Fix qnn module tutorial for TorchLayer #247
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albi3ro
approved these changes
Apr 13, 2021
| @@ -86,7 +86,10 @@ | |||
| @qml.qnode(dev) | |||
| def qnode(inputs, weights): | |||
| qml.templates.AngleEmbedding(inputs, wires=range(n_qubits)) | |||
| qml.templates.BasicEntanglerLayers(weights, wires=range(n_qubits)) | |||
| for weights_layer in weights: | |||
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| for weights_layer in weights: | |
| # explicit `qml.templates.BasicEngtnglerLayers` until a bug is fixed | |
| for weights_layer in weights: |
Maybe just a comment here that there is usually a better way of doing this.
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🤔 I see your point, although wonder if it may confuse the reader - unless they also look at the Keras tutorial they may not be expecting to see BasicEntanglerLayers.
trbromley
commented
Apr 14, 2021
Comment on lines
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| # Embedding | ||
| qml.RX(inputs[0], wires=0) | ||
| qml.RX(inputs[1], wires=1) |
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@albi3ro, sorry to rerequest your review! We additionally have to change this, as the bug is also present in AngleEmbedding.
albi3ro
approved these changes
Apr 14, 2021
trbromley
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Apr 16, 2021
This reverts commit 1866e7e.
trbromley
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Apr 19, 2021
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Currently the tutorial is failing due to the issue highlighted here: PennyLaneAI/pennylane#1210.
As a quick fix in this PR, we swap out
BasicEntanglerLayersfor its explicit decomposition.