program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-tensorflow", "2.11.0"}, {"coremltools-version", "7.1.2"}, {"mldb_token", "mldb-wzxy8wby59"}})]
{
    func main<ios15>(tensor<fp32, [1, 10]> x_sen, tensor<fp32, [1, 50]> x_sub) {
            tensor<int32, []> model_4_lstm_8_PartitionedCall_time = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_time"), val = tensor<int32, []>(0)];
            tensor<int32, []> model_4_lstm_8_PartitionedCall_TensorArrayV2_1_num_elements = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_TensorArrayV2_1_num_elements"), val = tensor<int32, []>(1)];
            tensor<int32, [3]> model_4_lstm_8_PartitionedCall_transpose_perm = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_transpose_perm"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, []> model_4_lstm_9_PartitionedCall_time = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_time"), val = tensor<int32, []>(0)];
            tensor<int32, []> model_4_lstm_9_PartitionedCall_TensorArrayV2_1_num_elements = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_TensorArrayV2_1_num_elements"), val = tensor<int32, []>(1)];
            tensor<int32, [3]> model_4_lstm_9_PartitionedCall_transpose_perm = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_transpose_perm"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, []> model_4_concatenate_4_concat_axis = const()[name = tensor<string, []>("model_4_concatenate_4_concat_axis"), val = tensor<int32, []>(1)];
            tensor<fp32, [100, 400]> Func_model_4_lstm_8_PartitionedCall_input__14 = const()[name = tensor<string, []>("Func_model_4_lstm_8_PartitionedCall_input__14"), val = tensor<fp32, [100, 400]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
            tensor<fp32, [100, 400]> Func_model_4_lstm_8_PartitionedCall_input__15 = const()[name = tensor<string, []>("Func_model_4_lstm_8_PartitionedCall_input__15"), val = tensor<fp32, [100, 400]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(160128)))];
            tensor<fp32, [400]> Func_model_4_lstm_8_PartitionedCall_input__16 = const()[name = tensor<string, []>("Func_model_4_lstm_8_PartitionedCall_input__16"), val = tensor<fp32, [400]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(320192)))];
            tensor<fp32, [10, 64]> Func_model_4_lstm_9_PartitionedCall_input__3 = const()[name = tensor<string, []>("Func_model_4_lstm_9_PartitionedCall_input__3"), val = tensor<fp32, [10, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(321856)))];
            tensor<fp32, [16, 64]> Func_model_4_lstm_9_PartitionedCall_input__4 = const()[name = tensor<string, []>("Func_model_4_lstm_9_PartitionedCall_input__4"), val = tensor<fp32, [16, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(324480)))];
            tensor<fp32, [64]> Func_model_4_lstm_9_PartitionedCall_input__5 = const()[name = tensor<string, []>("Func_model_4_lstm_9_PartitionedCall_input__5"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(328640)))];
            tensor<string, []> model_4_embedding_8_Cast_dtype_0 = const()[name = tensor<string, []>("model_4_embedding_8_Cast_dtype_0"), val = tensor<string, []>("int32")];
            tensor<string, []> model_4_embedding_9_Cast_dtype_0 = const()[name = tensor<string, []>("model_4_embedding_9_Cast_dtype_0"), val = tensor<string, []>("int32")];
            tensor<string, []> model_4_lstm_8_PartitionedCall_TensorArrayV2_1_dtype_0 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_TensorArrayV2_1_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<bool, []> model_4_lstm_8_PartitionedCall_TensorArrayV2_1_dynamic_length_0 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_TensorArrayV2_1_dynamic_length_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> model_4_lstm_8_PartitionedCall_TensorArrayV2_1_elem_shape0_0 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_TensorArrayV2_1_elem_shape0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> model_4_lstm_8_PartitionedCall_TensorArrayV2_1_elem_shape1_0 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_TensorArrayV2_1_elem_shape1_0"), val = tensor<int32, []>(100)];
            list<tensor<fp32, [1, 100]>, 1> model_4_lstm_8_PartitionedCall_TensorArrayV2_1 = make_list(dtype = model_4_lstm_8_PartitionedCall_TensorArrayV2_1_dtype_0, dynamic_length = model_4_lstm_8_PartitionedCall_TensorArrayV2_1_dynamic_length_0, elem_shape = (model_4_lstm_8_PartitionedCall_TensorArrayV2_1_elem_shape0_0, model_4_lstm_8_PartitionedCall_TensorArrayV2_1_elem_shape1_0), init_length = model_4_lstm_8_PartitionedCall_TensorArrayV2_1_num_elements)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_TensorArrayV2_1")];
