[Build] Fix status check names#21
Merged
hughperkins merged 3 commits intomainfrom Jun 16, 2025
Merged
Conversation
CharlesMasson
approved these changes
Jun 10, 2025
duburcqa
approved these changes
Jun 16, 2025
Collaborator
Author
|
Thanks! |
hughperkins
added a commit
that referenced
this pull request
Apr 26, 2026
Introduce the helper machinery that the per-class to_torch / to_numpy methods will migrate to in subsequent commits. Existing public symbols (can_zerocopy, dlpack_to_torch, invalidate_zerocopy_cache, current_arch_is_cpu) are preserved as deprecated shims so the in-tree pre-rework callers continue to work; they will be removed once every call site is migrated. New surface: - _ZerocopyCache: per-instance container with two independent slots (torch tensor + numpy ndarray), each filled lazily on first access via torch.utils.dlpack.from_dlpack and numpy.from_dlpack respectively. Numpy zero-copy now bypasses torch entirely (closes review #6). - make_zerocopy_cache_if_supported(owner, ...): constructs a cache when zero-copy is supported and registers `owner` with `pyquadrants.cache_holders` so invalidation is wired automatically (closes review #18). - get_zerocopy_torch / get_zerocopy_numpy: thin entry points that implement the always-zerocopy-then-clone semantic (closes review #15, #16, #21) and the Apple Metal double-sync (qd.sync() on read AND torch.mps.synchronize() after .clone()/.to(); closes review #1, #22, #23). Also applies the small lints from the review: - Module-level constant for the torch>2.9.1 MPS bytes_offset probe; drops the pointless lru_cache wrapper around a zero-arg helper (closes review #2). - ASCII '...' instead of Unicode horizontal ellipsis '\u2026' in the docstring (closes review #3). - Top-level imports for numpy and torch (try/except for the no-torch CI case); no per-call lazy imports in the new code path (closes review #7, #9). The deprecated shim still does what the existing per-class methods expect; the new helpers are torch-clean. cache_holders is still empty until the next commits register Ndarray / ScalarField / MatrixField; this commit alone is no-op behaviourally.
hughperkins
added a commit
that referenced
this pull request
Apr 26, 2026
Convert Ndarray.to_torch / _ndarray_to_numpy / _ndarray_matrix_to_numpy to thin calls into _interop.get_zerocopy_torch / get_zerocopy_numpy. Behaviour changes vs. the previous PR state: - to_torch(copy=True) now ALSO uses the zerocopy export and clones the result, instead of skipping zerocopy entirely. Zerocopy DLPack is cheaper than the kernel-copy fallback even when followed by a clone (closes review #15, #16, #21). - to_torch on Apple Metal now does both syncs: qd.sync() before the read AND torch.mps.synchronize() after the .clone() so the cloned buffer is actually populated by the time the call returns (closes review #1, #22, #23). - to_numpy(copy=False) now goes through numpy.from_dlpack directly -- no torch round-trip, no torch import required (closes review #6). - to_numpy default (copy=None) keeps the current "independent copy" semantics: numpy arrays conventionally outlive their source, so the default is the safer one. Zero-copy is opt-in via copy=False. Cache invalidation switches from the legacy _qd_dlpack_tc attribute to the per-class _zerocopy_cache (cached_property) + _invalidate_zerocopy_cache method. Registration in pyquadrants.cache_holders happens automatically on first cache access (closes review #18). The existing _reset hook drops its zerocopy invalidation call: that work is now handled by the cache_holders loop in impl.reset() BEFORE C++ teardown, eliminating the use-after-free that motivated the Genesis to_numpy() always-copy workaround.
hughperkins
added a commit
that referenced
this pull request
Apr 26, 2026
Convert ScalarField.to_torch / to_numpy to thin calls into _interop.get_zerocopy_torch / get_zerocopy_numpy, mirroring the Ndarray migration in the previous commit. - Adds Field._invalidate_zerocopy_cache method (used by all subclasses) so the impl.reset() cache_holders loop has a single contract to call. - Adds ScalarField._zerocopy_cache as a cached_property; constructed once per instance instead of re-checking can_zerocopy on every call (closes review #17). - Registers ScalarField in pyquadrants.cache_holders on first cache access (closes review #18). - to_torch(copy=True) now zerocopies and clones rather than skipping zerocopy entirely (closes review #15, #16, #21); to_torch on Metal does both syncs (closes review #1, #22, #23). - to_numpy(copy=False) goes through numpy.from_dlpack directly, no torch round-trip and no torch import required (closes review #6). Default to_numpy semantic (copy=None) remains "independent copy" for lifetime safety; zero-copy is opt-in via copy=False.
hughperkins
added a commit
that referenced
this pull request
Apr 26, 2026
Convert MatrixField.to_torch / to_numpy to thin calls into _interop.get_zerocopy_torch / get_zerocopy_numpy. Adds a single _matrix_view_shape() helper that returns (expected_shape, as_vector); both to_torch and to_numpy now go through it instead of duplicating the n / m / keep_dims branching (closes review #13, #14). Same wins as the ScalarField migration: - _zerocopy_cache as cached_property (closes review #17) - automatic registration with pyquadrants.cache_holders (closes #18) - copy=True now zerocopies + clones (closes #15, #16, #21) - to_numpy(copy=False) goes through numpy.from_dlpack directly, no torch round-trip (closes #6) - Apple Metal double-sync via the centralised helpers (closes #1, #22, #23) The redundant reshape after zerocopy stays (DLPack returns the field's flat n-d shape; numpy/torch users expect the matrix dims appended) but it's now in one place per method instead of two.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Issue: #
Brief Summary
copilot:summary
Walkthrough
copilot:walkthrough