Add dynamic_one_shot tensorflow support + expanded testing #5973
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**Context:** This is a follow up to this [PR](#5789) which added detailed documentation for the new PennyLane Debugger feature. --------- Co-authored-by: Astral Cai <astral.cai@xanadu.ai> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: Yushao Chen (Jerry) <chenys13@outlook.com> Co-authored-by: Christina Lee <chrissie.c.l@gmail.com> Co-authored-by: Mudit Pandey <mudit.pandey@xanadu.ai> Co-authored-by: Thomas R. Bromley <49409390+trbromley@users.noreply.github.com> Co-authored-by: soranjh <40344468+soranjh@users.noreply.github.com>
**Context:** When creating an initial MPS from a dense state vector, the order of wires was not preserved since we were not providing the `wire_order` parameter to `state_vector`. **Description of the Change:** As above. **Benefits:** If the MPS is created from a dense state vector, now the order of wires is preserved. **Possible Drawbacks:** None that I can think of. **Related GitHub Issues:** None. **Related ShortCut Stories**: [sc-66787]
The objective of this PR is to reorganize the changelog into sections. Please don't worry about the content in each bullet point, we can polish that in follow up PRs.
**Context:** Currently, `draw()` and `draw_mpl()` can only be requested after applying the full transform program, with the exception of the stages provided through expansion_strategy. **Description of the Change:** Using the new `level` argument from construct_batch, the functions are adapted to make use of the argument as well, which allows for more flexible requests and ability to pinpoint where exactly in the transform program to draw a circuit. As done before, the new functionality works with transforms that split the tape (only in the case for `draw`. For `draw_mpl`, a warning is raised and only the first tape is plotted). **Benefits:** Better plotting UX. **Note for Reviewers:** Minor bugs in `construct_batch` have been discovered during work on this PR, and so expect minor fixes to tests relating to `specs`. [[sc-53735](https://app.shortcut.com/xanaduai/story/53735)] Supersedes #5139 --------- Co-authored-by: Mudit Pandey <mudit.pandey@xanadu.ai> Co-authored-by: Thomas R. Bromley <49409390+trbromley@users.noreply.github.com>
**Context:** Adds a transform for adding `NoiseModels`. **Description of the Change:** Adds `add_noise.py` under `pennylane/transforms` that gives the said method for inserting operations according to a provided noise model. **Benefits:** We support noise models. **Possible Drawbacks:** None. **Related GitHub Issues:** [sc-64843] --------- Co-authored-by: Jay Soni <jbsoni@uwaterloo.ca>
Automatic update of stable requirement files to snapshot valid python environments. Because bots are not able to trigger CI on their own, please do so by pushing an empty commit to this branch using the following command: ``` git commit --allow-empty -m 'trigger ci' ``` Alternatively, wait for this branch to be out-of-date with master, then just use the "Update branch" button! Note that it is expected that the PennyLane-Lightning repo is a version ahead of the release, because the version number is taken from the dev branch. Trying to `pip install` from the files will fail until that major version of Lightning is released. If pip install fails with a not found error when installing because of this, it can be fixed by manually downgrading the PennyLane-Lightning version number in the file by 1 version and trying again. --------- Co-authored-by: GitHub Actions Bot <> Co-authored-by: Christina Lee <christina@xanadu.ai>
**Context:** Adding documentation for the new debugger feature. --------- Co-authored-by: Mikhail Andrenkov <mikhail@xanadu.ai> Co-authored-by: Utkarsh <utkarshazad98@gmail.com> Co-authored-by: Diego <67476785+DSGuala@users.noreply.github.com> Co-authored-by: Josh Izaac <josh146@gmail.com> Co-authored-by: soranjh <40344468+soranjh@users.noreply.github.com> Co-authored-by: Diego <diego_guala@hotmail.com>
…asets (#5484) **Context:** Users have trouble finding all `bondlength` and `basis` combinations for qchem molecules. They end up using the slider on the website to check which bond lengths are available one-by-one.  **Description of the Change:** - Updated the quickstart guide to say "viewing available datasets" instead of "dataset structure" - Updated the `qml.data` docs to encourage users to first read the quickstart guide **Benefits:** Users should be more likely to reach the `list_datasets` description in the quickstart guide and know that it can be used to view the available datasets. **Possible Drawbacks:** Users who use pennylane.ai/datasets but don't go to the documentation still won't see this. --------- Co-authored-by: Utkarsh <utkarshazad98@gmail.com>
