private IEnumerable <((int[][], int[])[], int[][])> minibatches(CoNLLDataset data, int minibatch_size)
{
var x_batch = new List <(int[][], int[])>();
var y_batch = new List <int[]>();
foreach (var(x, y) in data.GetItems())
{
if (len(y_batch) == minibatch_size)
{
yield return(x_batch.ToArray(), y_batch.ToArray());
x_batch.Clear();
y_batch.Clear();
}
var x3 = (x.Select(x1 => x1.Item1).ToArray(), x.Select(x2 => x2.Item2).ToArray());
x_batch.Add(x3);
y_batch.Add(y);
}
if (len(y_batch) > 0)
{
yield return(x_batch.ToArray(), y_batch.ToArray());
}
}
private float run_epoch(Session sess, CoNLLDataset train, CoNLLDataset dev, int epoch)
{
float accuracy = 0;
// iterate over dataset
var batches = minibatches(train, hp.batch_size);
foreach (var(words, labels) in batches)
{
var(fd, _) = get_feed_dict(words, labels, hp.lr, hp.dropout);
(_, accuracy) = sess.run((train_op, loss), feed_dict: fd);
}
return(accuracy);
}
private float run_epoch(Session sess, CoNLLDataset train, CoNLLDataset dev, int epoch)
{
NDArray results = null;
// iterate over dataset
var batches = minibatches(train, hp.batch_size);
foreach (var(words, labels) in batches)
{
var(fd, _) = get_feed_dict(words, labels, hp.lr, hp.dropout);
results = sess.run(new ITensorOrOperation[] { train_op, loss }, feed_dict: fd);
}
return(results[1]);
}