            tensor<string, []> model_4_lstm_9_PartitionedCall_TensorArrayV2_1_dtype_0 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_TensorArrayV2_1_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<bool, []> model_4_lstm_9_PartitionedCall_TensorArrayV2_1_dynamic_length_0 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_TensorArrayV2_1_dynamic_length_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> model_4_lstm_9_PartitionedCall_TensorArrayV2_1_elem_shape0_0 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_TensorArrayV2_1_elem_shape0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> model_4_lstm_9_PartitionedCall_TensorArrayV2_1_elem_shape1_0 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_TensorArrayV2_1_elem_shape1_0"), val = tensor<int32, []>(16)];
            list<tensor<fp32, [1, 16]>, 1> model_4_lstm_9_PartitionedCall_TensorArrayV2_1 = make_list(dtype = model_4_lstm_9_PartitionedCall_TensorArrayV2_1_dtype_0, dynamic_length = model_4_lstm_9_PartitionedCall_TensorArrayV2_1_dynamic_length_0, elem_shape = (model_4_lstm_9_PartitionedCall_TensorArrayV2_1_elem_shape0_0, model_4_lstm_9_PartitionedCall_TensorArrayV2_1_elem_shape1_0), init_length = model_4_lstm_9_PartitionedCall_TensorArrayV2_1_num_elements)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_TensorArrayV2_1")];
            tensor<int32, []> model_4_embedding_8_embedding_lookup_axis_0 = const()[name = tensor<string, []>("model_4_embedding_8_embedding_lookup_axis_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [10000, 100]> model_4_embedding_8_embedding_lookup_56841557_to_fp16 = const()[name = tensor<string, []>("model_4_embedding_8_embedding_lookup_56841557_to_fp16"), val = tensor<fp16, [10000, 100]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(328960)))];
            tensor<int32, [1, 50]> cast_5 = cast(dtype = model_4_embedding_8_Cast_dtype_0, x = x_sub)[name = tensor<string, []>("cast_5")];
            tensor<fp16, [1, 50, 100]> model_4_embedding_8_embedding_lookup_cast_fp16 = gather(axis = model_4_embedding_8_embedding_lookup_axis_0, indices = cast_5, x = model_4_embedding_8_embedding_lookup_56841557_to_fp16)[name = tensor<string, []>("model_4_embedding_8_embedding_lookup_cast_fp16")];
            tensor<string, []> model_4_embedding_8_embedding_lookup_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("model_4_embedding_8_embedding_lookup_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<int32, []> model_4_embedding_9_embedding_lookup_axis_0 = const()[name = tensor<string, []>("model_4_embedding_9_embedding_lookup_axis_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [1000, 10]> model_4_embedding_9_embedding_lookup_56841551_to_fp16 = const()[name = tensor<string, []>("model_4_embedding_9_embedding_lookup_56841551_to_fp16"), val = tensor<fp16, [1000, 10]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2329024)))];
            tensor<int32, [1, 10]> cast_4 = cast(dtype = model_4_embedding_9_Cast_dtype_0, x = x_sen)[name = tensor<string, []>("cast_4")];
            tensor<fp16, [1, 10, 10]> model_4_embedding_9_embedding_lookup_cast_fp16 = gather(axis = model_4_embedding_9_embedding_lookup_axis_0, indices = cast_4, x = model_4_embedding_9_embedding_lookup_56841551_to_fp16)[name = tensor<string, []>("model_4_embedding_9_embedding_lookup_cast_fp16")];
            tensor<string, []> model_4_embedding_9_embedding_lookup_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("model_4_embedding_9_embedding_lookup_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<int32, []> slice_by_index_0 = const()[name = tensor<string, []>("slice_by_index_0"), val = tensor<int32, []>(50)];
            tensor<string, []> tf_make_list_0_dtype_0 = const()[name = tensor<string, []>("tf_make_list_0_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<bool, []> tf_make_list_0_dynamic_length_0 = const()[name = tensor<string, []>("tf_make_list_0_dynamic_length_0"), val = tensor<bool, []>(true)];
            tensor<int32, []> tf_make_list_0_elem_shape0_0 = const()[name = tensor<string, []>("tf_make_list_0_elem_shape0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> tf_make_list_0_elem_shape1_0 = const()[name = tensor<string, []>("tf_make_list_0_elem_shape1_0"), val = tensor<int32, []>(100)];
            list<tensor<fp32, [1, 100]>, 50> tf_make_list_0 = make_list(dtype = tf_make_list_0_dtype_0, dynamic_length = tf_make_list_0_dynamic_length_0, elem_shape = (tf_make_list_0_elem_shape0_0, tf_make_list_0_elem_shape1_0), init_length = slice_by_index_0)[name = tensor<string, []>("tf_make_list_0")];
