()[name = string("attention_scores_61_transpose_y_1"), val = bool(true)];
            tensor<int32, [4]> transpose_94_perm_0 = const()[name = string("transpose_94_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_95_perm_0 = const()[name = string("transpose_95_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<fp16, [1, 8, 188, 128]> transpose_95 = transpose(perm = transpose_95_perm_0, x = _inversed_key_cast_fp16)[name = string("transpose_98")];
            tensor<fp16, [1, 8, 256, 128]> transpose_94 = transpose(perm = transpose_94_perm_0, x = _inversed_query_cast_fp16)[name = string("transpose_99")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_61_cast_fp16 = matmul(transpose_x = attention_scores_61_transpose_x_1, transpose_y = attention_scores_61_transpose_y_1, x = transpose_94, y = transpose_95)[name = string("attention_scores_61_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> attention_scores_cast_fp16 = add(x = attention_scores_61_cast_fp16, y = attention_mask_9_cast_fp16)[name = string("attention_scores_cast_fp16")];
            tensor<fp16, [1, 8, 256, 188]> input_231_cast_fp16 = softmax(axis = var_24, x = attention_scores_cast_fp16)[name = string("input_231_cast_fp16")];
            bool context_61_transpose_x_0 = const()[name = string("context_61_transpose_x_0"), val = bool(false)];
            bool context_61_transpose_y_0 = const()[name = string("context_61_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_cast_fp16 = transpose(perm = var_1328, x = x_cast_fp16)[name = string("transpose_97")];
            tensor<fp16, [1, 8, 256, 128]> context_61_cast_fp16 = matmul(transpose_x = context_61_transpose_x_0, transpose_y = context_61_transpose_y_0, x = input_231_cast_fp16, y = value_cast_fp16)[name = string("context_61_cast_fp16")];
            tensor<int32, [4]> var_1342 = const()[name = string("op_1342"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1347 = const()[name = string("op_1347"), val = tensor<int32, [3]>([1, 256, 1024])];
            tensor<fp16, [1, 256, 8, 128]> var_1343_cast_fp16 = transpose(perm = var_1342, x = context_61_cast_fp16)[name = string("transpose_96")];
            tensor<fp16, [1, 256, 1024]> input_233_cast_fp16 = reshape(shape = var_1347, x = var_1343_cast_fp16)[name = string("input_233_cast_fp16")];
            tensor<fp16, [1024, 1024]> module__decoder_layers_7_second_sub_layer_out_projection_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80074432))), scale = tensor<fp16, [1024, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80598784))))[name = string("module__decoder_layers_7_second_sub_layer_out_projection_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_7_second_sub_layer_out_projection_bias_to_fp16 = const()[name = string("module__decoder_layers_7_second_sub_layer_out_projection_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80664384)))];
            tensor<fp16, [1, 256, 1024]> linear_77_cast_fp16 = linear(bias = module__decoder_layers_7_second_sub_layer_out_projection_bias_to_fp16, weight = module__decoder_layers_7_second_sub_layer_out_projection_weight_to_fp16_quantized, x = input_233_cast_fp16)[name = string("linear_77_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_237_cast_fp16 = add(x = linear_77_cast_fp16, y = input_227_cast_fp16)[name = string("input_237_cast_fp16")];
            tensor<int32, [1]> input_239_axes_0 = const()[name = string("input_239_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_layers_7_layer_norm_3_weight_to_fp16 = const()[name = string("module__decoder_layers_7_layer_norm_3_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80666496)))];
            tensor<fp16, [1024]> module__decoder_layers_7_layer_norm_3_bias_to_fp16 = const()[name = string("module__decoder_layers_7_layer_norm_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80668608)))];
            tensor<fp16, [1, 256, 1024]> input_239_cast_fp16 = layer_norm(axes = input_239_axes_0, beta = module__decoder_layers_7_layer_norm_3_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_layers_7_layer_norm_3_weight_to_fp16, x = input_237_cast_fp16)[name = string("input_239_cast_fp16")];
            tensor<fp16, [4096, 1024]> module__decoder_layers_7_third_sub_layer_dense_in_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80670720))), scale = tensor<fp16, [4096, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(82767936))))[name = string("module__decoder_layers_7_third_sub_layer_dense_in_weight_to_fp16_quantized")];
            tensor<fp16, [4096]> module__decoder_layers_7_third_sub_layer_dense_in_bias_to_fp16 = const()[name = string("module__decoder_layers_7_third_sub_layer_dense_in_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(83030144)))];
            tensor<fp16, [1, 256, 4096]> linear_78_cast_fp16 = linear(bias = module__decoder_layers_7_third_sub_layer_dense_in_bias_to_fp16, weight = module__decoder_layers_7_third_sub_layer_dense_in_weight_to_fp16_quantized, x = input_239_cast_fp16)[name = string("linear_78_cast_fp16")];
            tensor<fp16, [1, 256, 4096]> input_241_cast_fp16 = relu(x = linear_78_cast_fp16)[name = string("input_241_cast_fp16")];
            tensor<fp16, [1024, 4096]> module__decoder_layers_7_third_sub_layer_dense_out_weight_to_fp16_quantized = constexpr_blockwise_shift_scale(data = tensor<int4, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(83038400))), scale = tensor<fp16, [1024, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(85135616))))[name = string("module__decoder_layers_7_third_sub_layer_dense_out_weight_to_fp16_quantized")];
            tensor<fp16, [1024]> module__decoder_layers_7_third_sub_layer_dense_out_bias_to_fp16 = const()[name = string("module__decoder_layers_7_third_sub_layer_dense_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(85397824)))];
            tensor<fp16, [1, 256, 1024]> linear_79_cast_fp16 = linear(bias = module__decoder_layers_7_third_sub_layer_dense_out_bias_to_fp16, weight = module__decoder_layers_7_third_sub_layer_dense_out_weight_to_fp16_quantized, x = input_241_cast_fp16)[name = string("linear_79_cast_fp16")];
            tensor<fp16, [1, 256, 1024]> input_cast_fp16 = add(x = linear_79_cast_fp16, y = input_237_cast_fp16)[name = string("input_cast_fp16")];
            tensor<int32, [1]> out_objects_axes_0 = const()[name = string("out_objects_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module__decoder_final_layer_norm_weight_to_fp16 = const()[name = string("module__decoder_final_layer_norm_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(85399936)))];
            tensor<fp16, [1024]> module__decoder_final_layer_norm_bias_to_fp16 = const()[name = string("module__decoder_final_layer_norm_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(85402048)))];
            tensor<fp16, [1, 256, 1024]> out_objects_cast_fp16 = layer_norm(axes = out_objects_axes_0, beta = module__decoder_final_layer_norm_bias_to_fp16, epsilon = var_26_to_fp16, gamma = module__decoder_final_layer_norm_weight_to_fp16, x = input_cast_fp16)[name = string("out_objects_cast_fp16")];
            string out_objects_cast_fp16_to_fp32_dtype_0 = const()[name = string("out_objects_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
            tensor<fp32, [1, 256, 1024]> decoder = cast(dtype = out_objects_cast_fp16_to_fp32_dtype_0, x = out_objects_cast_fp16)[name = string("cast_1")];
        } -> (decoder);
}