public IEnumerator Train()
{
yield return(StartCoroutine(FocusTraining()));
NeuralNetworkProperties properties = new NeuralNetworkProperties(batchSize, trainingInput, trainingAnswer, testingInput, testingAnswer, hiddenLayerSizes);
yield return(StartCoroutine(client.deepLearningClient.DeepLearning(properties)));
DefocusTraining();
}
public IEnumerator DeepLearning(NeuralNetworkProperties properties)
{
string json = JsonUtility.ToJson(properties);
Debug.Log(json);
byte[] data = System.Text.Encoding.UTF8.GetBytes("ni" + json);
int bytes;
string responseData = "";
netStream.Write(data, 0, data.Length);
ReportDeepLearningAccuracy();
Debug.Log("Begin training...");
int i = 0;
while (true)
{
if (breakFlag)
{
breakFlag = false;
break;
}
data = System.Text.Encoding.UTF8.GetBytes("nt");
netStream.Write(data, 0, data.Length);
data = new byte[1024];
bytes = netStream.Read(data, 0, data.Length);
responseData = System.Text.Encoding.UTF8.GetString(data, 0, bytes);
//float loss = float.Parse(responseData);
//Debug.Log(loss);
if (i % 10 == 0)
{
ReportDeepLearningAccuracy();
}
i += 1;
yield return(null);
}
Debug.Log("Finished");
ReportDeepLearningAccuracy();
}
