(self, mode)

(self, mode)

(run_id, log, metrics, num_images, real_passes, minibatch_size=None)

(tfrecord_dir, output_dir)

(self, mode, minibatch)

(self, mode, minibatch)

(self, mode, minibatch)

(path)

(self, module, name)

(run_id, snapshot=None, num_pngs=1, image_shrink=1, png_prefix=None, random_seed=1000, minibatch_size=8)

(x)

(seconds)

(run_id, snapshot=None, grid_size=[1,1],batch_size=8, num_pngs=1, image_shrink=1, png_prefix=None, random_seed

(run_id, snapshot=None, grid_size=[1,1], num_pngs=1, image_shrink=1, png_prefix=None, random_seed=1000, miniba

(run_id, snapshot=None, grid_size=[1,1], image_shrink=1, image_zoom=1, duration_sec=60.0, smoothing_sec=1.0, m

(run_id, snapshot=None, grid_size=[1,1], image_shrink=1, image_zoom=1, duration_sec=60.0, smoothing_sec=1.0, m

(run_id, snapshot=None, grid_size=[1,1], image_shrink=1, image_zoom=1, duration_sec=60.0, smoothing_sec=1.0, m

(run_id, duration_sec=20.0, time_warp=1.5, mp4=None, mp4_fps=30, mp4_codec='libx265', mp4_bitrate='16M')

(run_id, snapshot=None, image_shrink=1, minibatch_size=8)

(network_pkl)

(self)

(self)

(self)

(self)

(self)

(self, minibatch_size, lod=0)

(self, minibatch_size)

(self, minibatch_size)

(self, var_or_localname)

(state)

()

(config_dict=dict())

(x, alpha=0.2)

(a, b, t)

(class_name='dataset.TFRecordDataset', data_dir=None, verbose=False, **kwargs)

(run_id, **kwargs)

(run_id_or_result_subdir_or_network_pkl, snapshot=None)

(x)

(t)

(self, record)

(state)

(num_latents, G, random_state=None)

(pyramid)

(scope, parent_ops, level)

(self)

()

(img)

(self)

(image, filename, drange=[0,1], quality=95)

(images, filename, drange=[0,1], grid_size=None)

(obj, filename)

(filewriter, global_step=None)

(self, var_or_localname, new_value)

(prepared, idx)

(img)

( G_smoothing = 0.999, # Exponential running average of generator weights. D_repe

( G_smoothing = 0.999, # Exponential running average of generator weights. D_repeat

(self, data)