Releases: jcmgray/cotengra
Releases · jcmgray/cotengra
v0.6.2
Bug fixes
- Fix final, output contractions being mistakenly marked as not tensordot-able.
- When contracting with
implementation="autoray"
, don't require a backend to have botheinsum
andtensordot
, instead fallback tocotengra
's own.
Full Changelog: v0.6.1...v0.6.2
v0.6.1
What's Changed
Breaking changes
- The number of workers initialized (for non-distributed pools) is now set to, in order of preference, 1. the environment variable
COTENGRA_NUM_WORKERS
, 2. the environment variableOMP_NUM_THREADS
, or 3.os.cpu_count()
.
Enhancements
- add RandomGreedyOptimizer which is a lightweight and performant randomized greedy optimizer, eschewing both hyper parameter tuning and full contraction tree construction, making it suitable for very large contractions (10,000s of tensors+).
- add optimize_random_greedy_track_flops which runs N trials of (random) greedy path optimization, whilst computing the FLOP count simultaneously. This or its accelerated rust counterpart in
cotengrust
is the driver for the above optimizer. - add
parallel="threads"
backend, and make it the default forRandomGreedyOptimizer
whencotengrust
is present, since its version ofoptimize_random_greedy_track_flops
releases the GIL. - significantly improve both the speed and memory usage of
SliceFinder
- alias
tree.total_cost()
totree.combo_cost()
Full Changelog: v0.6.0...v0.6.1
v0.6.0
Bug fixes
- all input node legs and pre-processing steps are now calculated lazily, allowing slicing of indices including those 'simplified' away #31.
- make
tree.peak_size
more accurate, by taking max assuming left, right and parent present at the same time.
Enhancements
- add simulated annealing tree refinement (in
path_simulated_annealing.py
), based on "Multi-Tensor Contraction for XEB Verification of Quantum Circuits" by Gleb Kalachev, Pavel Panteleev, Man-Hong Yung (arXiv:2108.05665), and the "treesa" implementation in OMEinsumContractionOrders.jl by Jin-Guo Liu and Pan Zhang. This can be accessed most easily by supplyingopt = HyperOptimizer(simulated_annealing_opts={})
. - add
ContractionTree.plot_flat
: a new method for plotting the contraction tree as a flat diagram showing all indices on
every intermediate (without requiring any graph layouts), which is useful for visualizing and understanding small contractions.
HyperGraph.plot
: support showing hyper outer indices, multi-edges, and automatic unique coloring of nodes and indices (to matchplot_flat
).- add `ContractionTree.plot_circuit for plotting the contraction tree as a circuit diagram, which is fast and useful for visualizing the traversal ordering for larger trees.
- add
ContractionTree.restore_ind
for 'unslicing' or 'unprojecting' previously removed indices. ContractionTree.from_path
: add optioncomplete
to automatically complete the tree given an incomplete path (usually disconnected subgraphs - #29).- add
ContractionTree.get_incomplete_nodes
for finding all uncontracted childless-parentless node groups. - add
ContractionTree.autocomplete
for automatically completing a contraction tree, using above method. tree.plot_flat
: show any preprocessing steps and optionally list sliced indices- add get_rng as a single entry point for getting or propagating a random number generator, to help determinism.
- set
autojit="auto"
for contractions, which by default turns on jit forbackend="jax"
only. - add
tree.describe
for a various levels of information about a tree, e.g.tree.describe("full")
andtree.describe("concise")
. - add ctg.GreedyOptimizer and ctg.OptimalOptimizer to the top namespace.
- add ContractionTree.benchmark for for automatically assessing hardware performance vs theoretical cost.
- contraction trees now have a
get_default_objective
method to return the objective function they were optimized with, for simpler further refinement or scoring, where it is now picked up automatically. - change the default 'sub' optimizer on divisive partition building algorithms to be
'greedy'
rather than'auto'
. This might make individual trials slightly worse but makes each cheaper, see discussion: #27.
Full Changelog: v0.5.6...v0.6.0
v0.5.6
Bug fixes
- fix a very rare but very infuriating bug related somehow to ReusableHyperOptimizer not being thread-safe and returning the wrong tree, especially on github actions
Full Changelog: v0.5.5...v0.5.6
v0.5.5
Enhancements
HyperOptimizer
: by default simply warn if an individual trial fails, rather than raising an exception. This is to ensure rare failures do not spoil an entire optimization run. The behavior can be controlled with theon_trial_error
argument.
Bug fixes
- fixed bug in greedy optimizer that produced negative scores and otherwise inaccurate scores.
- fixed bug for contraction with many inputs and also preprocessing steps
Full Changelog: v0.5.4...v0.5.5
v0.5.4
v0.5.3
Features
einsum
,einsum_tree
andeinsum_expression
: add support for all numpy input formats, including interleaved indices and ellipses.
Bug fixes
- remove some hidden
opt_einsum
dependence (via aPathOptimizer
method)
Full Changelog: v0.5.2...v0.5.3
v0.5.2
- add
array_contract_path
- support for checking size and flops of 'tree' of size 1.
Full Changelog: v0.5.1...v0.5.2
v0.5.1
Full Changelog: v0.5.0...v0.5.1
v0.5.0
- add
einsum
- add
einsum_tree
- add
einsum_expression
- add
array_contract
- add
array_contract_tree
- add
array_contract_expression
- add
AutoOptimizer
- add
AutoHQOptimizer
- remove most hard dependencies (
numpy
,opt_einsum
) - update
tree.plot_contractions
Full Changelog: v0.4.0...v0.5.0