Table of Contents

0.2.3dev

Home

Welcome to ⚡ Lightning Thunder
Install
Hello World
Using examine

Basic

Overview
Zero to Thunder
Thunder step by step
The sharp edges
Train a MLP on MNIST
Thunder Concepts - Trace, BoundSymbol, Symbol and Proxy
Hello world ThunderFX
FAQ

Intermediate

Additional executors
Distributed Data Parallel
What's next
FSDP Under the Hood Tutorial
Benchmarking Thunder
Introduction
Transforms
Thunder bindings for Liger operators
RoPE
Test
End to end example

Advanced

Inside thunder
Extending thunder
Extend Thunder with CUDA-Python
Running our kernel in Thunder
Inspect
Comparing implementations
Summary
Defining new Thunder operators
Defining custom forward and backward for existing operators
Contributing to Thunder

Experimental dev tutorials

Extending Thunder

API reference

thunder
thunder.common
thunder.core
thunder.clang
thunder.examine
thunder.distributed
thunder.executors
thunder.torch
thunder.extend
thunder.transforms
thunder.dynamo

Overview
Team management
Production
Security
Open source
- Overview
- PyTorch Lightning
- Fabric
- Lit-GPT
- Torchmetrics
- Litdata
- Lit LLaMA
- Litserve
Examples
Glossary
FAQ

Docs >
thunder.executors

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thunder.executors

get_nvfuser_executor()

rtype:: Optional[Executor]

get_torch_executor()

rtype:: Executor

nvfuser_available()

rtype:: bool

APEX Executor
cuDNN Executor
nvFuser Executor
Optimization Passes
Python Executor
Torch Compile Executor
PyTorch Executor
Triton Executor
Utils

thunder.executors

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