MRINufftAutoGrad#

class mrinufft.operators.autodiff.MRINufftAutoGrad(nufft_op, wrt_data=True, wrt_traj=False)[source]#

Bases: Module

Wraps the NUFFT operator to support torch autodiff.

Parameters:

nufft_op (Classic Non differentiable MRI-NUFFT operator.)

Methods

__init__

Initialize internal Module state, shared by both nn.Module and ScriptModule.

add_module

Add a child module to the current module.

adj_op

Compute the adjoint k-space -> image.

apply

Apply fn recursively to every submodule (as returned by .children()) as well as self.

bfloat16

Casts all floating point parameters and buffers to bfloat16 datatype.

buffers

Return an iterator over module buffers.

children

Return an iterator over immediate children modules.

compile

Compile this Module's forward using torch.compile().

cpu

Move all model parameters and buffers to the CPU.

cuda

Move all model parameters and buffers to the GPU.

double

Casts all floating point parameters and buffers to double datatype.

eval

Set the module in evaluation mode.

extra_repr

Set the extra representation of the module.

float

Casts all floating point parameters and buffers to float datatype.

forward

Define the computation performed at every call.

get_buffer

Return the buffer given by target if it exists, otherwise throw an error.

get_extra_state

Return any extra state to include in the module's state_dict.

get_parameter

Return the parameter given by target if it exists, otherwise throw an error.

get_submodule

Return the submodule given by target if it exists, otherwise throw an error.

half

Casts all floating point parameters and buffers to half datatype.

ipu

Move all model parameters and buffers to the IPU.

load_state_dict

Copy parameters and buffers from state_dict into this module and its descendants.

modules

Return an iterator over all modules in the network.

mtia

Move all model parameters and buffers to the MTIA.

named_buffers

Return an iterator over module buffers, yielding both the name of the buffer as well as the buffer itself.

named_children

Return an iterator over immediate children modules, yielding both the name of the module as well as the module itself.

named_modules

Return an iterator over all modules in the network, yielding both the name of the module as well as the module itself.

named_parameters

Return an iterator over module parameters, yielding both the name of the parameter as well as the parameter itself.

op

Compute the forward image -> k-space.

parameters

Return an iterator over module parameters.

register_backward_hook

Register a backward hook on the module.

register_buffer

Add a buffer to the module.

register_forward_hook

Register a forward hook on the module.

register_forward_pre_hook

Register a forward pre-hook on the module.

register_full_backward_hook

Register a backward hook on the module.

register_full_backward_pre_hook

Register a backward pre-hook on the module.

register_load_state_dict_post_hook

Register a post-hook to be run after module's load_state_dict() is called.

register_load_state_dict_pre_hook

Register a pre-hook to be run before module's load_state_dict() is called.

register_module

Alias for add_module().

register_parameter

Add a parameter to the module.

register_state_dict_post_hook

Register a post-hook for the state_dict() method.

register_state_dict_pre_hook

Register a pre-hook for the state_dict() method.

requires_grad_

Change if autograd should record operations on parameters in this module.

set_extra_state

Set extra state contained in the loaded state_dict.

set_submodule

Set the submodule given by target if it exists, otherwise throw an error.

share_memory

See torch.Tensor.share_memory_().

state_dict

Return a dictionary containing references to the whole state of the module.

to

Move and/or cast the parameters and buffers.

to_empty

Move the parameters and buffers to the specified device without copying storage.

train

Set the module in training mode.

type

Casts all parameters and buffers to dst_type.

xpu

Move all model parameters and buffers to the XPU.

zero_grad

Reset gradients of all model parameters.

Attributes

T_destination

call_super_init

dump_patches

samples

Get the samples.

training

op(x)[source]#

Compute the forward image -> k-space.

adj_op(kspace)[source]#

Compute the adjoint k-space -> image.

property samples#

Get the samples.