            tensor<int32, [50]> range_1d_0 = const()[name = tensor<string, []>("range_1d_0"), val = tensor<int32, [50]>([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49])];
            tensor<fp32, [1, 50, 100]> cast_3 = cast(dtype = model_4_embedding_8_embedding_lookup_cast_fp16_to_fp32_dtype_0, x = model_4_embedding_8_embedding_lookup_cast_fp16)[name = tensor<string, []>("cast_3")];
            tensor<fp32, [50, 1, 100]> transpose_2 = transpose(perm = model_4_lstm_8_PartitionedCall_transpose_perm, x = cast_3)[name = tensor<string, []>("transpose_2")];
            list<tensor<fp32, [1, 100]>, 50> model_4_lstm_8_PartitionedCall_TensorArrayUnstack_TensorListFromTensor = list_scatter(indices = range_1d_0, ls = tf_make_list_0, value = transpose_2)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_TensorArrayUnstack_TensorListFromTensor")];
            tensor<int32, []> slice_by_index_1 = const()[name = tensor<string, []>("slice_by_index_1"), val = tensor<int32, []>(10)];
            tensor<string, []> tf_make_list_1_dtype_0 = const()[name = tensor<string, []>("tf_make_list_1_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<bool, []> tf_make_list_1_dynamic_length_0 = const()[name = tensor<string, []>("tf_make_list_1_dynamic_length_0"), val = tensor<bool, []>(true)];
            tensor<int32, []> tf_make_list_1_elem_shape0_0 = const()[name = tensor<string, []>("tf_make_list_1_elem_shape0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> tf_make_list_1_elem_shape1_0 = const()[name = tensor<string, []>("tf_make_list_1_elem_shape1_0"), val = tensor<int32, []>(10)];
            list<tensor<fp32, [1, 10]>, 10> tf_make_list_1 = make_list(dtype = tf_make_list_1_dtype_0, dynamic_length = tf_make_list_1_dynamic_length_0, elem_shape = (tf_make_list_1_elem_shape0_0, tf_make_list_1_elem_shape1_0), init_length = slice_by_index_1)[name = tensor<string, []>("tf_make_list_1")];
            tensor<int32, [10]> range_1d_1 = const()[name = tensor<string, []>("range_1d_1"), val = tensor<int32, [10]>([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])];
            tensor<fp32, [1, 10, 10]> cast_2 = cast(dtype = model_4_embedding_9_embedding_lookup_cast_fp16_to_fp32_dtype_0, x = model_4_embedding_9_embedding_lookup_cast_fp16)[name = tensor<string, []>("cast_2")];
            tensor<fp32, [10, 1, 10]> transpose_1 = transpose(perm = model_4_lstm_9_PartitionedCall_transpose_perm, x = cast_2)[name = tensor<string, []>("transpose_1")];
            list<tensor<fp32, [1, 10]>, 10> model_4_lstm_9_PartitionedCall_TensorArrayUnstack_TensorListFromTensor = list_scatter(indices = range_1d_1, ls = tf_make_list_1, value = transpose_1)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_TensorArrayUnstack_TensorListFromTensor")];
            tensor<int32, []> model_4_lstm_8_PartitionedCall_strided_slice = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_strided_slice"), val = tensor<int32, []>(50)];
            tensor<int32, []> model_4_lstm_9_PartitionedCall_strided_slice = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_strided_slice"), val = tensor<int32, []>(10)];
            tensor<fp32, [1, 100]> model_4_lstm_8_zeros = const()[name = tensor<string, []>("model_4_lstm_8_zeros"), val = tensor<fp32, [1, 100]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2349120)))];
            tensor<fp32, [1, 16]> model_4_lstm_9_zeros = const()[name = tensor<string, []>("model_4_lstm_9_zeros"), val = tensor<fp32, [1, 16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2349632)))];
            tensor<fp32, [1, 16]> model_4_lstm_9_zeros_1 = const()[name = tensor<string, []>("model_4_lstm_9_zeros_1"), val = tensor<fp32, [1, 16]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2349760)))];
            tensor<int32, []> model_4_lstm_8_PartitionedCall_while_0, list<tensor<fp32, [1, 100]>, 1> model_4_lstm_8_PartitionedCall_while_1, tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_2, tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_3 = while_loop(loop_vars = (model_4_lstm_8_PartitionedCall_time, model_4_lstm_8_PartitionedCall_TensorArrayV2_1, model_4_lstm_8_zeros, model_4_lstm_8_zeros))[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_renamed")]
                (tensor<int32, []> model_4_lstm_8_PartitionedCall_time_x0_1_1_0, list<tensor<fp32, [1, 100]>, 1> model_4_lstm_8_PartitionedCall_TensorArrayV2_1_x0, tensor<fp32, [1, 100]> model_4_lstm_8_zeros_x0_1_1_0, tensor<fp32, [1, 100]> model_4_lstm_8_zeros_1_x0_1_1_0) {
                    tensor<bool, []> model_4_lstm_8_PartitionedCall_while_while_cond_56842055_while_Less = less(x = model_4_lstm_8_PartitionedCall_time_x0_1_1_0, y = model_4_lstm_8_PartitionedCall_strided_slice)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_cond_56842055_while_Less")];
