layers.py 文件源码

def __init__(self, cell, location_softmax, pointing_output,
                 input_size, decoder_inputs=None,
                 trainable=True, name=None, **kwargs):
        """Initializes a new PointingSoftmaxDecoder instance.

        See the class documentation for the escription of all the arguments.
        """
        super(PointingSoftmaxDecoder, self).__init__(
            trainable=trainable, name=name, **kwargs)
        self._cell = cell
        self._loc = location_softmax
        self._out = pointing_output
        self._inp_size = input_size

        if decoder_inputs is not None:
            tensors = tf.transpose(decoder_inputs, [1, 0, 2])
            dtype = tensors.dtype
            size = tf.shape(tensors)[0]
            element_shape = tensors.get_shape()[1:]
            tensor_array = tf.TensorArray(dtype=dtype, size=size, element_shape=element_shape)
            decoder_inputs = tensor_array.unstack(tensors)
        self._inputs_ta = decoder_inputs

        # infer the batch/location size from the `states` tensor
        # of the attention layer of the injected location softmax.
        states = self._loc.attention.states
        self._batch_size = utils.get_dimension(states, 0)
        self._loc_size = utils.get_dimension(states, 1)