Backward function for Sparse Matrix Multiplication QmK. Args: ctx: Autograd context to retrieve saved tensors.

Generate a bivariate isotropic or anisotropic Gaussian kernel. In the isotropic mode, only `sig_x` is used. `sig_y` and `theta` is ignored.

Generate a bivariate generalized Gaussian kernel. ``Paper: Parameter Estimation For Multivariate Generalized Gaussian Distributions`` In

Generate a plateau-like anisotropic kernel. 1 / (1+x^(beta)) Reference: https://stats.stackexchange.com/questions/203629/is-there-a-plat

Calculate metric from data and options. Args: opt (dict): Configuration. It must contain: type (str): Model type.

Calculate PSNR (Peak Signal-to-Noise Ratio). Reference: https://en.wikipedia.org/wiki/Peak_signal-to-noise_ratio Args: img (nda

Calculate SSIM (structural similarity). ``Paper: Image quality assessment: From error visibility to structural similarity`` The results

Check resume states and pretrain_network paths. Args: opt (dict): Options. resume_iter (int): Resume iteration.

Initialize network weights. Args: module_list (list[nn.Module] | nn.Module): Modules to be initialized. scale (float): Scale

Dequantize an array. Args: arr (ndarray): Input array. min_val (scalar): Minimum value to be clipped. max_val (scala

Recover from quantized flow. Args: dx (ndarray): Quantized dx. dy (ndarray): Quantized dy. max_val (float): Maximum

Generate Gaussian kernel used in `duf_downsample`. Args: kernel_size (int): Kernel size. Default: 13. sigma (float): Sigma of

Get local weights for generating the artifact map of LDL. It is only called by the `get_refined_artifact_map` function. Args: r

Get the position from a period list. It will return the index of the right-closest number in the period list. For example, the cumulative_

Write image to file. Args: img (ndarray): Image array to be written. file_path (str): Image file path. params (None

We now only use wandb to sync tensorboard log.

Mod crop images, used during testing. Args: img (ndarray): Input image. scale (int): Scale factor. Returns: n

Model to device. It also warps models with DistributedDataParallel or DataParallel. Args: net (nn.Module)

Generate paired paths from folders. Args: folders (list[str]): A list of folder path. The order of list should be [input_

Generate paired paths from lmdb files. Contents of lmdb. Taking the `lq.lmdb` for example, the file structure is: :: lq.lmdb

Generate paired paths from an meta information file. Each line in the meta information file contains the image names and image shape (usua

Paired random crop. Support Numpy array and Tensor inputs. It crops lists of lq and gt images with corresponding locations. Args:

Calculate PDF of the bivariate Gaussian distribution. Args: sigma_matrix (ndarray): with the shape (2, 2) grid (ndarray): gen

Print the str and parameter number of a network. Args: net (nn.Module)

Quantize an array of (-inf, inf) to [0, levels-1]. Args: arr (ndarray): Input array. min_val (scalar): Minimum value to be cl

Quantize flow to [0, 255]. After this step, the size of flow will be much smaller, and can be dumped as jpeg images. Args:

Read image worker. Args: path (str): Image path. key (str): Image key. compress_level (int): Compress level when enc

Reduce loss as specified. Args: loss (Tensor): Elementwise loss tensor. reduction (str): Options are 'none', 'mean' and 'sum'

reduce loss dict. In distributed training, it averages the losses among different GPUs . Args: loss_dict (OrderedDi

Reload the optimizers and schedulers for resumed training. Args: resume_state (dict): Resume state.

Save training states during training, which will be used for resuming. Args: epoch (int): Current epoch.

Set random seeds.

Set up schedulers.

Update learning rate. Args: current_iter (int): Current iteration. warmup_iter (int): Warm-up iter numbers. -1 fo

Apply element-wise weight and reduce loss. Args: loss (Tensor): Element-wise loss. weight (Tensor): Element-wise weights. Def

Args: windows: (num_windows*b, window_size, window_size, c) window_size (int): Window size h (int): Height of image

Load yaml file or string. Args: f (str): File path or a python string. Returns: dict: Loaded dict.

Format logging message. Args: log_vars (dict): It contains the following keys: epoch (int): Epoch number.