                } -> (model_4_lstm_8_PartitionedCall_while_while_cond_56842055_while_Less)
                (tensor<int32, []> model_4_lstm_8_PartitionedCall_time_x0_1_1_1, list<tensor<fp32, [1, 100]>, 1> model_4_lstm_8_PartitionedCall_TensorArrayV2_1_x0_1, tensor<fp32, [1, 100]> model_4_lstm_8_zeros_x0_1_1_1, tensor<fp32, [1, 100]> model_4_lstm_8_zeros_1_x0_1_1_1) {
                    tensor<int32, []> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_split_dim = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_split_dim"), val = tensor<int32, []>(1)];
                    tensor<int32, []> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_TensorArrayV2Write_TensorListSetItem_index = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_TensorArrayV2Write_TensorListSetItem_index"), val = tensor<int32, []>(0)];
                    tensor<int32, []> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_add_2_y = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_add_2_y"), val = tensor<int32, []>(1)];
                    tensor<int32, []> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_add_2 = add(x = model_4_lstm_8_PartitionedCall_time_x0_1_1_1, y = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_add_2_y)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_add_2")];
                    tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_TensorArrayV2Read_TensorListGetItem = list_read(index = model_4_lstm_8_PartitionedCall_time_x0_1_1_1, ls = model_4_lstm_8_PartitionedCall_TensorArrayUnstack_TensorListFromTensor)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_TensorArrayV2Read_TensorListGetItem")];
                    tensor<bool, []> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_1_transpose_x_1 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_1_transpose_x_1"), val = tensor<bool, []>(false)];
                    tensor<bool, []> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_1_transpose_y_1 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_1_transpose_y_1"), val = tensor<bool, []>(false)];
                    tensor<fp32, [1, 400]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_1 = matmul(transpose_x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_1_transpose_x_1, transpose_y = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_1_transpose_y_1, x = model_4_lstm_8_zeros_x0_1_1_1, y = Func_model_4_lstm_8_PartitionedCall_input__15)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_1")];
                    tensor<bool, []> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_transpose_x_1 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_transpose_x_1"), val = tensor<bool, []>(false)];
                    tensor<bool, []> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_transpose_y_1 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_transpose_y_1"), val = tensor<bool, []>(false)];
                    tensor<fp32, [1, 400]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul = matmul(transpose_x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_transpose_x_1, transpose_y = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_transpose_y_1, x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_TensorArrayV2Read_TensorListGetItem, y = Func_model_4_lstm_8_PartitionedCall_input__14)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul")];
                    tensor<fp32, [1, 400]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_add = add(x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul, y = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_MatMul_1)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_add")];
                    tensor<fp32, [1, 400]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_BiasAdd = add(x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_add, y = Func_model_4_lstm_8_PartitionedCall_input__16)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_BiasAdd")];
                    tensor<int32, []> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_num_splits_1 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_num_splits_1"), val = tensor<int32, []>(4)];
                    tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_0, tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_1, tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_2, tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_3 = split(axis = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_split_dim, num_splits = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_num_splits_1, x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_BiasAdd)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split")];
