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Hybrid Quantum-Classical Machine Learning in TensorFlow
Thanks to #590 we can now roll our own proto structures + serialization code. We should do some work to try and make our `program.proto` wire size and serialization code...
Our C.I. has been starting to develop some interesting flakiness when it comes to checking python code formatting with yapf. It might be time to upgrade the version we depend...
Lately in a lot of our CI runs we have been running into issues with the `gradients_test` -> `bazel test //tensorflow_quantum/python/differentiators/gradient_test` running for a very long time and sometimes flaking....
I previously outlined an issue in the rendering on TFQ API docs that was solved. However, it appears as though the updates did not fully solve the problem, but merely...
From a comment in the code: TODO (mbbrough): Remove this workaround class once cirq.PauliSumCollector can be used end to end with engine. This current issue is that cirq.PauliSumCollector does not...
Is there an option to use a Quantum channel in my network.
We recently had our first outside contributor add to TFQ datasets. Big thanks @therooler and the rest of the U of T folks! Now that we have our first example...
With all the information we have floating around with how to best use Engine + TFQ we might want to add a page like this: https://cirq.readthedocs.io/en/latest/google/best_practices.html but for TFQ soon....
Right now our sampler code for custom `cirq.Sampler` instances is not as clean as it could be. At some point we should make a more deliberate effort to clean this...
Right now Cirq does not allow such things as: ```python3 a = cirq.Z(q0) * cirq.Z(q0) + projector(0111011001) a.expectation_from_wavefunction(a, ...) ``` One must manually write out the projection operators like: ```python3...
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Hybrid Quantum-Classical Machine Learning in TensorFlow