Changelog for python311-cotengra-0.6.2-lp160.2.1.noarch.rpm :

* Tue May 28 2024 John Paul Adrian Glaubitz - Update to version 0.6.2
* Fix final, output contractions being mistakenly marked as not tensordot-able.
* When `implementation=\"autoray\"` don\'t require a backend to have both `einsum` and `tensordot`, instead fallback to `cotengra`\'s own.- from version 0.6.1
* 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 variable `OMP_NUM_THREADS`, or 3. `os.cpu_count()`.
* Add [RandomGreedyOptimizer](cotengra.pathfinders.path_basic.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](cotengra.pathfinders.path_basic.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 for `RandomGreedyOptimizer` when `cotengrust` is present, since its version of `optimize_random_greedy_track_flops` releases the GIL.
* Significantly improve both the speed and memory usage of [`SliceFinder`](cotengra.slicer.SliceFinder)
* Alias `tree.total_cost()` to `tree.combo_cost()`- from version 0.6.0
* All input node legs and pre-processing steps are now calculated lazily, allowing slicing of indices including those \'simplified\' away {issue}`31`.
* Make [`tree.peak_size`](cotengra.ContractionTree.peak_size) more accurate, by taking max assuming left, right and parent intermediate tensors are all present at the same time.
* 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 supplying `opt = HyperOptimizer(simulated_annealing_opts={})`.
* Add [`ContractionTree.plot_flat`](cotengra.plot.plot_tree_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`](cotengra.plot.plot_hypergraph): support showing hyper outer indices, multi-edges, and automatic unique coloring of nodes and indices (to match `plot_flat`).
* Add [`ContractionTree.plot_circuit](cotengra.plot.plot_tree_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`](cotengra.ContractionTree.restore_ind) for \'unslicing\' or \'unprojecting\' previously removed indices.
* [`ContractionTree.from_path`](cotengra.ContractionTree.from_path): add option `complete` to automatically complete the tree given an incomplete path (usually disconnected subgraphs - {issue}`29`).
* Add [`ContractionTree.get_incomplete_nodes`](cotengra.ContractionTree.get_incomplete_nodes) for finding all uncontracted childless-parentless node groups.
* Add [`ContractionTree.autocomplete`](cotengra.ContractionTree.autocomplete) for automatically completing a contraction tree, using above method.
* [`tree.plot_flat`](cotengra.plot.plot_tree_flat): show any preprocessing steps and optionally list sliced indices
* Add [get_rng](cotengra.utils.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 for `backend=\"jax\"` only.
* Add [`tree.describe`](cotengra.ContractionTree.describe) for a various levels of information about a tree, e.g. `tree.describe(\"full\")` and `tree.describe(\"concise\")`.
* Add [ctg.GreedyOptimizer](cotengra.pathfinders.path_basic.GreedyOptimizer) and [ctg.OptimalOptimizer](cotengra.pathfinders.path_basic.OptimalOptimizer) to the top namespace.
* Add [ContractionTree.benchmark](cotengra.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: ({issue}`27`).- Drop patches for issues fixed upstream
* fix-check.patch
* Thu Mar 21 2024 Guillaume GARDET - Fix test for aarch64 with:
* fix-check.patch
* Tue Feb 27 2024 Ben Greiner - Initial specfile for v0.5.6 required by quimb