Inference Module

EMCqMRI.core.base.base_inference_model.InferenceModel.forward(self, inputs)

Abstract function that defines the forward pass of the inference model. It supports conventional and Deep Learning methods. For iterative methods, the steps must be implemented within this function.

Need subclass to implement different logics, like MLE, ResNet, RIM, etc.

Parameters

inputs ([list]) – list of torch.Tensors, containing one or more inputs. If one of the inputs is an image, it must have shape [B, N, X, Y, …], where B is the batch size, N is the number of channels and X,Y,… are the image dimensions. If one of the inputs are scalar parameters, it must have shape [B, N, X], where B is the batch size, N is the number of channels and X the number of parameters.

Raises

NotImplementedError – When the subclass does not override this method.

Returns

The subclass implementation should return the parameter estimates. If estimates are images, they should have shape [B, C, X, Y, …], where B is the batch size, C is the number of parameters and X, Y,… are the image dimensions. If estimates are scalars, they should have shape [B, X], where B is the batch size and X are parameters.

Return type

([torch.Tensor])