Merge pull request #500 from BindsNET/hananel

Fix issues cause by torch._six upgrade

bindsnet/datasets/collate.py

@@ -73,15 +73,15 @@ def time_aware_collate(batch):
             return torch.as_tensor(batch)
     elif isinstance(elem, float):
         return torch.tensor(batch, dtype=torch.float64)
-    elif isinstance(elem, int_classes):
+    elif isinstance(elem, int):
         return torch.tensor(batch)
     elif isinstance(elem, string_classes):
         return batch
-    elif isinstance(elem, container_abcs.Mapping):
+    elif isinstance(elem, collections.Mapping):
         return {key: time_aware_collate([d[key] for d in batch]) for key in elem}
     elif isinstance(elem, tuple) and hasattr(elem, "_fields"):  # namedtuple
         return elem_type(*(time_aware_collate(samples) for samples in zip(*batch)))
-    elif isinstance(elem, container_abcs.Sequence):
+    elif isinstance(elem, collections.Sequence):
         transposed = zip(*batch)
         return [time_aware_collate(samples) for samples in transposed]
 

bindsnet/pipeline/base_pipeline.py

@@ -25,11 +25,11 @@ def recursive_to(item, device):
         return item.to(device)
     elif isinstance(item, (string_classes, int, float, bool)):
         return item
-    elif isinstance(item, container_abcs.Mapping):
+    elif isinstance(item, collections.Mapping):
         return {key: recursive_to(item[key], device) for key in item}
     elif isinstance(item, tuple) and hasattr(item, "_fields"):
         return type(item)(*(recursive_to(i, device) for i in item))
-    elif isinstance(item, container_abcs.Sequence):
+    elif isinstance(item, collections.Sequence):
         return [recursive_to(i, device) for i in item]
     else:
         raise NotImplementedError(f"Target type {type(item)} not supported.")