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Transformer Engine 2.20.0.dev0 - Home Transformer Engine 2.20.0.dev0 - Home

Transformer Engine 2.20.0.dev0

  • GitHub
Transformer Engine 2.20.0.dev0 - Home Transformer Engine 2.20.0.dev0 - Home

Transformer Engine 2.20.0.dev0

  • GitHub

Table of Contents

  • Home

Getting Started

  • Installation
  • Getting Started
  • Frequently Asked Questions (FAQ)
  • Transformer Engine vX.YZ Release Notes

Python API documentation

  • Common API
  • Framework-specific API
    • PyTorch
    • Jax

Features

  • Low precision training
    • Introduction
    • Performance Considerations
    • FP8 Current Scaling
    • FP8 Delayed Scaling
    • FP8 Blockwise Scaling
    • MXFP8
    • NVFP4
    • GEMM Speedups Across Precisions
  • Other optimizations
    • CPU Offloading

Examples and Tutorials

  • Using FP8 and FP4 with Transformer Engine
  • Performance Optimizations
  • Accelerating Hugging Face Llama 2 and 3 Fine-Tuning with Transformer Engine
  • Accelerating Hugging Face Gemma Inference with Transformer Engine
  • Accelerating Hugging Face Mixtral MoE Fine-Tuning with Transformer Engine
  • Export to ONNX and inference using TensorRT
  • JAX: Integrating TransformerEngine into an existing framework
    • JAX: Dense GEMMs with TransformerEngine
    • JAX: Collective GEMMs with TransformerEngine
    • JAX: Attention with TransformerEngine
      • JAX: Single-GPU Attention with TransformerEngine
      • JAX: Context-Parallel Attention with TransformerEngine
    • JAX: Expert Parallelism with TransformerEngine
  • Operation fuser API
  • GEMM Profiling Tutorial

Advanced

  • C/C++ API
    • transformer_engine.h
    • activation.h
    • cast_transpose_noop.h
    • cast.h
    • cudnn.h
    • fused_attn.h
    • fused_rope.h
    • gemm.h
    • multi_tensor.h
    • normalization.h
    • padding.h
    • permutation.h
    • recipe.h
    • softmax.h
    • swizzle.h
    • transpose.h
  • Precision debug tools
    • Getting started
    • Config File Structure
    • API
      • Setup
      • Debug features
      • Calls to Nvidia-DL-Framework-Inspect
    • Distributed training
    • Adding custom feature to precision debug tools
  • Environment Variables
  • Attention Is All You Need!
  • Deep Dive into CP + THD + AG + Striped>1 + SWA support for Transformer Engine JAX
  • Precision debug tools
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Precision debug tools#

Precision debug tools

  • Getting started
    • Example training script
    • Config file
    • Adjusting Python file
    • Inspecting the logs
    • Logging using TensorBoard
  • Config File Structure
    • General Format
    • Layer Specification
    • Names in Transformer Layers
    • Structured Configuration for GEMMs and Tensors
    • Enabling or Disabling Sections and Features
  • API
    • Setup
      • initialize()
      • set_tensor_reduction_group()
      • set_weight_tensor_tp_group_reduce()
    • Debug features
      • LogTensorStats
      • LogFp8TensorStats
      • LogNvfp4TensorStats
      • DisableQuantizationGEMM
      • DisableQuantizationLayer
      • PerTensorScaling
      • FakeQuant
      • DisableFP8GEMM
      • DisableFP8Layer
      • DumpTensors
    • Calls to Nvidia-DL-Framework-Inspect
      • modify_tensor()
      • modify_tensor_enabled()
      • fp8_gemm_enabled()
      • inspect_tensor()
      • inspect_tensor_postquantize()
      • inspect_tensor_enabled()
      • inspect_tensor_postquantize_enabled()
  • Distributed training
    • Behavior of the features
    • Reduction groups
    • Microbatching
    • Logging to files and TensorBoard
  • Adding custom feature to precision debug tools

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