                    tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Sigmoid = sigmoid(x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_0)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Sigmoid")];
                    tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Sigmoid_1 = sigmoid(x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_1)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Sigmoid_1")];
                    tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Tanh = tanh(x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_2)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Tanh")];
                    tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Sigmoid_2 = sigmoid(x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_split_3)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Sigmoid_2")];
                    tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_mul = mul(x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Sigmoid_1, y = model_4_lstm_8_zeros_1_x0_1_1_1)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_mul")];
                    tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_mul_1 = mul(x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Sigmoid, y = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Tanh)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_mul_1")];
                    tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_add_1 = add(x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_mul, y = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_mul_1)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_add_1")];
                    tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Tanh_1 = tanh(x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_add_1)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Tanh_1")];
                    tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_mul_2 = mul(x = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Sigmoid_2, y = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_Tanh_1)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_mul_2")];
                    list<tensor<fp32, [1, 100]>, 1> model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_TensorArrayV2Write_TensorListSetItem = list_write(index = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_TensorArrayV2Write_TensorListSetItem_index, ls = model_4_lstm_8_PartitionedCall_TensorArrayV2_1_x0_1, value = model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_mul_2)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_TensorArrayV2Write_TensorListSetItem")];
                } -> (model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_add_2, model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_TensorArrayV2Write_TensorListSetItem, model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_mul_2, model_4_lstm_8_PartitionedCall_while_while_body_56842056_while_add_1);
            tensor<int32, []> model_4_lstm_9_PartitionedCall_while_0, list<tensor<fp32, [1, 16]>, 1> model_4_lstm_9_PartitionedCall_while_1, tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_2, tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_3 = while_loop(loop_vars = (model_4_lstm_9_PartitionedCall_time, model_4_lstm_9_PartitionedCall_TensorArrayV2_1, model_4_lstm_9_zeros, model_4_lstm_9_zeros_1))[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_renamed")]
                (tensor<int32, []> model_4_lstm_9_PartitionedCall_time_x0_1_1_0, list<tensor<fp32, [1, 16]>, 1> model_4_lstm_9_PartitionedCall_TensorArrayV2_1_x0, tensor<fp32, [1, 16]> model_4_lstm_9_zeros_x0_1_1_0, tensor<fp32, [1, 16]> model_4_lstm_9_zeros_1_x0_1_1_0) {
                    tensor<bool, []> model_4_lstm_9_PartitionedCall_while_while_cond_56841630_while_Less = less(x = model_4_lstm_9_PartitionedCall_time_x0_1_1_0, y = model_4_lstm_9_PartitionedCall_strided_slice)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_cond_56841630_while_Less")];
                } -> (model_4_lstm_9_PartitionedCall_while_while_cond_56841630_while_Less)
                (tensor<int32, []> model_4_lstm_9_PartitionedCall_time_x0_1_1_1, list<tensor<fp32, [1, 16]>, 1> model_4_lstm_9_PartitionedCall_TensorArrayV2_1_x0_1, tensor<fp32, [1, 16]> model_4_lstm_9_zeros_x0_1_1_1, tensor<fp32, [1, 16]> model_4_lstm_9_zeros_1_x0_1_1_1) {
                    tensor<int32, []> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_split_dim = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_split_dim"), val = tensor<int32, []>(1)];
