auto inputs = func_ty.getInputs();
  block->addArguments(inputs, SmallVector<Location>(inputs.size(), loc));
  mlir::func::CallOp call_op = rewriter.create<mlir::func::CallOp>(
      loc, func, func_ty.getResults(), block->getArguments());
  rewriter.create<mhlo::ReturnOp>(loc, call_op.getResults());
}

//===----------------------------------------------------------------------===//
// Op converters.

				d = callDeferStack
			}
			s.call(n.Call.(*ir.CallExpr), d, false, n.DeferAt)
		}
	case ir.OGO:
		n := n.(*ir.GoDeferStmt)
		s.callResult(n.Call.(*ir.CallExpr), callGo)

	case ir.OAS2DOTTYPE:
		n := n.(*ir.AssignListStmt)
		var res, resok *ssa.Value
		if n.Rhs[0].Op() == ir.ODOTTYPE2 {
			res, resok = s.dottype(n.Rhs[0].(*ir.TypeAssertExpr), true)
		} else {

  // The argument types don't match the parameter types for the
  // pcall_multi_in_out function. That's fine for a PartitionedCallOp but not
  // for a standard CallOp, so this op can't be lowered.
  // CHECK: "tf.PartitionedCall"