starling
Getting Started
Getting Started
Installation
Command Line Interface
Core Workflows
Ensemble Generation
Guided Sampling with Constraints
Performance Optimization
Sequence Embeddings
Working with Ensembles
BME Reweighting
Utilities
Search & Diagnostics
Similarity Search
Possible Issues and Solutions
API Reference
API reference
High-level functions
Structure & Ensembles
Frontend
Inference
Models
starling.models.vae
starling.models.diffusion
starling.models.unet
starling.models.vit
starling.models.transformer
starling.models.attention
starling.models.blocks
starling.models.blocks.instance_norm
starling.models.blocks.layer_norm
starling.models.blocks.DownsampleBlock
starling.models.blocks.LayerNorm
starling.models.blocks.MinPool2d
starling.models.blocks.ResBlockDecBasic
starling.models.blocks.ResBlockDecBottleneck
starling.models.blocks.ResBlockEncBasic
starling.models.blocks.ResBlockEncBottleneck
starling.models.blocks.ResizeConv2d
starling.models.blocks.UpsampleBlock
starling.models.blocks.vanilla_Decoder
starling.models.blocks.vanilla_Encoder
starling.models.normalization
starling.models.ema
starling.models.continuous_diffusion
starling.models.vae_components
starling.models.quantize
starling.models.resnets_original
Samplers
Data Processing
Search & Indexing
Configuration & Utilities
Training
starling
API reference
starling.models.blocks
starling.models.blocks.layer_norm
View page source
starling.models.blocks.layer_norm
layer_norm
(
out_channels
,
starting_dimension
,
**
kwargs
)
[source]