def _as_variant_tensor(self): return gen_dataset_ops.dense_to_sparse_batch_dataset( self._input_dataset._as_variant_tensor(), # pylint: disable=protected-access self._batch_size, row_shape=dataset_ops._partial_shape_to_tensor(self._row_shape), # pylint: disable=protected-access output_shapes=nest.flatten( sparse.as_dense_shapes(self.output_shapes, self.output_classes)), output_types=nest.flatten( sparse.as_dense_types(self.output_types, self.output_classes)))
def __init__(self, input_dataset, batch_size, row_shape): """See `Dataset.dense_to_sparse_batch()` for more details.""" super(DenseToSparseBatchDataset, self).__init__() if not isinstance(input_dataset.output_types, dtypes.DType): raise TypeError("DenseToSparseDataset requires an input whose elements " "have a single component, whereas the input has %r." % input_dataset.output_types) self._input_dataset = input_dataset self._batch_size = batch_size # pylint: disable=protected-access self._row_shape = dataset_ops._partial_shape_to_tensor(row_shape)