# deepinv > DeepInverse is the leading open-source PyTorch-based library for solving imaging inverse problems with deep learning. It provides imaging operators, pretrained reconstruction networks and denoisers, plug-and-play and unfolded optimization, sampling algorithms, training losses and datasets. deepinverse contributors 2026 ## Pages - [DeepInverse: a Python library for imaging with deep learning](https://deepinv.org/index.html.md): [![pip install](https://img.shields.io/pypi/dm/deepinv.svg?logo=pypi&label=pip%20install&color=fedcb... - [Quickstart](https://deepinv.org/quickstart.html.md): - [Examples](https://deepinv.org/auto_examples/index.html.md): All the examples have a download link at the end. You can load the example’s notebook on - [Basics](https://deepinv.org/auto_examples/basics/index.html.md):
- [5 minute quickstart tutorial](https://deepinv.org/auto_examples/basics/demo_quickstart.html.md): Follow this example to get started with DeepInverse in under 5 minutes. - [Use a pretrained model](https://deepinv.org/auto_examples/basics/demo_pretrained_model.html.md): Follow this example to reconstruct images using a pretrained model in one line. - [Use iterative reconstruction algorithms](https://deepinv.org/auto_examples/basics/demo_custom_optim.html.md): Follow this example to reconstruct images using an iterative algorithm. - [Bring your own dataset](https://deepinv.org/auto_examples/basics/demo_custom_dataset.html.md): This example shows how to use DeepInverse with your own dataset. - [Bring your own physics](https://deepinv.org/auto_examples/basics/demo_custom_physics.html.md): This examples shows you how to use DeepInverse with your own physics. - [Models](https://deepinv.org/auto_examples/models/index.html.md):
- [Inference and fine-tune a foundation model](https://deepinv.org/auto_examples/models/demo_foundation_model.html.md): This example shows how to perform inference on and fine-tune the Reconstruct Anything Model (RAM) fo... - [Training a reconstruction model](https://deepinv.org/auto_examples/models/demo_training.html.md): This example provides a very simple quick start introduction to training reconstruction networks wit... - [Benchmarking pretrained denoisers](https://deepinv.org/auto_examples/models/demo_denoiser_tour.html.md): This example provides a tour of the denoisers in DeepInverse. - [Super-resolution with SRResNet](https://deepinv.org/auto_examples/models/demo_super_resolution.html.md): Single-image super-resolution (SISR) is the inverse problem of recovering a - [Physics](https://deepinv.org/auto_examples/physics/index.html.md):
- [Tour of forward sensing operators](https://deepinv.org/auto_examples/physics/demo_physics_tour.html.md): This example provides a tour of some of the forward operators implemented in DeepInverse. - [Tour of blur operators](https://deepinv.org/auto_examples/physics/demo_blur_tour.html.md): This example provides a tour of 2D blur operators in DeepInverse. - [Tour of MRI functionality in DeepInverse](https://deepinv.org/auto_examples/physics/demo_mri_tour.html.md): This example presents the various datasets, forward physics and models - [3D diffraction PSF](https://deepinv.org/auto_examples/physics/demo_microscopy_3d.html.md): This example provides a tour of 3D blur operators in the library. - [Random phase retrieval and reconstruction methods.](https://deepinv.org/auto_examples/physics/demo_phase_retrieval.html.md): This example shows how to create a random phase retrieval operator and generate phaseless measuremen... - [Spectral Methods for Non-Circular Deblurring with Liu-Jia Padding](https://deepinv.org/auto_examples/physics/demo_liu_jia_padding.html.md): Real-world blurry images have decorrelated opposite boundaries, unlike images synthetically - [Positron emission tomography (PET) in 3D](https://deepinv.org/auto_examples/physics/demo_pet3d.html.md): This demo shows how to define a non time-of-flight PET scanner, simulate measurements - [Inverse scattering problem](https://deepinv.org/auto_examples/physics/demo_scattering.html.md): In this example we show how to use the [`deepinv.physics.Scattering`](https://deepinv.org/api/stubs/... - [Single photon lidar operator for depth ranging.](https://deepinv.org/auto_examples/physics/demo_lidar.html.md): In this example we show how to use the [`deepinv.physics.SinglePhotonLidar`](https://deepinv.org/api... - [Ptychography phase retrieval](https://deepinv.org/auto_examples/physics/demo_ptychography.html.md): This example shows how to create a Ptychography phase retrieval operator and generate phaseless meas... - [Positron emission tomography (PET) in 2D](https://deepinv.org/auto_examples/physics/demo_pet2d.html.md): This demo shows how to define a non time-of-flight PET scanner, simulate measurements - [Spatial unwrapping and modulo imaging](https://deepinv.org/auto_examples/physics/demo_spatial_unwrapping.html.md): This demo shows the use of the [`deepinv.physics.SpatialUnwrapping`](https://deepinv.org/api/stubs/d... - [Remote sensing with satellite images](https://deepinv.org/auto_examples/physics/demo_remote_sensing.html.md): In this example we demonstrate remote sensing inverse problems for multispectral satellite imaging. - [Poisson-Gaussian Denoising with the Generalized Anscombe Transform](https://deepinv.org/auto_examples/physics/demo_anscombe.html.md): This example demonstrates how to denoise images corrupted by - [Pattern Ordering in a Compressive Single Pixel Camera](https://deepinv.org/auto_examples/physics/demo_spc.html.md): This demo illustrates the impact of different Hadamard pattern ordering algorithms in the Single Pix... - [Optimization](https://deepinv.org/auto_examples/optimization/index.html.md):
- [3D denoising of brain MRI with wavelet and TV priors](https://deepinv.org/auto_examples/optimization/demo_3D_denoising.html.md): This example shows how to use variational 3D denoisers for denoising a 3D image. We first apply a st... - [Expected Patch Log Likelihood (EPLL) for Denoising and Inpainting](https://deepinv.org/auto_examples/optimization/demo_epll.html.md): In this example we use the expected patch log likelihood (EPLL) prior Zoran and Weiss[1](#footc... - [Image deblurring with Total-Variation (TV) prior](https://deepinv.org/auto_examples/optimization/demo_TV_minimisation.html.md): This example shows how to use a standard TV prior for image deblurring. The problem writes as $y = A... - [Image deblurring with custom deep explicit prior.](https://deepinv.org/auto_examples/optimization/demo_custom_prior.html.md): In this example, we show how to solve a deblurring inverse problem using an explicit prior. - [Image inpainting with wavelet prior](https://deepinv.org/auto_examples/optimization/demo_wavelet_prior.html.md): This example shows how to use a standard wavelet prior for image inpainting. The problem writes as $... - [Multispectral demosaicing from raw sensor data](https://deepinv.org/auto_examples/optimization/demo_multispectral_demosaicing.html.md): This example reconstructs a full-resolution multispectral image from raw snapshot - [Patch priors for limited-angle computed tomography](https://deepinv.org/auto_examples/optimization/demo_patch_priors_CT.html.md): In this example we use patch priors for limited angle computed tomography. More precisely, we consid... - [Poisson Inverse Problems with Maximum-Likelihood Expectation-Maximization (MLEM)](https://deepinv.org/auto_examples/optimization/demo_poisson_mlem.html.md): This example demonstrates how to solve Poisson inverse problems using the - [Reconstructing an image using the deep image prior.](https://deepinv.org/auto_examples/optimization/demo_dip.html.md): This code shows how to reconstruct a noisy and incomplete image using the deep image prior. - [Plug-and-Play](https://deepinv.org/auto_examples/plug-and-play/index.html.md):
- [DPIR method for PnP image deblurring.](https://deepinv.org/auto_examples/plug-and-play/demo_PnP_DPIR_deblur.html.md): This example shows how to use the DPIR method to solve a PnP image deblurring problem. The DPIR meth... - [Multi-scale Plug-and-Play for Inpainting](https://deepinv.org/auto_examples/plug-and-play/demo_PnP_multiscale.html.md): Plug-and-Play (PnP) is known to be challenging to apply to certain inverse problems - [Plug-and-Play algorithm with Mirror Descent for Poisson noise inverse problems.](https://deepinv.org/auto_examples/plug-and-play/demo_PnP_mirror_descent.html.md): This is a simple example to show how to use a mirror descent algorithm for solving an inverse proble... - [PnP with custom optimization algorithm (Primal-Dual Condat-Vu)](https://deepinv.org/auto_examples/plug-and-play/demo_PnP_custom_optim.html.md): This example shows how to define your own optimization algorithm. - [Regularization by Denoising (RED) for Super-Resolution.](https://deepinv.org/auto_examples/plug-and-play/demo_RED_GSPnP_SR.html.md): Implementation of Romano *et al.*[1](#footcite-romano2017little) using as plug-in denoise... - [Vanilla PnP for computed tomography (CT).](https://deepinv.org/auto_examples/plug-and-play/demo_vanilla_PnP.html.md): This example shows how to use a standard PnP algorithm with DnCNN denoiser for computed tomography. - [Diffusion & MCMC](https://deepinv.org/auto_examples/sampling/index.html.md):
- [Building your custom MCMC sampling algorithm.](https://deepinv.org/auto_examples/sampling/demo_custom_kernel.html.md): This code shows how to build your custom sampling kernel. Here we build a preconditioned Unadjusted ... - [Building your diffusion posterior sampling method using SDEs](https://deepinv.org/auto_examples/sampling/demo_diffusion_sde.html.md): This demo shows you how to use - [DPS – Posterior Sampling with Diffusion Models](https://deepinv.org/auto_examples/sampling/demo_dps.html.md): In this tutorial, we will go over the steps in the Diffusion Posterior Sampling (DPS) algorithm intr... - [Flow-Matching for posterior sampling and unconditional generation](https://deepinv.org/auto_examples/sampling/demo_flow_matching.html.md): This demo shows you how to perform unconditional image generation and posterior sampling using Flow ... - [Image reconstruction with a diffusion model](https://deepinv.org/auto_examples/sampling/demo_ddrm.html.md): This code shows you how to use the DDRM diffusion algorithm Kawar *et al.*[1](#footcite-kawar20... - [Implementing DiffPIR](https://deepinv.org/auto_examples/sampling/demo_diffpir.html.md): In this tutorial, we revisit the implementation of the DiffPIR diffusion algorithm for image reconst... - [Noisy data-fidelity terms for diffusion posterior sampling](https://deepinv.org/auto_examples/sampling/demo_noisy_data_fidelity.html.md): This example compares six approximations of the measurement-matching term - [Uncertainty quantification with PnP-ULA.](https://deepinv.org/auto_examples/sampling/demo_sampling.html.md): This code shows you how to use sampling algorithms to quantify uncertainty of a reconstruction - [Using state-of-the-art diffusion models from HuggingFace Diffusers with DeepInverse](https://deepinv.org/auto_examples/sampling/demo_diffusers.html.md): This demo shows you how to use our wrapper - [Unfolded](https://deepinv.org/auto_examples/unfolded/index.html.md):
- [DEAL denoising and reconstruction](https://deepinv.org/auto_examples/unfolded/demo_deal.html.md): This example shows how to use the Deep Equilibrium Attention Least Squares - [Deep Equilibrium (DEQ) algorithms for image deblurring](https://deepinv.org/auto_examples/unfolded/demo_DEQ.html.md): This a toy example to show you how to use DEQ to solve a deblurring problem. - [Learned Iterative Soft-Thresholding Algorithm (LISTA) for compressed sensing](https://deepinv.org/auto_examples/unfolded/demo_LISTA.html.md): This example shows how to implement the LISTA algorithm Gregor and LeCun[1](#footcite-gregor201... - [Learned Primal-Dual algorithm for CT scan.](https://deepinv.org/auto_examples/unfolded/demo_learned_primal_dual.html.md): Implementation of the Unfolded Primal-Dual algorithm from Adler and Öktem[1](#footcite-adler201... - [Learned iterative custom prior](https://deepinv.org/auto_examples/unfolded/demo_custom_prior_unfolded.html.md): This example shows how to implement a learned unrolled proximal gradient descent algorithm with a cu... - [Reducing the memory and computational complexity of unfolded network training](https://deepinv.org/auto_examples/unfolded/demo_unfolded_constant_memory.html.md): Some unfolded architectures rely on a [`least-squares solver`](https://deepinv.org/api/stubs/deepinv... - [Unfolded Chambolle-Pock for constrained image inpainting](https://deepinv.org/auto_examples/unfolded/demo_unfolded_constrained_LISTA.html.md): Image inpainting consists in solving $y = Ax$ where $A$ is a mask operator. - [Vanilla Unfolded algorithm for super-resolution](https://deepinv.org/auto_examples/unfolded/demo_vanilla_unfolded.html.md): This is a simple example to show how to use vanilla unfolded Plug-and-Play. - [Blind Inverse Problems](https://deepinv.org/auto_examples/blind-inverse-problems/index.html.md):
