Beispiel #1
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    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()
            }
Beispiel #2
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    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()
            }
Beispiel #3
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    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]