AbstractContext* ctx) {
  auto CallFn = [fn_name, fn, ctx](TaggedValue args_,
                                   TaggedValue kwargs_) -> TaggedValue {
    std::cout << "Calling " << fn_name << std::endl;
    tensorflow::StatusOr<TaggedValue> v = fn.Execute(ctx, args_);
    return v.value();
  };
  return TaggedValue(CallFn);
}

// Import a module from a saved model.
//

# CHECK-SAME: _xla_compile_device_type = "GPU"
# CHECK-SAME: allow_soft_placement
# CHECK-SAME: control_outputs = ""
# CHECK-SAME: inputs = "args_0,args_1,args_2,args_3"
# CHECK-SAME: outputs = "rets_0,rets_1"
# CHECK:          %[[ISLAND_0:.*]], %[[ISLAND_0_control:.*]] = tf_executor.island wraps "tf.Const"

NODES=4

args1=()
args2=()
for i in $(seq 1 $NODES); do
	args1+=("http://localhost:$((9000 + i))/tmp/xl/1/$i ")
	args2+=("http://localhost:$((9100 + i))/tmp/xl/2/$i ")
done

for i in $(seq 1 $NODES); do
	./minio server --address "127.0.0.1:$((9000 + i))" ${args1[@]} & # | tee /tmp/minio/node.$i &
	./minio server --address "127.0.0.1:$((9100 + i))" ${args2[@]} & # | tee /tmp/minio/node.$i &
done

}

// IsEmpty - returns whether reader args is empty or not.
func (args *ReaderArgs) IsEmpty() bool {
	return !args.unmarshaled
}

// UnmarshalXML - decodes XML data.
func (args *ReaderArgs) UnmarshalXML(d *xml.Decoder, start xml.StartElement) (err error) {
	args.FileHeaderInfo = none
	args.RecordDelimiter = defaultRecordDelimiter
	args.FieldDelimiter = defaultFieldDelimiter
	args.QuoteCharacter = defaultQuoteCharacter

	return "arg"
}

func (argsTopic) Activate(context fw.TopicContext) {
	tmpl := assets.ParseTemplate(context.Layout(), "templates/args.html")

	_ = context.HTMLRouter().StrictSlash(true).NewRoute().Path("/").HandlerFunc(func(w http.ResponseWriter, req *http.Request) {
		fw.RenderHTML(w, tmpl, os.Args)
	})

zirain <******@****.***> 1684861711 +0800

    value {
      type: DT_FLOAT
    }
  }
}
node {
  name: "args_0"
  op: "_Arg"
  attr {
    key: "T"
    value {
      type: DT_RESOURCE
    }
  }
  attr {
    key: "index"
    value {
      i: 0
    }
  }
}
node {
  name: "spc1"
  op: "StatefulPartitionedCall"
  input: "input0"
  input: "args_0"
  attr {
    key: "Tin"
    value {
      list {

    func.return %1#0, %1#1: tensor<i64>, tensor<i32>
}

func.func private @__reduce_func_3(%arg0: tensor<i64> {tf._user_specified_name = "args_0"}, %arg1: tensor<i32> {tf._user_specified_name = "args_1"},
  %arg2: tensor<32xf32> {tf._user_specified_name = "args_2"}, %arg3: tensor<64xf64> {tf._user_specified_name = "args_3"},
  %arg4: tensor<!tf_type.resource<tensor<64xf32>>>, %arg5: tensor<!tf_type.resource<tensor<128xf32>>>)

Frank Wessels <******@****.***> 1705552466 -0800

        ParameterizedClassDesc[] args = desc.getArguments();
        assertThat(args.length, is(1));
        assertThat(args[0].getRawClass(), is(sameClass(Integer.class)));

        desc = ParameterizedClassDescFactory.createParameterizedClassDesc(method, 1, map);
        assertThat(desc.getRawClass(), is(sameClass(Map.class)));
        args = desc.getArguments();
        assertThat(args.length, is(2));