ConvDecoder

class deepinv.models.ConvDecoder(img_shape, in_size=(4, 4), layers=7, channels=256)

Bases: Module

Convolutional decoder network.

The architecture was introduced in “Accelerated MRI with Un-trained Neural Networks”, and it is well suited as a deep image prior (see deepinv.models.DeepImagePrior).

Parameters:

• img_shape (tuple) – shape of the output image.

• in_size (tuple) – size of the input vector.

• layers (int) – number of layers in the network.

• channels (int) – number of channels in the network.

forward(x, scale_out=1)

Forward pass through the ConvDecoder network.

Parameters:

• x (torch.Tensor) – Input tensor.

• scale_out (float) – Output scaling factor.

Examples using ConvDecoder:

Reconstructing an image using the deep image prior.

Reconstructing an image using the deep image prior.