(self, d_model: int, n_head: int, attn_mask: torch.Tensor = None)

(self, width: int, layers: int, heads: int, attn_mask: torch.Tensor = None)

(self, input_resolution: int, patch_size: int, width: int, layers: int, heads: int, output_dim: int)

(self, in_channels, out_channels, kernel_size=3,

(self, global_disc_cfg, local_disc_cfg)

(self, in_channels, mid_channels)

(self, in_channels, mid_channels=64, skip_connection=True)

(self, in_channels, max_channels, num_convs=5,

(self, global_disc_cfg, local_disc_cfg)

(self, in_channels=3, in_size=160)

(self, in_channels, base_channels=64, num_conv=3,

(self, in_channels, base_channels=64, num_conv=3,

(self, encoder_attention=dict( type='DeepFillEncoder', encoder_type='sta

(self, conv_channels=64, pretrained=None)

(self, in_dim, out_dim, hidden_list)

(self, in_channels=None, eps=1e-6)

(self, name='weight', gain=2**0.5, mode='fan_in', lr_mul=1.0)

(self, *args, equalized_lr_cfg=dict(mode='fan_in'), **kwargs)

(self, *args, equalized_lr_cfg=dict(mode='fan_in'), **kwargs)

(self, *args, equalized_lr_cfg=dict(gain=1., lr_mul=1.), bi

(self, kernel, factor=2)

(self, kernel, factor=2)

(self, in_channels, out_channels, kernel_size,

(self, noise_weight_init=0.)

(self, channel, size=4)

(self, in_channels, out_channels, kernel_size,

(self, in_channels, out_channels, kernel_size,

(self, in_channels, out_channels, kernel_size,

(self, in_channels, style_channels, out_channels=3,

(self, in_channels, out_channels, kernel_size,

(self, in_channels, out_channels, blur_kernel=[1, 3, 3, 1])

(self, group_size=4, channel_groups=1, sync_groups=None,

(self, in_size, channel_multiplier=2, blur_kernel=[1, 3, 3,

(self, encoder, decoder)

(self, encoder, decoder)

(self, encoder=dict(type='GLEncoder'), decoder=dict(type='GLDecoder'),

(self, stage1=dict( type='GLEncoderDecoder', encode

(self, encoder=dict(type='AOTEncoder'), decoder=dict(type='AOTDecoder'),

(self, in_channels=256, dilation_rates=(1, 2, 4, 8), num_ao

(self, in_channels, conv_type='conv', conv_cfg=None,

(self, in_channels=256, conv_type='conv', norm_cfg=None,

(self, in_channels=3, num_layers=7, conv_cfg=dict(type='PCo

(self, in_channels, norm_cfg=dict(type='BN'), use_context=F

(self, in_channels, norm_cfg=dict(type='BN'), use_context=F

(self, in_channels, out_channels, stride,

(self, norm_cfg=None, act_cfg=dict(type='ReLU'))

(self, in_channels=5, conv_type='conv', norm_cfg=None,

(self, in_channels, batch_norm=False, aspp=False,

(self, in_channels, out_channels, kernel_size=3,

(self, block, layers, in_channels, conv_cf

(self, block, layers, in_channels, conv_cf

(self, inplanes, planes, stride=1, dilatio

(self, inplanes, planes, stride=1, dilatio

(self, in_channels=4, mid_channels=64, out_channels=256,

(self, in_channels=256, mid_channels=128, out_channels=3,

(self, block, layers, in_channels, kernel_

(self, in_channels, conv_type='conv', norm_cfg=None,

(self, pool_scales, in_channels, channels,

(self, in_channels, kernel_size=5, norm_cfg=dict(type='BN')

(self, in_channels)

(self, in_channels=256, norm_cfg=None, act_cfg=dict(type='R

(self, num_layers=7, interpolation='nearest', conv_cfg=dict

(self)

(self, adapt_official_weights=False)

(self, mid_channels=64, num_propagation_blocks=20, num_clea

(self, in_channels=3, out_channel=3, mid_channels=64,

(self, *args, **kwargs)

(self, encoder, imnet, local_ensemble=True,

(self, encoder, imnet, local_ensemble=True,

(self, *args, **kwargs)

(self, clip_model)

(self, classnames, clip_model, n_ctx=16, ctx_init="", cfg_imsize=224, class_specify=False, class_token_positio

(self, n_input, n_output, n_hidden=128)

(self, classnames, backbone_name='ViT-B/32', n_ctx=16, ctx_init="", cfg_imsize=224, class_specify=False, class

(self, classnames, backbone_name='RN50', pos_embedding=False)

(self, mid_channels=64, num_blocks=30, spynet_pretrained=None)

(self, in_channels, out_channels=64, num_blocks=30)

(self)

(self, in_channels, out_channels, mid_channels=64,

(self, mid_channels)

(self, mid_channels)

(self, mid_channels, out_channels)

(self, in_channels, out_channels, mid_channels=64,

(self, scale, mid_channels)

(self, channels=(3, 64, 32, 3), kernel_sizes=(9, 1, 5), ups

(self, in_channels=3, mid_channels=64, num_blocks=23,

(self, in_channels, out_channels)

(self, in_channels, out_channels, mid_channels=64,

(self, filter_size=(5, 5))

(self, mid_channels=64, growth_channels=32)

(self, in_channels, out_channels, mid_channels=64,

(self, *args, **kwargs)

(self, mid_channels=64, deform_groups=8, act_cfg=dict(type=

(self, mid_channels=64, num_frames=5, center_frame_idx=2,

(self, mid_channels, num_blocks, upscale_factor,

(self, in_channels, mid_channels, num_blocks, upscale_factor)

(self, in_channels, out_channels, mid_channels,

(self, in_channels, num_heatmaps, num_blocks,

(self, mid_channels, num_blocks, upscale_factor,

(self, in_channels, out_channels, base_channels=64,