r"""Hook that is called internally by the `pickle` module to unpickle a persistent object.

r"""Returns the averages accumulated between the last two calls to `update()` as an `dnnlib.EasyDict`. The contents are as follows:

Ask the user the question until the user inputs a valid answer.

r"""Fused bias and activation function. Adds bias `b` to activation tensor `x`, evaluates activation function `act`, and scales the result by

Build optimizer, set weight decay of normalization to 0 by default.

Compute the entire variational lower-bound, measured in bits-per-dim, as well as other related quantities. :param model: the

Calculates the FID of two paths

End DDP training.

Finds the python class with the given name and constructs it with the given arguments.

Compute the log-likelihood of a continuous Gaussian distribution. :param x: the targets :param means: the Gaussian mean Tensor. :para

r"""2D convolution with optional up/downsampling. Padding is performed only once at the beginning, not between the operations. Args:

Takes in a list of tuples of (src, dst) paths and copies files. Will create all necessary directories.

Create a logger that writes to a log file and stdout.

Create a ScheduleSampler from a library of pre-defined samplers. :param name: the name of the sampler. :param diffusion: the diffusion ob

Sample x_{t+1} from the model using DDIM reverse ODE.

Generate samples from the model using DDIM. Same usage as p_sample_loop().

r"""Downsample a batch of 2D images using the given 2D FIR filter. By default, the result is padded so that its shape is a fraction of the input.