File python-cotengra.changes of Package python-cotengra

Overview Repositories Revisions Requests Users Attributes Meta

File python-cotengra.changes of Package python-cotengra

-------------------------------------------------------------------
Tue May 28 07:54:10 UTC 2024 - John Paul Adrian Glaubitz <adrian.glaubitz@suse.com>

- 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 09:04:19 UTC 2024 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Fix test for aarch64 with:
  * fix-check.patch

-------------------------------------------------------------------
Tue Feb 27 20:19:35 UTC 2024 - Ben Greiner <code@bnavigator.de>

- Initial specfile for v0.5.6 required by quimb

Places

File python-cotengra.changes of Package python-cotengra

Places