Refactor get_random_contraction_path to use opt_einsum for better initial paths#47
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Refactor get_random_contraction_path to use opt_einsum for better initial paths#47
get_random_contraction_path to use opt_einsum for better initial paths#47Conversation
… initial paths The original `get_random_contraction_path` implementation generated paths with extremely high contraction costs due to its purely random nature. This frequently resulted in `OverflowError` (integers too large to convert to floats) when these paths were processed by the C++ API. To mitigate this, `get_random_contraction_path` now leverages `opt_einsum.contract_path` with a `RandomGreedy` optimizer. This approach produces more efficient initial contraction paths within a tunable time limit (`max_time`), effectively preventing overflows. Key changes: - Re-implemented `get_random_contraction_path` in `tnco/utils/tn.py` using `opt_einsum`. - Updated the `get_random_contraction_path` API to require `output_inds` and `dims`, and added a `max_time` parameter for the greedy search. - Promoted `opt_einsum` from a testing dependency to a core dependency in `pyproject.toml`. - Updated all callers in `tnco/app` and the test suite to support the new API and configurable `random_greedy_max_time`. - Fixed a bug in scalar contraction validation (where shared indices are empty) in both `include/tnco/ctree.hpp` and `tnco/ctree.py`. - Added `OverflowError` handling in `tests/test_core.py` to gracefully skip tests if costs remain excessively large.
At the moment, `tnco` guarantees that multiple calls, even on different python environments, will provide the same results. However, `opt_einsum.contract_path` does not provide a way to fix the seed across multiple Python environments.
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The original
get_random_contraction_pathimplementation generated paths with extremely high contraction costs. This frequently resulted inOverflowError(integers too large to convert to floats) when these paths were processed by the C++ API.To mitigate this,
get_random_contraction_pathnow leveragesopt_einsum.contract_pathwith aRandomGreedyoptimizer. This approach produces more efficient initial contraction paths within a tunable time limit (max_time), effectively preventing overflows.Key changes:
get_random_contraction_pathintnco/utils/tn.pyusingopt_einsum.get_random_contraction_pathAPI to requireoutput_indsanddims, and added amax_timeparameter for the greedy search.opt_einsumfrom a testing dependency to a core dependency inpyproject.toml.tnco/appand the test suite to support the new API and configurablerandom_greedy_max_time.include/tnco/ctree.hppandtnco/ctree.py.OverflowErrorhandling intests/test_core.pyto gracefully skip tests if costs remain excessively large.