This document is relevant for: Trn2, Trn3

TorchNeuron reference

Reference materials for TorchNeuron configuration, supported operations, and external resources.

API reference reference

Compatibility guide and supported operators for torch-neuronx on Neuron.

TorchNeuron resources reference

Links to Neuron native PyTorch open-source repositories, documentation, and relevant PyTorch community resources.

Best practices for TorchNeuron best practice

Recommended methods for optimizing eager mode, torch.compile, distributed training, and mixed precision on Trainium.

TorchNeuron environment variables reference

Variables that configure torch-neuronx behavior: the neuron backend for torch.compile, caching, eager execution, distributed collectives, and the memory allocator.

Guidelines for memory management reference

NUMA CPU affinity, Neuron caching allocator tuning, 64-bit dtype behavior, and cache placement.

This document is relevant for: Trn2, Trn3