I received this error in DDPG "Model input sizes must match the dimensions specified in the corresponding observation and action info specifications."

Question

ali kadkhodaei 2023-10-12

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2032274-i-received-this-error-in-ddpg-model-input-sizes-must-match-the-dimensions-specified-in-the-correspo

回答： Emmanouil Tzorakoleftherakis 2023-10-13

hi every body

i want to impliment LSTM layers in state path of my critic network

my code is :

obsInfo = rlNumericSpec([42 1]);

obsInfo.Name = 'observation';

actInfo = rlNumericSpec([6 1]);

actInfo.Name = 'action';

actInfo.UpperLimit =0.01*ones(6,1);

actInfo.LowerLimit =-0.01*ones(6,1);

numObs=prod(obsInfo.Dimension) ;

numAcs=prod(actInfo.Dimension) ;

numHiddenUnits=100;

statePath = [sequenceInputLayer(numObs)

lstmLayer(numHiddenUnits,'OutputMode','sequence')

fullyConnectedLayer(500,'Name','CriticStateFC1')

reluLayer('Name', 'CriticStateRelu1')

fullyConnectedLayer(450,'Name','CriticStateFC2')

reluLayer('Name', 'CriticStateRelu2')

fullyConnectedLayer(300,'Name','CriticStateFC3')

reluLayer('Name', 'CriticStateRelu3')

fullyConnectedLayer(250,'Name','CriticStateFC4')

reluLayer('Name', 'CriticStateRelu4')

fullyConnectedLayer(200,'Name','CriticStateFC5')

reluLayer('Name', 'CriticStateRelu5')

fullyConnectedLayer(100,'Name','CriticStateFC6')

reluLayer('Name', 'CriticStateRelu6')

fullyConnectedLayer(50,'Name','CriticStateFC7')

reluLayer('Name', 'CriticStateRelu7')

fullyConnectedLayer(25,'Name','CriticStateFC8')

];

actionPath = [

sequenceInputLayer(numAcs)

fullyConnectedLayer(300,'Name','CriticActionFC1')

reluLayer('Name', 'CriticActionRelu1')

fullyConnectedLayer(250,'Name','CriticActionFC2')

reluLayer('Name', 'CriticActionRelu2')

fullyConnectedLayer(200,'Name','CriticActionFC3')

reluLayer('Name', 'CriticActionRelu3')

fullyConnectedLayer(100,'Name','CriticActionFC4')

reluLayer('Name', 'CriticActionRelu4')

fullyConnectedLayer(50,'Name','CriticActionFC5')

reluLayer('Name', 'CriticActionRelu5')

fullyConnectedLayer(25,'Name','CriticActionFC6')];

commonPath = [

concatenationLayer(1,2,Name='concat')

reluLayer('Name','CriticCommonRelu')

fullyConnectedLayer(512,'Name','CriticCommon1')

reluLayer('Name','CriticCommonRelu2')

fullyConnectedLayer(300,'Name','CriticCommon2')

reluLayer('Name','CriticCommonRelu3')

fullyConnectedLayer(1,'Name','CriticOutput')];

criticOpts =rlOptimizerOptions(LearnRate=1e-04,GradientThreshold=inf,...

L2RegularizationFactor=0.0001,Optimizer="adam");

criticNetwork = layerGraph();

criticNetwork = addLayers(criticNetwork,statePath);

criticNetwork = addLayers(criticNetwork,actionPath);

criticNetwork = addLayers(criticNetwork,commonPath);

criticNetwork = connectLayers(criticNetwork,'CriticStateFC8','concat/in1');

criticNetwork = connectLayers(criticNetwork,'CriticActionFC6','concat/in2');

criticNetwork = dlnetwork(criticNetwork);

analyzeNetwork(criticNetwork)

critic = rlQValueFunction(criticNetwork,obsInfo,actInfo,...

ObservationInputNames='observation',ActionInputNames='action',UseDevice="gpu");

when i run above code i received this error

"Error using rlQValueFunction

Model input sizes must match the dimensions specified in the corresponding observation

and action info specifications." please help me

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Answer 1

Emmanouil Tzorakoleftherakis 2023-10-13

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2032274-i-received-this-error-in-ddpg-model-input-sizes-must-match-the-dimensions-specified-in-the-correspo#answer_1332699

The easiest way to discover your error yourself is to use the default agent feature have use the network architecture that's automatically generated by Reinforcement Learning Toolbox. Please take a look here. Don't forget to indicate that you want your network to use LSTM layers in the initialization options.

Per the example in the link above, after the agent is created, you can extract the actor and critic and compare the generated architecture with what you have.

Hope this helps