Add Cyclic Group Representation (CGR) class

README.md

@@ -95,6 +95,7 @@ Currently, the library supports the following HDC/VSA models:
 - [Holographic Reduced Representations (HRR)](https://torchhd.readthedocs.io/en/stable/generated/torchhd.HRRTensor.html)
 - [Fourier Holographic Reduced Representations (FHRR)](https://torchhd.readthedocs.io/en/stable/generated/torchhd.FHRRTensor.html)
 - [Binary Sparse Block Codes (B-SBC)](https://torchhd.readthedocs.io/en/stable/generated/torchhd.BSBCTensor.html)
+- [Cyclic Group Representation (CGR)](https://torchhd.readthedocs.io/en/stable/generated/torchhd.CGRTensor.html)
 - [Modular Composite Representation (MCR)](https://torchhd.readthedocs.io/en/stable/generated/torchhd.MCRTensor.html)
 - [Vector-Derived Transformation Binding (VTB)](https://torchhd.readthedocs.io/en/stable/generated/torchhd.VTBTensor.html)
 

docs/torchhd.rst

@@ -10,7 +10,7 @@ This module consists of the basic hypervector generation functions and operation
 Basis-hypervector sets
 ----------------------------------
 
-.. autosummary:: 
+.. autosummary::
     :toctree: generated/
     :template: function.rst
 
@@ -20,7 +20,7 @@ Basis-hypervector sets
     level
     thermometer
     circular
-    
+
 
 Operations
 --------------------
@@ -51,7 +51,7 @@ Similarities
 .. autosummary::
     :toctree: generated/
     :template: function.rst
-    
+
     cosine_similarity
     dot_similarity
     hamming_similarity
@@ -87,7 +87,9 @@ VSA Models
     HRRTensor
     FHRRTensor
     BSBCTensor
+    BaseMCRTensor
     MCRTensor
+    CGRTensor
     VTBTensor
 
 
@@ -97,7 +99,7 @@ Utilities
 .. autosummary::
     :toctree: generated/
     :template: function.rst
-    
+
     ensure_vsa_tensor
     map_range
     value_to_index

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()