                    tensor<int32, []> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_TensorArrayV2Write_TensorListSetItem_index = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_TensorArrayV2Write_TensorListSetItem_index"), val = tensor<int32, []>(0)];
                    tensor<int32, []> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_add_2_y = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_add_2_y"), val = tensor<int32, []>(1)];
                    tensor<int32, []> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_add_2 = add(x = model_4_lstm_9_PartitionedCall_time_x0_1_1_1, y = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_add_2_y)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_add_2")];
                    tensor<fp32, [1, 10]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_TensorArrayV2Read_TensorListGetItem = list_read(index = model_4_lstm_9_PartitionedCall_time_x0_1_1_1, ls = model_4_lstm_9_PartitionedCall_TensorArrayUnstack_TensorListFromTensor)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_TensorArrayV2Read_TensorListGetItem")];
                    tensor<bool, []> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_1_transpose_x_1 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_1_transpose_x_1"), val = tensor<bool, []>(false)];
                    tensor<bool, []> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_1_transpose_y_1 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_1_transpose_y_1"), val = tensor<bool, []>(false)];
                    tensor<fp32, [1, 64]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_1 = matmul(transpose_x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_1_transpose_x_1, transpose_y = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_1_transpose_y_1, x = model_4_lstm_9_zeros_x0_1_1_1, y = Func_model_4_lstm_9_PartitionedCall_input__4)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_1")];
                    tensor<bool, []> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_transpose_x_1 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_transpose_x_1"), val = tensor<bool, []>(false)];
                    tensor<bool, []> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_transpose_y_1 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_transpose_y_1"), val = tensor<bool, []>(false)];
                    tensor<fp32, [1, 64]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul = matmul(transpose_x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_transpose_x_1, transpose_y = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_transpose_y_1, x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_TensorArrayV2Read_TensorListGetItem, y = Func_model_4_lstm_9_PartitionedCall_input__3)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul")];
                    tensor<fp32, [1, 64]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_add = add(x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul, y = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_MatMul_1)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_add")];
                    tensor<fp32, [1, 64]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_BiasAdd = add(x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_add, y = Func_model_4_lstm_9_PartitionedCall_input__5)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_BiasAdd")];
                    tensor<int32, []> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_num_splits_1 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_num_splits_1"), val = tensor<int32, []>(4)];
                    tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_0, tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_1, tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_2, tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_3 = split(axis = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_split_dim, num_splits = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_num_splits_1, x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_BiasAdd)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split")];
                    tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Sigmoid = sigmoid(x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_0)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Sigmoid")];
                    tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Sigmoid_1 = sigmoid(x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_1)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Sigmoid_1")];
