{
    (%stack_0, %inlet_0, %outlet_0) = "cf.stack_create" () {} : () -> cf.stack, cf.inlet, cf.outlet
    (%stack_1, %inlet_1, %outlet_1) = "cf.stack_create" () {} : () -> cf.stack, cf.inlet, cf.outlet
    (%stack_2, %inlet_2, %outlet_2) = "cf.stack_create" () {} : () -> cf.stack, cf.inlet, cf.outlet
    (%0) = "pd_op.data" () {dtype:float32,name:"_jst.0.x.0",place:Place(undefined:0),shape:[5,5],stop_gradient:[false]} : () -> tensor<5x5xf32>
    (%1) = "pd_op.numel" (%0) {stop_gradient:[false]} : (tensor<5x5xf32>) -> tensor<i64>
    (%2) = "pd_op.full" () {dtype:int64,place:Place(undefined:0),shape:[],stop_gradient:[true],value:0} : () -> tensor<i64>
    (%3) = "pd_op.greater_than" (%1, %2) {stop_gradient:[true]} : (tensor<i64>, tensor<i64>) -> tensor<b>
    (%4) = "pd_op.if" (%3) {stop_gradient:[false]} -> tensor<5x5xf32> {
        (%5) = "pd_op.tanh" (%0) {stop_gradient:[false]} : (tensor<5x5xf32>) -> tensor<5x5xf32>
        () = "cf.tuple_push" (%inlet_2, %5) {} : (cf.inlet, tensor<5x5xf32>) -> 
        () = "cf.tuple_push" (%inlet_0, %5) {} : (cf.inlet, tensor<5x5xf32>) -> 
        () = "cf.yield" (%5) {} : (tensor<5x5xf32>) -> 
    } else {
        () = "cf.yield" (%0) {} : (tensor<5x5xf32>) -> 
    }
    (%6) = "pd_op.full" () {dtype:float32,place:Place(cpu),shape:[1],stop_gradient:[true],value:1} : () -> tensor<1xf32>
    (%7) = "pd_op.full_like" (%4, %6) {dtype:float32,place:Place(undefined:0),stop_gradient:[false]} : (tensor<5x5xf32>, tensor<1xf32>) -> tensor<5x5xf32>
    (%8) = "pd_op.if" (%3) {stop_gradient:[false]} -> tensor<5x5xf32> {
        (%9) = "cf.tuple_pop" (%outlet_2) {stop_gradient:[false]} : (cf.outlet) -> tensor<5x5xf32>
        (%10) = "pd_op.tanh_grad" (%9, %7) {stop_gradient:[false]} : (tensor<5x5xf32>, tensor<5x5xf32>) -> tensor<5x5xf32>
        () = "cf.tuple_push" (%inlet_1, %9, %10) {} : (cf.inlet, tensor<5x5xf32>, tensor<5x5xf32>) -> 
        () = "cf.yield" (%10) {} : (tensor<5x5xf32>) -> 
    } else {
        () = "cf.yield" (%7) {} : (tensor<5x5xf32>) -> 
    }
    (%11) = "pd_op.full_int_array" () {dtype:int64,place:Place(cpu),stop_gradient:[true],value:[]} : () -> tensor<0xi64>
    (%12) = "pd_op.mean" (%8, %11) {keepdim:false,stop_gradient:[false]} : (tensor<5x5xf32>, tensor<0xi64>) -> tensor<f32>
    () = "builtin.shadow_output" (%12) {output_name:"output_0"} : (tensor<f32>) -> 
    (%13) = "pd_op.full" () {dtype:float32,place:Place(cpu),shape:[1],stop_gradient:[true],value:1} : () -> tensor<1xf32>
    (%14) = "pd_op.full_like" (%12, %13) {dtype:float32,place:Place(undefined:0),stop_gradient:[false]} : (tensor<f32>, tensor<1xf32>) -> tensor<f32>
    () = "builtin.shadow_output" (%14) {output_name:"grad_input_0"} : (tensor<f32>) -> 
    (%15) = "pd_op.mean_grad" (%8, %14, %11) {keepdim:false,reduce_all:false,stop_gradient:[false]} : (tensor<5x5xf32>, tensor<f32>, tensor<0xi64>) -> tensor<5x5xf32>
    (%16, %17) = "pd_op.if" (%3) {stop_gradient:[false,false]} -> tensor<5x5xf32>, tensor<5x5xf32> {
        (%18, %19) = "cf.tuple_pop" (%outlet_1) {stop_gradient:[false,false]} : (cf.outlet) -> tensor<5x5xf32>, tensor<5x5xf32>
        (%20, %21) = "pd_op.tanh_double_grad" (%18, %7, %15) {stop_gradient:[false,false]} : (tensor<5x5xf32>, tensor<5x5xf32>, tensor<5x5xf32>) -> tensor<5x5xf32>, tensor<5x5xf32>
        () = "cf.yield" (%21, %20) {} : (tensor<5x5xf32>, tensor<5x5xf32>) -> 
    } else {
        () = "cf.yield" (%15, <<NULL VALUE>>) {} : (tensor<5x5xf32>, <<NULL TYPE>>) -> 
    }
    (%22) = "pd_op.if" (%3) {stop_gradient:[false]} -> tensor<5x5xf32> {
        (%23) = "cf.tuple_pop" (%outlet_0) {stop_gradient:[false]} : (cf.outlet) -> tensor<5x5xf32>
        (%24) = "pd_op.tanh_grad" (%23, %17) {stop_gradient:[false]} : (tensor<5x5xf32>, tensor<5x5xf32>) -> tensor<5x5xf32>
        () = "cf.yield" (%24) {} : (tensor<5x5xf32>) -> 
    } else {
        () = "cf.yield" (%17) {} : (tensor<5x5xf32>) -> 
    }
}