# A simple Neural Spline Flow flow = zuko.flows.NSF( features=3, # Dimensionality of data context=0, # Conditional context size (0 for unconditional) transforms=5, # Number of transformation layers hidden_features=[64] * 3 ) Actress Shalu Menon Hot Videos Cracked
# Sampling samples = flow.sample((1000,)) El Efecto Leopi | Pdf
# Log-likelihood evaluation log_prob = flow.log_prob(samples) | Feature | Zuko | nflows | FrEIA | | :--- | :--- | :--- | :--- | | Framework | Pure PyTorch | PyTorch | PyTorch (Graph-based) | | Complexity | Low (Pythonic) | Medium | High (Graph management) | | Conditioning | Native support | Supported | Supported | | CNF Support | Yes (via zuko.flows.CNF ) | Limited | Yes | | Use Case | Research, SBI backends | General purpose | INN (Invertible Neural Nets) |
import torch import zuko