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?

I want to create a macOS application that runs Python script locally. As now I found that using 'PythonKit' library and disabling Sandbox allow me to do that, but disabling sandbox makes the app can't be published. Any idea how I can solve this problem? Thanks

So I was watching the WWDC video [Add configuration and intelligence to you widget] (https://developer.apple.com/videos/play/wwdc2020/10194) and it seemed like there Xcode automatically generated the IntentHandler.swift file. But I can't find the IntentHandler.swift file in my Xcode. Of course, I added Widget as target checking add intent configuration, and also added intent parameters too. What I am doing wrong here? Or is that I Xcode doesn't automatically generate IntentHandler.swift file ? Thanks

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