RC to master #2323
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RC to master #2323
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* Exclude Snapshot from adjoint backwards pass * Add snapshots test for diff_methods * Changelog * Trigger rebuild Co-authored-by: antalszava <antalszava@gmail.com>
* batching ability for non-trainable inputs only following issue #2037 This function creates multiple circuit executions for batched input examples and executes all batch inputs with the same trainable variables. The main difference between the proposed version in the issue and this commit is the input `argnum` this indicates the location of the given input hence gives the ability to work across platforms. * adaptation for batch execution * improvements according to PR rules * minor update according to PR errors * modify according to codefactor-io * reformatted code style * adjust line lenght for linting * update linting * disable linting for too many arguments * add testing for batch input in keras * format test_keras.py * add tests for remaining functions * adapt the defaults * update docstring according to @josh146 's suggestions * remove keras sterilazation * add batch_input to the docstring * docstring update for readability: pennylane/transforms/batch_input.py Co-authored-by: Josh Izaac <josh146@gmail.com> * minor fix in documentation * change assertion error to valueerror * test valueerror * modify the definition of argnum * change argnum -> batch_idx * update changelog-dev.md * apply @josh146 's suggestions * linting * tests * more Co-authored-by: antalszava <antalszava@gmail.com> Co-authored-by: Josh Izaac <josh146@gmail.com>
* Redo imports * Update docs * Update wording * Fix ID * Add to docs * Add to docs * Fix * Update docstrings * Use nx.MultiDiGraph * Update fragment_graph * Update graph_to_tape * Update remap_tape_wires * Rename to expand_fragment_tape * Update expand_fragment_tape * Update CutStrategy * Update qcut_processing_fn * Remove note * Update cut_circuit * Work on docs * Add to docs * Update pennylane/transforms/qcut.py * Add to changelog * Move device definition * Mention WireCut * Move details * QCut module * Fix image location * Fix init * Apply suggestions from code review Co-authored-by: anthayes92 <34694788+anthayes92@users.noreply.github.com> * Add link to communication graph * Reword * Move around * fix * fix Co-authored-by: antalszava <antalszava@gmail.com> Co-authored-by: Josh Izaac <josh146@gmail.com> Co-authored-by: anthayes92 <34694788+anthayes92@users.noreply.github.com>
* Redo imports * Update docs * Update wording * Fix ID * Add to docs * Add to docs * Fix * Update docstrings * Use nx.MultiDiGraph * Update fragment_graph * Update graph_to_tape * Update remap_tape_wires * Rename to expand_fragment_tape * Update expand_fragment_tape * Update CutStrategy * Update qcut_processing_fn * Remove note * Update cut_circuit * Work on docs * Add to docs * Update pennylane/transforms/qcut.py * Add to changelog * Move device definition * Mention WireCut * Move details * QCut module * Fix image location * Fix init * Update changelog * Link to docs page * Update wording * Apply suggestions from code review Co-authored-by: Josh Izaac <josh146@gmail.com> * Move * Update doc/releases/changelog-dev.md Co-authored-by: Nathan Killoran <co9olguy@users.noreply.github.com> * Remove * Update Co-authored-by: antalszava <antalszava@gmail.com> Co-authored-by: Josh Izaac <josh146@gmail.com> Co-authored-by: Nathan Killoran <co9olguy@users.noreply.github.com>
* Produce consisten output shapes In the absence of trainable params, some gradient transforms did not produce an empty tuple yet like the rest of our functions. * Minor formatting changes in param_shift_hessian * Fix param_shift_hessian for all zero diff_methods * Fix missing requires_grad & catch expected warning * Changelog Co-authored-by: Jay Soni <jbsoni@uwaterloo.ca>
* Deprecate the Jacobian tape * Deprecate tape subclasses * changelog * more test fixes * tests * Apply suggestions from code review Co-authored-by: antalszava <antalszava@gmail.com> Co-authored-by: antalszava <antalszava@gmail.com>
* generator doc fixes * more fixing
* Remove temp fixes for lightning * Include diff_method tests for all devices * Changelog * Update CI to use pennylane-lightning dev Co-authored-by: antalszava <antalszava@gmail.com>
* Fix Operator docstring hyperrefs * Fix example for top-level matrix function * Add example to Snapshot op docstring * Fix tape drawing examples in docs * Apply suggestions from code review * Update pennylane/ops/snapshot.py Co-authored-by: Christina Lee <christina@xanadu.ai>
* Add qfunc and else to cond's UsageDetails * copy when inverting MV under the hood; add equivalent test case for inversion; add err msg when calling == of MV with unexpected typed obj; more examples * format * test docstr * format * correct examples * format * docstring * have #2300 on rc too * lambda example * intro extend, docstring * changelog PR num * link * note update * updates * Apply suggestions from code review * updates Co-authored-by: Christina Lee <christina@xanadu.ai>
* Add qml.generator(op) backwards compatibility * Apply suggestions from code review Co-authored-by: David Wierichs <davidwierichs@gmail.com> * fix docstring Co-authored-by: David Wierichs <davidwierichs@gmail.com>
…2314) * array() * print() to get the output formatting correct * revert array() * print() Co-authored-by: Maria Schuld <mariaschuld@gmail.com> Co-authored-by: Josh Izaac <josh146@gmail.com>
* updates * - lower * updates * contract_tensor ref updates * rename test file: batch_input * explicit requires_grad upon param generation * torch.Tensor as type * Update pennylane/transforms/__init__.py Co-authored-by: Tom Bromley <49409390+trbromley@users.noreply.github.com> * use tf in example Co-authored-by: Josh Izaac <josh146@gmail.com> Co-authored-by: Tom Bromley <49409390+trbromley@users.noreply.github.com>
* controlled, adjoint * Remove print * Match adjoint signature of parent class * Add tests for ctrl/adj support * Update Barrier.adjoint signature * Add ctrl test for Barrier * Update tests/test_debugging.py * Update tests/ops/test_snapshot.py * Update tests/ops/test_snapshot.py * changelog * trigger build Co-authored-by: Antal Szava <antalszava@gmail.com>
* version * log ref * rename * sections; emojis * format * improvements order * format * addition; collabs; v0.21.0 collab alphabet fix * reorder * collab; deprecation item * more PRs; collab list extended * update * sections * op section break up * correct matrix example * suggestions * suggestions * a few more * fix typo in code * update * no tf import * update Co-authored-by: Josh Izaac <josh146@gmail.com>
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Hello. You may have forgotten to update the changelog!
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josh146
approved these changes
Mar 15, 2022
Codecov Report
@@ Coverage Diff @@
## master #2323 +/- ##
==========================================
- Coverage 99.32% 99.32% -0.01%
==========================================
Files 242 242
Lines 19166 19190 +24
==========================================
+ Hits 19037 19060 +23
- Misses 129 130 +1
Continue to review full report at Codecov.
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Note: requires Lightning v0.22.0 to have been released.