Remove default schemes

fuel/datasets/base.py

@@ -28,10 +28,6 @@ class Dataset(object):
         'targets')`` for MNIST (regardless of which data the data stream
         actually requests). Any implementation of a dataset should set this
         attribute on the class (or at least before calling ``super``).
-    default_iteration_scheme : :class:`.IterationScheme`, optional
-        The default iteration scheme that will be used by
-        :meth:`get_default_stream` to create a data stream without needing
-        to specify what iteration scheme to use.
 
     Notes
     -----
@@ -139,12 +135,6 @@ def get_data(self, state=None, request=None):
         """
         raise NotImplementedError
 
-    def get_default_stream(self):
-        """Use the default iteration scheme to construct a data stream."""
-        if not hasattr(self, 'default_scheme'):
-            raise ValueError("Dataset does not provide a default iterator")
-        return DataStream(self, iteration_scheme=self.default_scheme)
-
     def filter_sources(self, data):
         """Filter the requested sources from those provided by the dataset.
 

fuel/datasets/binarized_mnist.py

@@ -61,7 +61,6 @@ def __init__(self, which_set, **kwargs):
             raise ValueError("available splits are 'train', 'valid' and "
                              "'test'")
         self.num_examples = 50000 if which_set == 'train' else 10000
-        self.default_scheme = SequentialScheme(self.num_examples, 1)
         super(BinarizedMNIST, self).__init__(**kwargs)
 
         self.which_set = which_set

fuel/datasets/cifar10.py

@@ -57,7 +57,6 @@ def __init__(self, which_set, start=None, stop=None, **kwargs):
         if start is None:
             start = 0
         self.num_examples = stop - start
-        self.default_scheme = SequentialScheme(self.num_examples, 1)
         super(CIFAR10, self).__init__(**kwargs)
 
         self.which_set = which_set

fuel/datasets/container.py

@@ -23,8 +23,6 @@ class ContainerDataset(Dataset):
     :class:`BatchDataStream` data stream.
 
     """
-    default_scheme = None
-
     def __init__(self, container, sources=None):
         if isinstance(container, dict):
             self.provides_sources = (sources if sources is not None

fuel/datasets/mnist.py

@@ -58,7 +58,6 @@ def __init__(self, which_set, start=None, stop=None, binary=False,
         if start is None:
             start = 0
         self.num_examples = stop - start
-        self.default_scheme = SequentialScheme(self.num_examples, 1)
         super(MNIST, self).__init__(**kwargs)
 
         self.which_set = which_set

fuel/datasets/text.py

@@ -49,7 +49,8 @@ class TextFile(Dataset):
     >>> text_data = TextFile(files=['sentences.txt'],
     ...                      dictionary=dictionary, bos_token=None,
     ...                      preprocess=lower)
-    >>> for data in text_data.get_default_stream().get_epoch_iterator():
+    >>> from fuel.streams import DataStream
+    >>> for data in DataStream(text_data).get_epoch_iterator():
     ...     print(data)
     ([2, 0, 3, 0, 1],)
     ([2, 0, 4, 1],)
@@ -62,7 +63,6 @@ class TextFile(Dataset):
 
     """
     provides_sources = ('features',)
-    default_scheme = None
 
     def __init__(self, files, dictionary, bos_token='<S>', eos_token='</S>',
                  unk_token='<UNK>', level='word', preprocess=None):

tests/test_binarized_mnist.py

@@ -1,10 +1,11 @@
-import numpy
 from numpy.testing import assert_raises
 
 from fuel.datasets import BinarizedMNIST
+from tests import skip_if_not_available
 
 
 def test_mnist():
+    skip_if_not_available(datasets=['binarized_mnist'])
     mnist_train = BinarizedMNIST('train')
     assert len(mnist_train.features) == 50000
     assert mnist_train.num_examples == 50000

tests/test_datasets.py

@@ -18,7 +18,7 @@
 def test_dataset():
     data = [1, 2, 3]
     # The default stream requests an example at a time
-    stream = ContainerDataset(data).get_default_stream()
+    stream = DataStream(ContainerDataset(data))
     epoch = stream.get_epoch_iterator()
     assert list(epoch) == list(zip(data))
 
