/// <summary>
/// Trains the model with a single minibatch of data
/// </summary>
/// <param name="features">Features for the batch</param>
/// <param name="targets">Targets for the batch</param>
public void TrainMinibatch(Dictionary <Input, Array> features, Dictionary <Layer, Array> targets)
{
if (_graph == null)
{
throw new InvalidOperationException("The model must be compiled first before you can train it.");
}
if (!features.Select(x => _inputMapping.ContainsKey(x.Key)).All(x => x))
{
throw new ArgumentException("Not all inputs have a value provided for them. Please make sure that you provide data for each of the inputs of the model.");
}
if (!targets.Select(x => _placeholderMapping.ContainsKey(x.Key)).All(x => x))
{
throw new ArgumentException("Not all targets have a value provided for them. Please make sure that you provide data for each of the targets of the model.");
}
EnsureSession();
var modelInputs = new Dictionary <TFOutput, Array>();
foreach (var keyValuePair in features)
{
modelInputs.Add(_inputMapping[keyValuePair.Key], keyValuePair.Value);
}
foreach (var keyValuePair in targets)
{
modelInputs.Add(_placeholderMapping[keyValuePair.Key], keyValuePair.Value);
}
_optimizer.Execute(_session, modelInputs);
}
