NeurIPS camera-ready

Author: zsyzzsoft

DiffAugment-stylegan2/run_100_shot.py

@@ -96,11 +96,11 @@ def run(dataset, resolution, result_dir, DiffAugment, num_gpus, batch_size, tota
 # ----------------------------------------------------------------------------
 
 
-def run_eval(dataset, resolution, result_dir, DiffAugment, num_gpus, batch_size, total_kimg, ema_kimg, num_samples, gamma, fmap_base, fmap_max, latent_size, mirror_augment, impl, metrics, resume, resume_kimg, num_repeats, eval):
+def run_eval(dataset, resolution, num_gpus, metrics, resume, num_repeats, **kwargs):
     dataset = dataset_tool.create_dataset(dataset, resolution)
     print('Evaluating metrics "%s" for "%s"...' % (','.join(metrics), resume))
     tflib.init_tf()
-    dataset_args = dnnlib.EasyDict(tfrecord_dir=dataset, num_samples=num_samples, resolution=resolution, from_tfrecords=True)
+    dataset_args = dnnlib.EasyDict(tfrecord_dir=dataset, resolution=resolution, from_tfrecords=True)
     metric_group = metric_base.MetricGroup([metric_defaults[metric] for metric in metrics], num_repeats=num_repeats)
     metric_group.run(resume, dataset_args=dataset_args, num_gpus=num_gpus)
 

DiffAugment-stylegan2/run_cifar.py

@@ -92,7 +92,7 @@ def run(dataset, resolution, result_dir, DiffAugment, num_gpus, batch_size, tota
 # ----------------------------------------------------------------------------
 
 
-def run_eval(dataset, resolution, result_dir, DiffAugment, num_gpus, batch_size, total_kimg, ema_kimg, num_samples, gamma, fmap_base, fmap_max, latent_size, mirror_augment, impl, metrics, resume, resume_kimg, num_repeats, eval):
+def run_eval(dataset, resolution, num_gpus, metrics, resume, num_repeats, **kwargs):
     print('Evaluating metrics "%s" for "%s"...' % (','.join(metrics), resume))
     tflib.init_tf()
     dataset_args = dnnlib.EasyDict(tfrecord_dir=dataset, shuffle_mb=0)

DiffAugment-stylegan2/run_ffhq.py

@@ -96,7 +96,7 @@ def run(dataset, resolution, result_dir, DiffAugment, num_gpus, batch_size, tota
 # ----------------------------------------------------------------------------
 
 
-def run_eval(dataset, resolution, result_dir, DiffAugment, num_gpus, batch_size, total_kimg, ema_kimg, num_samples, gamma, fmap_base, fmap_max, latent_size, mirror_augment, impl, metrics, resume, resume_kimg, num_repeats, eval):
+def run_eval(dataset, resolution, num_gpus, metrics, resume, num_repeats, **kwargs):
     dataset = dataset_tool.create_dataset(dataset, resolution)
     print('Evaluating metrics "%s" for "%s"...' % (','.join(metrics), resume))
     tflib.init_tf()