def iterator(self,
mode=None,
batch_size=None,
num_batches=None,
topo=None,
targets=None,
rng=None):
# TODO: Refactor, deduplicate with DenseDesignMatrix.iterator
if mode is None:
if hasattr(self, '_iter_subset_class'):
mode = self._iter_subset_class
else:
raise ValueError('iteration mode not provided and no default '
'mode set for %s' % str(self))
else:
mode = resolve_iterator_class(mode)
if batch_size is None:
batch_size = getattr(self, '_iter_batch_size', None)
if num_batches is None:
num_batches = getattr(self, '_iter_num_batches', None)
if topo is None:
topo = getattr(self, '_iter_topo', False)
if targets is None:
targets = getattr(self, '_iter_targets', False)
if rng is None and mode.stochastic:
rng = self.rng
return FiniteDatasetIteratorPyTables(
self, mode(self.X.shape[0], batch_size, num_batches, rng), topo,
targets)
def iterator(self,
mode=None,
batch_size=None,
num_batches=None,
topo=None,
targets=None,
rng=None,
data_specs=None,
return_tuple=False):
warnings.warn(
"Overloading this method is not necessary with the new "
"interface change and this will be removed around November "
"7th 2013",
stacklevel=2)
if topo is not None or targets is not None:
if data_specs is not None:
raise ValueError(
"In DenseDesignMatrix.iterator, both "
"the `data_specs` argument and deprecated arguments "
"`topo` or `targets` were provided.",
(data_specs, topo, targets))
warnings.warn(
"Usage of `topo` and `target` arguments are being "
"deprecated, and will be removed around November 7th, "
"2013. `data_specs` should be used instead.",
stacklevel=2)
# build data_specs from topo and targets if needed
if topo is None:
topo = getattr(self, '_iter_topo', False)
if topo:
# self.iterator is called without a data_specs, and with
# "topo=True", so we use the default topological space
# stored in self.X_topo_space
assert self.X_topo_space is not None
X_space = self.X_topo_space
else:
X_space = self.X_space
if targets is None:
targets = getattr(self, '_iter_targets', False)
if targets:
assert self.y is not None
y_space = self.data_specs[0][1]
space = (X_space, y_space)
source = ('features', 'targets')
else:
space = X_space
source = 'features'
data_specs = (space, source)
_deprecated_interface = True
else:
_deprecated_interface = False
# TODO: Refactor
if mode is None:
if hasattr(self, '_iter_subset_class'):
mode = self._iter_subset_class
else:
raise ValueError('iteration mode not provided and no default '
'mode set for %s' % str(self))
else:
mode = resolve_iterator_class(mode)
if batch_size is None:
batch_size = getattr(self, '_iter_batch_size', None)
if num_batches is None:
num_batches = getattr(self, '_iter_num_batches', None)
if rng is None and mode.stochastic:
rng = self.rng
if data_specs is None:
data_specs = self._iter_data_specs
if _deprecated_interface:
return FiniteDatasetIteratorPyTables(self,
mode(self.X.shape[0],
batch_size, num_batches,
rng),
data_specs=data_specs,
return_tuple=return_tuple)
else:
return FiniteDatasetIterator(self,
mode(self.X.shape[0], batch_size,
num_batches, rng),
data_specs=data_specs,
return_tuple=return_tuple)