- [Blind deblurring with kernel estimation network](https://deepinv.org/auto_examples/blind-inverse-problems/demo_blind_deblurring.html.md): This example demonstrates blind image deblurring using the pretrained kernel estimation network from - [Blind denoising with noise level estimation](https://deepinv.org/auto_examples/blind-inverse-problems/demo_blind_denoising.html.md): This example focuses on blind image Gaussian denoising, i.e. the problem - [Calibrating physics operators](https://deepinv.org/auto_examples/blind-inverse-problems/demo_optimizing_physics_parameter.html.md): This demo shows you how to use - [Self-Supervised Learning](https://deepinv.org/auto_examples/self-supervised-learning/index.html.md):
- [Image transformations for Equivariant Imaging](https://deepinv.org/auto_examples/self-supervised-learning/demo_ei_transforms.html.md): This example demonstrates various geometric image transformations - [Low-field MRI denoising without ground truth](https://deepinv.org/auto_examples/self-supervised-learning/demo_lowfieldmri.html.md): We demonstrate self-supervised (blind) denoising of a low-field MRI scan without ground truth data. - [Poisson denoising using Poisson2Sparse](https://deepinv.org/auto_examples/self-supervised-learning/demo_poisson2sparse.html.md): This code shows how to restore a single image corrupted by Poisson noise using Poisson2Sparse, witho... - [Scan-specific zero-shot SSDU for MRI](https://deepinv.org/auto_examples/self-supervised-learning/demo_scan_specific.html.md): We demonstrate scan-specific self-supervised learning, that is, learning to - [Self-supervised MRI reconstruction with Artifact2Artifact](https://deepinv.org/auto_examples/self-supervised-learning/demo_artifact2artifact.html.md): We demonstrate the self-supervised Artifact2Artifact loss for solving an - [Self-supervised denoising with the Generalized R2R loss.](https://deepinv.org/auto_examples/self-supervised-learning/demo_r2r_denoising.html.md): This example shows you how to train a denoiser network in a fully self-supervised way, - [Self-supervised denoising with the Neighbor2Neighbor loss.](https://deepinv.org/auto_examples/self-supervised-learning/demo_n2n_denoising.html.md): This example shows you how to train a denoiser network in a fully self-supervised way, - [Self-supervised denoising with the SURE loss.](https://deepinv.org/auto_examples/self-supervised-learning/demo_sure_denoising.html.md): This example shows you how to train a denoiser network in a fully self-supervised way, - [Self-supervised denoising with the UNSURE loss.](https://deepinv.org/auto_examples/self-supervised-learning/demo_unsure.html.md): This example shows you how to train a denoiser network in a fully self-supervised way, - [Self-supervised learning from incomplete measurements of multiple operators.](https://deepinv.org/auto_examples/self-supervised-learning/demo_multioperator_imaging.html.md): This example shows you how to train a reconstruction network for an inpainting - [Self-supervised learning with Equivariant Imaging for MRI.](https://deepinv.org/auto_examples/self-supervised-learning/demo_equivariant_imaging.html.md): This example shows you how to train a reconstruction network for an MRI inverse problem on a fully s... - [Self-supervised learning with Equivariant Splitting](https://deepinv.org/auto_examples/self-supervised-learning/demo_equivariant_splitting.html.md): Equivariant splitting consists in minimizing a self-supervised loss to train a reconstruction model ... - [Self-supervised learning with measurement splitting](https://deepinv.org/auto_examples/self-supervised-learning/demo_splitting_loss.html.md): We demonstrate self-supervised learning with measurement splitting, to - [Ultrasound despeckling from B-mode images](https://deepinv.org/auto_examples/self-supervised-learning/demo_ultrasound_despeckling.html.md): This example despeckles real clinical ultrasound B-mode images with Speckle2Self - [Transformations & Equivariance](https://deepinv.org/auto_examples/transforms-equivariance/index.html.md):
- [Image transforms for equivariance & augmentations](https://deepinv.org/auto_examples/transforms-equivariance/demo_transforms.html.md): We demonstrate the use of our `deepinv.transform` module for use in - [Adversarial Learning](https://deepinv.org/auto_examples/adversarial-learning/index.html.md):
- [Imaging inverse problems with adversarial networks](https://deepinv.org/auto_examples/adversarial-learning/demo_gan_imaging.html.md): This example shows you how to train various networks using adversarial - [External Libraries](https://deepinv.org/auto_examples/external-libraries/index.html.md):
- [Loading scientific images](https://deepinv.org/auto_examples/external-libraries/demo_io.html.md): This example presents the various input/output functions provided by DeepInverse - [Low-dose CT with ASTRA backend and Total-Variation (TV) prior](https://deepinv.org/auto_examples/external-libraries/demo_astra_tomography.html.md): This example shows how to use the Astra tomography toolbox with deepinv, a popular toolbox for tomog... - [Low-intensity STED fluorescence microscopy denoising](https://deepinv.org/auto_examples/external-libraries/demo_microscopy_denoising.html.md): This example shows how to denoise low-intensity STED fluorescence microscopy - [Radio interferometric imaging with deepinverse](https://deepinv.org/auto_examples/external-libraries/demo_ri_basic.html.md): In this example, we investigate a simple 2D Radio Interferometry (RI) imaging task with deepinverse. - [Reconstruct real CT sinograms with the 2DeteCT benchmark](https://deepinv.org/auto_examples/external-libraries/demo_astra_2detect.html.md): We demonstrate image reconstruction of acquired CT projection data in sparse-view, limited-angle - [Single-pixel imaging with Spyrit](https://deepinv.org/auto_examples/external-libraries/demo_connect_spyrit.html.md): This example shows how to use Spyrit linear models and measurements with DeepInverse. - [Using HuggingFace datasets](https://deepinv.org/auto_examples/external-libraries/demo_hf_dataset.html.md): This example shows how to load and prepare properly a HuggingFace dataset - [Distributed Computing](https://deepinv.org/auto_examples/distributed/index.html.md):
- [Distributed Denoiser with Image Tiling](https://deepinv.org/auto_examples/distributed/demo_denoiser_distributed.html.md): In many imaging problems, the data to be processed can be very large, making it challenging to fit t... - [Distributed Physics Operators](https://deepinv.org/auto_examples/distributed/demo_physics_distributed.html.md): Many large-scale imaging problems involve operators that can be naturally decomposed as a stack of - [Distributed Plug-and-Play (PnP) Reconstruction](https://deepinv.org/auto_examples/distributed/demo_pnp_distributed.html.md): Many large-scale imaging problems involve operators that can be naturally decomposed as a stack of - [Distributed Training of Unfolded Networks](https://deepinv.org/auto_examples/distributed/demo_unrolled_distributed.html.md): In many large-scale imaging problems, the size of the image/volume to reconstruct is very large, mak... - [Metrics](https://deepinv.org/auto_examples/metrics/index.html.md):
- [Blind inverse problems with no reference metrics](https://deepinv.org/auto_examples/metrics/demo_test_time_tuning.html.md): In blind inverse problems, some parameters of the physics are unknown at test time. - [Fitting NIQE on a custom dataset](https://deepinv.org/auto_examples/metrics/demo_custom_niqe.html.md): This example shows how to fit [`deepinv.loss.metric.NIQE`](https://deepinv.org/api/stubs/deepinv.los... - [User Guide](https://deepinv.org/user_guide.html.md): Imaging inverse problems are described by the equation $y = \noise{\forw{x}}$ where - [Introduction](https://deepinv.org/user_guide/physics/intro.html.md): This module contains a large collection of forward operators appearing in imaging applications. - [Operators & Noise](https://deepinv.org/user_guide/physics/physics.html.md): Operators describe the forward model $z = A(x,\theta)$, where - [Functional](https://deepinv.org/user_guide/physics/functional.html.md): The toolbox is based on efficient PyTorch implementations of basic operations such as diagonal multi... - [Introduction](https://deepinv.org/user_guide/reconstruction/introduction.html.md): Reconstruction algorithms define an inversion function $\hat{x}=\inversef{y}{A}$ - [Pseudoinverse](https://deepinv.org/user_guide/reconstruction/least-squares.html.md): This section describes reconstruction methods that do not require priors or training, and can be use... - [Pretrained Models](https://deepinv.org/user_guide/reconstruction/pretrained-models.html.md): Some methods do not require any training and can be quickly deployed to your problem. - [Denoisers](https://deepinv.org/user_guide/reconstruction/denoisers.html.md): The [`deepinv.models.Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepin... - [Deep Reconstruction Models](https://deepinv.org/user_guide/reconstruction/deep-reconstructors.html.md): The simplest method for reconstructing an image from measurements is to pass it through a feedforwar... - [Optimization](https://deepinv.org/user_guide/reconstruction/optimization.html.md): This module contains a collection of routines that optimize - [Iterative Reconstruction (PnP, RED, etc.)](https://deepinv.org/user_guide/reconstruction/iterative.html.md): Many image reconstruction algorithms can be shown to be solving - [Diffusion and MCMC Algorithms](https://deepinv.org/user_guide/reconstruction/sampling.html.md): This module contains posterior sampling algorithms, based on diffusion models and Markov Chain Monte... - [Unfolded Algorithms](https://deepinv.org/user_guide/reconstruction/unfolded.html.md): Unfolded architectures (sometimes called ‘unrolled architectures’) are obtained by replacing parts o... - [Adversarial Networks](https://deepinv.org/user_guide/reconstruction/adversarial.html.md): There are two types of adversarial networks for imaging: conditional and unconditional. - [Blind Inverse Problems](https://deepinv.org/user_guide/reconstruction/blind.html.md): Following the [notation of the library](https://deepinv.org/user_guide/physics/intro.html.md#paramet... - [Trainer](https://deepinv.org/user_guide/training/trainer.html.md): Training a reconstruction model can be done using the [`deepinv.Trainer`](https://deepinv.org/api/st... - [Datasets](https://deepinv.org/user_guide/training/datasets.html.md): The datasets module lets you use datasets with DeepInverse, for testing and training. - [Training Losses](https://deepinv.org/user_guide/training/loss.html.md): This module contains popular training losses for supervised and self-supervised learning, - [Metrics](https://deepinv.org/user_guide/training/metric.html.md): This module contains popular metrics for inverse problems. - [Transforms](https://deepinv.org/user_guide/training/transforms.html.md): This module contains different transforms which can be used for data augmentation or together with t... - [Using Multiple GPUs](https://deepinv.org/user_guide/training/multigpu.html.md): Since all deepinv building blocks inherit from [`torch.nn.Module`](https://docs.pytorch.org/docs/sta... - [Utils](https://deepinv.org/user_guide/other/utils.html.md): We provide some plotting functions that are adapted to inverse problems. - [Math Notation](https://deepinv.org/user_guide/other/notation.html.md): The documentation of `deepinv` uses a unified mathematical notation that is summarized in the follow... - [Environment Variables](https://deepinv.org/user_guide/other/env_variable.html.md): The following environment variables can be used to configure the behavior of the `deepinv` library: - [Distributed Reconstruction](https://deepinv.org/user_guide/distributed/reconstruction.html.md): For large-scale inverse problems, the memory and compute of a single device might not be enough. - [Distributed Training](https://deepinv.org/user_guide/distributed/training.html.md): The distributed framework can be used during training when a - [API](https://deepinv.org/API.html.md): * [deepinv.datasets](https://deepinv.org/api/deepinv.datasets.html.md) - [deepinv.datasets](https://deepinv.org/api/deepinv.datasets.html.md): This module can be used for defining datasets or generating reconstruction datasets from other base ... - [ImageDataset](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md): Bases: [`Dataset`](https://docs.pytorch.org/docs/stable/data.html#torch.utils.data.Dataset) - [ImageFolder](https://deepinv.org/api/stubs/deepinv.datasets.ImageFolder.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [TensorDataset](https://deepinv.org/api/stubs/deepinv.datasets.TensorDataset.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [check_dataset](https://deepinv.org/api/stubs/deepinv.datasets.check_dataset.html.md): Check that a torch dataset is compatible with DeepInverse. - [HDF5Dataset](https://deepinv.org/api/stubs/deepinv.datasets.HDF5Dataset.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [generate_dataset](https://deepinv.org/api/stubs/deepinv.datasets.generate_dataset.html.md): Generates dataset of signal/measurement pairs from base dataset. - [DIV2K](https://deepinv.org/api/stubs/deepinv.datasets.DIV2K.html.md): Bases: [`ImageFolder`](https://deepinv.org/api/stubs/deepinv.datasets.ImageFolder.html.md#deepinv.da... - [Urban100HR](https://deepinv.org/api/stubs/deepinv.datasets.Urban100HR.html.md): Bases: [`ImageFolder`](https://deepinv.org/api/stubs/deepinv.datasets.ImageFolder.html.md#deepinv.da... - [Set14HR](https://deepinv.org/api/stubs/deepinv.datasets.Set14HR.html.md): Bases: [`ImageFolder`](https://deepinv.org/api/stubs/deepinv.datasets.ImageFolder.html.md#deepinv.da... - [Set5HR](https://deepinv.org/api/stubs/deepinv.datasets.Set5HR.html.md): Bases: [`ImageFolder`](https://deepinv.org/api/stubs/deepinv.datasets.ImageFolder.html.md#deepinv.da... - [BSDS500](https://deepinv.org/api/stubs/deepinv.datasets.BSDS500.