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QueueContext is not empty #1957

Merged
merged 5 commits into from
Dec 1, 2021
Merged

QueueContext is not empty #1957

merged 5 commits into from
Dec 1, 2021

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KetpuntoG
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Context:
When importing pennylane QueueContext is not empty. You can check it by typing print(self.name) in the queue method of Operator.

Description of the Change:
The gates that were being added have been found.

@github-actions
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Hello. You may have forgotten to update the changelog!
Please edit doc/releases/changelog-dev.md with:

  • A one-to-two sentence description of the change. You may include a small working example for new features.
  • A link back to this PR.
  • Your name (or GitHub username) in the contributors section.

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codecov bot commented Nov 30, 2021 •
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Codecov Report

Merging #1957 (2704bf5) into master (42482b1) will not change coverage.
The diff coverage is 100.00%.

Impacted file tree graph

@@           Coverage Diff           @@
##           master    #1957   +/-   ##
=======================================
  Coverage   98.81%   98.81%           
=======================================
  Files         225      225           
  Lines       17187    17187           
=======================================
  Hits        16983    16983           
  Misses        204      204
Impacted Files Coverage Δ
...ane/transforms/decompositions/two_qubit_unitary.py 100.00% <100.00%> (ø)

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@co9olguy
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Well spotted! 👀

@josh146
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josh146 commented Dec 1, 2021

wow, nice catch @KetpuntoG! I'm curious how these gates ended up in a queuing context, since they seem to just be run at the module level, not within any tape/QNode 🤔

@KetpuntoG
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I'm still learning about queues so I'm not entirely sure @josh146 . What I would say is that the __init__ of the gates call the queue method, which takes context = QueueContext if none is passed to the method.

Jaybsoni
Jaybsoni approved these changes Dec 1, 2021
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Looks good !

pennylane/transforms/decompositions/two_qubit_unitary.py
Comment on lines +52 to +54
CNOT01 = np.array([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0]])
CNOT10 = np.array([[1, 0, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0], [0, 1, 0, 0]])
SWAP = qml.SWAP(wires=[0, 1]).matrix
SWAP = np.array([[1, 0, 0, 0], [0, 0, 1, 0], [0, 1, 0, 0], [0, 0, 0, 1]])
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Great find actually, never would have guessed that we start adding to the questions through here !

@KetpuntoG KetpuntoG merged commit 4b62d06 into master Dec 1, 2021
@KetpuntoG KetpuntoG deleted the queue_issue branch December 1, 2021 14:45
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@Jaybsoni Jaybsoni Jaybsoni approved these changes

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4 participants
@KetpuntoG @co9olguy @josh146 @Jaybsoni