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github.com/NVlabs/stylegan2
/ types & classes
Types & classes
28 in github.com/NVlabs/stylegan2
⨍
Functions
345
◇
Types & classes
28
↓ 33 callers
Class
EasyDict
Convenience class that behaves like a dict but allows access with the attribute syntax.
dnnlib/util.py:35
↓ 10 callers
Class
TFRecordExporter
dataset_tool.py:32
↓ 2 callers
Class
ManifoldEstimator
Finds an estimate for the manifold of given feature vectors.
metrics/precision_recall.py:61
↓ 1 callers
Class
DistanceBlock
Distance block.
metrics/precision_recall.py:38
↓ 1 callers
Class
ExceptionInfo
dataset_tool.py:105
↓ 1 callers
Class
Network
Generic network abstraction. Acts as a convenience wrapper for a parameterized network construction function, providing several utility metho
dnnlib/tflib/network.py:35
↓ 1 callers
Class
PlatformExtras
A mixed bag of values used by dnnlib heuristics. Attributes: data_reader_buffer_size: Used by DataReader to size internal shared memory
dnnlib/submission/submit.py:49
↓ 1 callers
Class
RunContext
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
dnnlib/submission/run_context.py:23
↓ 1 callers
Class
WorkerThread
dataset_tool.py:112
Class
DummyMetric
metrics/metric_base.py:163
Class
FID
metrics/frechet_inception_distance.py:20
Class
IS
metrics/inception_score.py:18
Class
LS
metrics/linear_separability.py:103
Class
Logger
Redirect stderr to stdout, optionally print stdout to a file, and optionally force flushing on both stdout and the file.
dnnlib/util.py:51
Class
MetricBase
metrics/metric_base.py:23
Class
MetricGroup
metrics/metric_base.py:145
Class
Optimizer
A Wrapper for tf.train.Optimizer. Automatically takes care of: - Gradient averaging for multi-GPU training. - Gradient accumulation for a
dnnlib/tflib/optimizer.py:26
Class
PPL
metrics/perceptual_path_length.py:34
Class
PR
metrics/precision_recall.py:171
Class
PathType
Determines in which format should a path be formatted. WINDOWS: Format with Windows style. LINUX: Format with Linux/Posix style. AUTO: Us
dnnlib/submission/submit.py:37
Class
Projector
projector.py:16
Class
SimpleAdam
Simplified version of tf.train.AdamOptimizer that behaves identically when used with dnnlib.tflib.Optimizer.
dnnlib/tflib/optimizer.py:324
Class
SubmitConfig
Strongly typed config dict needed to submit runs. Attributes: run_dir_root: Path to the run dir root. Can be optionally templated with ta
dnnlib/submission/submit.py:64
Class
SubmitTarget
The target where the function should be run. LOCAL: Run it locally.
dnnlib/submission/submit.py:29
Class
TFRecordDataset
training/dataset.py:19
Class
Target
dnnlib/submission/internal/local.py:11
Class
TargetOptions
dnnlib/submission/internal/local.py:7
Class
ThreadPool
dataset_tool.py:130