Is this what you're looking for ?
```
@I.ir_module
class InputModule:
@R.function
def foo(x: R.Tensor((3, 4), "float32"), y: R.Tensor((3, 4), "float32")):
z = R.add(x, y)
return z
lib = tvm.relax.build(InputModule, target="llvm")
print(lib.mod.imported_modules[0].get_source())
```
You can also inspect C code by lowering to C
```
lib = tvm.relax.build(InputModule, target="c")
print(lib.mod.imported_modules[0].get_source())
```
Here, you have to lower Relax IR before generating LLVM, through
`tvm.relax.build` that gives a `VMExecutable` of which you retrieve the module.
<br/>
It's usually simpler to get llvm code from TIR (that you can get from lowering
Relax to TIR, for example with `tvm.relax.transform.LegalizeOps`)
```
@I.ir_module
class TirModule:
@T.prim_func
def add(x: T.Buffer((T.int64(3), T.int64(4)), "float32"), y:
T.Buffer((T.int64(3), T.int64(4)), "float32"), T_add: T.Buffer((T.int64(3),
T.int64(4)), "float32")):
T.func_attr({"tir.noalias": T.bool(True)})
# with T.block("root"):
for ax0, ax1 in T.grid(T.int64(3), T.int64(4)):
with T.block("T_add"):
v_ax0, v_ax1 = T.axis.remap("SS", [ax0, ax1])
T.reads(x[v_ax0, v_ax1], y[v_ax0, v_ax1])
T.writes(T_add[v_ax0, v_ax1])
T_add[v_ax0, v_ax1] = x[v_ax0, v_ax1] + y[v_ax0, v_ax1]
print(tvm.build(TirModule, target="c").get_source()) # or target="llvm" of
course
```
---
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Topic](https://discuss.tvm.apache.org/t/tvm0-20-0-relax-how-to-codegen-llvm-ir-with-relax/18409/3)
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