from __future__ import print_function


class Hyperparams(object):
    """
    Hyperparameters for LSTM network
    """
    def __init__(self):
        # Training hyper parameters
        self._train_epoch_size = 30000
        self._eval_epoch_size = 3000
        self._num_epoch = 20
        self._learning_rate = 0.001
        self._momentum = 0.9
        self._bn_mom = 0.9
        self._workspace = 512
        self._loss_type = "ctc"  # ["warpctc"  "ctc"]

        self._batch_size = 128
        self._num_classes = 11
        self._img_width = 100
        self._img_height = 32

        # DenseNet hyper parameters
        self._depth = 161
        self._growrate = 32
        self._reduction = 0.5

        # LSTM hyper parameters
        self._num_hidden = 100
        self._num_lstm_layer = 2
        self.seq_len_cmpr_ratio = 8  # 模型对于图片宽度压缩的比例（模型中的卷积层造成的）
        self._seq_length = self._img_width // self.seq_len_cmpr_ratio
        self._num_label = 4
        self._drop_out = 0.5

    @property
    def train_epoch_size(self):
        return self._train_epoch_size

    @property
    def eval_epoch_size(self):
        return self._eval_epoch_size

    @property
    def num_epoch(self):
        return self._num_epoch

    @property
    def learning_rate(self):
        return self._learning_rate

    @property
    def momentum(self):
        return self._momentum

    @property
    def bn_mom(self):
        return self._bn_mom

    @property
    def workspace(self):
        return self._workspace

    @property
    def loss_type(self):
        return self._loss_type

    @property
    def batch_size(self):
        return self._batch_size

    @property
    def num_classes(self):
        return self._num_classes

    @property
    def img_width(self):
        return self._img_width

    @property
    def img_height(self):
        return self._img_height

    @property
    def depth(self):
        return self._depth

    @property
    def growrate(self):
        return self._growrate

    @property
    def reduction(self):
        return self._reduction

    @property
    def num_hidden(self):
        return self._num_hidden

    @property
    def num_lstm_layer(self):
        return self._num_lstm_layer

    @property
    def seq_length(self):
        return self._seq_length

    @property
    def num_label(self):
        return self._num_label

    @property
    def dropout(self):
        return self._drop_out