TransformedLoader fix

docs/example_usage/changelog.rst

@@ -1,6 +1,9 @@
 CHANGELOG
 =========
 
+robustness 1.1.post2
+- Critical fix in :meth:`robustness.loaders.TransformedLoader`, allow for data shuffling
+
 robustness 1.1
 ''''''''''''''
 - Added ability to superclass ImageNet to make 

robustness/loaders.py

@@ -184,7 +184,8 @@ def __getattr__(self, attr):
         return getattr(self.data_loader, attr)
 
 def TransformedLoader(loader, func, transforms, workers=None, 
-        batch_size=None, do_tqdm=False, augment=False, fraction=1.0):
+        batch_size=None, do_tqdm=False, augment=False, fraction=1.0,
+        shuffle=True):
     '''
     This is a function that allows one to apply any given (fixed) 
     transformation to the output from the loader *once*. 
@@ -214,6 +215,8 @@ def TransformedLoader(loader, func, transforms, workers=None,
         fraction (float): fraction of image-label pairs in the output loader 
             which are transformed. The remainder is just original image-label 
             pairs from loader. 
+        shuffle (bool) : whether or not the resulting loader should shuffle every 
+            epoch (defaults to True)
 
     Returns:
         A loader and validation loader according to the
@@ -245,4 +248,4 @@ def TransformedLoader(loader, func, transforms, workers=None,
 
     dataset = folder.TensorDataset(ch.cat(new_ims, 0), ch.cat(new_targs, 0), transform=transforms)
     return ch.utils.data.DataLoader(dataset, num_workers=workers, 
-                                    batch_size=batch_size)
+                        batch_size=batch_size, shuffle=shuffle)

setup.py

@@ -22,7 +22,7 @@
   # Versions should comply with PEP440.  For a discussion on single-sourcing
   # the version across setup.py and the project code, see
   # https://packaging.python.org/en/latest/single_source_version.html
-  version='1.1.post1',
+  version='1.1.post2',
 
   description='Tools for Robustness',
   long_description=long_description,