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Fix HDF5 dataset #1545

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Fix HDF5 dataset #1545

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19 changes: 9 additions & 10 deletions pylearn2/datasets/hdf5.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,7 @@
import tables
except ImportError:
tables = None
import numpy as np
import warnings
from os.path import isfile
from pylearn2.compat import OrderedDict
Expand Down Expand Up @@ -86,9 +87,7 @@ def __new__(cls, filename, X=None, topo_view=None, y=None, load_all=False,
return HDF5DatasetDeprecated(filename, X, topo_view, y, load_all,
cache_size, **kwargs)
else:
return super(HDF5Dataset, cls).__new__(
cls, filename, sources, spaces, aliases, load_all, cache_size,
use_h5py, **kwargs)
return super(HDF5Dataset, cls).__new__(cls)

def __init__(self, filename, sources, spaces, aliases=None, load_all=False,
cache_size=None, use_h5py='auto', **kwargs):
Expand Down Expand Up @@ -204,7 +203,7 @@ def iterator(self, mode=None, data_specs=None, batch_size=None,
provided when the dataset object has been created will be used.
"""
if data_specs is None:
data_specs = (self._get_sources, self._get_spaces)
data_specs = (self._get_spaces(), self._get_sources())

[mode, batch_size, num_batches, rng, data_specs] = self._init_iterator(
mode, batch_size, num_batches, rng, data_specs)
Expand Down Expand Up @@ -240,7 +239,7 @@ def _get_spaces(self):
-------
A Space or a list of Spaces.
"""
space = [self.spaces[s] for s in self._get_sources]
space = [self.spaces[s] for s in self._get_sources()]
return space[0] if len(space) == 1 else tuple(space)

def get_data_specs(self, source_or_alias=None):
Expand Down Expand Up @@ -310,16 +309,16 @@ def get(self, sources, indexes):
sources[s], *e.args))
if (isinstance(indexes, (slice, py_integer_types)) or
len(indexes) == 1):
rval.append(sdata[indexes])
val = sdata[indexes]
else:
warnings.warn('Accessing non sequential elements of an '
'HDF5 file will be at best VERY slow. Avoid '
'using iteration schemes that access '
'random/shuffled data with hdf5 datasets!!')
val = []
[val.append(sdata[idx]) for idx in indexes]
rval.append(val)
return tuple(rval)
val = [sdata[idx] for idx in indexes]
val = tuple(tuple(row) for row in val)
rval.append(val)
return tuple(np.array(v) for v in rval)

@wraps(Dataset.get_num_examples, assigned=(), updated=())
def get_num_examples(self, source_or_alias=None):
Expand Down