import tensorflow as tf

               batch_size=10, model_params=None, c2v=None,
               max_sequence_len=None,
               dropout_keep_prob=None,
               weights=None):
    self.params = model_params
    self._out_vocab_size = out_vocab_size # num. of languages
    self.weights = tf.constant(weights, dtype=tf.float32, name='class_weights')

    with tf.variable_scope("tweetff"):
      hidden = tf.get_variable("ff_hidden",
                               [c2v.embedding_dims, out_vocab_size])
      bias = tf.get_variable('ff_bias', [out_vocab_size])

    #probably useless. at least I don't want to use it
    self.seq_lens = tf.placeholder(tf.int64, [batch_size], name='seq_lens')

    self.x = tf.placeholder(tf.int32, [batch_size, max_sequence_len],
                            name='x')
