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github.com/NVlabs/stylegan2-ada
/ types & classes
Types & classes
25 in github.com/NVlabs/stylegan2-ada
⨍
Functions
336
◇
Types & classes
25
↓ 26 callers
Class
UserError
train.py:26
↓ 23 callers
Class
EasyDict
Convenience class that behaves like a dict but allows access with the attribute syntax.
dnnlib/util.py:40
↓ 11 callers
Class
TFRecordExporter
dataset_tool.py:38
↓ 5 callers
Class
_FilterKernel
dnnlib/tflib/ops/upfirdn_2d.py:370
↓ 4 callers
Class
UserError
calc_metrics.py:22
↓ 2 callers
Class
HDF5Exporter
dataset_tool.py:116
↓ 2 callers
Class
ManifoldEstimator
Finds an estimate for the manifold of given feature vectors.
metrics/precision_recall.py:64
↓ 2 callers
Class
TFRecordDataset
training/dataset.py:20
↓ 1 callers
Class
DistanceBlock
Distance block.
metrics/precision_recall.py:41
↓ 1 callers
Class
ExceptionInfo
dataset_tool.py:211
↓ 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:42
↓ 1 callers
Class
Projector
projector.py:24
↓ 1 callers
Class
WorkerThread
dataset_tool.py:218
Class
AdaptiveAugment
training/augment.py:27
Class
FID
metrics/frechet_inception_distance.py:24
Class
IS
metrics/inception_score.py:22
Class
KID
metrics/kernel_inception_distance.py:37
Class
LS
metrics/linear_separability.py:107
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:56
Class
MetricBase
metrics/metric_base.py:25
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:28
Class
PPL
metrics/perceptual_path_length.py:38
Class
PR
metrics/precision_recall.py:174
Class
SimpleAdam
Simplified version of tf.train.AdamOptimizer that behaves identically when used with dnnlib.tflib.Optimizer.
dnnlib/tflib/optimizer.py:326
Class
ThreadPool
dataset_tool.py:236