kaira.models.image.DeepJSCCFeedbackDecoder

Inheritance diagram for DeepJSCCFeedbackDecoder

class kaira.models.image.DeepJSCCFeedbackDecoder(n_channels: int, *args: Any, **kwargs: Any)

Bases: BaseModel

Decoder network for DeepJSCC with Feedback [Kurka and Gündüz, 2020].

This decoder reconstructs the image from the received noisy channel output. The architecture uses transposed convolutions with inverse GDN activations to convert the channel signal back into an image.

Parameters:

n_channels (int) – Number of channels in the output image (typically 3 for RGB).

Methods

__init__	Initialize the DeepJSCCFeedbackDecoder.
forward	Forward pass through the decoder.

__init__(n_channels: int, *args: Any, **kwargs: Any)

Initialize the DeepJSCCFeedbackDecoder.

Parameters:

• n_channels (int) – Number of channels in the output image.

• *args – Variable positional arguments passed to the base class.

• **kwargs – Variable keyword arguments passed to the base class.

forward(x: Tensor, *args: Any, **kwargs: Any) → Tensor

Forward pass through the decoder.

Parameters:

• x (torch.Tensor) – Channel output tensor to be decoded.

• *args – Additional positional arguments (passed to internal layers).

• **kwargs – Additional keyword arguments (passed to internal layers).

Returns:

Reconstructed image in range [0, 1].

Return type:

torch.Tensor