```
A = tvm.placeholder((64, 32), dtype=dtype, name="A")
C1 = tvm.compute((64, 32), lambda i, j: 7*A[i][j], name="C1")
C2 = tvm.compute((64, 64), lambda i, j: 5*A[i][j%32], name="C2")
s=create_schedule([C1.op,C2.op])
```

C1 and C2 are not a pair of consumer and producer, but obviousily, they have the same axis[0] derived from A.axis[0]. the fllowing IR is expected, how to generate the following IR ?

```
produce C2{
for(i0,0,64){
produce C1{
for(i1,0,32){
C1(i0,i1)=7*A(i0,i1)
}
}
for(i2,0,32){
C2(i0,i2)=5*A(i0,i2)
}
}
}
```

and we expected the interface in python to be

```
s[C1].compute_at(s[C2],s[C2].op.axis[0])
```

what key difficulties are approaching to us