{"Tperm", DT_INT32},
                                  }}},
                                {{"c", "t0:y:0"}});

  AttrValue true_attribute;
  true_attribute.set_b(true);
  (*called_func.mutable_attr())[kXlaMustCompileAttr] = true_attribute;
  *library.add_function() = called_func;
  TF_ASSERT_OK(root.graph()->AddFunctionLibrary(library));

  std::unique_ptr<FunctionLibraryDefinition> lib_def_;
  std::unique_ptr<ProcessFunctionLibraryRuntime> pflr_;

  std::unique_ptr<OpKernel> kernel_;
};

AttrValue BoolAttr(bool b) {
  AttrValue v;
  v.set_b(b);
  return v;
}

TEST_F(XlaKernelCreatorTest, OneFloatOneResourceArgument) {
  FunctionDef fdef = XTimesY();
  (*fdef.mutable_attr())["_XlaMustCompile"] = BoolAttr(true);
  Init({fdef});

// Call the returned function to disable logging.
func (t *testLogger) SetLogTB(tb testing.TB) func() {
	return t.setTB(tb, logMessage)
}

// SetErrorTB will set the logger to output to tb.Error.
// Call the returned function to disable logging.
func (t *testLogger) SetErrorTB(tb testing.TB) func() {
	return t.setTB(tb, errorMessage)
}

// SetFatalTB will set the logger to output to tb.Panic.

            (*node_def.mutable_attr())["shared_name"].set_s(node_def.name());
          } else {
            // Use the concat of function name and node name for such ops in a
            // function as the shared_name. "@" is used as the separator because
            // it is not allowed in the function name or the node name.
            (*node_def.mutable_attr())["shared_name"].set_s(
                absl::StrCat(node_def.name(), "@", func_name));

  // Return if the function contains only non-side-effecting ops or TensorArray
  // ops.
  bool HasAtMostTensorArrayEffect(mlir::func::FuncOp func_op) const {
    return set_.count(func_op) > 0;
  }

 private:
  llvm::DenseSet<mlir::func::FuncOp> set_;
};

}  // namespace tfrt_compiler
}  // namespace tensorflow

TensorArraySideEffectAnalysis::TensorArraySideEffectAnalysis(
    mlir::ModuleOp module) {
  for (auto func_op : module.getOps<mlir::func::FuncOp>()) {
    if (FunctionContainsOnlyNoSideEffectOpOrTensorArrayOp(func_op)) {
      set_.insert(func_op);
    }
  }
}

}  // namespace tfrt_compiler

router_b = APIRouter(route_class=APIRouteB)
router_c = APIRouter(route_class=APIRouteC)


@router_a.get("/")
def get_a():
    return {"msg": "A"}


@router_b.get("/")
def get_b():
    return {"msg": "B"}


@router_c.get("/")
def get_c():
    return {"msg": "C"}


router_b.include_router(router=router_c, prefix="/c")
router_a.include_router(router=router_b, prefix="/b")

#else
#define _LDBEX	MOVD
#define _LWBEX	MOVW
#define _LHBEX	MOVH
#endif

#ifdef GOPPC64_power9
#define SETB_CR0(rout) SETB CR0, rout
#define SETB_CR1(rout) SETB CR1, rout
#define SETB_INIT()
#define SETB_CR0_NE(rout) SETB_CR0(rout)
#else
// A helper macro to emulate SETB on P8. This assumes
// -1 is in R20, and 1 is in R21. crxlt and crxeq must
// also be the same CR field.
#define _SETB(crxlt, crxeq, rout) \

Java Modules are a feature of Java itself, available since Java 9, that allows for better encapsulation.

In Gradle, each _source set_ containing Java sources can be turned into a module by adding a `module-info.java` file.
Typically, in a project with Java Modules like this one, the _main_ source set of a subproject represents a module.

```
src
└── main

def get_a_b():
    return "Hello A B"


@router_a_b_override.get("/override", response_class=HTMLResponse)
def get_a_b_path_override():
    return "Hello A B"


@router_b_override.get("/")
def get_b():
    return "Hello B"


@router_b_override.get("/override", response_class=HTMLResponse)
def get_b_path_override():
    return "Hello B"


@router_b_a.get("/")
def get_b_a():
    return "Hello B A"