Merge branch 'updates' into 'master'

Updates

See merge request !53

bob/pipelines/__init__.py

@@ -3,7 +3,7 @@ from . import transformers  # noqa
 from . import utils  # noqa
 from . import xarray as xr  # noqa
 from .sample import DelayedSample
-from .sample import DelayedSampleSet
+from .sample import DelayedSampleSet, DelayedSampleSetCached
 from .sample import Sample
 from .sample import SampleSet
 from .sample import SampleBatch

bob/pipelines/sample.py

@@ -187,6 +187,21 @@ class DelayedSampleSet(SampleSet):
         return self._load()
 
 
+class DelayedSampleSetCached(DelayedSampleSet):
+    """A cached version of DelayedSampleSet"""
+
+    def __init__(self, load, parent=None, **kwargs):
+        super().__init__(load, parent=parent, kwargs=kwargs)
+        self._data = None
+        _copy_attributes(self, parent, kwargs)
+
+    @property
+    def samples(self):
+        if self._data is None:
+            self._data = self._load()
+        return self._data
+
+
 class SampleBatch(Sequence, _ReprMixin):
     """A batch of samples that looks like [s.data for s in samples]
 

bob/pipelines/tests/test_samples.py

@@ -8,7 +8,7 @@ import h5py
 import numpy as np
 
 from bob.pipelines import DelayedSample
-from bob.pipelines import DelayedSampleSet
+from bob.pipelines import DelayedSampleSet, DelayedSampleSetCached
 from bob.pipelines import Sample
 from bob.pipelines import SampleSet
 from bob.pipelines import hdf5_to_sample
@@ -56,6 +56,19 @@ def test_sampleset_collection():
         assert len(sampleset) == n_samples
         assert sampleset.samples == samples
 
+    # Testing delayed sampleset cached
+    with tempfile.TemporaryDirectory() as dir_name:
+
+        samples = [Sample(data, key=str(i)) for i, data in enumerate(X)]
+        filename = os.path.join(dir_name, "samples.pkl")
+        with open(filename, "wb") as f:
+            f.write(pickle.dumps(samples))
+
+        sampleset = DelayedSampleSetCached(functools.partial(_load, filename), key=1)
+
+        assert len(sampleset) == n_samples
+        assert sampleset.samples == samples
+
 
 def test_sample_hdf5():
     n_samples = 10

bob/pipelines/tests/test_wrappers.py

@@ -189,8 +189,9 @@ def test_checkpoint_function_sample_transfomer():
         )
 
         features = transformer.transform(samples)
-        # Checking if we have 8 chars in the second level
-        assert len(features[0]._load.args[0].split("/")[-2]) == 8
+        # Checking if we can cast the has as integer
+        assert isinstance(int(features[0]._load.args[0].split("/")[-2]), int)
+
         _assert_all_close_numpy_array(oracle, [s.data for s in features])
 
 

bob/pipelines/utils.py

@@ -2,8 +2,6 @@ import pickle
 
 import nose
 import numpy as np
-import random
-import string
 
 
 def is_picklable(obj):
@@ -80,9 +78,10 @@ def isinstance_nested(instance, attribute, isinstance_of):
         return isinstance_nested(getattr(instance, attribute), attribute, isinstance_of)
 
 
-def hash_string(key, bucket_size=1000, word_length=8):
+def hash_string(key, bucket_size=1000):
     """
     Generates a hash code given a string.
+    The have is given by the `sum(ord([string])) mod bucket_size`
     
     Parameters
     ----------
@@ -93,18 +92,5 @@ def hash_string(key, bucket_size=1000, word_length=8):
     bucket_size: int
       Size of the hash table.
 
-    word_lenth: str
-      Size of the output string
-
-    
-
     """
-    letters = string.ascii_lowercase
-
-    # Getting an integer value from the key
-    # and mod `n_slots` to have values between 0 and 1000
-    string_seed = sum([ord(i) for i in (key)]) % bucket_size
-
-    # Defining the seed so we have predictable values
-    random.seed(string_seed)
-    return "".join(random.choice(letters) for i in range(word_length))
+    return str(sum([ord(i) for i in (key)]) % bucket_size)