Update tests

hyperdimensional-computing · Mar 6, 2024 · f0b9232 · f0b9232
1 parent 5a75491
commit f0b9232
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Showing 3 changed files with 14 additions and 22 deletions.
diff --git a/torchhd/tests/test_embeddings.py b/torchhd/tests/test_embeddings.py
@@ -74,7 +74,7 @@ def test_dtype(self, vsa):
         if vsa == "BSC":
             assert emb(idx).dtype == torch.bool
         elif vsa == "MAP" or vsa == "HRR":
-            assert emb(idx).dtype == torch.float
+            assert emb(idx).dtype == torch.get_default_dtype()
         elif vsa == "FHRR":
             assert (
                 emb(idx).dtype == torch.complex64 or emb(idx).dtype == torch.complex32
@@ -142,7 +142,7 @@ def test_dtype(self, vsa):
         if vsa == "BSC":
             assert emb(idx).dtype == torch.bool
         elif vsa in {"MAP", "HRR", "VTB"}:
-            assert emb(idx).dtype == torch.float
+            assert emb(idx).dtype == torch.get_default_dtype()
         elif vsa == "FHRR":
             assert emb(idx).dtype in {torch.complex64, torch.complex32}
 
@@ -244,7 +244,7 @@ def test_dtype(self, vsa):
         if vsa == "BSC":
             assert emb(idx).dtype == torch.bool
         elif vsa in {"MAP", "HRR", "VTB"}:
-            assert emb(idx).dtype == torch.float
+            assert emb(idx).dtype == torch.get_default_dtype()
         elif vsa == "FHRR":
             assert emb(idx).dtype in {torch.complex64, torch.complex32}
 
@@ -295,7 +295,7 @@ def test_dtype(self, vsa):
         if vsa == "BSC":
             assert emb(idx).dtype == torch.bool
         elif vsa in {"MAP", "HRR", "VTB"}:
-            assert emb(idx).dtype == torch.float
+            assert emb(idx).dtype == torch.get_default_dtype()
         elif vsa == "FHRR":
             assert emb(idx).dtype in {torch.complex64, torch.complex32}
 
@@ -365,7 +365,7 @@ def test_dtype(self, vsa):
         if vsa == "BSC":
             assert emb(angle).dtype == torch.bool
         elif vsa == "MAP":
-            assert emb(angle).dtype == torch.float
+            assert emb(angle).dtype == torch.get_default_dtype()
         elif vsa == "FHRR":
             assert (
                 emb(angle).dtype == torch.complex64
@@ -441,7 +441,7 @@ def test_dtype(self, vsa):
         if vsa == "BSC":
             assert emb(angle).dtype == torch.bool
         elif vsa == "MAP":
-            assert emb(angle).dtype == torch.float
+            assert emb(angle).dtype == torch.get_default_dtype()
         elif vsa == "FHRR":
             assert (
                 emb(angle).dtype == torch.complex64
@@ -504,7 +504,7 @@ def test_dtype(self, vsa):
         emb = embeddings.Projection(in_features, out_features, vsa=vsa)
         x = torch.randn(1, in_features)
         if vsa == "MAP" or vsa == "HRR":
-            assert emb(x).dtype == torch.float
+            assert emb(x).dtype == torch.get_default_dtype()
         else:
             return
 
@@ -549,7 +549,7 @@ def test_dtype(self, vsa):
         emb = embeddings.Sinusoid(in_features, out_features, vsa=vsa)
         x = torch.randn(1, in_features)
         if vsa == "MAP" or vsa == "HRR":
-            assert emb(x).dtype == torch.float
+            assert emb(x).dtype == torch.get_default_dtype()
         else:
             return
 
@@ -611,7 +611,7 @@ def test_dtype(self, vsa):
         if vsa == "BSC":
             assert emb(x).dtype == torch.bool
         elif vsa == "MAP":
-            assert emb(x).dtype == torch.float
+            assert emb(x).dtype == torch.get_default_dtype()
         elif vsa == "FHRR":
             assert emb(x).dtype == torch.complex64 or emb(x).dtype == torch.complex32
         else:
@@ -664,9 +664,9 @@ def test_default_dtype(self, vsa):
         assert y.shape == (2, dimensions)
 
         if vsa == "HRR":
-            assert y.dtype == torch.float32
+            assert y.dtype == torch.get_default_dtype()
         elif vsa == "FHRR":
-            assert y.dtype == torch.complex64
+            assert fhrr_type_conversion[y.dtype] == torch.get_default_dtype()
         else:
             return
 

diff --git a/torchhd/tests/test_encodings.py b/torchhd/tests/test_encodings.py
@@ -141,10 +141,6 @@ def test_dtype(self, dtype):
         hv = torch.zeros(23, 1000, dtype=dtype).as_subclass(MAPTensor)
 
         if dtype in {torch.float16}:
-            # torch.product is not implemented on CPU for these dtypes
-            with pytest.raises(RuntimeError):
-                functional.multibind(hv)
-
             return
 
         res = functional.multibind(hv)
@@ -288,10 +284,6 @@ def test_dtype(self, dtype):
         hv = torch.zeros(23, 1000, dtype=dtype).as_subclass(MAPTensor)
 
         if dtype in {torch.float16}:
-            # torch.product is not implemented on CPU for these dtypes
-            with pytest.raises(RuntimeError):
-                functional.multibind(hv)
-
             return
 
         res = functional.bind_sequence(hv)

diff --git a/torchhd/tests/test_similarities.py b/torchhd/tests/test_similarities.py
@@ -118,7 +118,7 @@ def test_value(self, vsa, dtype):
             ).as_subclass(BSCTensor)
 
             res = functional.dot_similarity(hv, hv)
-            exp = torch.tensor([[10, 4], [4, 10]], dtype=torch.long)
+            exp = torch.tensor([[10, 4], [4, 10]], dtype=res.dtype)
             assert torch.all(res == exp).item()
 
         elif vsa == "FHRR":
@@ -339,7 +339,7 @@ def test_value(self, vsa, dtype):
             ).as_subclass(BSCTensor)
 
             res = functional.cosine_similarity(hv, hv)
-            exp = torch.tensor([[1, 0.4], [0.4, 1]], dtype=torch.float)
+            exp = torch.tensor([[1, 0.4], [0.4, 1]], dtype=res.dtype)
             assert torch.allclose(res, exp)
 
         elif vsa == "FHRR":
@@ -529,7 +529,7 @@ def test_value(self, vsa, dtype):
             ).as_subclass(BSCTensor)
 
             res = functional.hamming_similarity(hv, hv)
-            exp = torch.tensor([[10, 7], [7, 10]], dtype=torch.long)
+            exp = torch.tensor([[10, 7], [7, 10]], dtype=res.dtype)
             assert torch.all(res == exp).item()
 
         elif vsa == "FHRR":