amend

test/test_specs.py

@@ -759,7 +759,7 @@ def test_equality_bounded(self):
             minimum, maximum + 1, torch.Size((1,)), device, dtype
         )
         assert ts != ts_other
-        if torch.has_cuda:
+        if torch.cuda.device_count():
             ts_other = BoundedTensorSpec(
                 minimum, maximum, torch.Size((1,)), "cuda:0", dtype
             )
@@ -795,7 +795,7 @@ def test_equality_onehot(self):
         )
         assert ts != ts_other
 
-        if torch.has_cuda:
+        if torch.cuda.device_count():
             ts_other = OneHotDiscreteTensorSpec(
                 n=n, device="cuda:0", dtype=dtype, use_register=use_register
             )
@@ -825,7 +825,7 @@ def test_equality_unbounded(self):
         ts_same = UnboundedContinuousTensorSpec(device=device, dtype=dtype)
         assert ts == ts_same
 
-        if torch.has_cuda:
+        if torch.cuda.device_count():
             ts_other = UnboundedContinuousTensorSpec(device="cuda:0", dtype=dtype)
             assert ts != ts_other
 
@@ -860,7 +860,7 @@ def test_equality_ndbounded(self):
         )
         assert ts != ts_other
 
-        if torch.has_cuda:
+        if torch.cuda.device_count():
             ts_other = BoundedTensorSpec(
                 low=minimum, high=maximum, device="cuda:0", dtype=dtype
             )
@@ -890,7 +890,7 @@ def test_equality_discrete(self):
         ts_other = DiscreteTensorSpec(n=n + 1, shape=shape, device=device, dtype=dtype)
         assert ts != ts_other
 
-        if torch.has_cuda:
+        if torch.cuda.device_count():
             ts_other = DiscreteTensorSpec(
                 n=n, shape=shape, device="cuda:0", dtype=dtype
             )
@@ -934,7 +934,7 @@ def test_equality_ndunbounded(self, shape):
         )
         assert ts != ts_other
 
-        if torch.has_cuda:
+        if torch.cuda.device_count():
             ts_other = UnboundedContinuousTensorSpec(
                 shape=shape, device="cuda:0", dtype=dtype
             )
@@ -948,7 +948,8 @@ def test_equality_ndunbounded(self, shape):
         ts_other = TestEquality._ts_make_all_fields_equal(
             BoundedTensorSpec(0, 1, torch.Size((1,)), device, dtype), ts
         )
-        assert ts != ts_other
+        # Unbounded and bounded without space are technically the same
+        assert ts == ts_other
 
     def test_equality_binary(self):
         n = 5
@@ -963,7 +964,7 @@ def test_equality_binary(self):
         ts_other = BinaryDiscreteTensorSpec(n=n + 5, device=device, dtype=dtype)
         assert ts != ts_other
 
-        if torch.has_cuda:
+        if torch.cuda.device_count():
             ts_other = BinaryDiscreteTensorSpec(n=n, device="cuda:0", dtype=dtype)
             assert ts != ts_other
 
@@ -1003,7 +1004,7 @@ def test_equality_multi_onehot(self, nvec):
         )
         assert ts != ts_other
 
-        if torch.has_cuda:
+        if torch.cuda.device_count():
             ts_other = MultiOneHotDiscreteTensorSpec(
                 nvec=nvec, device="cuda:0", dtype=dtype
             )
@@ -1041,7 +1042,7 @@ def test_equality_multi_discrete(self, nvec):
         ts_other = MultiDiscreteTensorSpec(nvec=other_nvec, device=device, dtype=dtype)
         assert ts != ts_other
 
-        if torch.has_cuda:
+        if torch.cuda.device_count():
             ts_other = MultiDiscreteTensorSpec(nvec=nvec, device="cuda:0", dtype=dtype)
             assert ts != ts_other