kaira.models.image.Xie2023DTDeepJSCCEncoder

Inheritance diagram for Xie2023DTDeepJSCCEncoder
- class kaira.models.image.Xie2023DTDeepJSCCEncoder(in_channels, latent_channels, architecture='cifar10', num_embeddings=None, input_size=None, *args, **kwargs)[source]
Bases:
BaseModelDiscrete Task-Oriented Deep JSCC encoder [Xie et al., 2023].
This implements the encoder part of the DT-DeepJSCC architecture as described in [Xie et al., 2023]. It maps input images to discrete latent representations that are robust to channel impairments.
- Parameters:
architecture (str, optional) – Type of architecture to use. Defaults to ‘cifar10’. Options: ‘cifar10’ or ‘custom’.
in_channels (int) – Number of input image channels (3 for RGB, 1 for grayscale)
latent_channels (int) – Number of channels in the latent representation
num_embeddings (int, optional) – Size of the discrete codebook. Defaults to None (automatically determined by architecture).
input_size (tuple, optional) – Input image size as (height, width). Defaults to None (automatically determined by architecture).
- Returns:
Encoded discrete representation of the input.
References
Methods
Forward pass for the DT-DeepJSCC encoder.
Create model instance from configuration.
Create model from Hydra DictConfig.
Create model from Hugging Face PretrainedConfig.
- __init__(in_channels, latent_channels, architecture='cifar10', num_embeddings=None, input_size=None, *args, **kwargs)[source]
- forward(x)[source]
Forward pass for the DT-DeepJSCC encoder.
- Parameters:
x (torch.Tensor) – Input image tensor [batch_size, channels, height, width]
- Returns:
Bits representation [batch_size, h*w, bits_per_symbol]
- 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