kaira.models.image.Tung2022DeepJSCCQDecoder

Inheritance diagram for Tung2022DeepJSCCQDecoder
- class kaira.models.image.Tung2022DeepJSCCQDecoder(N: int, M: int, out_ch: int = 3, *args: Any, **kwargs: Any)[source]
Bases:
BaseModelDeepJSCCQ Decoder Module [Tung et al., 2022].
This module decodes a latent representation into an image using a series of convolutional layers and AFModules.
Methods
Initialize the DeepJSCCQDecoder.
Forward pass through the decoder.
Create model instance from configuration.
Create model from Hydra DictConfig.
Create model from Hugging Face PretrainedConfig.
- __init__(N: int, M: int, out_ch: int = 3, *args: Any, **kwargs: Any) None[source]
Initialize the DeepJSCCQDecoder.
- forward(x: Tensor, *args: Any, **kwargs: Any) Tensor[source]
Forward pass through the decoder.
- Parameters:
x (torch.Tensor) – The encoded latent representation.
*args – Additional positional arguments (unused).
**kwargs – Additional keyword arguments (unused).
- Returns:
The decoded image.
- Return type:
- classmethod from_config(config, **kwargs)
Create model instance from configuration.
- Parameters:
config – Configuration object (PretrainedConfig, DictConfig, or dict)
**kwargs – Additional parameters to override config
- Returns:
Model instance
- classmethod from_hydra_config(config: DictConfig, **kwargs)
Create model from Hydra DictConfig.
- Parameters:
config – Hydra configuration
**kwargs – Additional parameters
- Returns:
Model instance
- classmethod from_pretrained_config(config: PretrainedConfig, **kwargs)
Create model from Hugging Face PretrainedConfig.
- Parameters:
config – PretrainedConfig instance
**kwargs – Additional parameters
- Returns:
Model instance