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [BSD100HR](https://deepinv.org/api/stubs/deepinv.datasets.BSD100HR.html.md): Bases: [`ImageFolder`](https://deepinv.org/api/stubs/deepinv.datasets.ImageFolder.html.md#deepinv.da... - [McMaster](https://deepinv.org/api/stubs/deepinv.datasets.McMaster.html.md): Bases: [`ImageFolder`](https://deepinv.org/api/stubs/deepinv.datasets.ImageFolder.html.md#deepinv.da... - [Kodak24](https://deepinv.org/api/stubs/deepinv.datasets.Kodak24.html.md): Bases: [`ImageFolder`](https://deepinv.org/api/stubs/deepinv.datasets.ImageFolder.html.md#deepinv.da... - [CBSD68](https://deepinv.org/api/stubs/deepinv.datasets.CBSD68.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [FastMRISliceDataset](https://deepinv.org/api/stubs/deepinv.datasets.FastMRISliceDataset.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [SimpleFastMRISliceDataset](https://deepinv.org/api/stubs/deepinv.datasets.SimpleFastMRISliceDataset.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [CMRxReconSliceDataset](https://deepinv.org/api/stubs/deepinv.datasets.CMRxReconSliceDataset.html.md): Bases: [`FastMRISliceDataset`](https://deepinv.org/api/stubs/deepinv.datasets.FastMRISliceDataset.ht... - [SKMTEASliceDataset](https://deepinv.org/api/stubs/deepinv.datasets.SKMTEASliceDataset.html.md): Bases: [`FastMRISliceDataset`](https://deepinv.org/api/stubs/deepinv.datasets.FastMRISliceDataset.ht... - [LidcIdriSliceDataset](https://deepinv.org/api/stubs/deepinv.datasets.LidcIdriSliceDataset.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [DeteCTDataset](https://deepinv.org/api/stubs/deepinv.datasets.DeteCTDataset.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [Flickr2kHR](https://deepinv.org/api/stubs/deepinv.datasets.Flickr2kHR.html.md): Bases: [`ImageFolder`](https://deepinv.org/api/stubs/deepinv.datasets.ImageFolder.html.md#deepinv.da... - [LsdirHR](https://deepinv.org/api/stubs/deepinv.datasets.LsdirHR.html.md): Bases: [`ImageFolder`](https://deepinv.org/api/stubs/deepinv.datasets.ImageFolder.html.md#deepinv.da... - [FMD](https://deepinv.org/api/stubs/deepinv.datasets.FMD.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [Kohler](https://deepinv.org/api/stubs/deepinv.datasets.Kohler.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [NBUDataset](https://deepinv.org/api/stubs/deepinv.datasets.NBUDataset.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [BrainWebPET](https://deepinv.org/api/stubs/deepinv.datasets.BrainWebPET.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [BrainWebMRI](https://deepinv.org/api/stubs/deepinv.datasets.BrainWebMRI.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [PatchDataset](https://deepinv.org/api/stubs/deepinv.datasets.PatchDataset.html.md): Bases: [`TiledMixin2d`](https://deepinv.org/api/stubs/deepinv.utils.TiledMixin2d.html.md#deepinv.uti... - [RandomPatchSampler](https://deepinv.org/api/stubs/deepinv.datasets.RandomPatchSampler.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [PlaceholderDataset](https://deepinv.org/api/stubs/deepinv.datasets.utils.PlaceholderDataset.html.md): Bases: [`ImageDataset`](https://deepinv.org/api/stubs/deepinv.datasets.ImageDataset.html.md#deepinv.... - [Rescale](https://deepinv.org/api/stubs/deepinv.datasets.utils.Rescale.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [ToComplex](https://deepinv.org/api/stubs/deepinv.datasets.utils.ToComplex.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [Crop](https://deepinv.org/api/stubs/deepinv.datasets.utils.Crop.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [MRISliceTransform](https://deepinv.org/api/stubs/deepinv.datasets.MRISliceTransform.html.md): Bases: [`MRIMixin`](https://deepinv.org/api/stubs/deepinv.utils.MRIMixin.html.md#deepinv.utils.MRIMi... - [deepinv.distributed](https://deepinv.org/api/deepinv.distributed.html.md): This module provides a simplified API for distributing DeepInverse objects across - [DistributedContext](https://deepinv.org/api/stubs/deepinv.distributed.DistributedContext.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [distribute](https://deepinv.org/api/stubs/deepinv.distributed.distribute.html.md): Distribute a DeepInverse object across multiple devices. - [DistributedStackedPhysics](https://deepinv.org/api/stubs/deepinv.distributed.framework.DistributedStackedPhysics.html.md): Bases: [`Physics`](https://deepinv.org/api/stubs/deepinv.physics.Physics.html.md#deepinv.physics.Phy... - [DistributedStackedLinearPhysics](https://deepinv.org/api/stubs/deepinv.distributed.framework.DistributedStackedLinearPhysics.html.md): Bases: [`DistributedStackedPhysics`](https://deepinv.org/api/stubs/deepinv.distributed.framework.Dis... - [DistributedProcessing](https://deepinv.org/api/stubs/deepinv.distributed.framework.DistributedProcessing.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [DistributedDataFidelity](https://deepinv.org/api/stubs/deepinv.distributed.framework.DistributedDataFidelity.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [DistributedReplicatedParameters](https://deepinv.org/api/stubs/deepinv.distributed.framework.DistributedReplicatedParameters.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [DistributedSignalStrategy](https://deepinv.org/api/stubs/deepinv.distributed.strategies.DistributedSignalStrategy.html.md): Bases: [`ABC`](https://docs.python.org/3.9/library/abc.html#abc.ABC) - [TilingStrategy](https://deepinv.org/api/stubs/deepinv.distributed.strategies.distributed_strategies.TilingStrategy.html.md): Bases: [`DistributedSignalStrategy`](https://deepinv.org/api/stubs/deepinv.distributed.strategies.Di... - [create_strategy](https://deepinv.org/api/stubs/deepinv.distributed.strategies.create_strategy.html.md): Create a distributed signal strategy. - [deepinv.loss](https://deepinv.org/api/deepinv.loss.html.md): This module provides a collection of supervised and self-supervised loss functions for training reco... - [Loss](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [StackedPhysicsLoss](https://deepinv.org/api/stubs/deepinv.loss.StackedPhysicsLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [SupLoss](https://deepinv.org/api/stubs/deepinv.loss.SupLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [MCLoss](https://deepinv.org/api/stubs/deepinv.loss.MCLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [EILoss](https://deepinv.org/api/stubs/deepinv.loss.EILoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [EquivariantSplittingLoss](https://deepinv.org/api/stubs/deepinv.loss.EquivariantSplittingLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [MOILoss](https://deepinv.org/api/stubs/deepinv.loss.MOILoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [MOEILoss](https://deepinv.org/api/stubs/deepinv.loss.MOEILoss.html.md): Bases: [`EILoss`](https://deepinv.org/api/stubs/deepinv.loss.EILoss.html.md#deepinv.loss.EILoss), [`... - [Neighbor2Neighbor](https://deepinv.org/api/stubs/deepinv.loss.Neighbor2Neighbor.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [SplittingLoss](https://deepinv.org/api/stubs/deepinv.loss.SplittingLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [SureGaussianLoss](https://deepinv.org/api/stubs/deepinv.loss.SureGaussianLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [SurePoissonLoss](https://deepinv.org/api/stubs/deepinv.loss.SurePoissonLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [SurePGLoss](https://deepinv.org/api/stubs/deepinv.loss.SurePGLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [TVLoss](https://deepinv.org/api/stubs/deepinv.loss.TVLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [R2RLoss](https://deepinv.org/api/stubs/deepinv.loss.R2RLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [ScoreLoss](https://deepinv.org/api/stubs/deepinv.loss.ScoreLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [AugmentConsistencyLoss](https://deepinv.org/api/stubs/deepinv.loss.AugmentConsistencyLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [ReducedResolutionLoss](https://deepinv.org/api/stubs/deepinv.loss.ReducedResolutionLoss.html.md): Bases: [`SupLoss`](https://deepinv.org/api/stubs/deepinv.loss.SupLoss.html.md#deepinv.loss.SupLoss) - [WeightedSplittingLoss](https://deepinv.org/api/stubs/deepinv.loss.mri.WeightedSplittingLoss.html.md): Bases: [`SplittingLoss`](https://deepinv.org/api/stubs/deepinv.loss.SplittingLoss.html.md#deepinv.lo... - [RobustSplittingLoss](https://deepinv.org/api/stubs/deepinv.loss.mri.RobustSplittingLoss.html.md): Bases: [`WeightedSplittingLoss`](https://deepinv.org/api/stubs/deepinv.loss.mri.WeightedSplittingLos... - [Phase2PhaseLoss](https://deepinv.org/api/stubs/deepinv.loss.mri.Phase2PhaseLoss.html.md): Bases: [`SplittingLoss`](https://deepinv.org/api/stubs/deepinv.loss.SplittingLoss.html.md#deepinv.lo... - [Artifact2ArtifactLoss](https://deepinv.org/api/stubs/deepinv.loss.mri.Artifact2ArtifactLoss.html.md): Bases: [`Phase2PhaseLoss`](https://deepinv.org/api/stubs/deepinv.loss.mri.Phase2PhaseLoss.html.md#de... - [ENSURELoss](https://deepinv.org/api/stubs/deepinv.loss.mri.ENSURELoss.html.md): Bases: [`SureGaussianLoss`](https://deepinv.org/api/stubs/deepinv.loss.SureGaussianLoss.html.md#deep... - [DiscriminatorMetric](https://deepinv.org/api/stubs/deepinv.loss.adversarial.DiscriminatorMetric.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [GeneratorLoss](https://deepinv.org/api/stubs/deepinv.loss.adversarial.GeneratorLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [DiscriminatorLoss](https://deepinv.org/api/stubs/deepinv.loss.adversarial.DiscriminatorLoss.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [SupAdversarialGeneratorLoss](https://deepinv.org/api/stubs/deepinv.loss.adversarial.SupAdversarialGeneratorLoss.html.md): Bases: [`GeneratorLoss`](https://deepinv.org/api/stubs/deepinv.loss.adversarial.GeneratorLoss.html.m... - [SupAdversarialDiscriminatorLoss](https://deepinv.org/api/stubs/deepinv.loss.adversarial.SupAdversarialDiscriminatorLoss.html.md): Bases: [`DiscriminatorLoss`](https://deepinv.org/api/stubs/deepinv.loss.adversarial.DiscriminatorLos... - [UnsupAdversarialGeneratorLoss](https://deepinv.org/api/stubs/deepinv.loss.adversarial.UnsupAdversarialGeneratorLoss.html.md): Bases: [`GeneratorLoss`](https://deepinv.org/api/stubs/deepinv.loss.adversarial.GeneratorLoss.html.m... - [UnsupAdversarialDiscriminatorLoss](https://deepinv.org/api/stubs/deepinv.loss.adversarial.UnsupAdversarialDiscriminatorLoss.html.md): Bases: [`DiscriminatorLoss`](https://deepinv.org/api/stubs/deepinv.loss.adversarial.DiscriminatorLos... - [UAIRGeneratorLoss](https://deepinv.org/api/stubs/deepinv.loss.adversarial.UAIRGeneratorLoss.html.md): Bases: [`GeneratorLoss`](https://deepinv.org/api/stubs/deepinv.loss.adversarial.GeneratorLoss.html.m... - [JacobianSpectralNorm](https://deepinv.org/api/stubs/deepinv.loss.JacobianSpectralNorm.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [FNEJacobianSpectralNorm](https://deepinv.org/api/stubs/deepinv.loss.FNEJacobianSpectralNorm.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [BaseLossScheduler](https://deepinv.org/api/stubs/deepinv.loss.BaseLossScheduler.html.md): Bases: [`Loss`](https://deepinv.org/api/stubs/deepinv.loss.Loss.html.md#deepinv.loss.Loss) - [RandomLossScheduler](https://deepinv.org/api/stubs/deepinv.loss.RandomLossScheduler.html.md): Bases: [`BaseLossScheduler`](https://deepinv.org/api/stubs/deepinv.loss.BaseLossScheduler.html.md#de... - [InterleavedLossScheduler](https://deepinv.org/api/stubs/deepinv.loss.InterleavedLossScheduler.html.md): Bases: [`BaseLossScheduler`](https://deepinv.org/api/stubs/deepinv.loss.BaseLossScheduler.html.md#de... - [InterleavedEpochLossScheduler](https://deepinv.org/api/stubs/deepinv.loss.InterleavedEpochLossScheduler.html.md): Bases: [`BaseLossScheduler`](https://deepinv.org/api/stubs/deepinv.loss.BaseLossScheduler.html.md#de... - [StepLossScheduler](https://deepinv.org/api/stubs/deepinv.loss.StepLossScheduler.html.md): Bases: [`BaseLossScheduler`](https://deepinv.org/api/stubs/deepinv.loss.BaseLossScheduler.html.md#de... - [deepinv.models](https://deepinv.org/api/deepinv.models.html.md): This module contains a collection of models for denoising and reconstruction. - [Denoiser](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [Reconstructor](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [BM3D](https://deepinv.org/api/stubs/deepinv.models.BM3D.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [BilateralFilter](https://deepinv.org/api/stubs/deepinv.models.BilateralFilter.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [MedianFilter](https://deepinv.org/api/stubs/deepinv.models.MedianFilter.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [TVDenoiser](https://deepinv.org/api/stubs/deepinv.models.TVDenoiser.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [TVL1Denoiser](https://deepinv.org/api/stubs/deepinv.models.TVL1Denoiser.html.md): Bases: [`TVDenoiser`](https://deepinv.org/api/stubs/deepinv.models.TVDenoiser.html.md#deepinv.models... - [TGVDenoiser](https://deepinv.org/api/stubs/deepinv.models.TGVDenoiser.