/// <summary>
/// Retrain the TensorFlow model on new data.
/// The model is not loaded again instead the information contained in <see cref="TensorFlowModel"/> class is reused
/// (c.f. <see cref="TensorFlowModel.ModelPath"/> and <see cref="TensorFlowModel.Session"/>).
/// </summary>
/// <param name="inputColumnNames"> The names of the model inputs.</param>
/// <param name="outputColumnNames">The names of the requested model outputs.</param>
/// <param name="labelColumnName">Name of the label column.</param>
/// <param name="tensorFlowLabel">Name of the node in TensorFlow graph that is used as label during training in TensorFlow.
/// The value of <paramref name="labelColumnName"/> from <see cref="IDataView"/> is fed to this node.</param>
/// <param name="optimizationOperation">The name of the optimization operation in the TensorFlow graph.</param>
/// <param name="epoch">Number of training iterations.</param>
/// <param name="batchSize">Number of samples to use for mini-batch training.</param>
/// <param name="lossOperation">The name of the operation in the TensorFlow graph to compute training loss (Optional).</param>
/// <param name="metricOperation">The name of the operation in the TensorFlow graph to compute performance metric during training (Optional).</param>
/// <param name="learningRateOperation">The name of the operation in the TensorFlow graph which sets optimizer learning rate (Optional).</param>
/// <param name="learningRate">Learning rate to use during optimization (Optional).</param>
/// <remarks>
/// The support for retraining is experimental.
/// </remarks>
public TensorFlowEstimator RetrainTensorFlowModel(
string[] outputColumnNames,
string[] inputColumnNames,
string labelColumnName,
string tensorFlowLabel,
string optimizationOperation,
int epoch = 10,
int batchSize = 20,
string lossOperation = null,
string metricOperation = null,
string learningRateOperation = null,
float learningRate = 0.01f)
{
var options = new TensorFlowEstimator.Options()
{
ModelLocation = ModelPath,
InputColumns = inputColumnNames,
OutputColumns = outputColumnNames,
LabelColumn = labelColumnName,
TensorFlowLabel = tensorFlowLabel,
OptimizationOperation = optimizationOperation,
LossOperation = lossOperation,
MetricOperation = metricOperation,
Epoch = epoch,
LearningRateOperation = learningRateOperation,
LearningRate = learningRate,
BatchSize = batchSize,
ReTrain = true
};
return(new TensorFlowEstimator(_env, options, this));
}
/// <summary>
/// Score or Retrain a tensorflow model (based on setting of the <see cref="TensorFlowEstimator.Options.ReTrain"/>) setting.
/// The model is specified in the <see cref="TensorFlowEstimator.Options.ModelLocation"/>.
/// </summary>
/// <param name="catalog">The transform's catalog.</param>
/// <param name="options">The <see cref="TensorFlowEstimator.Options"/> specifying the inputs and the settings of the <see cref="TensorFlowEstimator"/>.</param>
public static TensorFlowEstimator TensorFlow(this TransformsCatalog catalog,
TensorFlowEstimator.Options options)
=> new TensorFlowEstimator(CatalogUtils.GetEnvironment(catalog), options);