Comments (3)
The original motivation for switching to tf.Variable
was that it allowed the flexibility to directly access the whole suite of Gradient based optimizers defined in tf.keras.optimizer
. I can go back and check if there is another way to continue that integration without fully rewriting parts of the tensorflow related codebase.
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We should integrate the tf.Variable
with the Paramatermap and C3Obj, such that only the elements that need gradients are made into variables, the others are made tf.constant
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Possibly closed in #46
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Related Issues (20)
- PWC pulse has incorrect dimensions HOT 3
- CI takes too long (drop Ubuntu 18.04)
- Piecewise Constant Pulses through Qiskit Interface
- Tutorial docs missing notebooks from examples
- Frequency specified response function
- Call of set_opt_map() breaks experiment for further simulations
- Interaction picture
- Missing lindbladian evolution
- Large numbers of parameters unreadable
- Missing get Hamiltonian for a signal input
- Wrong definition of the lindblad coefficient for T1
- Ideal gate assignment missing in Instruction class constructor
- Wrong sign in xy_angle in phase in Instruction class
- Updating Instruction name directly doesn't update its ideal gate
- CMAES optimisers can silently make parameters be OOB HOT 1
- Slow test due to Response
- PWC optimization - printing parameters for non gradient based algorithm
- Errors when amplitude of slepian shaped pulses is zero
- Problems in examples/Full_loop_single_qubit.ipynb
- Migrate to Qiskit 1.0
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