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [WaveletDenoiser](https://deepinv.org/api/stubs/deepinv.models.WaveletDenoiser.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [WaveletDictDenoiser](https://deepinv.org/api/stubs/deepinv.models.WaveletDictDenoiser.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [EPLLDenoiser](https://deepinv.org/api/stubs/deepinv.models.EPLLDenoiser.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [MMSE](https://deepinv.org/api/stubs/deepinv.models.MMSE.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [AutoEncoder](https://deepinv.org/api/stubs/deepinv.models.AutoEncoder.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [UNet](https://deepinv.org/api/stubs/deepinv.models.UNet.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [DnCNN](https://deepinv.org/api/stubs/deepinv.models.DnCNN.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [DRUNet](https://deepinv.org/api/stubs/deepinv.models.DRUNet.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [SCUNet](https://deepinv.org/api/stubs/deepinv.models.SCUNet.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [GSDRUNet](https://deepinv.org/api/stubs/deepinv.models.GSDRUNet.html.md): Gradient Step Denoiser with DRUNet architecture. - [SwinIR](https://deepinv.org/api/stubs/deepinv.models.SwinIR.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [PromptIR](https://deepinv.org/api/stubs/deepinv.models.PromptIR.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [DiffUNet](https://deepinv.org/api/stubs/deepinv.models.DiffUNet.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [Restormer](https://deepinv.org/api/stubs/deepinv.models.Restormer.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [ICNN](https://deepinv.org/api/stubs/deepinv.models.ICNN.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [VarNet](https://deepinv.org/api/stubs/deepinv.models.VarNet.html.md): Bases: [`ArtifactRemoval`](https://deepinv.org/api/stubs/deepinv.models.ArtifactRemoval.html.md#deep... - [MoDL](https://deepinv.org/api/stubs/deepinv.models.MoDL.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [PanNet](https://deepinv.org/api/stubs/deepinv.models.PanNet.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [ADMUNet](https://deepinv.org/api/stubs/deepinv.models.ADMUNet.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [NCSNpp](https://deepinv.org/api/stubs/deepinv.models.NCSNpp.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [DScCP](https://deepinv.org/api/stubs/deepinv.models.DScCP.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [RAM](https://deepinv.org/api/stubs/deepinv.models.RAM.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [DEAL](https://deepinv.org/api/stubs/deepinv.models.DEAL.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [ArtifactRemoval](https://deepinv.org/api/stubs/deepinv.models.ArtifactRemoval.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [SRResNet](https://deepinv.org/api/stubs/deepinv.models.SRResNet.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [FFDNet](https://deepinv.org/api/stubs/deepinv.models.FFDNet.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [EquivariantDenoiser](https://deepinv.org/api/stubs/deepinv.models.EquivariantDenoiser.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [EquivariantReconstructor](https://deepinv.org/api/stubs/deepinv.models.EquivariantReconstructor.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [TimeAgnosticNet](https://deepinv.org/api/stubs/deepinv.models.TimeAgnosticNet.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [TimeAveragingNet](https://deepinv.org/api/stubs/deepinv.models.TimeAveragingNet.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [Client](https://deepinv.org/api/stubs/deepinv.models.Client.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [AnscombeDenoiser](https://deepinv.org/api/stubs/deepinv.models.AnscombeDenoiser.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [to_complex_denoiser](https://deepinv.org/api/stubs/deepinv.models.complex.to_complex_denoiser.html.md): Converts a denoiser with real inputs into the one with complex inputs. - [generalized_anscombe_transform](https://deepinv.org/api/stubs/deepinv.models.generalized_anscombe_transform.html.md): Generalized Anscombe Transform (GAT) - [inverse_generalized_anscombe_transform](https://deepinv.org/api/stubs/deepinv.models.inverse_generalized_anscombe_transform.html.md): Inverse Generalized Anscombe Transform (IGAT) - [ScoreModelWrapper](https://deepinv.org/api/stubs/deepinv.models.ScoreModelWrapper.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [DiffusersDenoiserWrapper](https://deepinv.org/api/stubs/deepinv.models.DiffusersDenoiserWrapper.html.md): Bases: [`ScoreModelWrapper`](https://deepinv.org/api/stubs/deepinv.models.ScoreModelWrapper.html.md#... - [ComplexDenoiserWrapper](https://deepinv.org/api/stubs/deepinv.models.ComplexDenoiserWrapper.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [MinusOneOneDenoiserWrapper](https://deepinv.org/api/stubs/deepinv.models.MinusOneOneDenoiserWrapper.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [DeepImagePrior](https://deepinv.org/api/stubs/deepinv.models.DeepImagePrior.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [ConvDecoder](https://deepinv.org/api/stubs/deepinv.models.ConvDecoder.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [Poisson2Sparse](https://deepinv.org/api/stubs/deepinv.models.Poisson2Sparse.html.md): Bases: [`Denoiser`](https://deepinv.org/api/stubs/deepinv.models.Denoiser.html.md#deepinv.models.Den... - [ConvLista](https://deepinv.org/api/stubs/deepinv.models.ConvLista.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [PatchGANDiscriminator](https://deepinv.org/api/stubs/deepinv.models.PatchGANDiscriminator.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [ESRGANDiscriminator](https://deepinv.org/api/stubs/deepinv.models.ESRGANDiscriminator.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [DCGANGenerator](https://deepinv.org/api/stubs/deepinv.models.DCGANGenerator.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [DCGANDiscriminator](https://deepinv.org/api/stubs/deepinv.models.DCGANDiscriminator.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [CSGMGenerator](https://deepinv.org/api/stubs/deepinv.models.CSGMGenerator.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [KernelIdentificationNetwork](https://deepinv.org/api/stubs/deepinv.models.KernelIdentificationNetwork.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [WaveletNoiseEstimator](https://deepinv.org/api/stubs/deepinv.models.WaveletNoiseEstimator.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [PatchCovarianceNoiseEstimator](https://deepinv.org/api/stubs/deepinv.models.PatchCovarianceNoiseEstimator.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [deepinv.metric](https://deepinv.org/api/deepinv.metric.html.md): Metrics are generally used to evaluate the performance of a model, or as the distance function insid... - [Metric](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [MSE](https://deepinv.org/api/stubs/deepinv.loss.metric.MSE.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [NMSE](https://deepinv.org/api/stubs/deepinv.loss.metric.NMSE.html.md): Bases: [`MSE`](https://deepinv.org/api/stubs/deepinv.loss.metric.MSE.html.md#deepinv.loss.metric.MSE... - [MAE](https://deepinv.org/api/stubs/deepinv.loss.metric.MAE.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [PSNR](https://deepinv.org/api/stubs/deepinv.loss.metric.PSNR.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [SNR](https://deepinv.org/api/stubs/deepinv.loss.metric.SNR.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [SSIM](https://deepinv.org/api/stubs/deepinv.loss.metric.SSIM.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [L1L2](https://deepinv.org/api/stubs/deepinv.loss.metric.L1L2.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [LpNorm](https://deepinv.org/api/stubs/deepinv.loss.metric.LpNorm.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [LPIPS](https://deepinv.org/api/stubs/deepinv.loss.metric.LPIPS.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [SpectralAngleMapper](https://deepinv.org/api/stubs/deepinv.loss.metric.SpectralAngleMapper.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [ERGAS](https://deepinv.org/api/stubs/deepinv.loss.metric.ERGAS.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [HaarPSI](https://deepinv.org/api/stubs/deepinv.loss.metric.HaarPSI.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [CosineSimilarity](https://deepinv.org/api/stubs/deepinv.loss.metric.CosineSimilarity.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [GMSD](https://deepinv.org/api/stubs/deepinv.loss.metric.GMSD.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [RecoveryCoefficient](https://deepinv.org/api/stubs/deepinv.loss.metric.RecoveryCoefficient.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [NRMSE](https://deepinv.org/api/stubs/deepinv.loss.metric.NRMSE.html.md): Bases: [`NMSE`](https://deepinv.org/api/stubs/deepinv.loss.metric.NMSE.html.md#deepinv.loss.metric.N... - [NIQE](https://deepinv.org/api/stubs/deepinv.loss.metric.NIQE.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [BRISQUE](https://deepinv.org/api/stubs/deepinv.loss.metric.BRISQUE.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [NIMA](https://deepinv.org/api/stubs/deepinv.loss.metric.NIMA.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [QNR](https://deepinv.org/api/stubs/deepinv.loss.metric.QNR.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [BlurStrength](https://deepinv.org/api/stubs/deepinv.loss.metric.BlurStrength.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [SharpnessIndex](https://deepinv.org/api/stubs/deepinv.loss.metric.SharpnessIndex.html.md): Bases: [`Metric`](https://deepinv.org/api/stubs/deepinv.loss.metric.Metric.html.md#deepinv.loss.metr... - [deepinv.optim](https://deepinv.org/api/deepinv.optim.html.md): This module provides optimization utils for constructing reconstruction models based on optimization... - [optim_builder](https://deepinv.org/api/stubs/deepinv.optim.optim_builder.html.md): > Helper function for building an instance of the [`deepinv.optim.BaseOptim`](https://deepinv.org/ap... - [BaseOptim](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [BacktrackingConfig](https://deepinv.org/api/stubs/deepinv.optim.BacktrackingConfig.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [AndersonAccelerationConfig](https://deepinv.org/api/stubs/deepinv.optim.AndersonAccelerationConfig.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [DEQConfig](https://deepinv.org/api/stubs/deepinv.optim.DEQConfig.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [GD](https://deepinv.org/api/stubs/deepinv.optim.GD.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [PGD](https://deepinv.org/api/stubs/deepinv.optim.PGD.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [FISTA](https://deepinv.org/api/stubs/deepinv.optim.FISTA.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [ADMM](https://deepinv.org/api/stubs/deepinv.optim.ADMM.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [DRS](https://deepinv.org/api/stubs/deepinv.optim.DRS.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [HQS](https://deepinv.org/api/stubs/deepinv.optim.HQS.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [MD](https://deepinv.org/api/stubs/deepinv.optim.MD.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [PMD](https://deepinv.org/api/stubs/deepinv.optim.PMD.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [PDCP](https://deepinv.org/api/stubs/deepinv.optim.PDCP.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [SIRT](https://deepinv.org/api/stubs/deepinv.optim.SIRT.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [MLEM](https://deepinv.org/api/stubs/deepinv.optim.MLEM.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [OSEM](https://deepinv.org/api/stubs/deepinv.optim.OSEM.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [Potential](https://deepinv.org/api/stubs/deepinv.optim.Potential.