Add Cyclic Group Representation (CGR) class

torchhd/__init__.py

@@ -37,7 +37,9 @@
 from torchhd.tensors.fhrr import FHRRTensor
 from torchhd.tensors.bsbc import BSBCTensor
 from torchhd.tensors.vtb import VTBTensor
+from torchhd.tensors.basemcr import BaseMCRTensor
 from torchhd.tensors.mcr import MCRTensor
+from torchhd.tensors.cgr import CGRTensor
 
 from torchhd.functional import (
     ensure_vsa_tensor,
@@ -91,7 +93,9 @@
     "FHRRTensor",
     "BSBCTensor",
     "VTBTensor",
+    "BaseMCRTensor",
     "MCRTensor",
+    "CGRTensor",
     "functional",
     "embeddings",
     "structures",

torchhd/functional.py

@@ -36,6 +36,7 @@
 from torchhd.tensors.bsbc import BSBCTensor
 from torchhd.tensors.vtb import VTBTensor
 from torchhd.tensors.mcr import MCRTensor
+from torchhd.tensors.cgr import CGRTensor
 from torchhd.types import VSAOptions
 
 
@@ -93,6 +94,8 @@ def get_vsa_tensor_class(vsa: VSAOptions) -> Type[VSATensor]:
         return VTBTensor
     elif vsa == "MCR":
         return MCRTensor
+    elif vsa == "CGR":
+        return CGRTensor
 
     raise ValueError(f"Provided VSA model is not supported, specified: {vsa}")
 
@@ -361,7 +364,7 @@ def level(
         device=span_hv.device,
     ).as_subclass(vsa_tensor)
 
-    if vsa == "BSBC" or vsa == "MCR":
+    if vsa == "BSBC" or vsa == "MCR" or vsa == "CGR":
         hv.block_size = span_hv.block_size
 
     for i in range(num_vectors):
@@ -588,7 +591,7 @@ def circular(
         device=span_hv.device,
     ).as_subclass(vsa_tensor)
 
-    if vsa == "BSBC" or vsa == "MCR":
+    if vsa == "BSBC" or vsa == "MCR" or vsa == "CGR":
         hv.block_size = span_hv.block_size
 
     mutation_history = deque()