**Context:** The PennyLane documentation has a quickstart page on measurements, which includes a large section about mid-circuit measurements. With the focus on dynamic circuits and mid-circuit measurements more generally, we would like to make the content on MCMs more visible. **Description of the Change:** Extracts the MCM part of the measurements quickstart and adds it as its own quickstart page. Adds some details on simulation techniques and polishes the content. **Benefits:** Visibility, documentation extent for MCMs **Possible Drawbacks:** **Related GitHub Issues:** [sc-65318] --------- Co-authored-by: Vincent Michaud-Rioux <vincentm@nanoacademic.com>
**Context:** Previously, the QASM circuit converted to PL had no measurements (even if the circuit ended with measurements, the assumption was we remove those and add PL measurements once the circuit is converted). In the UnitaryHack, a contributor added the option to specify measurements when converting a circuit `from_qasm`, like the `from_qiskit` function. In doing so, the `from_qasm` circuit took on the current `from_qiskit` convention. Calling `from_qasm(qasm_str)` previously returned only the operators, and now returns operators + measurements. This is a breaking change with no deprecation cycle. PennyLaneAI/pennylane-qiskit#469 **Description of the Change:** Adds a deprecation warning to `from_qasm` [sc-66318] --------- Co-authored-by: lillian542 <38584660+lillian542@users.noreply.github.com> Co-authored-by: Christina Lee <christina@xanadu.ai> Co-authored-by: David Wierichs <david.wierichs@xanadu.ai>
**Context:** The `from_openfermion` function is updated to supports the conversion of qubit operators in addition to fermionic operators. **Description of the Change:** **Benefits:** **Possible Drawbacks:** **Related GitHub Issues:**
**Context:** PyTrees are an ideal format for dataset attributes, since they provide a compact representation of deeply nested structures, and Pennylane Operators can easily be converted to and from pytrees. Shortcut story: https://app.shortcut.com/xanaduai/story/63174/datasets-serialization-using-pytrees **Description of the Change:** - Adds a `pytree.serialization` module for converting `PyTreeStructure` objects to and from a JSON representation - Adds a `DatasetPyTree` data attribute type that can store any pytree-compatible type - `DatasetPyTree` is now the default attribute type for `Operator` - The `pytree.unflatten` method disables recording, to prevent deserialized operators from being queued **Benefits:** - Datasets support any Pennylane object with a Pytree representation and serializable metadata - Complex serialization logic in ``DatasetOperator`` can be deprecated - Reduces file size of datasets **Possible Drawbacks:** - Pytree datasets will not be compatible with versions < 0.37 - Type information for metadata is not preserved - `tuple`, `Wires`, and `Shots` objects will all be converted to `list` on a round-trip. `__init__` methods are responsible for ensuring that metadata is converted to the correct type --------- Co-authored-by: albi3ro <chrissie.c.l@gmail.com> Co-authored-by: Christina Lee <christina@xanadu.ai> Co-authored-by: Thomas R. Bromley <49409390+trbromley@users.noreply.github.com> Co-authored-by: Mudit Pandey <mudit.pandey@xanadu.ai> Co-authored-by: Paul Finlay <50180049+doctorperceptron@users.noreply.github.com> Co-authored-by: Diego <67476785+DSGuala@users.noreply.github.com> Co-authored-by: Utkarsh <utkarshazad98@gmail.com> Co-authored-by: Diego <diego_guala@hotmail.com>
**Context:** Catalyst PR #837 (PennyLaneAI/catalyst#837) needs a couple minor updates to the capture module. **Description of the Change:** 1) makes it possible to do `from pennylane.capture import AbstractOperator, AbstractMeasurement, qnode_prim` so we don't have to touch private functions 2) Adds `qnode` as a keyword argument that gets bound to the qnode primitive 3) Makes it so we can capture a sample measurement specified like `qml.sample(wires=1)` **Benefits:** **Possible Drawbacks:** **Related GitHub Issues:** [sc-66703] --------- Co-authored-by: David Wierichs <david.wierichs@xanadu.ai>
…convention changes. (#5853) **Context:** Allow for `qml.qsvt()` to accept phase angles as jax arrays and perform convention conversions. --------- Co-authored-by: David Ittah <dime10@users.noreply.github.com>
**Context:**
Currently the decomposition of a Pauli Rotation with an identity as
Pauli word returns an empty list. I.e,
```python
qml.PauliRot(theta, Pauli_word="I").decomposition() == []
```
**Description of the Change:**
Implement the correct decomposition for this case using
`qml.GlobalPhase`
**Benefits:**
The `TrotterProduct` for Hamiltonians with an identity using
`default.qubit` and `default.lightning` now return the same correct
result.
