def __init__(self, datasets):
DataIteratorBase.__init__(self, datasets)
self._variable_scope = get_unique_named_variable_scope('data_iterator')
with tf.variable_scope(self._variable_scope):
arb_dataset = self._datasets[next(iter(self._datasets))]
self._iterator = tf.data.Iterator.from_structure(
arb_dataset.output_types, arb_dataset.output_shapes)
self._iterator_init_ops = {
name: self._iterator.make_initializer(d)
for name, d in self._datasets.items()
}
def __init__(self, datasets):
DataIteratorBase.__init__(self, datasets)
self._variable_scope = get_unique_named_variable_scope(
'feedable_data_iterator')
with tf.variable_scope(self._variable_scope):
self._handle = tf.placeholder(tf.string, shape=[], name='handle')
arb_dataset = self._datasets[next(iter(self._datasets))]
self._iterator = tf.data.Iterator.from_string_handle(
self._handle, arb_dataset.output_types,
arb_dataset.output_shapes)
self._dataset_iterators = {
name: dataset.make_initializable_iterator()
for name, dataset in self._datasets.items()
}
def __init__(self, hparams=None):
self._hparams = HParams(hparams, self.default_hparams())
name = self._hparams.name
self._variable_scope = get_unique_named_variable_scope(name)
self._unique_name = self._variable_scope.name.split("/")[-1]