Two questions regard converting Decoder into a CoreML

I converted a decoder model into CoreML using following way:

input_1 = ct.TensorType(name="input_1", shape=ct.Shape((1, ct.RangeDim(lower_bound=1, upper_bound=50), 512)), dtype=np.float32)
input_2 = ct.TensorType(name="input_2", shape=ct.Shape((1, ct.RangeDim(lower_bound=1, upper_bound=50), 512)), dtype=np.float32)

decoder_iOS2 = ct.convert(decoder_layer,
                          inputs=[input_1, input_2]
                          )

But if load the model in Xcode it gives me two errors:

Error1:

MLE5Engine is not currently supported for models with range shape inputs that try to utilize the Neural Engine.

Q1: As having a Flexible Input shape is nature of the Decoder, I can ignore this error message, right? This is the things that can't be fixed.?

Erro2:

doUnloadModel:options:qos:error:: model=_ANEModel: { modelURL=file:///var/containers/Bundle/Application/CB2207C5-B549-4868-AEB5-FFA7A3E24397/Photo2ASCII.app/Deocder_iOS_test2.mlmodelc/model.mil : sourceURL= (null) : key={"isegment":0,"inputs":{"input_1":{"shape":[512,1,1,1,1]},"input_2":{"shape":[512,1,1,1,1]}},"outputs":{"Identity":{"shape":[512,1,1,1,1]}}} : identifierSource=0 : cacheURLIdentifier=A93CE297F87F752D426002C8D1CE79094E614BEA1C0E96113228C8D3F06831FA_F055BF0F9A381C4C6DC99CE8FCF5C98E7E8B83EA5BF7CFD0EDC15EF776B29413 : string_id=0x00000000 : program=_ANEProgramForEvaluation: { programHandle=6885927629810 : intermediateBufferHandle=6885928772758 : queueDepth=127 } : state=3 : programHandle=6885927629810 : intermediateBufferHandle=6885928772758 : queueDepth=127 : attr={
    ANEFModelDescription =     {
        ANEFModelInput16KAlignmentArray =         (
        );
        ANEFModelOutput16KAlignmentArray =         (
        );
        ANEFModelProcedures =         (
                        {
                ANEFModelInputSymbolIndexArray =                 (
                    0,
                    1
                );
                ANEFModelOutputSymbolIndexArray =                 (
                    0
                );
                ANEFModelProcedureID = 0;
            }
        );
        kANEFModelInputSymbolsArrayKey =         (
            "input_1",
            "input_2"
        );
        kANEFModelOutputSymbolsArrayKey =         (
            "Identity@output"
        );
        kANEFModelProcedureNameToIDMapKey =         {
            net = 0;
        };
    };
    NetworkStatusList =     (
                {
            LiveInputList =             (
                                {
                    BatchStride = 1024;
                    Batches = 1;
                    Channels = 1;
                    Depth = 1;
                    DepthStride = 1024;
                    Height = 1;
                    Interleave = 1;
                    Name = "input_1";
                    PlaneCount = 1;
                    PlaneStride = 1024;
                    RowStride = 1024;
                    Symbol = "input_1";
                    Type = Float16;
                    Width = 512;
                },
                                {
                    BatchStride = 1024;
                    Batches = 1;
                    Channels = 1;
                    Depth = 1;
                    DepthStride = 1024;
                    Height = 1;
                    Interleave = 1;
                    Name = "input_2";
                    PlaneCount = 1;
                    PlaneStride = 1024;
                    RowStride = 1024;
                    Symbol = "input_2";
                    Type = Float16;
                    Width = 512;
                }
            );
            LiveOutputList =             (
                                {
                    BatchStride = 1024;
                    Batches = 1;
                    Channels = 1;
                    Depth = 1;
                    DepthStride = 1024;
                    Height = 1;
                    Interleave = 1;
                    Name = "Identity@output";
                    PlaneCount = 1;
                    PlaneStride = 1024;
                    RowStride = 1024;
                    Symbol = "Identity@output";
                    Type = Float16;
                    Width = 512;
                }
            );
            Name = net;
        }
    );
} : perfStatsMask=0}  was not loaded by the client.

Q2: Is that I can ignore this error message, if I'm gonna use CPU/GPU when running the model?

Two questions regard converting Decoder into a CoreML
 
 
Q