'Stores argument in member variable for further use.
Args:
net: A tensor with shape [batch_size, num_features, feature_size] which
contains some extracted image features.
labels_one_hot: An optional (can be None) ground truth labels for the
input features. Is a tensor with shape
[batch_size, seq_length, num_char_classes]
model_params: A namedtuple with model parameters (model.ModelParams).
method_params: A SequenceLayerParams instance.'

def __init__(self, net, labels_one_hot, model_params, method_params):

    self._params = model_params
    self._mparams = method_params
    self._net = net
    self._labels_one_hot = labels_one_hot
    self._batch_size = net.get_shape().dims[0].value
    self._char_logits = {}
    regularizer = slim.l2_regularizer(self._mparams.weight_decay)
    self._softmax_w = slim.model_variable('softmax_w', [self._mparams.num_lstm_units, self._params.num_char_classes], initializer=orthogonal_initializer, regularizer=regularizer)
    self._softmax_b = slim.model_variable('softmax_b', [self._params.num_char_classes], initializer=tf.zeros_initializer(), regularizer=regularizer)
