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Since PennyLane PR #959 optimizers can accept cost functions with non-trainable data, multiple trainable parameters, and keywords. Our demos should reflect this flexibility, instead of using lambda functions and other workarounds.
The text was updated successfully, but these errors were encountered:
Since PennyLane PR #959 optimizers can accept cost functions with non-trainable data, multiple trainable parameters, and keywords. Our demos should reflect this flexibility, instead of using lambda functions and other workarounds.
The text was updated successfully, but these errors were encountered: