r"""Returns the mean of the scalars that were accumulated for the given statistic between the last two calls to `update()`, or NaN if

Wrapper for the underlying `conv2d()` and `conv_transpose2d()` implementations.

r"""Copies current values of the internal counters to the user-visible state and resets them for the next round. If `keep_previous=Tr

Flush written text to both stdout and a file, if open.

Write text to stdout (and a file) and optionally flush.

r"""Returns the raw moments that were accumulated for the given statistic between the last two calls to `update()`, or zero if no scal

Traverses the object name and returns the last (rightmost) python object.

r"""Pad, upsample, filter, and downsample a batch of 2D images. Performs the following sequence of operations for each channel: 1. Upsample

Fast CUDA implementation of `upfirdn2d()` using custom ops.

Searches for the underlying module behind the name to some python object. Returns the module and the object name (original name with module part r

r"""Test whether the given object or class is persistent, i.e., whether it will save its source code when pickled.

r"""Returns the names of all statistics broadcasted so far that match the regular expression specified at construction time.

r"""Returns the standard deviation of the scalars that were accumulated for the given statistic between the last two calls to `update(

Fast CUDA implementation of `bias_act()` using custom ops.

Slow reference implementation of `bias_act()` using standard TensorFlow ops.

r"""Check that the given object is pickleable, raising an exception if it is not. This function is expected to be considerably more efficient

r"""Query the source code of a given Python module.

r"""Get or create a Python module for the given source code.

r"""Synchronize the global cumulative counters across devices and processes. Called internally by `Collector.update()`.

Slow reference implementation of `upfirdn2d()` using standard PyTorch ops.

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

Calculate quality metrics for previous training run or pretrained network pickle. Examples: \b # Previous training run: look up options

Finds the python object with the given name and calls it as a function.

Flush, close possible files, and remove stdout/stderr mirroring.

Convert an image dataset into a dataset archive usable with StyleGAN2 ADA PyTorch. The input dataset format is guessed from the --source argument

Convert legacy network pickle into the native PyTorch format. The tool is able to load the main network configurations exported using the TensorF

Generate images using pretrained network pickle. Examples: \b # Generate curated MetFaces images without truncation (Fig.10 left) py

Finds the python object with the given name.