[fix] device cannot be Nonetype object. (#3822)

* fix device = none to cpu.

* fix singleton-comparison

* modify device is none

* fix use uva

* add docs

* add edge dataloader

* add doc

* fix trailing-whitespace

* modify default
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>

python/dgl/dataloading/dataloader.py

@@ -589,7 +589,9 @@ class DataLoader(torch.utils.data.DataLoader):
         The device of the generated MFGs in each iteration, which should be a
         PyTorch device object (e.g., ``torch.device``).
 
-        By default this value is the same as the device of :attr:`g`.
+        By default this value is None. If :attr:`use_uva` is True, MFGs and graphs will
+        generated in torch.cuda.current_device(), otherwise generated in the same device
+        of :attr:`g`.
     use_ddp : boolean, optional
         If True, tells the DataLoader to split the training set for each
         participating process appropriately using
@@ -686,7 +688,7 @@ class DataLoader(torch.utils.data.DataLoader):
 
       - Otherwise, both the sampling and subgraph construction will take place on the CPU.
     """
-    def __init__(self, graph, indices, graph_sampler, device='cpu', use_ddp=False,
+    def __init__(self, graph, indices, graph_sampler, device=None, use_ddp=False,
                  ddp_seed=0, batch_size=1, drop_last=False, shuffle=False,
                  use_prefetch_thread=None, use_alternate_streams=None,
                  pin_prefetcher=None, use_uva=False, **kwargs):
@@ -719,11 +721,18 @@ class DataLoader(torch.utils.data.DataLoader):
         except:     # pylint: disable=bare-except
             # ignore when it fails to convert to torch Tensors.
             pass
+
         if indices_device is None:
             if not hasattr(indices, 'device'):
                 raise AttributeError('Custom indices dataset requires a \"device\" \
                 attribute indicating where the indices is.')
             indices_device = indices.device
+
+        if device is None:
+            if use_uva:
+                device = torch.cuda.current_device()
+            else:
+                device = self.graph.device
         self.device = _get_device(device)
 
         # Sanity check - we only check for DGLGraphs.
@@ -868,12 +877,18 @@ class EdgeDataLoader(DataLoader):
                 g, train_eid, sampler,
                 batch_size=1024, shuffle=True, drop_last=False, num_workers=4)
     """
-    def __init__(self, graph, indices, graph_sampler, device='cpu', use_ddp=False,
+    def __init__(self, graph, indices, graph_sampler, device=None, use_ddp=False,
                  ddp_seed=0, batch_size=1, drop_last=False, shuffle=False,
                  use_prefetch_thread=False, use_alternate_streams=True,
                  pin_prefetcher=False,
                  exclude=None, reverse_eids=None, reverse_etypes=None, negative_sampler=None,
                  use_uva=False, **kwargs):
+
+        if device is None:
+            if use_uva:
+                device = torch.cuda.current_device()
+            else:
+                device = self.graph.device
         device = _get_device(device)
 
         if isinstance(graph_sampler, BlockSampler):