                    tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Tanh = tanh(x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_2)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Tanh")];
                    tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Sigmoid_2 = sigmoid(x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_split_3)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Sigmoid_2")];
                    tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_mul = mul(x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Sigmoid_1, y = model_4_lstm_9_zeros_1_x0_1_1_1)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_mul")];
                    tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_mul_1 = mul(x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Sigmoid, y = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Tanh)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_mul_1")];
                    tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_add_1 = add(x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_mul, y = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_mul_1)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_add_1")];
                    tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Tanh_1 = tanh(x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_add_1)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Tanh_1")];
                    tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_mul_2 = mul(x = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Sigmoid_2, y = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_Tanh_1)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_mul_2")];
                    list<tensor<fp32, [1, 16]>, 1> model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_TensorArrayV2Write_TensorListSetItem = list_write(index = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_TensorArrayV2Write_TensorListSetItem_index, ls = model_4_lstm_9_PartitionedCall_TensorArrayV2_1_x0_1, value = model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_mul_2)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_TensorArrayV2Write_TensorListSetItem")];
                } -> (model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_add_2, model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_TensorArrayV2Write_TensorListSetItem, model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_mul_2, model_4_lstm_9_PartitionedCall_while_while_body_56841631_while_add_1);
            tensor<int32, [1]> range_1d_2 = const()[name = tensor<string, []>("range_1d_2"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, 1, 100]> model_4_lstm_8_PartitionedCall_TensorArrayV2Stack_TensorListStack = list_gather(indices = range_1d_2, ls = model_4_lstm_8_PartitionedCall_while_1)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_TensorArrayV2Stack_TensorListStack")];
            tensor<int32, [1]> range_1d_3 = const()[name = tensor<string, []>("range_1d_3"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, 1, 16]> model_4_lstm_9_PartitionedCall_TensorArrayV2Stack_TensorListStack = list_gather(indices = range_1d_3, ls = model_4_lstm_9_PartitionedCall_while_1)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_TensorArrayV2Stack_TensorListStack")];
            tensor<int32, [3]> model_4_lstm_8_PartitionedCall_strided_slice_2_begin_0 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_strided_slice_2_begin_0"), val = tensor<int32, [3]>([-1, 0, 0])];
            tensor<int32, [3]> model_4_lstm_8_PartitionedCall_strided_slice_2_end_0 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_strided_slice_2_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> model_4_lstm_8_PartitionedCall_strided_slice_2_stride_0 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_strided_slice_2_stride_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<bool, [3]> model_4_lstm_8_PartitionedCall_strided_slice_2_begin_mask_0 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_strided_slice_2_begin_mask_0"), val = tensor<bool, [3]>([false, true, true])];
            tensor<bool, [3]> model_4_lstm_8_PartitionedCall_strided_slice_2_end_mask_0 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_strided_slice_2_end_mask_0"), val = tensor<bool, [3]>([false, true, true])];
            tensor<bool, [3]> model_4_lstm_8_PartitionedCall_strided_slice_2_squeeze_mask_0 = const()[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_strided_slice_2_squeeze_mask_0"), val = tensor<bool, [3]>([true, false, false])];
