Convenience class that behaves like a dict but allows access with the attribute syntax.

Generic network abstraction. Acts as a convenience wrapper for a parameterized network construction function, providing several utility metho

Helper class to make neural nets for use in continuous normalizing flows

A mixed bag of values used by dnnlib heuristics. Attributes: data_reader_buffer_size: Used by DataReader to size internal shared memory

Helper class for managing the run/training loop. The context will hide the implementation details of a basic run/training loop. It will set t

A generalized nn.Sequential container for normalizing flows.

Computes and stores the average and current value

Redirect stderr to stdout, optionally print stdout to a file, and optionally force flushing on both stdout and the file.

A Wrapper for tf.train.Optimizer. Automatically takes care of: - Gradient averaging for multi-GPU training. - Gradient accumulation for a

Determines in which format should a path be formatted. WINDOWS: Format with Windows style. LINUX: Format with Linux/Posix style. AUTO: Us

Simplified version of tf.train.AdamOptimizer that behaves identically when used with dnnlib.tflib.Optimizer.

Strongly typed config dict needed to submit runs. Attributes: run_dir_root: Path to the run dir root. Can be optionally templated with ta

The target where the function should be run. LOCAL: Run it locally.