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [DataFidelity](https://deepinv.org/api/stubs/deepinv.optim.DataFidelity.html.md): Bases: [`Potential`](https://deepinv.org/api/stubs/deepinv.optim.Potential.html.md#deepinv.optim.Pot... - [StackedPhysicsDataFidelity](https://deepinv.org/api/stubs/deepinv.optim.StackedPhysicsDataFidelity.html.md): Bases: [`DataFidelity`](https://deepinv.org/api/stubs/deepinv.optim.DataFidelity.html.md#deepinv.opt... - [L1](https://deepinv.org/api/stubs/deepinv.optim.L1.html.md): Bases: [`DataFidelity`](https://deepinv.org/api/stubs/deepinv.optim.DataFidelity.html.md#deepinv.opt... - [L2](https://deepinv.org/api/stubs/deepinv.optim.L2.html.md): Bases: [`DataFidelity`](https://deepinv.org/api/stubs/deepinv.optim.DataFidelity.html.md#deepinv.opt... - [IndicatorL2](https://deepinv.org/api/stubs/deepinv.optim.IndicatorL2.html.md): Bases: [`DataFidelity`](https://deepinv.org/api/stubs/deepinv.optim.DataFidelity.html.md#deepinv.opt... - [PoissonLikelihood](https://deepinv.org/api/stubs/deepinv.optim.PoissonLikelihood.html.md): Bases: [`DataFidelity`](https://deepinv.org/api/stubs/deepinv.optim.DataFidelity.html.md#deepinv.opt... - [LogPoissonLikelihood](https://deepinv.org/api/stubs/deepinv.optim.LogPoissonLikelihood.html.md): Bases: [`DataFidelity`](https://deepinv.org/api/stubs/deepinv.optim.DataFidelity.html.md#deepinv.opt... - [AmplitudeLoss](https://deepinv.org/api/stubs/deepinv.optim.AmplitudeLoss.html.md): Bases: [`DataFidelity`](https://deepinv.org/api/stubs/deepinv.optim.DataFidelity.html.md#deepinv.opt... - [ZeroFidelity](https://deepinv.org/api/stubs/deepinv.optim.ZeroFidelity.html.md): Bases: [`DataFidelity`](https://deepinv.org/api/stubs/deepinv.optim.DataFidelity.html.md#deepinv.opt... - [ItohFidelity](https://deepinv.org/api/stubs/deepinv.optim.ItohFidelity.html.md): Bases: [`L2`](https://deepinv.org/api/stubs/deepinv.optim.L2.html.md#deepinv.optim.L2) - [Prior](https://deepinv.org/api/stubs/deepinv.optim.Prior.html.md): Bases: [`Potential`](https://deepinv.org/api/stubs/deepinv.optim.Potential.html.md#deepinv.optim.Pot... - [PnP](https://deepinv.org/api/stubs/deepinv.optim.PnP.html.md): Bases: [`Prior`](https://deepinv.org/api/stubs/deepinv.optim.Prior.html.md#deepinv.optim.Prior) - [RED](https://deepinv.org/api/stubs/deepinv.optim.RED.html.md): Bases: [`Prior`](https://deepinv.org/api/stubs/deepinv.optim.Prior.html.md#deepinv.optim.Prior) - [ScorePrior](https://deepinv.org/api/stubs/deepinv.optim.ScorePrior.html.md): Bases: [`Prior`](https://deepinv.org/api/stubs/deepinv.optim.Prior.html.md#deepinv.optim.Prior) - [ZeroPrior](https://deepinv.org/api/stubs/deepinv.optim.ZeroPrior.html.md): Bases: [`Prior`](https://deepinv.org/api/stubs/deepinv.optim.Prior.html.md#deepinv.optim.Prior) - [Tikhonov](https://deepinv.org/api/stubs/deepinv.optim.Tikhonov.html.md): Bases: [`Prior`](https://deepinv.org/api/stubs/deepinv.optim.Prior.html.md#deepinv.optim.Prior) - [L1Prior](https://deepinv.org/api/stubs/deepinv.optim.L1Prior.html.md): Bases: [`Prior`](https://deepinv.org/api/stubs/deepinv.optim.Prior.html.md#deepinv.optim.Prior) - [WaveletPrior](https://deepinv.org/api/stubs/deepinv.optim.WaveletPrior.html.md): Bases: [`Prior`](https://deepinv.org/api/stubs/deepinv.optim.Prior.html.md#deepinv.optim.Prior) - [TVPrior](https://deepinv.org/api/stubs/deepinv.optim.TVPrior.html.md): Bases: [`Prior`](https://deepinv.org/api/stubs/deepinv.optim.Prior.html.md#deepinv.optim.Prior) - [TVL1Prior](https://deepinv.org/api/stubs/deepinv.optim.TVL1Prior.html.md): Bases: [`TVPrior`](https://deepinv.org/api/stubs/deepinv.optim.TVPrior.html.md#deepinv.optim.TVPrior... - [PatchPrior](https://deepinv.org/api/stubs/deepinv.optim.PatchPrior.html.md): Bases: [`Prior`](https://deepinv.org/api/stubs/deepinv.optim.Prior.html.md#deepinv.optim.Prior) - [L12Prior](https://deepinv.org/api/stubs/deepinv.optim.L12Prior.html.md): Bases: [`Prior`](https://deepinv.org/api/stubs/deepinv.optim.Prior.html.md#deepinv.optim.Prior) - [PatchNR](https://deepinv.org/api/stubs/deepinv.optim.PatchNR.html.md): Bases: [`Prior`](https://deepinv.org/api/stubs/deepinv.optim.Prior.html.md#deepinv.optim.Prior) - [NormalizingFlow](https://deepinv.org/api/stubs/deepinv.optim.prior.NormalizingFlow.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [GLOWCouplingBlock](https://deepinv.org/api/stubs/deepinv.optim.prior.GLOWCouplingBlock.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [DPIR](https://deepinv.org/api/stubs/deepinv.optim.DPIR.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [EPLL](https://deepinv.org/api/stubs/deepinv.optim.EPLL.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [Bregman](https://deepinv.org/api/stubs/deepinv.optim.Bregman.html.md): Bases: [`Potential`](https://deepinv.org/api/stubs/deepinv.optim.Potential.html.md#deepinv.optim.Pot... - [BregmanL2](https://deepinv.org/api/stubs/deepinv.optim.BregmanL2.html.md): Bases: [`Bregman`](https://deepinv.org/api/stubs/deepinv.optim.Bregman.html.md#deepinv.optim.Bregman... - [BurgEntropy](https://deepinv.org/api/stubs/deepinv.optim.BurgEntropy.html.md): Bases: [`Bregman`](https://deepinv.org/api/stubs/deepinv.optim.Bregman.html.md#deepinv.optim.Bregman... - [NegEntropy](https://deepinv.org/api/stubs/deepinv.optim.NegEntropy.html.md): Bases: [`Bregman`](https://deepinv.org/api/stubs/deepinv.optim.Bregman.html.md#deepinv.optim.Bregman... - [Bregman_ICNN](https://deepinv.org/api/stubs/deepinv.optim.Bregman_ICNN.html.md): Bases: [`Bregman`](https://deepinv.org/api/stubs/deepinv.optim.Bregman.html.md#deepinv.optim.Bregman... - [Distance](https://deepinv.org/api/stubs/deepinv.optim.Distance.html.md): Bases: [`Potential`](https://deepinv.org/api/stubs/deepinv.optim.Potential.html.md#deepinv.optim.Pot... - [L2Distance](https://deepinv.org/api/stubs/deepinv.optim.L2Distance.html.md): Bases: [`Distance`](https://deepinv.org/api/stubs/deepinv.optim.Distance.html.md#deepinv.optim.Dista... - [IndicatorL2Distance](https://deepinv.org/api/stubs/deepinv.optim.IndicatorL2Distance.html.md): Bases: [`Distance`](https://deepinv.org/api/stubs/deepinv.optim.Distance.html.md#deepinv.optim.Dista... - [PoissonLikelihoodDistance](https://deepinv.org/api/stubs/deepinv.optim.PoissonLikelihoodDistance.html.md): Bases: [`Distance`](https://deepinv.org/api/stubs/deepinv.optim.Distance.html.md#deepinv.optim.Dista... - [L1Distance](https://deepinv.org/api/stubs/deepinv.optim.L1Distance.html.md): Bases: [`Distance`](https://deepinv.org/api/stubs/deepinv.optim.Distance.html.md#deepinv.optim.Dista... - [AmplitudeLossDistance](https://deepinv.org/api/stubs/deepinv.optim.AmplitudeLossDistance.html.md): Bases: [`Distance`](https://deepinv.org/api/stubs/deepinv.optim.Distance.html.md#deepinv.optim.Dista... - [LogPoissonLikelihoodDistance](https://deepinv.org/api/stubs/deepinv.optim.LogPoissonLikelihoodDistance.html.md): Bases: [`Distance`](https://deepinv.org/api/stubs/deepinv.optim.Distance.html.md#deepinv.optim.Dista... - [ZeroDistance](https://deepinv.org/api/stubs/deepinv.optim.ZeroDistance.html.md): Bases: [`Distance`](https://deepinv.org/api/stubs/deepinv.optim.Distance.html.md#deepinv.optim.Dista... - [FixedPoint](https://deepinv.org/api/stubs/deepinv.optim.FixedPoint.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [OptimIterator](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [fStep](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.fStep.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [gStep](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.gStep.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [GDIteration](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.GDIteration.html.md): Bases: [`OptimIterator`](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md#deepinv.o... - [PGDIteration](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.PGDIteration.html.md): Bases: [`OptimIterator`](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md#deepinv.o... - [FISTAIteration](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.FISTAIteration.html.md): Bases: [`OptimIterator`](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md#deepinv.o... - [CPIteration](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.CPIteration.html.md): Bases: [`OptimIterator`](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md#deepinv.o... - [ADMMIteration](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.ADMMIteration.html.md): Bases: [`OptimIterator`](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md#deepinv.o... - [DRSIteration](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.DRSIteration.html.md): Bases: [`OptimIterator`](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md#deepinv.o... - [HQSIteration](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.HQSIteration.html.md): Bases: [`OptimIterator`](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md#deepinv.o... - [MDIteration](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.MDIteration.html.md): Bases: [`OptimIterator`](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md#deepinv.o... - [PMDIteration](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.PMDIteration.html.md): Bases: [`OptimIterator`](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md#deepinv.o... - [SMIteration](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.SMIteration.html.md): Bases: [`OptimIterator`](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md#deepinv.o... - [MLEMIteration](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.MLEMIteration.html.md): Bases: [`OptimIterator`](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md#deepinv.o... - [OSEMIteration](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.OSEMIteration.html.md): Bases: [`OptimIterator`](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md#deepinv.o... - [SIRTIteration](https://deepinv.org/api/stubs/deepinv.optim.optim_iterators.SIRTIteration.html.md): Bases: [`OptimIterator`](https://deepinv.org/api/stubs/deepinv.optim.OptimIterator.html.md#deepinv.o... - [least_squares](https://deepinv.org/api/stubs/deepinv.optim.linear.least_squares.html.md): Solves $\min_x \|Ax-y\|^2 + \frac{1}{\gamma}\|x-z\|^2$ using the specified solver. - [least_squares_implicit_backward](https://deepinv.org/api/stubs/deepinv.optim.linear.least_squares_implicit_backward.html.md): Least squares solver with O(1) memory backward propagation using implicit differentiation. - [lsqr](https://deepinv.org/api/stubs/deepinv.optim.linear.lsqr.html.md): LSQR algorithm for solving linear systems. - [bicgstab](https://deepinv.org/api/stubs/deepinv.optim.linear.bicgstab.html.md): Biconjugate gradient stabilized algorithm. - [minres](https://deepinv.org/api/stubs/deepinv.optim.linear.minres.html.md): Minimal Residual Method for solving symmetric equations. - [conjugate_gradient](https://deepinv.org/api/stubs/deepinv.optim.linear.conjugate_gradient.html.md): Standard conjugate gradient algorithm. - [gradient_descent](https://deepinv.org/api/stubs/deepinv.optim.utils.gradient_descent.html.md): Standard gradient descent algorithm\`. - [correct_global_phase](https://deepinv.org/api/stubs/deepinv.optim.phase_retrieval.correct_global_phase.html.md): Corrects the global phase shift (and optionally magnitude scaling) of reconstructed complex signals ... - [spectral_methods](https://deepinv.org/api/stubs/deepinv.optim.phase_retrieval.spectral_methods.html.md): Utility function for spectral methods. - [GaussianMixtureModel](https://deepinv.org/api/stubs/deepinv.optim.utils.GaussianMixtureModel.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [deepinv.physics](https://deepinv.org/api/deepinv.physics.html.md): This module provides a set of forward operators for various imaging modalities. - [Physics](https://deepinv.org/api/stubs/deepinv.physics.Physics.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [LinearPhysics](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md): Bases: [`Physics`](https://deepinv.org/api/stubs/deepinv.physics.Physics.html.md#deepinv.physics.Phy... - [DecomposablePhysics](https://deepinv.org/api/stubs/deepinv.physics.DecomposablePhysics.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [StackedPhysics](https://deepinv.org/api/stubs/deepinv.physics.StackedPhysics.html.md): Bases: [`Physics`](https://deepinv.org/api/stubs/deepinv.physics.Physics.html.md#deepinv.physics.Phy... - [StackedLinearPhysics](https://deepinv.org/api/stubs/deepinv.physics.StackedLinearPhysics.html.md): Bases: [`StackedPhysics`](https://deepinv.org/api/stubs/deepinv.physics.StackedPhysics.html.md#deepi... - [ComposedPhysics](https://deepinv.org/api/stubs/deepinv.physics.ComposedPhysics.html.md): Bases: [`Physics`](https://deepinv.org/api/stubs/deepinv.physics.Physics.html.md#deepinv.physics.Phy... - [ComposedLinearPhysics](https://deepinv.org/api/stubs/deepinv.physics.ComposedLinearPhysics.html.md): Bases: [`ComposedPhysics`](https://deepinv.org/api/stubs/deepinv.physics.ComposedPhysics.html.md#dee... - [VirtualLinearPhysics](https://deepinv.org/api/stubs/deepinv.physics.VirtualLinearPhysics.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [PhysicsMultiScaler](https://deepinv.org/api/stubs/deepinv.physics.PhysicsMultiScaler.html.md): Bases: [`Physics`](https://deepinv.org/api/stubs/deepinv.physics.Physics.html.md#deepinv.physics.Phy... - [LinearPhysicsMultiScaler](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysicsMultiScaler.html.md): Bases: [`PhysicsMultiScaler`](https://deepinv.org/api/stubs/deepinv.physics.PhysicsMultiScaler.html.... - [PhysicsCropper](https://deepinv.org/api/stubs/deepinv.physics.PhysicsCropper.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [NoiseModel](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [Denoising](https://deepinv.org/api/stubs/deepinv.physics.Denoising.html.md): Bases: [`DecomposablePhysics`](https://deepinv.org/api/stubs/deepinv.physics.DecomposablePhysics.htm... - [Inpainting](https://deepinv.org/api/stubs/deepinv.physics.Inpainting.html.md): Bases: [`DecomposablePhysics`](https://deepinv.org/api/stubs/deepinv.physics.DecomposablePhysics.htm... - [Decolorize](https://deepinv.org/api/stubs/deepinv.physics.Decolorize.html.md): Bases: [`DecomposablePhysics`](https://deepinv.org/api/stubs/deepinv.physics.DecomposablePhysics.htm... - [Demosaicing](https://deepinv.org/api/stubs/deepinv.physics.Demosaicing.html.md): Bases: [`Inpainting`](https://deepinv.org/api/stubs/deepinv.physics.Inpainting.html.md#deepinv.physi... - [Blur](https://deepinv.org/api/stubs/deepinv.physics.Blur.