From f58c4ca4aab939a212483a0cc95dac7148609df4 Mon Sep 17 00:00:00 2001 From: rmoyard Date: Fri, 13 Oct 2023 16:45:43 -0400 Subject: [PATCH] Update changelog --- doc/releases/changelog-dev.md | 3 +++ pennylane/interfaces/execution.py | 2 ++ 2 files changed, 5 insertions(+) diff --git a/doc/releases/changelog-dev.md b/doc/releases/changelog-dev.md index cb5f4a98005..d327f2829b3 100644 --- a/doc/releases/changelog-dev.md +++ b/doc/releases/changelog-dev.md @@ -63,6 +63,9 @@ * Transforms can be applied on devices following the new device API. [(#4667)](https://github.com/PennyLaneAI/pennylane/pull/4667) +* All gradient transforms are updated to the new transform program system. + [(#4595)](https://github.com/PennyLaneAI/pennylane/pull/4595) + * All quantum functions transforms are update to the new transform program system. [(#4439)](https://github.com/PennyLaneAI/pennylane/pull/4439) diff --git a/pennylane/interfaces/execution.py b/pennylane/interfaces/execution.py index dc736e619a4..202ed42488a 100644 --- a/pennylane/interfaces/execution.py +++ b/pennylane/interfaces/execution.py @@ -424,6 +424,8 @@ def execute( interface (str): The interface that will be used for classical autodifferentiation. This affects the types of parameters that can exist on the input tapes. Available options include ``autograd``, ``torch``, ``tf``, ``jax`` and ``auto``. + transform_program(qml.transforms.core.TransformProgram): A transform program to be applied to the initial tape. + config (qml.devices.ExecutionConfig): A datastructure describing the parameters needed to fully describe the execution. grad_on_execution (bool, str): Whether the gradients should be computed on the execution or not. Only applies if the device is queried for the gradient; gradient transform functions available in ``qml.gradients`` are only supported on the backward