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Types & classes25 in github.com/NVlabs/stylegan2-ada

↓ 26 callersClassUserError
train.py:26
↓ 23 callersClassEasyDict
Convenience class that behaves like a dict but allows access with the attribute syntax.
dnnlib/util.py:40
↓ 11 callersClassTFRecordExporter
dataset_tool.py:38
↓ 5 callersClass_FilterKernel
dnnlib/tflib/ops/upfirdn_2d.py:370
↓ 4 callersClassUserError
calc_metrics.py:22
↓ 2 callersClassHDF5Exporter
dataset_tool.py:116
↓ 2 callersClassManifoldEstimator
Finds an estimate for the manifold of given feature vectors.
metrics/precision_recall.py:64
↓ 2 callersClassTFRecordDataset
training/dataset.py:20
↓ 1 callersClassDistanceBlock
Distance block.
metrics/precision_recall.py:41
↓ 1 callersClassExceptionInfo
dataset_tool.py:211
↓ 1 callersClassNetwork
Generic network abstraction. Acts as a convenience wrapper for a parameterized network construction function, providing several utility metho
dnnlib/tflib/network.py:42
↓ 1 callersClassProjector
projector.py:24
↓ 1 callersClassWorkerThread
dataset_tool.py:218
ClassAdaptiveAugment
training/augment.py:27
ClassFID
metrics/frechet_inception_distance.py:24
ClassIS
metrics/inception_score.py:22
ClassKID
metrics/kernel_inception_distance.py:37
ClassLS
metrics/linear_separability.py:107
ClassLogger
Redirect stderr to stdout, optionally print stdout to a file, and optionally force flushing on both stdout and the file.
dnnlib/util.py:56
ClassMetricBase
metrics/metric_base.py:25
ClassOptimizer
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
ClassPPL
metrics/perceptual_path_length.py:38
ClassPR
metrics/precision_recall.py:174
ClassSimpleAdam
Simplified version of tf.train.AdamOptimizer that behaves identically when used with dnnlib.tflib.Optimizer.
dnnlib/tflib/optimizer.py:326
ClassThreadPool
dataset_tool.py:236