Merge pull request #108 from bartvm/metaclass

Replaced the Python 2 __metaclass__ = ABCMeta with six's version

blocks/algorithms/__init__.py

@@ -3,11 +3,13 @@
 from collections import OrderedDict
 
 import theano
+from six import add_metaclass
 from theano import tensor
 
 from blocks.graph import ComputationGraph
 
 
+@add_metaclass(ABCMeta)
 class TrainingAlgorithm(object):
     """Base class for training algorithms.
 
@@ -18,8 +20,6 @@ class TrainingAlgorithm(object):
     called with a batch of training data as a parameter.
 
     """
-    __metaclass__ = ABCMeta
-
     @abstractmethod
     def initialize(self):
         """Initialize the training algorithm."""
@@ -38,6 +38,7 @@ def process_batch(self, batch):
         pass
 
 
+@add_metaclass(ABCMeta)
 class DifferentiableCostMinimizer(TrainingAlgorithm):
     """Minimizes a differentiable cost given as a Theano expression.
 
@@ -82,8 +83,6 @@ class the parameter used only inside scans are not fetched
         currently.
 
     """
-    __metaclass__ = ABCMeta
-
     def __init__(self, cost, params=None):
         self.cost = cost
         self.params = (params if params

blocks/bricks/__init__.py

@@ -7,6 +7,7 @@
 from itertools import chain
 
 import numpy
+from six import add_metaclass
 from theano import tensor
 
 from blocks.utils import (pack, repr_attrs, reraise_as, shared_floatx_zeros,
@@ -17,6 +18,7 @@
 logger = logging.getLogger(__name__)
 
 
+@add_metaclass(ABCMeta)
 class Brick(object):
     """A brick encapsulates Theano operations with parameters.
 
@@ -164,7 +166,6 @@ class Brick(object):
     linear_apply_output
 
     """
-    __metaclass__ = ABCMeta
     #: See :attr:`Brick.lazy`
     lazy = True
     #: See :attr:`Brick.print_shapes`

blocks/bricks/sequence_generators.py

@@ -1,6 +1,7 @@
 """Sequence generation framework."""
 from abc import ABCMeta, abstractmethod
 
+from six import add_metaclass
 from theano import tensor
 
 from blocks.bricks import (application, Brick, Initializable, Identity, lazy,
@@ -12,6 +13,7 @@
 from blocks.utils import dict_subset, dict_union, update_instance
 
 
+@add_metaclass(ABCMeta)
 class BaseSequenceGenerator(Initializable):
     """A generic sequence generator.
 
@@ -243,8 +245,6 @@ def initial_state(self, name, batch_size, *args, **kwargs):
 
 class AbstractEmitter(Brick):
     """The interface for the emitter component of a readout."""
-    __metaclass__ = ABCMeta
-
     @abstractmethod
     def emit(self, readouts):
         pass
@@ -258,15 +258,15 @@ def initial_outputs(self, batch_size, *args, **kwargs):
         pass
 
 
+@add_metaclass(ABCMeta)
 class AbstractFeedback(Brick):
     """The interface for the feedback component of a readout."""
-    __metaclass__ = ABCMeta
-
     @abstractmethod
     def feedback(self, outputs):
         pass
 
 
+@add_metaclass(ABCMeta)
 class AbstractReadout(AbstractEmitter, AbstractFeedback):
     """The interface for the readout component of a sequence generator.
 
@@ -275,21 +275,18 @@ class AbstractReadout(AbstractEmitter, AbstractFeedback):
        Explain what the methods should do.
 
     """
-    __metaclass__ = ABCMeta
-
     @abstractmethod
     def readout(self, **kwargs):
         pass
 
 
+@add_metaclass(ABCMeta)
 class AbstractAttentionTransition(BaseRecurrent):
     """A base class for a transition component of a sequence generator.
 
     A recurrent transition combined with an attention mechanism.
 
     """
-    __metaclass__ = ABCMeta
-
     @abstractmethod
     def apply(self, **kwargs):
         pass

blocks/datasets/__init__.py

@@ -2,10 +2,12 @@
 
 import numpy
 import six
+from six import add_metaclass
 
 from blocks.utils import update_instance
 
 
+@add_metaclass(ABCMeta)
 class Dataset(object):
     """A dataset.
 
@@ -36,8 +38,6 @@ class Dataset(object):
     simultaneously.
 
     """
-    __metaclass__ = ABCMeta
-
     def __init__(self, sources=None):
         if sources is not None:
             if not all(source in self.sources for source in sources):
@@ -130,6 +130,7 @@ def get_default_stream(self):
         return DataStream(self, iteration_scheme=self.default_scheme)
 
 
+@add_metaclass(ABCMeta)
 class ContainerDataset(Dataset):
     """Equips a Python container with the dataset interface.
 
