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Eigvals are floats #5607
Eigvals are floats #5607
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As name says. --------- Co-authored-by: Astral Cai <astral.cai@xanadu.ai>
**Context:** Some newly added test cases failing with legacy opmath **Description of the Change:** Skip these tests if new opmath is disabled: `test_measure_identity_no_wires` in `tests/devices/qubit/test_measure.py` `test_identity_on_no_wires_with_other_observables` in `tests/devices/qubit/test_sampling.py` `test_observables_on_no_wires_coeffs` in `tests/pauli/grouping/test_pauli_group_observables.py` `test_multiple_hamiltonian_expansion_finite_shots` in `tests/test_qnode_legacy.py` **Related Shortcut Issues:** [sc-62144] [sc-62143]
**Context:** 1. `Hamiltonian` does not remove ops from queue if `simplify=True` 2. `TrotterProduct` does not remove `Hamiltonian` **Description of the Change:** Manually dequeue said ops **Related Shortcut Issues:** [sc-62142] --------- Co-authored-by: Mudit Pandey <mudit.pandey@xanadu.ai>
### Before submitting Please complete the following checklist when submitting a PR: - [x] All new features must include a unit test. If you've fixed a bug or added code that should be tested, add a test to the test directory! - [x] All new functions and code must be clearly commented and documented. If you do make documentation changes, make sure that the docs build and render correctly by running `make docs`. - [x] Ensure that the test suite passes, by running `make test`. - [x] Add a new entry to the `doc/releases/changelog-dev.md` file, summarizing the change, and including a link back to the PR. - [x] The PennyLane source code conforms to [PEP8 standards](https://www.python.org/dev/peps/pep-0008/). We check all of our code against [Pylint](https://www.pylint.org/). To lint modified files, simply `pip install pylint`, and then run `pylint pennylane/path/to/file.py`. When all the above are checked, delete everything above the dashed line and fill in the pull request template. ------------------------------------------------------------------------------------------------------------ **Context:** `qml.counts` does not return the same `keys` with `dynamic_one_shot` and `defer_measurements`. **Description of the Change:** Cast `keys` to the type produced by `concretize`. **Benefits:** Consistent `keys`. **Possible Drawbacks:** Slight (likely unnoticeable) performance decrease since `NDArray` object cannot be preallocated. **Related GitHub Issues:** #5566 --------- Co-authored-by: David Wierichs <david.wierichs@xanadu.ai>
- [x] Fix last open bug or open issue **Context:** Docs get out of sync over time. In particular, the output shape of gradient transforms applied to QNodes was changed in #4945 but not updated in the docs. **Description of the Change:** Update examples in docs of `qml.gradients` module. Also updates the `qml.kernels` docs, with a few very small changes. **Benefits:** **Possible Drawbacks:** **Related GitHub Issues:**
2 very minor corrections to documentation added in this release
**Context:** Fixes latest failures in the legacy opmath tests in the plugin test matrix. **Description of the Change:** 1. `convert_to_opmath` now dequeues the original op. 2. Skip test with `I()` when new opmath is disabled.
Hello. You may have forgotten to update the changelog!
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## master #5607 +/- ##
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- Coverage 99.68% 99.67% -0.01%
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Files 415 415
Lines 38888 38594 -294
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- Hits 38764 38469 -295
- Misses 124 125 +1 ☔ View full report in Codecov by Sentry. |
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Looks great, this change makes a lot of sense! 💯
just some minor comments from my side.
Co-authored-by: lillian542 <38584660+lillian542@users.noreply.github.com>
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Thanks @lillian542!
Approving conditioned on the (minor) change of the test docstring that references (then) removed code.
[sc-58742] |
Co-authored-by: Thomas R. Bromley <49409390+trbromley@users.noreply.github.com>
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Nice work @lillian542
Just 2 small questions from my side.
Also, this shouldn't cause any issues with the other frameworks, right? If it is worth a check, can you run the Torch GPU tests too, just to verify the dtype changes are all good there?
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💯
Context:
Most eigvals are floats, but specifically for X, Y, Z and Hadamard, they have been (1, -1). This can make trouble - for example, it caused an issue with JAX-JIT, because it doesn't know what dtype to anticipate coming from a sampled observable.
Description of the Change:
Main change here is changing eigvals to (1.0, -1.0) so that all observables have the same dtype for eigenvalues.
There is still some special handling for X, Y, Z and Hadamard, because it makes things JIT compatible for those operators, but it now pulls from the
op.eigvals()
property and returns floats.Benefits:
Possible Drawbacks:
If people were doing checks for
int
, or otherwise assuming they would get integers when returning fx.qml.sample(qml.X(0))
, this will be a breaking change for them.Related GitHub Issues:
#5369