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [BlurFFT](https://deepinv.org/api/stubs/deepinv.physics.BlurFFT.html.md): Bases: [`DecomposablePhysics`](https://deepinv.org/api/stubs/deepinv.physics.DecomposablePhysics.htm... - [SpaceVaryingBlur](https://deepinv.org/api/stubs/deepinv.physics.SpaceVaryingBlur.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [TiledSpaceVaryingBlur](https://deepinv.org/api/stubs/deepinv.physics.TiledSpaceVaryingBlur.html.md): Bases: [`TiledMixin2d`](https://deepinv.org/api/stubs/deepinv.utils.TiledMixin2d.html.md#deepinv.uti... - [Downsampling](https://deepinv.org/api/stubs/deepinv.physics.Downsampling.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [Upsampling](https://deepinv.org/api/stubs/deepinv.physics.Upsampling.html.md): Bases: [`Downsampling`](https://deepinv.org/api/stubs/deepinv.physics.Downsampling.html.md#deepinv.p... - [DownsamplingMatlab](https://deepinv.org/api/stubs/deepinv.physics.DownsamplingMatlab.html.md): Bases: [`Downsampling`](https://deepinv.org/api/stubs/deepinv.physics.Downsampling.html.md#deepinv.p... - [MRI](https://deepinv.org/api/stubs/deepinv.physics.MRI.html.md): Bases: [`MRIMixin`](https://deepinv.org/api/stubs/deepinv.utils.MRIMixin.html.md#deepinv.utils.MRIMi... - [DynamicMRI](https://deepinv.org/api/stubs/deepinv.physics.DynamicMRI.html.md): Bases: [`MRI`](https://deepinv.org/api/stubs/deepinv.physics.MRI.html.md#deepinv.physics.MRI), [`Tim... - [MultiCoilMRI](https://deepinv.org/api/stubs/deepinv.physics.MultiCoilMRI.html.md): Bases: [`MRIMixin`](https://deepinv.org/api/stubs/deepinv.utils.MRIMixin.html.md#deepinv.utils.MRIMi... - [SequentialMRI](https://deepinv.org/api/stubs/deepinv.physics.SequentialMRI.html.md): Bases: [`DynamicMRI`](https://deepinv.org/api/stubs/deepinv.physics.DynamicMRI.html.md#deepinv.physi... - [Tomography](https://deepinv.org/api/stubs/deepinv.physics.Tomography.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [TomographyWithAstra](https://deepinv.org/api/stubs/deepinv.physics.TomographyWithAstra.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [PET](https://deepinv.org/api/stubs/deepinv.physics.PET.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [Pansharpen](https://deepinv.org/api/stubs/deepinv.physics.Pansharpen.html.md): Bases: [`StackedLinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.StackedLinearPhysics.h... - [CompressiveSpectralImaging](https://deepinv.org/api/stubs/deepinv.physics.CompressiveSpectralImaging.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [HyperSpectralUnmixing](https://deepinv.org/api/stubs/deepinv.physics.HyperSpectralUnmixing.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [CompressedSensing](https://deepinv.org/api/stubs/deepinv.physics.CompressedSensing.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [StructuredRandom](https://deepinv.org/api/stubs/deepinv.physics.StructuredRandom.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [SinglePixelCamera](https://deepinv.org/api/stubs/deepinv.physics.SinglePixelCamera.html.md): Bases: [`DecomposablePhysics`](https://deepinv.org/api/stubs/deepinv.physics.DecomposablePhysics.htm... - [RadioInterferometry](https://deepinv.org/api/stubs/deepinv.physics.RadioInterferometry.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [SinglePhotonLidar](https://deepinv.org/api/stubs/deepinv.physics.SinglePhotonLidar.html.md): Bases: [`Physics`](https://deepinv.org/api/stubs/deepinv.physics.Physics.html.md#deepinv.physics.Phy... - [Haze](https://deepinv.org/api/stubs/deepinv.physics.Haze.html.md): Bases: [`Physics`](https://deepinv.org/api/stubs/deepinv.physics.Physics.html.md#deepinv.physics.Phy... - [PhaseRetrieval](https://deepinv.org/api/stubs/deepinv.physics.PhaseRetrieval.html.md): Bases: [`Physics`](https://deepinv.org/api/stubs/deepinv.physics.Physics.html.md#deepinv.physics.Phy... - [RandomPhaseRetrieval](https://deepinv.org/api/stubs/deepinv.physics.RandomPhaseRetrieval.html.md): Bases: [`PhaseRetrieval`](https://deepinv.org/api/stubs/deepinv.physics.PhaseRetrieval.html.md#deepi... - [SpatialUnwrapping](https://deepinv.org/api/stubs/deepinv.physics.SpatialUnwrapping.html.md): Bases: [`Physics`](https://deepinv.org/api/stubs/deepinv.physics.Physics.html.md#deepinv.physics.Phy... - [StructuredRandomPhaseRetrieval](https://deepinv.org/api/stubs/deepinv.physics.StructuredRandomPhaseRetrieval.html.md): Bases: [`PhaseRetrieval`](https://deepinv.org/api/stubs/deepinv.physics.PhaseRetrieval.html.md#deepi... - [Ptychography](https://deepinv.org/api/stubs/deepinv.physics.Ptychography.html.md): Bases: [`PhaseRetrieval`](https://deepinv.org/api/stubs/deepinv.physics.PhaseRetrieval.html.md#deepi... - [PtychographyLinearOperator](https://deepinv.org/api/stubs/deepinv.physics.PtychographyLinearOperator.html.md): Bases: [`LinearPhysics`](https://deepinv.org/api/stubs/deepinv.physics.LinearPhysics.html.md#deepinv... - [Scattering](https://deepinv.org/api/stubs/deepinv.physics.Scattering.html.md): Bases: [`Physics`](https://deepinv.org/api/stubs/deepinv.physics.Physics.html.md#deepinv.physics.Phy... - [to_multiscale](https://deepinv.org/api/stubs/deepinv.physics.to_multiscale.html.md): Convert a single-scale physics operator to a multi-scale physics operator - [PhysicsGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.PhysicsGenerator.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [GeneratorMixture](https://deepinv.org/api/stubs/deepinv.physics.generator.GeneratorMixture.html.md): Bases: [`PhysicsGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.PhysicsGenerator... - [BernoulliSplittingMaskGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.BernoulliSplittingMaskGenerator.html.md): Bases: [`PhysicsGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.PhysicsGenerator... - [GaussianSplittingMaskGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.GaussianSplittingMaskGenerator.html.md): Bases: [`BernoulliSplittingMaskGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.B... - [MultiplicativeSplittingMaskGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.MultiplicativeSplittingMaskGenerator.html.md): Bases: [`BernoulliSplittingMaskGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.B... - [Phase2PhaseSplittingMaskGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.Phase2PhaseSplittingMaskGenerator.html.md): Bases: [`BernoulliSplittingMaskGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.B... - [Artifact2ArtifactSplittingMaskGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.Artifact2ArtifactSplittingMaskGenerator.html.md): Bases: [`Phase2PhaseSplittingMaskGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator... - [PSFGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.PSFGenerator.html.md): Bases: [`PhysicsGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.PhysicsGenerator... - [GaussianBlurGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.GaussianBlurGenerator.html.md): Bases: [`PSFGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.PSFGenerator.html.md... - [MotionBlurGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.MotionBlurGenerator.html.md): Bases: [`PSFGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.PSFGenerator.html.md... - [DownsamplingGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.DownsamplingGenerator.html.md): Bases: [`PhysicsGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.PhysicsGenerator... - [DiffractionBlurGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.DiffractionBlurGenerator.html.md): Bases: [`PSFGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.PSFGenerator.html.md... - [DiffractionBlurGenerator3D](https://deepinv.org/api/stubs/deepinv.physics.generator.DiffractionBlurGenerator3D.html.md): Bases: [`PSFGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.PSFGenerator.html.md... - [ProductConvolutionBlurGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.ProductConvolutionBlurGenerator.html.md): Bases: [`PhysicsGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.PhysicsGenerator... - [TiledBlurGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.TiledBlurGenerator.html.md): Bases: [`TiledMixin2d`](https://deepinv.org/api/stubs/deepinv.utils.TiledMixin2d.html.md#deepinv.uti... - [ConfocalBlurGenerator3D](https://deepinv.org/api/stubs/deepinv.physics.generator.ConfocalBlurGenerator3D.html.md): Bases: [`PSFGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.PSFGenerator.html.md... - [Zernike](https://deepinv.org/api/stubs/deepinv.physics.generator.Zernike.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [BaseMaskGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.BaseMaskGenerator.html.md): Bases: [`PhysicsGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.PhysicsGenerator... - [GaussianMaskGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.GaussianMaskGenerator.html.md): Bases: [`RandomMaskGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.RandomMaskGen... - [RandomMaskGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.RandomMaskGenerator.html.md): Bases: [`BaseMaskGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.BaseMaskGenerat... - [EquispacedMaskGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.EquispacedMaskGenerator.html.md): Bases: [`BaseMaskGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.BaseMaskGenerat... - [PolyOrderMaskGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.PolyOrderMaskGenerator.html.md): Bases: [`BaseMaskGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.BaseMaskGenerat... - [build_probe](https://deepinv.org/api/stubs/deepinv.physics.phase_retrieval.build_probe.html.md): Builds a probe based on the specified type and radius. - [generate_shifts](https://deepinv.org/api/stubs/deepinv.physics.phase_retrieval.generate_shifts.html.md): Generates the array of probe shifts across the image. - [circular_sensors](https://deepinv.org/api/stubs/deepinv.physics.scattering.circular_sensors.html.md): Generate equispaced sensors on a circle. - [get_subset_tensor](https://deepinv.org/api/stubs/deepinv.physics.functional.tomography_subsets.get_subset_tensor.html.md): Return indices that interleave a tensor into equal subsets. - [split_measurements](https://deepinv.org/api/stubs/deepinv.physics.split_measurements.html.md): Splits tomography measurements into angular subsets. - [split_physics](https://deepinv.org/api/stubs/deepinv.physics.split_physics.html.md): Builds a stacked tomography physics with one operator per angular subset. - [ZeroNoise](https://deepinv.org/api/stubs/deepinv.physics.ZeroNoise.html.md): Bases: [`NoiseModel`](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md#deepinv.physi... - [GaussianNoise](https://deepinv.org/api/stubs/deepinv.physics.GaussianNoise.html.md): Bases: [`NoiseModel`](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md#deepinv.physi... - [LogPoissonNoise](https://deepinv.org/api/stubs/deepinv.physics.LogPoissonNoise.html.md): Bases: [`NoiseModel`](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md#deepinv.physi... - [PoissonNoise](https://deepinv.org/api/stubs/deepinv.physics.PoissonNoise.html.md): Bases: [`NoiseModel`](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md#deepinv.physi... - [PoissonGaussianNoise](https://deepinv.org/api/stubs/deepinv.physics.PoissonGaussianNoise.html.md): Bases: [`NoiseModel`](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md#deepinv.physi... - [LaplaceNoise](https://deepinv.org/api/stubs/deepinv.physics.LaplaceNoise.html.md): Bases: [`NoiseModel`](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md#deepinv.physi... - [UniformNoise](https://deepinv.org/api/stubs/deepinv.physics.UniformNoise.html.md): Bases: [`NoiseModel`](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md#deepinv.physi... - [UniformGaussianNoise](https://deepinv.org/api/stubs/deepinv.physics.UniformGaussianNoise.html.md): Bases: [`NoiseModel`](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md#deepinv.physi... - [GammaNoise](https://deepinv.org/api/stubs/deepinv.physics.GammaNoise.html.md): Bases: [`NoiseModel`](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md#deepinv.physi... - [SaltPepperNoise](https://deepinv.org/api/stubs/deepinv.physics.SaltPepperNoise.html.md): Bases: [`NoiseModel`](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md#deepinv.physi... - [FisherTippettNoise](https://deepinv.org/api/stubs/deepinv.physics.FisherTippettNoise.html.md): Bases: [`NoiseModel`](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md#deepinv.physi... - [RicianNoise](https://deepinv.org/api/stubs/deepinv.physics.RicianNoise.html.md): Bases: [`NoiseModel`](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md#deepinv.physi... - [SigmaGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.SigmaGenerator.html.md): Bases: [`PhysicsGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.PhysicsGenerator... - [GainGenerator](https://deepinv.org/api/stubs/deepinv.physics.generator.GainGenerator.html.md): Bases: [`PhysicsGenerator`](https://deepinv.org/api/stubs/deepinv.physics.generator.PhysicsGenerator... - [adjoint_function](https://deepinv.org/api/stubs/deepinv.physics.adjoint_function.html.md): Provides the adjoint function of a linear operator $A$, i.e., $A^{\top}$. - [stack](https://deepinv.org/api/stubs/deepinv.physics.stack.html.md): Stacks multiple forward operators $A = \begin{bmatrix} A_1(x) \\ A_2(x) \\ \vdots \\ A_n(x) \end{bma... - [compose](https://deepinv.org/api/stubs/deepinv.physics.compose.html.md): Composes multiple forward operators $A = A_1\circ A_2\circ \dots \circ A_n$. - [conv2d](https://deepinv.org/api/stubs/deepinv.physics.functional.conv2d.html.md): A helper function performing the 2d convolution of images `x` and `filter`. - [conv_transpose2d](https://deepinv.org/api/stubs/deepinv.physics.functional.conv_transpose2d.html.md): A helper function performing the 2d transposed convolution 2d of x and filter. The transposed of thi... - [conv2d_fft](https://deepinv.org/api/stubs/deepinv.physics.functional.conv2d_fft.html.md): A helper function performing the 2d convolution of images `x` and `filter` using FFT. - [conv_transpose2d_fft](https://deepinv.org/api/stubs/deepinv.physics.functional.conv_transpose2d_fft.html.md): A helper function performing the 2d transposed convolution 2d of `x` and `filter` using FFT. - [conv3d](https://deepinv.org/api/stubs/deepinv.physics.functional.conv3d.html.md): A helper function to perform 3D convolution of images `x` and `filter`. - [conv_transpose3d](https://deepinv.org/api/stubs/deepinv.physics.functional.conv_transpose3d.html.md): A helper function to perform 3D transpose convolution. - [conv3d_fft](https://deepinv.org/api/stubs/deepinv.physics.functional.conv3d_fft.html.md): A helper function performing the 3d convolution of `x` and `filter` using FFT. - [conv_transpose3d_fft](https://deepinv.org/api/stubs/deepinv.physics.functional.conv_transpose3d_fft.html.md): A helper function performing the 3d transposed convolution of `y` and `filter` using FFT. - [product_convolution2d](https://deepinv.org/api/stubs/deepinv.physics.functional.product_convolution2d.html.md): Product-convolution operator in 2d. Details available in the paper Escande and Weiss[1](#footci... - [multiplier](https://deepinv.org/api/stubs/deepinv.physics.functional.multiplier.html.md): Implements diagonal matrices or multipliers $x$ and `mult`. - [multiplier_adjoint](https://deepinv.org/api/stubs/deepinv.physics.functional.multiplier_adjoint.html.md): Implements the adjoint of diagonal matrices or multipliers $x$ and `mult`. - [histogramdd](https://deepinv.org/api/stubs/deepinv.physics.functional.histogramdd.html.md): Computes the multidimensional histogram of a tensor. - [histogram](https://deepinv.org/api/stubs/deepinv.physics.functional.histogram.html.md): Computes the histogram of a tensor. - [dst1](https://deepinv.org/api/stubs/deepinv.physics.functional.dst1.html.md): Compute the one-dimensional [discrete sine transform](https://en.wikipedia.org/wiki/Discrete_sine_tr... - [dct](https://deepinv.org/api/stubs/deepinv.physics.functional.dct.html.md): Discrete Cosine Transform, Type II (a.k.a. the DCT) - [idct](https://deepinv.org/api/stubs/deepinv.physics.functional.idct.html.md): The inverse to DCT-II, which is a scaled Discrete Cosine Transform, Type III - [dct_2d](https://deepinv.org/api/stubs/deepinv.physics.functional.dct_2d.html.md): 2-dimensional Discrete Cosine Transform, Type II (a.k.a. the DCT) - [idct_2d](https://deepinv.org/api/stubs/deepinv.physics.functional.idct_2d.html.md): The inverse to 2D DCT-II, which is a scaled Discrete Cosine Transform, Type III - [imresize_matlab](https://deepinv.org/api/stubs/deepinv.physics.functional.imresize_matlab.html.md): MATLAB imresize reimplementation. - [random_choice](https://deepinv.org/api/stubs/deepinv.physics.functional.random_choice.html.md): PyTorch equivalent of [`numpy.random.choice()`](https://numpy.org/doc/stable/reference/random/genera... - [power_method](https://deepinv.org/api/stubs/deepinv.physics.functional.power_method.html.md): Runs the power iteration method to estimate the largest singular value of a linear operator. - [gaussian_blur](https://deepinv.org/api/stubs/deepinv.physics.functional.gaussian_blur.html.md): Creates a batch of N-dimensional anisotropic Gaussian kernels (1D, 2D, or 3D) with independent sigma... - [bilinear_filter](https://deepinv.org/api/stubs/deepinv.physics.functional.bilinear_filter.html.md): Bilinear filter. - [bicubic_filter](https://deepinv.org/api/stubs/deepinv.physics.functional.bicubic_filter.html.md): Bicubic filter. - [sinc_filter](https://deepinv.org/api/stubs/deepinv.physics.functional.sinc_filter.html.md): Anti-aliasing sinc filter, optionally multiplied by a Kaiser window. - [liu_jia_pad](https://deepinv.org/api/stubs/deepinv.physics.functional.liu_jia_pad.html.md): Liu-Jia Padding - [Radon](https://deepinv.org/api/stubs/deepinv.physics.functional.Radon.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [IRadon](https://deepinv.org/api/stubs/deepinv.physics.functional.IRadon.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [XrayTransform](https://deepinv.org/api/stubs/deepinv.physics.functional.XrayTransform.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [deepinv.sampling](https://deepinv.org/api/deepinv.sampling.html.md): This module contains various posterior sampling algorithms, including diffusion-based methods and MC... - [BaseSDE](https://deepinv.org/api/stubs/deepinv.sampling.BaseSDE.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [DiffusionSDE](https://deepinv.org/api/stubs/deepinv.sampling.DiffusionSDE.html.md): Bases: [`BaseSDE`](https://deepinv.org/api/stubs/deepinv.sampling.BaseSDE.html.md#deepinv.sampling.B... - [EDMDiffusionSDE](https://deepinv.org/api/stubs/deepinv.sampling.EDMDiffusionSDE.html.md): Bases: [`DiffusionSDE`](https://deepinv.org/api/stubs/deepinv.sampling.DiffusionSDE.html.md#deepinv.... - [SongDiffusionSDE](https://deepinv.org/api/stubs/deepinv.sampling.SongDiffusionSDE.html.md): Bases: [`EDMDiffusionSDE`](https://deepinv.org/api/stubs/deepinv.sampling.EDMDiffusionSDE.html.md#de... - [FlowMatching](https://deepinv.org/api/stubs/deepinv.sampling.FlowMatching.html.md): Bases: [`EDMDiffusionSDE`](https://deepinv.org/api/stubs/deepinv.sampling.EDMDiffusionSDE.html.md#de... - [VarianceExplodingDiffusion](https://deepinv.org/api/stubs/deepinv.sampling.VarianceExplodingDiffusion.html.md): Bases: [`EDMDiffusionSDE`](https://deepinv.org/api/stubs/deepinv.sampling.EDMDiffusionSDE.html.md#de... - [VariancePreservingDiffusion](https://deepinv.org/api/stubs/deepinv.sampling.VariancePreservingDiffusion.html.md): Bases: [`SongDiffusionSDE`](https://deepinv.org/api/stubs/deepinv.sampling.SongDiffusionSDE.html.md#... - [PosteriorDiffusion](https://deepinv.org/api/stubs/deepinv.sampling.PosteriorDiffusion.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [NoisyDataFidelity](https://deepinv.org/api/stubs/deepinv.sampling.NoisyDataFidelity.html.md): Bases: [`DataFidelity`](https://deepinv.org/api/stubs/deepinv.optim.DataFidelity.html.md#deepinv.opt... - [ALDDataFidelity](https://deepinv.org/api/stubs/deepinv.sampling.ALDDataFidelity.html.md): Bases: [`NoisyDataFidelity`](https://deepinv.org/api/stubs/deepinv.sampling.NoisyDataFidelity.html.m... - [ScoreSDEDataFidelity](https://deepinv.org/api/stubs/deepinv.sampling.ScoreSDEDataFidelity.html.md): Bases: [`ALDDataFidelity`](https://deepinv.org/api/stubs/deepinv.sampling.ALDDataFidelity.html.md#de... - [ILVRDataFidelity](https://deepinv.org/api/stubs/deepinv.sampling.ILVRDataFidelity.html.md): Bases: [`ScoreSDEDataFidelity`](https://deepinv.org/api/stubs/deepinv.sampling.ScoreSDEDataFidelity.... - [DPSDataFidelity](https://deepinv.org/api/stubs/deepinv.sampling.DPSDataFidelity.html.md): Bases: [`NoisyDataFidelity`](https://deepinv.org/api/stubs/deepinv.sampling.NoisyDataFidelity.html.m... - [PiGDMDataFidelity](https://deepinv.org/api/stubs/deepinv.sampling.PiGDMDataFidelity.html.md): Bases: [`NoisyDataFidelity`](https://deepinv.org/api/stubs/deepinv.sampling.NoisyDataFidelity.html.m... - [MomentMatchingDataFidelity](https://deepinv.org/api/stubs/deepinv.sampling.MomentMatchingDataFidelity.html.md): Bases: [`NoisyDataFidelity`](https://deepinv.org/api/stubs/deepinv.sampling.NoisyDataFidelity.html.m... - [BaseSDESolver](https://deepinv.org/api/stubs/deepinv.sampling.BaseSDESolver.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [EulerSolver](https://deepinv.org/api/stubs/deepinv.sampling.EulerSolver.html.md): Bases: [`BaseSDESolver`](https://deepinv.org/api/stubs/deepinv.sampling.BaseSDESolver.html.md#deepin... - [HeunSolver](https://deepinv.org/api/stubs/deepinv.sampling.HeunSolver.html.md): Bases: [`BaseSDESolver`](https://deepinv.org/api/stubs/deepinv.sampling.BaseSDESolver.html.md#deepin... - [SDEOutput](https://deepinv.org/api/stubs/deepinv.sampling.SDEOutput.html.md): Bases: [`dict`](https://docs.python.org/3.9/library/stdtypes.html#dict) - [DDRM](https://deepinv.org/api/stubs/deepinv.sampling.DDRM.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [DiffPIR](https://deepinv.org/api/stubs/deepinv.sampling.DiffPIR.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [DPS](https://deepinv.org/api/stubs/deepinv.sampling.DPS.html.md): Bases: [`PosteriorDiffusion`](https://deepinv.org/api/stubs/deepinv.sampling.PosteriorDiffusion.html... - [DiffusionSampler](https://deepinv.org/api/stubs/deepinv.sampling.DiffusionSampler.html.md): Bases: [`BaseSampling`](https://deepinv.org/api/stubs/deepinv.sampling.BaseSampling.html.md#deepinv.... - [sampling_builder](https://deepinv.org/api/stubs/deepinv.sampling.sampling_builder.html.md): Helper function for building an instance of the [`deepinv.sampling.BaseSampling`](https://deepinv.or... - [BaseSampling](https://deepinv.org/api/stubs/deepinv.sampling.BaseSampling.html.md): Bases: [`Reconstructor`](https://deepinv.org/api/stubs/deepinv.models.Reconstructor.html.md#deepinv.... - [ULA](https://deepinv.org/api/stubs/deepinv.sampling.ULA.html.md): Bases: [`BaseSampling`](https://deepinv.org/api/stubs/deepinv.sampling.BaseSampling.html.md#deepinv.... - [SKRock](https://deepinv.org/api/stubs/deepinv.sampling.SKRock.html.md): Bases: [`BaseSampling`](https://deepinv.org/api/stubs/deepinv.sampling.BaseSampling.html.md#deepinv.... - [SamplingIterator](https://deepinv.org/api/stubs/deepinv.sampling.SamplingIterator.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [SKRockIterator](https://deepinv.org/api/stubs/deepinv.sampling.SKRockIterator.html.md): Bases: [`SamplingIterator`](https://deepinv.org/api/stubs/deepinv.sampling.SamplingIterator.html.md#... - [ULAIterator](https://deepinv.org/api/stubs/deepinv.sampling.ULAIterator.html.md): Bases: [`SamplingIterator`](https://deepinv.org/api/stubs/deepinv.sampling.SamplingIterator.html.md#... - [DiffusionIterator](https://deepinv.org/api/stubs/deepinv.sampling.DiffusionIterator.html.md): Bases: [`SamplingIterator`](https://deepinv.org/api/stubs/deepinv.sampling.SamplingIterator.html.md#... - [deepinv.transform](https://deepinv.org/api/deepinv.transform.html.md): This module contains different transforms which can be used for data augmentation or together with t... - [Transform](https://deepinv.org/api/stubs/deepinv.transform.Transform.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [Rotate](https://deepinv.org/api/stubs/deepinv.transform.Rotate.html.md): Bases: [`Transform`](https://deepinv.org/api/stubs/deepinv.transform.Transform.html.md#deepinv.trans... - [Shift](https://deepinv.org/api/stubs/deepinv.transform.Shift.html.md): Bases: [`Transform`](https://deepinv.org/api/stubs/deepinv.transform.Transform.html.md#deepinv.trans... - [Scale](https://deepinv.org/api/stubs/deepinv.transform.Scale.html.md): Bases: [`Transform`](https://deepinv.org/api/stubs/deepinv.transform.Transform.html.md#deepinv.trans... - [Reflect](https://deepinv.org/api/stubs/deepinv.transform.Reflect.html.md): Bases: [`Transform`](https://deepinv.org/api/stubs/deepinv.transform.Transform.html.md#deepinv.trans... - [Identity](https://deepinv.org/api/stubs/deepinv.transform.Identity.html.md): Bases: [`Transform`](https://deepinv.org/api/stubs/deepinv.transform.Transform.html.md#deepinv.trans... - [Homography](https://deepinv.org/api/stubs/deepinv.transform.Homography.html.md): Bases: [`Transform`](https://deepinv.org/api/stubs/deepinv.transform.Transform.html.md#deepinv.trans... - [Euclidean](https://deepinv.org/api/stubs/deepinv.transform.projective.Euclidean.html.md): Bases: [`Homography`](https://deepinv.org/api/stubs/deepinv.transform.Homography.html.md#deepinv.tra... - [Similarity](https://deepinv.org/api/stubs/deepinv.transform.projective.Similarity.html.md): Bases: [`Homography`](https://deepinv.org/api/stubs/deepinv.transform.Homography.html.md#deepinv.tra... - [Affine](https://deepinv.org/api/stubs/deepinv.transform.projective.Affine.html.md): Bases: [`Homography`](https://deepinv.org/api/stubs/deepinv.transform.Homography.html.md#deepinv.tra... - [PanTiltRotate](https://deepinv.org/api/stubs/deepinv.transform.projective.PanTiltRotate.html.md): Bases: [`Homography`](https://deepinv.org/api/stubs/deepinv.transform.Homography.html.md#deepinv.tra... - [CPABDiffeomorphism](https://deepinv.org/api/stubs/deepinv.transform.CPABDiffeomorphism.html.md): Bases: [`Transform`](https://deepinv.org/api/stubs/deepinv.transform.Transform.html.md#deepinv.trans... - [rotate_via_shear](https://deepinv.org/api/stubs/deepinv.transform.rotate_via_shear.html.md): 2D rotation of image by angle via shear composition through FFT. - [ShiftTime](https://deepinv.org/api/stubs/deepinv.transform.ShiftTime.html.md): Bases: [`Transform`](https://deepinv.org/api/stubs/deepinv.transform.Transform.html.md#deepinv.trans... - [RandomNoise](https://deepinv.org/api/stubs/deepinv.transform.RandomNoise.html.md): Bases: [`Transform`](https://deepinv.org/api/stubs/deepinv.transform.Transform.html.md#deepinv.trans... - [RandomPhaseError](https://deepinv.org/api/stubs/deepinv.transform.RandomPhaseError.html.md): Bases: [`Transform`](https://deepinv.org/api/stubs/deepinv.transform.Transform.html.md#deepinv.trans... - [deepinv.training](https://deepinv.org/api/deepinv.training.html.md): This module contains the training and testing functions. - [Trainer](https://deepinv.org/api/stubs/deepinv.Trainer.