@@ -200,8 +201,6 @@ class AbstractDataStream(object):
         given by the dataset.
 
     """
-    __metaclass__ = ABCMeta
-
     def __init__(self, iteration_scheme=None):
         self.iteration_scheme = iteration_scheme
 

blocks/datasets/schemes.py

@@ -1,7 +1,10 @@
 import itertools
 from abc import ABCMeta, abstractmethod
 
+from six import add_metaclass
 
+
+@add_metaclass(ABCMeta)
 class IterationScheme(object):
     """An iteration scheme.
 
@@ -23,8 +26,6 @@ class IterationScheme(object):
        https://docs.python.org/3.3/library/stdtypes.html#iterator-types
 
     """
-    __metaclass__ = ABCMeta
-
     @abstractmethod
     def get_request_iterator(self):
         raise NotImplementedError

blocks/extensions.py

@@ -1,7 +1,10 @@
 from __future__ import print_function
 from abc import ABCMeta, abstractmethod
 
+from six import add_metaclass
 
+
+@add_metaclass(ABCMeta)
 class TrainingExtension(object):
     """The base class for training extensions.
 
@@ -16,8 +19,6 @@ class TrainingExtension(object):
         The main loop to which the extension belongs.
 
     """
-    __metaclass__ = ABCMeta
-
     def dispatch(self, callback_name, *args):
         """Runs callback with the given name.
 

blocks/groundhog/__init__.py

@@ -3,6 +3,7 @@
 from abc import ABCMeta, abstractmethod
 
 import theano
+from six import add_metaclass
 from theano import tensor
 from theano import Variable
 
@@ -13,14 +14,13 @@
 logger = logging.getLogger(__name__)
 
 
+@add_metaclass(ABCMeta)
 class GroundhogIterator(object):
     """A base class for Groundhog compatible iterator.
 
     Has mock implementations of all required methods except `next`.
 
     """
-    __metaclass__ = ABCMeta
-
     def start(self, offset):
         pass
 

blocks/initialization.py

@@ -4,14 +4,14 @@
 import numpy
 import six
 import theano
+from six import add_metaclass
 
 from blocks.utils import update_instance
 
 
+@add_metaclass(ABCMeta)
 class NdarrayInitialization(object):
     """Base class specifying the interface for ndarray initialization."""
-    __metaclass__ = ABCMeta
-
     @abstractmethod
     def generate(self, rng, shape):
         """Generate an initial set of parameters from a given distribution.

blocks/log.py

@@ -2,7 +2,10 @@
 from abc import ABCMeta, abstractmethod
 from collections import defaultdict
 
+from six import add_metaclass
 
+
+@add_metaclass(ABCMeta)
 class AbstractTrainingStatus(object):
     """The base class for objects that carry the training status.
 
@@ -27,8 +30,6 @@ class AbstractTrainingStatus(object):
         printed or not.
 
     """
-    __metaclass__ = ABCMeta
-
     def __init__(self):
         self.iterations_done = 0
         self.epochs_done = 0
@@ -44,6 +45,7 @@ def __iter__(self):
         pass
 
 
+@add_metaclass(ABCMeta)
 class TrainingLogRow(object):
     """A convenience interface for a row of the training log.
 
@@ -88,8 +90,6 @@ class AbstractTrainingLog(object):
     to allow convenient access to the rows.
 
     """
-    __metaclass__ = ABCMeta
-
     @abstractmethod
     def get_status(self):
         """Returns the training status.

blocks/main_loop.py

@@ -1,10 +1,13 @@
 """The event-based main loop of Blocks."""
 from abc import ABCMeta
 
+from six import add_metaclass
+
 from blocks.log import TrainingLog
 from blocks.utils import update_instance
 
 
+@add_metaclass(ABCMeta)
 class MainLoop(object):
     """The standard main loop of Blocks.
 
@@ -39,8 +42,6 @@ class MainLoop(object):
         here.
 
     """
-    __metaclass__ = ABCMeta
-
     def __init__(self, model, data_stream, algorithm,
                  log=None, extensions=None):
         if not log:

blocks/monitoring/aggregation.py

@@ -2,11 +2,14 @@
 import logging
 from abc import ABCMeta, abstractmethod
 
+from six import add_metaclass
+
 from blocks.utils import shared_like, update_instance
 
 logger = logging.getLogger(__name__)
 
 
+@add_metaclass(ABCMeta)
 class AggregationScheme(object):
     """Specify how incrementally evaluate a Theano variable on a dataset.
 
@@ -25,8 +28,6 @@ class AggregationScheme(object):
         expression that computes the desired value on a single batch.
 
     """
-    __metaclass__ = ABCMeta
-
     @abstractmethod
     def get_aggregator(self):
         """Return a new Aggregator for this variable."""