Fix HDF5 dataset

1. Don't provide parameters for superclass __new__ method (object.__new__).
2. Add function calls where required.
3. Fix interaction with iterators.

Author: amikholap

pylearn2/datasets/hdf5.py

@@ -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
@@ -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):
@@ -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)
@@ -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):
@@ -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):