API Reference

API Reference

• PhysicsNeMo Models
  • PhysicsNeMo Modules
  • Fully Connected Network
  • Fourier Neural Operators
  • Graph Neural Networks
  • Convolutional Networks
  • Recurrent Neural Networks
  • Operator Models
  • Diffusion UNets
  • Diffusion Transformer (DiT)
  • Transolver
  • Weather / Climate Models
• PhysicsNeMo Mesh
  • Overview
  • Data Model
  • Quick Start
  • Key Features
  • Tutorials
  • API Reference
• PhysicsNeMo Layers
  • Activations
  • Attention and Transformers
  • Convolutional Layers
  • Embeddings
  • Fourier, FFT, and Spectral Layers
  • Fully Connected and MLP Layers
  • Normalization
  • Resampling and Interpolation
  • Regularization
  • Specialized Layers
  • Graph and Geometry Layers
• PhysicsNeMo Functionals
  • Neighbor Functionals
  • Geometry Functionals
  • FFT Functionals
  • Regularization and Parameterization Functionals
  • Interpolation Functionals
• PhysicsNeMo Active Learning
  • Developing Active Learning Workflows
  • API Reference
• PhysicsNeMo Core
  • PhysicsNemo Module
  • Filesystem Utils
• PhysicsNeMo Datapipes
  • Datapipes philosophy
  • Quick Start
  • Architecture
  • Core API
  • Extending the Pipeline
  • Legacy Datapipes
• PhysicsNeMo Diffusion
  • Introduction
  • Model Backbones
  • Noise Schedulers
  • Preconditioners
  • Metrics and Losses
  • Samplers and Solvers
  • Multi-Diffusion
  • Utilities
• PhysicsNeMo Distributed
  • How does this work?
• PhysicsNeMo domain_parallel
  • ShardTensor
  • Utility Functions
• PhysicsNeMo Metrics
  • Basics
  • General
  • Weather and climate metrics
• PhysicsNeMo NN
• PhysicsNeMo Optim
  • CombinedOptimizer
• PhysicsNeMo Utils
  • Weather and Climate Utils
  • Checkpointing
  • Profiling Utils
  • Optimization Utils
• PhysicsNeMo Logging
  • Launch Logger
  • Console Logger
  • MLflow Logger
  • Weights and Biases Logger
  • Logging Utils