SemianiakaVY/BotSharp
1
0
Fork 0
Code Issues Pull requests Actions Packages Projects Releases Wiki Activity

Move label to model dir

Browse source
This commit is contained in:
Wenbo Cao 2023-09-01 10:01:35 -05:00
parent db61b8b82d
commit 74ddd3ea13
1 changed files with 14 additions and 9 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

23
src/Plugins/BotSharp.Plugin.RoutingSpeeder/Providers/IntentClassifier.cs
View file

@ -50,7 +50,7 @@ public class IntentClassifier
{
return;
}
var vector = _services.GetRequiredService<ITextEmbedding>();
var layers = new List<ILayer>
@ -58,7 +58,7 @@ public class IntentClassifier
keras.layers.InputLayer((vector.Dimension), name: "Input"),
keras.layers.Dense(256, activation:"relu"),
keras.layers.Dense(256, activation:"relu"),
keras.layers.Dense(GetLabels().Length, activation: keras.activations.Softmax)
keras.layers.Dense(GetFiles().Length, activation: keras.activations.Softmax)
};
_model = keras.Sequential(layers);
@ -153,7 +153,7 @@ public class IntentClassifier
{
var agentService = _services.CreateScope().ServiceProvider.GetRequiredService<IAgentService>();
string rootDirectory = Path.Combine(agentService.GetDataDir(), _settings.RAW_DATA_DIR);
string saveLabelDirectory = Path.Combine(agentService.GetDataDir(), _settings.MODEL_DIR, _settings.LABEL_FILE_NAME);
if (!Directory.Exists(rootDirectory))
{
@ -174,7 +174,9 @@ public class IntentClassifier
labelList.AddRange(Enumerable.Repeat(fileName, texts.Count).ToList());
}
var uniqueLabelList = labelList.Distinct().ToList();
// Write label into local file
var uniqueLabelList = labelList.Distinct().OrderBy(x => x).ToArray();
File.WriteAllLines(saveLabelDirectory, uniqueLabelList);
var x = np.zeros((vectorList.Count, vector.Dimension), dtype: np.float32);
var y = np.zeros((vectorList.Count, 1), dtype: np.float32);
@ -182,7 +184,8 @@ public class IntentClassifier
for (int i = 0; i < vectorList.Count; i++)
{
x[i] = vectorList[i];
y[i] = (float)uniqueLabelList.IndexOf(labelList[i]);
// y[i] = (float)uniqueLabelList.IndexOf(labelList[i]);
y[i] = (float)Array.IndexOf(uniqueLabelList, labelList[i]);
}
return (x, y);
}
@ -197,7 +200,7 @@ public class IntentClassifier
public string[] GetLabels()
{
var agentService = _services.CreateScope().ServiceProvider.GetRequiredService<IAgentService>();
string rootDirectory = Path.Combine(agentService.GetDataDir(), _settings.RAW_DATA_DIR, _settings.LABEL_FILE_NAME);
string rootDirectory = Path.Combine(agentService.GetDataDir(), _settings.MODEL_DIR, _settings.LABEL_FILE_NAME);
var labelText = File.ReadAllLines(rootDirectory);
return labelText.OrderBy(x => x).ToArray();
}
@ -222,15 +225,17 @@ public class IntentClassifier
var prob = _model.predict(vector).numpy();
if (prob[0] < confidenceScore)
var probLabel = tf.arg_max(prob, -1).numpy().ToArray<long>();
prob = np.squeeze(prob, axis: 0);
if (prob[probLabel[0]] < confidenceScore)
{
return string.Empty;
}
var probLabel = tf.arg_max(prob, -1).numpy();
var prediction = GetLabels()[probLabel[0]];
return prediction;
}
public void InitClassifer()