```python
import pennylane as qml
import numpy as np
symbols = ["H", "H"]
coordinates = np.array([[0.0, 0.0, -0.6614], [0.0, 0.0, 0.6614]])
H, num_qubits = qml.qchem.molecular_hamiltonian(symbols, coordinates, basis="sto-3g")
results = []
for dev_name in ["default.qubit", "lightning.qubit"]:
dev = qml.device(dev_name, wires=num_qubits)
@qml.qnode(dev)
def circuit():
qml.TrotterProduct(H, 1.0)
return qml.state()
results.append(circuit())
qml.math.allclose(*results)
>> True
```
**Related GitHub Issues:**
[#5859]
[sc-66115]
**Context:** Some updates are being made to Catalyst for mid-circuit measurements that are dependent on the changes in this PR. **Description of the Change:** * Change reference in `dynamic_one_shot` to catalyst's `MidCircuitMeasure.out_classical_tracers` to `MidCircuitMeasure.mcm_tracer`. * Change `MidMeasureMP.name` to be more general. This is because `MidCircuitMeasure` will soon inherit `MidMeasureMP`, and this change makes more sense than adding a `name` property to `MidCircuitMeasure`. **Benefits:** **Possible Drawbacks:** **Related GitHub Issues:**
mudit2812
commented
Jul 19, 2024
vincentmr
reviewed
Jul 22, 2024
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@mudit2812 Nice PR @mudit2812! I think not relying on implicit rules and introducing "pad-invalid-samples" will make the code more robust. Kudos for disentangling the mcm_config spaghetti. The PR description says: "Add differentiation tests for jax, torch, autograd, tensorflow", am I correct that tests are limited to test_finite_diff_in_transform_program and we do not validate correctness yet? Will this PR's changes impact old-API devices and has it been sorted out?
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
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@vincentmr the PR description is a bit outdated. Because finite diff behaves weirdly with shots, the variance in the gradient value is so high that it's not really possible to test for gradient correctness. I'll remove that line from the PR description. |
mudit2812
commented
Jul 22, 2024
vincentmr
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Jul 23, 2024
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Just a couple questions from my side, but then I'm ready to approve. Nice PR @mudit2812 .
This was referenced Jul 24, 2024
Merged
Co-authored-by: Vincent Michaud-Rioux <vincent.michaud-rioux@xanadu.ai>
albi3ro
approved these changes
Jul 26, 2024
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added a commit
to PennyLaneAI/pennylane-lightning
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Jul 26, 2024
**Context:** Changes needed after PennyLaneAI/pennylane#5973 gets merged for correctness. **Description of the Change:** **Benefits:** **Possible Drawbacks:** **Related GitHub Issues:** --------- Co-authored-by: ringo-but-quantum <github-ringo-but-quantum@xanadu.ai>
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**Context:** As name says. Change needed for correctness after PennyLaneAI/pennylane#5973 gets merged. **Description of the Change:** Use `postselect_mode` instead of `interface` when calling postprocessing function in `dynamic_one_shot`. **Benefits:** **Possible Drawbacks:** **Related GitHub Issues:**
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Context:
As name says. Gradient workflows no longer raise errors after the merge of #5791 , but their correctness is yet to be verified.
Description of the Change:
dynamic_one_shot's processing function for tensorflow.QNodehas updated behaviour for howmcm_configis used during execution. InQNode._execution_component, a copy ofself.execute_kwargs["mcm_config"]is the source of truth, and inqml.execute,config.mcm_configis the source of truth.pad-invalid-samplespostselect_mode. Thepostselect_modeis switched to this automatically inqml.executeif executing with jax and shots andpostselect_mode == "hw-like". This way we standardize how the MCM transforms determine if jax is being used.capturemodule to accommodate the above changes.Benefits:
dynamic_one_shotdoesn't cast to interfaces inside the ML boundarydynamic_one_shotworks with tensorflowPossible Drawbacks:
Related GitHub Issues:
Fixes #5736, #5710
Duplicate of #5861 which was closed due to release branch merge stuff.