@@ -33,7 +33,7 @@ def test_dataset():
 def test_data_stream_mapping():
     data = [1, 2, 3]
     data_doubled = [2, 4, 6]
-    stream = ContainerDataset(data).get_default_stream()
+    stream = DataStream(ContainerDataset(data))
     wrapper1 = DataStreamMapping(
         stream, lambda d: (2 * d[0],))
     assert list(wrapper1.get_epoch_iterator()) == list(zip(data_doubled))
@@ -49,7 +49,7 @@ def test_data_stream_mapping_sort():
             [3, 2, 1]]
     data_sorted = [[1, 2, 3]] * 3
     data_sorted_rev = [[3, 2, 1]] * 3
-    stream = ContainerDataset(data).get_default_stream()
+    stream = DataStream(ContainerDataset(data))
     wrapper1 = DataStreamMapping(stream,
                                  mapping=SortMapping(operator.itemgetter(0)))
     assert list(wrapper1.get_epoch_iterator()) == list(zip(data_sorted))
@@ -71,7 +71,7 @@ def test_data_stream_mapping_sort_multisource_ndarrays():
     data_sorted = [(numpy.array([1, 2, 3]), numpy.array([6, 5, 4])),
                    (numpy.array([1, 2, 3]), numpy.array([4, 6, 5])),
                    (numpy.array([1, 2, 3]), numpy.array([4, 5, 6]))]
-    stream = ContainerDataset(data).get_default_stream()
+    stream = DataStream(ContainerDataset(data))
     wrapper = DataStreamMapping(stream,
                                 mapping=SortMapping(operator.itemgetter(0)))
     for output, ground_truth in zip(wrapper.get_epoch_iterator(), data_sorted):
@@ -87,7 +87,7 @@ def test_data_stream_mapping_sort_multisource():
     data_sorted = [([1, 2, 3], [6, 5, 4]),
                    ([1, 2, 3], [4, 6, 5]),
                    ([1, 2, 3], [4, 5, 6])]
-    stream = ContainerDataset(data).get_default_stream()
+    stream = DataStream(ContainerDataset(data))
     wrapper = DataStreamMapping(stream,
                                 mapping=SortMapping(operator.itemgetter(0)))
     assert list(wrapper.get_epoch_iterator()) == data_sorted
@@ -96,7 +96,7 @@ def test_data_stream_mapping_sort_multisource():
 def test_data_stream_filter():
     data = [1, 2, 3]
     data_filtered = [1, 3]
-    stream = ContainerDataset(data).get_default_stream()
+    stream = DataStream(ContainerDataset(data))
     wrapper = DataStreamFilter(stream, lambda d: d[0] % 2 == 1)
     assert list(wrapper.get_epoch_iterator()) == list(zip(data_filtered))
 
@@ -105,27 +105,27 @@ def test_floatx():
     x = [numpy.array(d, dtype="float64") for d in [[1, 2], [3, 4]]]
     y = [numpy.array(d, dtype="int64") for d in [1, 2, 3]]
     dataset = ContainerDataset(OrderedDict([("x", x), ("y", y)]))
-    data = next(ForceFloatX(dataset.get_default_stream()).get_epoch_iterator())
+    data = next(ForceFloatX(DataStream(dataset)).get_epoch_iterator())
     assert str(data[0].dtype) == floatX
     assert str(data[1].dtype) == "int64"
 
 
 def test_sources_selection():
     features = [5, 6, 7, 1]
     targets = [1, 0, 1, 1]
-    stream = ContainerDataset(OrderedDict(
-        [('features', features), ('targets', targets)])).get_default_stream()
+    stream = DataStream(ContainerDataset(OrderedDict(
+        [('features', features), ('targets', targets)])))
     assert list(stream.get_epoch_iterator()) == list(zip(features, targets))
 