            tensor<fp32, [1, 100]> model_4_lstm_8_PartitionedCall_strided_slice_2 = slice_by_index(begin = model_4_lstm_8_PartitionedCall_strided_slice_2_begin_0, begin_mask = model_4_lstm_8_PartitionedCall_strided_slice_2_begin_mask_0, end = model_4_lstm_8_PartitionedCall_strided_slice_2_end_0, end_mask = model_4_lstm_8_PartitionedCall_strided_slice_2_end_mask_0, squeeze_mask = model_4_lstm_8_PartitionedCall_strided_slice_2_squeeze_mask_0, stride = model_4_lstm_8_PartitionedCall_strided_slice_2_stride_0, x = model_4_lstm_8_PartitionedCall_TensorArrayV2Stack_TensorListStack)[name = tensor<string, []>("model_4_lstm_8_PartitionedCall_strided_slice_2")];
            tensor<int32, [3]> model_4_lstm_9_PartitionedCall_strided_slice_2_begin_0 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_strided_slice_2_begin_0"), val = tensor<int32, [3]>([-1, 0, 0])];
            tensor<int32, [3]> model_4_lstm_9_PartitionedCall_strided_slice_2_end_0 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_strided_slice_2_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> model_4_lstm_9_PartitionedCall_strided_slice_2_stride_0 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_strided_slice_2_stride_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<bool, [3]> model_4_lstm_9_PartitionedCall_strided_slice_2_begin_mask_0 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_strided_slice_2_begin_mask_0"), val = tensor<bool, [3]>([false, true, true])];
            tensor<bool, [3]> model_4_lstm_9_PartitionedCall_strided_slice_2_end_mask_0 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_strided_slice_2_end_mask_0"), val = tensor<bool, [3]>([false, true, true])];
            tensor<bool, [3]> model_4_lstm_9_PartitionedCall_strided_slice_2_squeeze_mask_0 = const()[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_strided_slice_2_squeeze_mask_0"), val = tensor<bool, [3]>([true, false, false])];
            tensor<fp32, [1, 16]> model_4_lstm_9_PartitionedCall_strided_slice_2 = slice_by_index(begin = model_4_lstm_9_PartitionedCall_strided_slice_2_begin_0, begin_mask = model_4_lstm_9_PartitionedCall_strided_slice_2_begin_mask_0, end = model_4_lstm_9_PartitionedCall_strided_slice_2_end_0, end_mask = model_4_lstm_9_PartitionedCall_strided_slice_2_end_mask_0, squeeze_mask = model_4_lstm_9_PartitionedCall_strided_slice_2_squeeze_mask_0, stride = model_4_lstm_9_PartitionedCall_strided_slice_2_stride_0, x = model_4_lstm_9_PartitionedCall_TensorArrayV2Stack_TensorListStack)[name = tensor<string, []>("model_4_lstm_9_PartitionedCall_strided_slice_2")];
            tensor<bool, []> model_4_concatenate_4_concat_interleave_0 = const()[name = tensor<string, []>("model_4_concatenate_4_concat_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp32, [1, 116]> model_4_concatenate_4_concat = concat(axis = model_4_concatenate_4_concat_axis, interleave = model_4_concatenate_4_concat_interleave_0, values = (model_4_lstm_8_PartitionedCall_strided_slice_2, model_4_lstm_9_PartitionedCall_strided_slice_2))[name = tensor<string, []>("model_4_concatenate_4_concat")];
            tensor<string, []> model_4_concatenate_4_concat_to_fp16_dtype_0 = const()[name = tensor<string, []>("model_4_concatenate_4_concat_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, [7, 116]> transpose_0_to_fp16 = const()[name = tensor<string, []>("transpose_0_to_fp16"), val = tensor<fp16, [7, 116]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2349888)))];
            tensor<fp16, [7]> model_4_dense_4_BiasAdd_bias_0_to_fp16 = const()[name = tensor<string, []>("model_4_dense_4_BiasAdd_bias_0_to_fp16"), val = tensor<fp16, [7]>([-0x1.644p+1, -0x1.b84p-2, 0x1.4e8p+1, -0x1.e8p-2, -0x1.b6cp-1, -0x1.d1cp+0, -0x1.488p+1])];
            tensor<fp16, [1, 116]> cast_1 = cast(dtype = model_4_concatenate_4_concat_to_fp16_dtype_0, x = model_4_concatenate_4_concat)[name = tensor<string, []>("cast_1")];
            tensor<fp16, [1, 7]> model_4_dense_4_BiasAdd_cast_fp16 = linear(bias = model_4_dense_4_BiasAdd_bias_0_to_fp16, weight = transpose_0_to_fp16, x = cast_1)[name = tensor<string, []>("model_4_dense_4_BiasAdd_cast_fp16")];
            tensor<string, []> model_4_dense_4_BiasAdd_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("model_4_dense_4_BiasAdd_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<int32, []> model_4_dense_4_Softmax_axis_0 = const()[name = tensor<string, []>("model_4_dense_4_Softmax_axis_0"), val = tensor<int32, []>(-1)];
            tensor<fp32, [1, 7]> cast_0 = cast(dtype = model_4_dense_4_BiasAdd_cast_fp16_to_fp32_dtype_0, x = model_4_dense_4_BiasAdd_cast_fp16)[name = tensor<string, []>("cast_0")];
            tensor<fp32, [1, 7]> Identity = softmax(axis = model_4_dense_4_Softmax_axis_0, x = cast_0)[name = tensor<string, []>("model_4_dense_4_Softmax")];
        } -> (Identity);
}