Method__init__(self, *, in_channels, out_channels=None, conv_shortcut=False,
dropout, temb_channels=512)
NAR-images/tokenizer/vqgan/layer.py:58
Method__init__(self, *, ch, out_ch, ch_mult=(1,2,4,8), num_res_blocks,
attn_resolutions, dropout=0.0, resam
NAR-images/tokenizer/vqgan/layer.py:270
Method__init__(self, in_channels=3, ch=128, ch_mult=(1,1,2,2,4), num_res_blocks=2,
norm_type='group', drop
NAR-images/tokenizer/tokenizer_image/vq_model.py:65
Method__init__(self, z_channels=256, ch=128, ch_mult=(1,1,2,2,4), num_res_blocks=2, norm_type="group",
drop
NAR-images/tokenizer/tokenizer_image/vq_model.py:129
Method__init__(self, n_e, e_dim, beta, entropy_loss_ratio, l2_norm, show_usage)
NAR-images/tokenizer/tokenizer_image/vq_model.py:198
Method__init__(self, in_channels, out_channels=None, conv_shortcut=False, dropout=0.0, norm_type='group')
NAR-images/tokenizer/tokenizer_image/vq_model.py:280
Method__init__(self, input_nc=3, ndf=64, n_layers=3, channel_multiplier=1, image_size=256)
NAR-images/tokenizer/tokenizer_image/discriminator.py:169
Method__init__(self, disc_start, disc_loss="hinge", disc_dim=64, disc_type='patchgan', image_size=256,
disc
NAR-images/tokenizer/tokenizer_image/vq_loss.py:50
Method__init__(self, input_nc=3, ndf=64, n_layers=3, channel_multiplier=1, image_size=256)
NAR-images/tokenizer/tokenizer_image/discriminator_stylegan.py:14
Method__init__(self, max_batch_size, max_seq_length, n_head, head_dim, dtype)
NAR-images/autoregressive/models/gpt.py:173
Method__init__(
self,
model,
dataset_csv,
root_path='data/metadata',
frame_num=16,
NAR-videos/eval/rfvd_evaluator.py:19
Method__init__(
self,
root_path,
frame_num,
cls_vid_num,
crop_size,
rand_fli
NAR-videos/datasets/video_dataset.py:61
Method__init__(
self,
dim,
depth,
n_head,
head_dim,
ff_dim=None,
dro
NAR-videos/models/transformer.py:36