public Agent(IxTrainerCallback icallback, MyCaffeControl <T> mycaffe, PropertySet properties, CryptoRandom random, Phase phase, BucketCollection rgVocabulary, bool bUsePreloadData, string strRunProperties = null)
{
m_icallback = icallback;
m_brain = new Brain <T>(mycaffe, properties, random, icallback as IxTrainerCallbackRNN, phase, rgVocabulary, bUsePreloadData, strRunProperties);
m_properties = properties;
m_random = random;
}
public void Initialize(int nThreads, IxTrainerCallback icallback)
{
for (int i = 0; i < nThreads; i++)
{
m_rgCollectors.Add(new DataCollector(icallback));
}
}
/// <summary>
/// The constructor.
/// </summary>
/// <param name="mycaffe">Specifies the MyCaffeControl to use for learning and prediction.</param>
/// <param name="properties">Specifies the property set containing the key/value pairs of property settings.</param>
/// <param name="random">Specifies a Random number generator used for random selection.</param>
/// <param name="icallback">Specifies the callback for parent notifications and queries.</param>
public TrainerNoisyDqn(MyCaffeControl <T> mycaffe, PropertySet properties, CryptoRandom random, IxTrainerCallback icallback)
{
m_icallback = icallback;
m_mycaffe = mycaffe;
m_properties = properties;
m_random = random;
}
/// <summary>
/// The constructor.
/// </summary>
/// <param name="icallback">Specifies the callback used for update notifications sent to the parent.</param>
/// <param name="mycaffe">Specifies the instance of MyCaffe with the open project.</param>
/// <param name="properties">Specifies the properties passed into the trainer.</param>
/// <param name="random">Specifies the random number generator used.</param>
/// <param name="phase">Specifies the phase of the internal network to use.</param>
public DqnAgent(IxTrainerCallback icallback, MyCaffeControl <T> mycaffe, PropertySet properties, CryptoRandom random, Phase phase)
{
m_icallback = icallback;
m_brain = new Brain <T>(mycaffe, properties, random, phase);
m_properties = properties;
m_random = random;
m_fGamma = (float)properties.GetPropertyAsDouble("Gamma", m_fGamma);
m_bUseRawInput = properties.GetPropertyAsBool("UseRawInput", m_bUseRawInput);
m_nMaxMemory = properties.GetPropertyAsInt("MaxMemory", m_nMaxMemory);
m_nTrainingUpdateFreq = properties.GetPropertyAsInt("TrainingUpdateFreq", m_nTrainingUpdateFreq);
m_nExplorationNum = properties.GetPropertyAsInt("ExplorationNum", m_nExplorationNum);
m_nEpsSteps = properties.GetPropertyAsInt("EpsSteps", m_nEpsSteps);
m_dfEpsStart = properties.GetPropertyAsDouble("EpsStart", m_dfEpsStart);
m_dfEpsEnd = properties.GetPropertyAsDouble("EpsEnd", m_dfEpsEnd);
m_dfEpsDelta = (m_dfEpsStart - m_dfEpsEnd) / m_nEpsSteps;
m_dfExplorationRate = m_dfEpsStart;
if (m_dfEpsStart < 0 || m_dfEpsStart > 1)
{
throw new Exception("The 'EpsStart' is out of range - please specify a real number in the range [0,1]");
}
if (m_dfEpsEnd < 0 || m_dfEpsEnd > 1)
{
throw new Exception("The 'EpsEnd' is out of range - please specify a real number in the range [0,1]");
}
if (m_dfEpsEnd > m_dfEpsStart)
{
throw new Exception("The 'EpsEnd' must be less than the 'EpsStart' value.");
}
}
/// <summary>
/// The constructor.
/// </summary>
/// <param name="mycaffe">Specifies the MyCaffeControl to use for learning and prediction.</param>
/// <param name="properties">Specifies the property set containing the key/value pairs of property settings.</param>
/// <param name="random">Specifies the random number generator to use.</param>
/// <param name="icallback">Specifies the callback for parent notifications and queries.</param>
/// <param name="rgVocabulary">Specifies the vocabulary to use.</param>
public TrainerRNN(MyCaffeControl <T> mycaffe, PropertySet properties, CryptoRandom random, IxTrainerCallback icallback, BucketCollection rgVocabulary)
{
m_icallback = icallback;
m_mycaffe = mycaffe;
m_properties = properties;
m_random = random;
m_rgVocabulary = rgVocabulary;
}
/// <summary>
/// The constructor.
/// </summary>
/// <param name="icallback">Specifies the callback used for update notifications sent to the parent.</param>
/// <param name="mycaffe">Specifies the instance of MyCaffe with the open project.</param>
/// <param name="properties">Specifies the properties passed into the trainer.</param>
/// <param name="random">Specifies the random number generator used.</param>
/// <param name="phase">Specifies the phase of the internal network to use.</param>
public DqnAgent(IxTrainerCallback icallback, MyCaffeControl <T> mycaffe, PropertySet properties, CryptoRandom random, Phase phase)
{
m_icallback = icallback;
m_brain = new Brain <T>(mycaffe, properties, random, phase);
m_properties = properties;
m_random = random;
m_fGamma = (float)properties.GetPropertyAsDouble("Gamma", m_fGamma);
m_bUseRawInput = properties.GetPropertyAsBool("UseRawInput", m_bUseRawInput);
}
public DataCollector(IxTrainerCallback icallback)
{
m_icallback = icallback;
m_thread = new Thread(new ThreadStart(doWork));
m_thread.Start();
}
/// <summary>
/// The constructor.
/// </summary>
/// <param name="mycaffe">Specifies the MyCaffeControl to use for learning and prediction.</param>
/// <param name="properties">Specifies the property set containing the key/value pairs of property settings.</param>
/// <param name="random">Specifies a Random number generator used for random selection.</param>
/// <param name="icallback">Specifies the callback for parent notifications and queries.</param>
public TrainerPG(MyCaffeControl <T> mycaffe, PropertySet properties, Random random, IxTrainerCallback icallback)
{
m_icallback = icallback;
m_mycaffe = mycaffe;
m_properties = properties;
}
