def __init__(self, lembedding, num_classes=2, ngrams=[1, 2, 3, 4, 5],
nfilters=64, rnn_type=GRU, rnn_dim=80, train_vectors=True,
optimizer=None):
if not isinstance(lembedding, TwoLevelsEmbedding):
raise LanguageClassifierException(
"The model only accepts two-level language embeddings")
if num_classes < 2:
raise LanguageClassifierException("Classes must be 2 or more")
self.optimizer = optimizer
model = self._generate_model(lembedding, num_classes, ngrams,
nfilters, rnn_type, rnn_dim, train_vectors)
super(RCNNClassifier, self).__init__(model, self.optimizer)
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