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"""
Tokenization strategies for Instance Learning Graph (ILG) embeddings.
Provides multiple methods for converting ILGs into fixed-dimensional vectors:
- WLTokenizer: Weisfeiler-Leman color refinement (wraps existing wlplan pipeline)
- SimHashTokenizer: Random projection hashing
- ShortestPathTokenizer: Shortest-path kernel features
- GraphBPETokenizer: Byte-pair encoding on graph structures
- RandomTokenizer: deterministic random baseline embeddings
"""
from code.tokenization.base import TokenizationStrategy
from code.tokenization.multidomain import MultiDomainUnionTokenizer
from code.tokenization.random import RandomTokenizer
from code.tokenization.simhash import SimHashTokenizer
from code.tokenization.shortest_path import ShortestPathTokenizer
from code.tokenization.graphbpe import GraphBPETokenizer
__all__ = [
"TokenizationStrategy",
"MultiDomainUnionTokenizer",
"RandomTokenizer",
"SimHashTokenizer",
"ShortestPathTokenizer",
"GraphBPETokenizer",
]