-    stream = ContainerDataset({'features': features, 'targets': targets},
-                              sources=('targets',)).get_default_stream()
+    stream = DataStream(ContainerDataset(
+        {'features': features, 'targets': targets},
+        sources=('targets',)))
     assert list(stream.get_epoch_iterator()) == list(zip(targets))
 
 
 def test_data_driven_epochs():
     class TestDataset(ContainerDataset):
         sources = ('data',)
-        default_scheme = ConstantScheme(1)
 
         def __init__(self):
             self.data = [[1, 2, 3, 4],
@@ -152,7 +152,7 @@ def get_data(self, state, request):
     epochs = []
     epochs.append([([1],), ([2],), ([3],), ([4],)])
     epochs.append([([5],), ([6],), ([7],), ([8],)])
-    stream = TestDataset().get_default_stream()
+    stream = DataStream(TestDataset(), iteration_scheme=ConstantScheme(1))
     assert list(stream.get_epoch_iterator()) == epochs[0]
     assert list(stream.get_epoch_iterator()) == epochs[1]
     assert list(stream.get_epoch_iterator()) == epochs[0]
@@ -206,7 +206,7 @@ def test_cache():
 
 
 def test_batch_data_stream():
-    stream = ContainerDataset([1, 2, 3, 4, 5]).get_default_stream()
+    stream = DataStream(ContainerDataset([1, 2, 3, 4, 5]))
     batches = list(BatchDataStream(stream, ConstantScheme(2))
                    .get_epoch_iterator())
     expected = [(numpy.array([1, 2]),),
@@ -223,16 +223,15 @@ def try_strict(strictness):
             .get_epoch_iterator())
     assert_raises(ValueError, try_strict, 2)
     assert len(try_strict(1)) == 2
-    stream2 = ContainerDataset([1, 2, 3, 4, 5, 6]).get_default_stream()
+    stream2 = DataStream(ContainerDataset([1, 2, 3, 4, 5, 6]))
     assert len(list(BatchDataStream(stream2, ConstantScheme(2), strictness=2)
                     .get_epoch_iterator())) == 3
 
 
 def test_padding_data_stream():
     # 1-D sequences
     stream = BatchDataStream(
-        ContainerDataset([[1], [2, 3], [], [4, 5, 6], [7]])
-        .get_default_stream(),
+        DataStream(ContainerDataset([[1], [2, 3], [], [4, 5, 6], [7]])),
         ConstantScheme(2))
     mask_stream = PaddingDataStream(stream)
     assert mask_stream.sources == ("data", "data_mask")
@@ -249,8 +248,8 @@ def test_padding_data_stream():
 
     # 2D sequences
     stream2 = BatchDataStream(
-        ContainerDataset([numpy.ones((3, 4)), 2 * numpy.ones((2, 4))])
-        .get_default_stream(),
+        DataStream(ContainerDataset([numpy.ones((3, 4)),
+                                     2 * numpy.ones((2, 4))])),
         ConstantScheme(2))
     it = PaddingDataStream(stream2).get_epoch_iterator()
     data, mask = next(it)
@@ -261,8 +260,7 @@ def test_padding_data_stream():
 
     # 2 sources
     stream3 = PaddingDataStream(BatchDataStream(
-        ContainerDataset(dict(features=[[1], [2, 3], []],
-                              targets=[[4, 5, 6], [7]]))
-        .get_default_stream(),
+        DataStream(ContainerDataset(dict(features=[[1], [2, 3], []],
+                              targets=[[4, 5, 6], [7]]))),
         ConstantScheme(2)))
     assert len(next(stream3.get_epoch_iterator())) == 4

tests/test_text.py

@@ -5,6 +5,7 @@
 from six.moves import cPickle
 
 from fuel.datasets import TextFile
+from fuel.streams import DataStream
 
 
 def lower(s):
@@ -25,7 +26,7 @@ def test_text():
     text_data = TextFile(files=[sentences1, sentences2],
                          dictionary=dictionary, bos_token=None,
                          preprocess=lower)
-    stream = text_data.get_default_stream()
+    stream = DataStream(text_data)
     epoch = stream.get_epoch_iterator()
     assert len(list(epoch)) == 4
     epoch = stream.get_epoch_iterator()
@@ -46,6 +47,6 @@ def test_text():
     text_data = TextFile(files=[sentences1, sentences2],
                          dictionary=dictionary, preprocess=lower,
                          level="character")
-    sentence = next(text_data.get_default_stream().get_epoch_iterator())[0]
+    sentence = next(DataStream(text_data).get_epoch_iterator())[0]
     assert sentence[:3] == [27, 19, 7]
     assert sentence[-3:] == [2, 4, 28]