def latent_bottleneck_from_config()

in shap_e/models/transmitter/bottleneck.py [0:0]

• 10 lines of code
• 4 McCabe index (conditional complexity)

def latent_bottleneck_from_config(config: Dict[str, Any], device: torch.device, d_latent: int):
    name = config.pop("name")
    if name == "clamp_noise":
        return ClampNoiseBottleneck(**config, device=device, d_latent=d_latent)
    elif name == "identity":
        return IdentityLatentBottleneck(**config, device=device, d_latent=d_latent)
    elif name == "clamp_diffusion_noise":
        return ClampDiffusionNoiseBottleneck(**config, device=device, d_latent=d_latent)
    else:
        raise ValueError(f"unknown latent bottleneck: {name}")