Fix bincount for empty input (pytorch#9757)

Summary:
Added tests too. Fixes pytorch#9756 .
Pull Request resolved: pytorch#9757

Differential Revision: D8966879

Pulled By: soumith

fbshipit-source-id: 9f08a9d5d5d037db16319141d7a227a5efa23869

Author: vishwakftw

test/test_torch.py

@@ -8335,6 +8335,12 @@ def _test_bincount(self, device):
         with self.assertRaisesRegex(RuntimeError, 'same length'):
             torch.bincount(torch.tensor([1, 0], device=device),
                            torch.tensor([1., 0.3, 0.5], device=device))
+        # 1-d input with no elements and default minlength
+        self.assertEqual(torch.bincount(torch.tensor([], device=device, dtype=torch.long)),
+                         torch.zeros(0, dtype=torch.long, device=device))
+        # 1-d input with no elements and specified minlength
+        self.assertEqual(torch.bincount(torch.tensor([], device=device, dtype=torch.long), minlength=10),
+                         torch.zeros(10, dtype=torch.long, device=device))
 
         # test tensor method without weights
         long_counts = torch.tensor(

torch/_torch_docs.py

@@ -607,19 +607,22 @@ def parse_kwargs(desc):
 Count the frequency of each value in an array of non-negative ints.
 
 The number of bins (size 1) is one larger than the largest value in
-:attr:`input`. If :attr:`minlength` is specified, the number of bins is at least
-:attr:`minlength`. If ``n`` is the value at position ``i``,
+:attr:`input` unless :attr:`input` is empty, in which case the result is a
+tensor of size 0. If :attr:`minlength` is specified, the number of bins is at least
+:attr:`minlength` and if :attr:`input` is empty, then the result is tensor of size
+:attr:`minlength` filled with zeros. If ``n`` is the value at position ``i``,
 :math:`out[n] += weights[i]` if :attr:`weights` is specified else
 :math:`out[n] += 1`.
 
 Arguments:
     input (Tensor): 1-d int tensor
     weights (Tensor): optional, weight for each value in the input tensor.
         Should be of same size as input tensor.
-    minlength (int): optional, min number of bins. Should be non-negative.
+    minlength (int): optional, minimum number of bins. Should be non-negative.
 
 Shape:
-    output (Tensor): ``Size([max(input) + 1])``
+    output (Tensor): ``Size([max(input) + 1])`` if :attr:`input` is non-empty, else
+                     ``Size(0)``
 
 Example::