PennyLane Python Frontend¶
Module: catalyst¶
This package contains the Catalyst Python interface.
Functions¶
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A just-in-time decorator for PennyLane and JAX programs using Catalyst. |
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Asserts at runtime that the given condition holds, raising an error with the provided message if it does not. |
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Execute a |
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Execute and return the results of a functionally pure Python function from within a qjit-compiled function. |
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Create a method that applies a controlled version of the provided op. |
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Create a method that applies a controlled version of the provided op. |
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Utility function to retrieve the source code of a function converted by AutoGraph. |
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Decorator that converts the given function into graph form. |
Classes¶
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Class representing a just-in-time compiled hybrid quantum-classical function. |
Errors related to Catalyst's AutoGraph module. |
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Error encountered in the compilation phase. |
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An error indicating an invalid differentiation configuration. |
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Generic compilation options, for which reasonable default values exist. |
Variables¶
Specify whether AutoGraph should avoid raising warnings when conversion fails and control flow instead falls back to being interpreted by Python at compile-time. |
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Specify whether AutoGraph should raise exceptions when conversion fails, rather than falling back to interpreting control flow by Python at compile-time. |
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Context decorator that disables AutoGraph for the given function/context. |
Module: catalyst.debug¶
Catalyst’s debug module contains functions useful for user program debugging.
Functions¶
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Execute a Python function with no return value and potential side effects from within a qjit-compiled function. |
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Returns the intermediate representation of one of the recorded compilation stages for a JIT-compiled function. |
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Return a C program that calls a jitted function with the provided arguments. |
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Compile a Catalyst function to binary code from the provided MLIR. |
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Instrumentation session to output information on wall time, CPU time, and intermediate program size of a program during compilation and execution. |
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Replace the IR at any compilation stage that will be used the next time the function runs. |
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Generate an executable binary for the native host architecture from a |
Module: catalyst.passes¶
This module contains which provides Python decorators for enabling and configuring individual Catalyst MLIR compiler passes.
Note
Unlike PennyLane circuit transformations, the QNode itself will not be changed or transformed by applying these decorators.
As a result, circuit inspection tools such as draw()
will continue
to display the circuit as written in Python.
Instead, these compiler passes are applied at the MLIR level, which occurs
outside of Python during compile time. To inspect the compiled MLIR from
Catalyst, use get_compilation_stage()
with
stage="QuantumCompilationPass"
.
Functions¶
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Specify that the |
Module: catalyst.third_party.cuda¶
This module contains a CudaQDevice and the qjit entry point.
Classes¶
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Base instruction set for CUDA-Quantum devices |
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The SoftwareQ Q++ statevector simulator. |
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The NVIDIA CuStateVec GPU simulator (with support for multi-gpu). |
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The NVIDIA CuTensorNet GPU simulator (with support for matrix product state) |