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [test](https://deepinv.org/api/stubs/deepinv.test.html.md): Tests a reconstruction model (algorithm or network). - [AdversarialTrainer](https://deepinv.org/api/stubs/deepinv.training.AdversarialTrainer.html.md): Bases: [`Trainer`](https://deepinv.org/api/stubs/deepinv.Trainer.html.md#deepinv.Trainer) - [AdversarialOptimizer](https://deepinv.org/api/stubs/deepinv.training.AdversarialOptimizer.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [deepinv.unfolded](https://deepinv.org/api/deepinv.unfolded.html.md): This module provides networks architectures based on unfolding optimization algorithms. - [unfolded_builder](https://deepinv.org/api/stubs/deepinv.unfolded.unfolded_builder.html.md): Helper function for building an unfolded architecture. - [BaseUnfold](https://deepinv.org/api/stubs/deepinv.unfolded.BaseUnfold.html.md): Bases: [`BaseOptim`](https://deepinv.org/api/stubs/deepinv.optim.BaseOptim.html.md#deepinv.optim.Bas... - [DEQ_builder](https://deepinv.org/api/stubs/deepinv.unfolded.DEQ_builder.html.md): Helper function for building an instance of the [`deepinv.unfolded.BaseDEQ`](https://deepinv.org/api... - [BaseDEQ](https://deepinv.org/api/stubs/deepinv.unfolded.BaseDEQ.html.md): Bases: [`BaseUnfold`](https://deepinv.org/api/stubs/deepinv.unfolded.BaseUnfold.html.md#deepinv.unfo... - [PDNet_PrimalBlock](https://deepinv.org/api/stubs/deepinv.models.PDNet_PrimalBlock.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [PDNet_DualBlock](https://deepinv.org/api/stubs/deepinv.models.PDNet_DualBlock.html.md): Bases: [`Module`](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Modul... - [deepinv.utils](https://deepinv.org/api/deepinv.utils.html.md): This module provides various plotting and utility functions. - [plot](https://deepinv.org/api/stubs/deepinv.utils.plot.html.md): Plots a list of images. - [plot_curves](https://deepinv.org/api/stubs/deepinv.utils.plot_curves.html.md): Plots the metrics of a Plug-and-Play algorithm. - [plot_parameters](https://deepinv.org/api/stubs/deepinv.utils.plot_parameters.html.md): Plot the parameters of the model before and after training. - [plot_inset](https://deepinv.org/api/stubs/deepinv.utils.plot_inset.html.md): Plots a list of images with zoomed-in insets extracted from the images. - [plot_videos](https://deepinv.org/api/stubs/deepinv.utils.plot_videos.html.md): Plots and animates a list of image sequences. - [save_videos](https://deepinv.org/api/stubs/deepinv.utils.save_videos.html.md): Saves an animation of a list of image sequences. - [plot_ortho3D](https://deepinv.org/api/stubs/deepinv.utils.plot_ortho3D.html.md): Plots an orthogonal view of 3D images. - [plot_napari](https://deepinv.org/api/stubs/deepinv.utils.plot_napari.html.md): View 2D images or 3D volumes in napari. - [disable_tex](https://deepinv.org/api/stubs/deepinv.utils.disable_tex.html.md): Globally disable LaTeX - [enable_tex](https://deepinv.org/api/stubs/deepinv.utils.enable_tex.html.md): Globally enable LaTeX - [normalize_signal](https://deepinv.org/api/stubs/deepinv.utils.normalize_signal.html.md): Normalize a batch of signals between zero and one. - [config_matplotlib](https://deepinv.org/api/stubs/deepinv.utils.plotting.config_matplotlib.html.md): Config matplotlib for nice plots in the examples. - [deepinv.utils.TensorList](https://deepinv.org/api/stubs/deepinv.utils.TensorList.html.md): Represents a list of [`torch.Tensor`](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor... - [zeros_like](https://deepinv.org/api/stubs/deepinv.utils.zeros_like.html.md): Returns a [`deepinv.utils.TensorList`](https://deepinv.org/api/stubs/deepinv.utils.TensorList.html.m... - [ones_like](https://deepinv.org/api/stubs/deepinv.utils.ones_like.html.md): Returns a [`deepinv.utils.TensorList`](https://deepinv.org/api/stubs/deepinv.utils.TensorList.html.m... - [randn_like](https://deepinv.org/api/stubs/deepinv.utils.randn_like.html.md): Returns a [`deepinv.utils.TensorList`](https://deepinv.org/api/stubs/deepinv.utils.TensorList.html.m... - [rand_like](https://deepinv.org/api/stubs/deepinv.utils.rand_like.html.md): Returns a [`deepinv.utils.TensorList`](https://deepinv.org/api/stubs/deepinv.utils.TensorList.html.m... - [AverageMeter](https://deepinv.org/api/stubs/deepinv.utils.AverageMeter.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [ProgressMeter](https://deepinv.org/api/stubs/deepinv.utils.ProgressMeter.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [get_timestamp](https://deepinv.org/api/stubs/deepinv.utils.get_timestamp.html.md): Get current timestamp string. - [MRIMixin](https://deepinv.org/api/stubs/deepinv.utils.MRIMixin.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [TimeMixin](https://deepinv.org/api/stubs/deepinv.utils.TimeMixin.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [TiledMixin2d](https://deepinv.org/api/stubs/deepinv.utils.TiledMixin2d.html.md): Bases: [`object`](https://docs.python.org/3.9/library/functions.html#object) - [load_dicom](https://deepinv.org/api/stubs/deepinv.utils.load_dicom.html.md): Load image from DICOM file. - [load_nifti](https://deepinv.org/api/stubs/deepinv.utils.load_nifti.html.md): Load volume from nifti file as torch tensor. - [load_tiff](https://deepinv.org/api/stubs/deepinv.utils.load_tiff.html.md): Load image or volume from a TIFF file as a torch tensor. - [load_url](https://deepinv.org/api/stubs/deepinv.utils.load_url.html.md): Load URL to a buffer. - [load_np](https://deepinv.org/api/stubs/deepinv.utils.load_np.html.md): Load numpy array from file as torch tensor. - [load_torch](https://deepinv.org/api/stubs/deepinv.utils.load_torch.html.md): Load torch tensor from file. - [load_mat](https://deepinv.org/api/stubs/deepinv.utils.load_mat.html.md): Load MATLAB array from file. - [load_raster](https://deepinv.org/api/stubs/deepinv.utils.load_raster.html.md): Load a raster image and return patches as tensors using `rasterio`. - [load_ismrmd](https://deepinv.org/api/stubs/deepinv.utils.load_ismrmd.html.md): Load complex MRI data from ISMRMD format. - [DownloadError](https://deepinv.org/api/stubs/deepinv.utils.DownloadError.html.md): Bases: [`RequestException`](https://docs.python-requests.org/en/latest/api/#requests.RequestExceptio... - [load_image](https://deepinv.org/api/stubs/deepinv.utils.load_image.html.md): Load an image from a file and return a torch.Tensor with a batch dimension. - [load_url_image](https://deepinv.org/api/stubs/deepinv.utils.load_url_image.html.md): Load an image from a URL and return a torch.Tensor with a batch dimension. - [load_np_url](https://deepinv.org/api/stubs/deepinv.utils.load_np_url.html.md): Load a numpy array from url and convert to tensor. - [load_torch_url](https://deepinv.org/api/stubs/deepinv.utils.load_torch_url.html.md): Load an array from url and read it by torch.load. - [load_example](https://deepinv.org/api/stubs/deepinv.utils.load_example.html.md): Load example image from the [DeepInverse HuggingFace](https://huggingface.co/datasets/deepinv/images... - [download_example](https://deepinv.org/api/stubs/deepinv.utils.download_example.html.md): Download an image from the [DeepInverse HuggingFace](https://huggingface.co/datasets/deepinv/images)... - [get_cache_home](https://deepinv.org/api/stubs/deepinv.utils.get_cache_home.html.md): Return a folder to store deepinv cache (datasets, models, etc.). - [get_image_url](https://deepinv.org/api/stubs/deepinv.utils.get_image_url.html.md): Get URL for image from DeepInverse HuggingFace repository. - [get_degradation_url](https://deepinv.org/api/stubs/deepinv.utils.get_degradation_url.html.md): Get URL for degradation from DeepInverse HuggingFace repository. - [load_dataset](https://deepinv.org/api/stubs/deepinv.utils.load_dataset.html.md): Loads an ImageFolder dataset from DeepInverse HuggingFace repository. - [load_degradation](https://deepinv.org/api/stubs/deepinv.utils.load_degradation.html.md): Loads a degradation tensor from DeepInverse HuggingFace repository. - [generate_shepp_logan](https://deepinv.org/api/stubs/deepinv.utils.phantoms.generate_shepp_logan.html.md): Generate a Shepp-Logan phantom approximation in PyTorch. - [generate_random_phantom](https://deepinv.org/api/stubs/deepinv.utils.phantoms.generate_random_phantom.html.md): Generate a random ellipsoid phantom directly using torch. - [generate_pet_phantom](https://deepinv.org/api/stubs/deepinv.utils.phantoms.generate_pet_phantom.html.md): Generate a 2D or 3D PET-like phantom and its corresponding attenuation map. - [SheppLoganDataset](https://deepinv.org/api/stubs/deepinv.utils.phantoms.SheppLoganDataset.html.md): Bases: [`Dataset`](https://docs.pytorch.org/docs/stable/data.html#torch.utils.data.Dataset) - [RandomPhantomDataset](https://deepinv.org/api/stubs/deepinv.utils.phantoms.RandomPhantomDataset.html.md): Bases: [`Dataset`](https://docs.pytorch.org/docs/stable/data.html#torch.utils.data.Dataset) - [patch_extractor](https://deepinv.org/api/stubs/deepinv.utils.patch_extractor.html.md): This function takes a `B x C x H x W` tensor as input and extracts `n_patches` random patches - [image_to_patches](https://deepinv.org/api/stubs/deepinv.utils.image_to_patches.html.md): Split a batch of images into overlapping 2D patches. - [patches_to_image](https://deepinv.org/api/stubs/deepinv.utils.patches_to_image.html.md): Reconstruct images from overlapping 2D patches. - [patchify](https://deepinv.org/api/stubs/deepinv.utils.patchify.html.md): Alias of [`deepinv.utils.image_to_patches()`](https://deepinv.org/api/stubs/deepinv.utils.image_to_p... - [get_freer_gpu](https://deepinv.org/api/stubs/deepinv.utils.get_freer_gpu.html.md): Returns the GPU device with the most free memory. - [dirac](https://deepinv.org/api/stubs/deepinv.utils.dirac.html.md): Returns a [`torch.Tensor`](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor) with a Di... - [dirac_like](https://deepinv.org/api/stubs/deepinv.utils.dirac_like.html.md): Returns a [`deepinv.utils.TensorList`](https://deepinv.org/api/stubs/deepinv.utils.TensorList.html.m... - [dirac_comb](https://deepinv.org/api/stubs/deepinv.utils.dirac_comb.html.md): Returns a [`torch.Tensor`](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor) with a Di... - [dirac_comb_like](https://deepinv.org/api/stubs/deepinv.utils.dirac_comb_like.html.md): Returns a [`deepinv.utils.TensorList`](https://deepinv.org/api/stubs/deepinv.utils.TensorList.html.m... - [Benchmarks](https://deepinv.org/auto_benchmarks/benchmarks.html.md): This section provides benchmark results for various datasets and physics models. - [Blur](https://deepinv.org/auto_benchmarks/blur_benchmarks.html.md): * [DIV2K Gaussian Deblurring](https://deepinv.org/auto_benchmarks/div2k_gaussian_deblurring.html.md) - [DIV2K Gaussian Deblurring](https://deepinv.org/auto_benchmarks/div2k_gaussian_deblurring.html.md): - *Dataset*: [`DIV2K`](https://deepinv.org/api/stubs/deepinv.datasets.DIV2K.html.md#deepinv.datasets... - [Denoising](https://deepinv.org/auto_benchmarks/denoising_benchmarks.html.md): * [CBSD68 gaussian denoising](https://deepinv.org/auto_benchmarks/cbsd68_gaussian_denoising.html.md) - [CBSD68 gaussian denoising](https://deepinv.org/auto_benchmarks/cbsd68_gaussian_denoising.html.md): - *Dataset*: [`CBSD68`](https://deepinv.org/api/stubs/deepinv.datasets.CBSD68.html.md#deepinv.datase... - [Downsampling](https://deepinv.org/auto_benchmarks/downsampling_benchmarks.html.md): * [DIV2K Super Resolution 2x](https://deepinv.org/auto_benchmarks/div2k_super_resolution_2x.html.md) - [DIV2K Super Resolution 2x](https://deepinv.org/auto_benchmarks/div2k_super_resolution_2x.html.md): - *Dataset*: [`DIV2K`](https://deepinv.org/api/stubs/deepinv.datasets.DIV2K.html.md#deepinv.datasets... - [Inpainting](https://deepinv.org/auto_benchmarks/inpainting_benchmarks.html.md): * [DIV2K Inpainting easy](https://deepinv.org/auto_benchmarks/div2k_inpainting_easy.html.md) - [DIV2K Inpainting easy](https://deepinv.org/auto_benchmarks/div2k_inpainting_easy.html.md): - *Dataset*: [`DIV2K`](https://deepinv.org/api/stubs/deepinv.datasets.DIV2K.html.md#deepinv.datasets... - [Finding Help](https://deepinv.org/finding_help.html.md): If you have any questions or suggestions, please join the conversation in our - [Contributing to DeepInverse](https://deepinv.org/contributing.html.md): DeepInverse is a community-driven project and welcomes contributions of all forms. - [Community](https://deepinv.org/community.html.md): DeepInverse contributors include researchers and practitioners from multiple institutions and compan... - [Change Log](https://deepinv.org/changelog.html.md): This change log is for the `main` branch. It contains changes for each release, with the date and au... - [DeepInverse Tutorial @ MICCAI 2026](https://deepinv.org/miccai-2026.html.md): Welcome to the DeepInverse tutorial at [International Conference on Medical Image Computing and Comp... --- For more comprehensive documentation, see [llms-full.txt](https://deepinv.org/llms-full.txt)