|---| | [ View source on GitHub](https://github.com/tensorflow/quantum/blob/v0.7.6/tensorflow_quantum/python/differentiators/__init__.py) | Module functions for tfq.differentiators.\* ## Classes [`class Adjoint`](https://www.tensorflow.org/quantum/api_docs/python/tfq/differentiators/Adjoint): Differentiate a circuit with respect to its inputs by adjoint method. [`class CentralDifference`](https://www.tensorflow.org/quantum/api_docs/python/tfq/differentiators/CentralDifference): Differentiates a circuit using Central Differencing. [`class Differentiator`](https://www.tensorflow.org/quantum/api_docs/python/tfq/differentiators/Differentiator): Interface that defines how to specify gradients for a quantum circuit. [`class ForwardDifference`](https://www.tensorflow.org/quantum/api_docs/python/tfq/differentiators/ForwardDifference): Differentiate a circuit using forward differencing. [`class LinearCombination`](https://www.tensorflow.org/quantum/api_docs/python/tfq/differentiators/LinearCombination): Differentiate a circuit with respect to its inputs by linearly combining values obtained by evaluating the op using parameter values perturbed about their forward-pass values. [`class ParameterShift`](https://www.tensorflow.org/quantum/api_docs/python/tfq/differentiators/ParameterShift): Calculate the general version of parameter-shift rule based gradients.