/// <summary>
/// Retrieves the weights of the model
/// </summary>
/// <returns>A flat list of Numpy arrays</returns>
public List <NDarray> GetWeights()
{
var args = new Dictionary <string, object>();
var pyWeights = PyInstance.get_weights();
List <NDarray> weights = new List <NDarray>();
foreach (PyObject weightsArray in pyWeights)
{
var n = np.array(new NDarray(weightsArray));
weights.Add(n);
}
return(weights);
}
/// <summary>
/// Summaries the specified line length.
/// </summary>
/// <param name="line_length">Length of the line.</param>
/// <param name="positions">The positions.</param>
public void Summary(int?line_length = null, float[] positions = null)
{
PyInstance.summary(line_length: line_length, positions: positions);
}
/// <summary>
/// Loads the weight to the model from a file.
/// </summary>
/// <param name="path">The path of of the weight file.</param>
public void LoadWeight(string path)
{
PyInstance.load_weights(path);
}
/// <summary>
/// Save the model to h5 file
/// </summary>
/// <param name="path">The path with filename eg: model.h5.</param>
public void Save(string filepath, bool overwrite = true, bool include_optimizer = true)
{
PyInstance.save(filepath: filepath, overwrite: overwrite, include_optimizer: include_optimizer);
}
/// <summary>
/// Saves the weight of the trained model to a file.
/// </summary>
/// <param name="path">The path of the weight to save.</param>
public void SaveWeight(string path)
{
PyInstance.save_weights(path);
}
/// <summary>
/// Converts the model to json.
/// </summary>
/// <returns></returns>
public string ToJson()
{
return(PyInstance.to_json().ToString());
}
/// <summary>
/// Save the model to h5 file
/// </summary>
/// <param name="path">The path with filename eg: model.h5.</param>
public void Save(string path)
{
PyInstance.save(path);
}
/// <summary>
/// You can also simply add layers via the .Add() method
/// </summary>
/// <param name="layer">The layer.</param>
public void Add(BaseLayer layer)
{
PyInstance.add(layer: layer.PyInstance);
}
