How to save pretrained DQN agent and extract the weights inside the network?
The following is part of the program. I want to know how to extract the weight values from the trained DQN network.
DQNnet = [
imageInputLayer([1 520 1],"Name","ImageFeatureInput","Normalization","none")
fullyConnectedLayer(1024,"Name","fc1")
reluLayer("Name","relu1")
% fullyConnectedLayer(512,"Name","fc2")
% reluLayer("Name","relu2")
fullyConnectedLayer(14,"Name","fc3")
softmaxLayer("Name","softmax")
classificationLayer("Name","ActionOutput")];
ObsInfo = getObservationInfo(env);
ActInfo = getActionInfo(env);
DQNOpts = rlRepresentationOptions(‘LearnRate’,0.0001,’GradientThreshold’,1,’UseDevice’,’gpu’);
DQNagent = rlQValueRepresentation(DQNnet,ObsInfo,ActInfo,’Observation’,{‘ImageFeatureInput’},’ActionInputNames’,{‘BoundingBox Actions’},DQNOpts);
agentOpts = rlDQNAgentOptions(…
‘UseDoubleDQN’,true …
,’MiniBatchSize’,256);
agentOpts.EpsilonGreedyExploration.Epsilon = 1;
agent = rlDQNAgent(DQNagent,agentOpts);
%% Agent Training
% Training options
trainOpts = rlTrainingOptions(…
‘MaxEpisodes’, 100, …
‘MaxStepsPerEpisode’, 100, …
‘Verbose’, true, …
‘Plots’,’training-progress’,…
‘ScoreAveragingWindowLength’,400,…
‘StopTrainingCriteria’,’AverageSteps’,…
‘StopTrainingValue’,1000000000,…
‘SaveAgentDirectory’, pwd + "agents");
% Agent training
trainingStats = train(agent,env,trainOpts);The following is part of the program. I want to know how to extract the weight values from the trained DQN network.
DQNnet = [
imageInputLayer([1 520 1],"Name","ImageFeatureInput","Normalization","none")
fullyConnectedLayer(1024,"Name","fc1")
reluLayer("Name","relu1")
% fullyConnectedLayer(512,"Name","fc2")
% reluLayer("Name","relu2")
fullyConnectedLayer(14,"Name","fc3")
softmaxLayer("Name","softmax")
classificationLayer("Name","ActionOutput")];
ObsInfo = getObservationInfo(env);
ActInfo = getActionInfo(env);
DQNOpts = rlRepresentationOptions(‘LearnRate’,0.0001,’GradientThreshold’,1,’UseDevice’,’gpu’);
DQNagent = rlQValueRepresentation(DQNnet,ObsInfo,ActInfo,’Observation’,{‘ImageFeatureInput’},’ActionInputNames’,{‘BoundingBox Actions’},DQNOpts);
agentOpts = rlDQNAgentOptions(…
‘UseDoubleDQN’,true …
,’MiniBatchSize’,256);
agentOpts.EpsilonGreedyExploration.Epsilon = 1;
agent = rlDQNAgent(DQNagent,agentOpts);
%% Agent Training
% Training options
trainOpts = rlTrainingOptions(…
‘MaxEpisodes’, 100, …
‘MaxStepsPerEpisode’, 100, …
‘Verbose’, true, …
‘Plots’,’training-progress’,…
‘ScoreAveragingWindowLength’,400,…
‘StopTrainingCriteria’,’AverageSteps’,…
‘StopTrainingValue’,1000000000,…
‘SaveAgentDirectory’, pwd + "agents");
% Agent training
trainingStats = train(agent,env,trainOpts); The following is part of the program. I want to know how to extract the weight values from the trained DQN network.
DQNnet = [
imageInputLayer([1 520 1],"Name","ImageFeatureInput","Normalization","none")
fullyConnectedLayer(1024,"Name","fc1")
reluLayer("Name","relu1")
% fullyConnectedLayer(512,"Name","fc2")
% reluLayer("Name","relu2")
fullyConnectedLayer(14,"Name","fc3")
softmaxLayer("Name","softmax")
classificationLayer("Name","ActionOutput")];
ObsInfo = getObservationInfo(env);
ActInfo = getActionInfo(env);
DQNOpts = rlRepresentationOptions(‘LearnRate’,0.0001,’GradientThreshold’,1,’UseDevice’,’gpu’);
DQNagent = rlQValueRepresentation(DQNnet,ObsInfo,ActInfo,’Observation’,{‘ImageFeatureInput’},’ActionInputNames’,{‘BoundingBox Actions’},DQNOpts);
agentOpts = rlDQNAgentOptions(…
‘UseDoubleDQN’,true …
,’MiniBatchSize’,256);
agentOpts.EpsilonGreedyExploration.Epsilon = 1;
agent = rlDQNAgent(DQNagent,agentOpts);
%% Agent Training
% Training options
trainOpts = rlTrainingOptions(…
‘MaxEpisodes’, 100, …
‘MaxStepsPerEpisode’, 100, …
‘Verbose’, true, …
‘Plots’,’training-progress’,…
‘ScoreAveragingWindowLength’,400,…
‘StopTrainingCriteria’,’AverageSteps’,…
‘StopTrainingValue’,1000000000,…
‘SaveAgentDirectory’, pwd + "agents");
% Agent training
trainingStats = train(agent,env,trainOpts); drl, neural network, dqn MATLAB Answers — New Questions
