(url='', **kwargs)

(self, dim, mlp_ratio=4, out_features=None, act_layer=StarReLU, drop=0., bias=False, **kwargs)

(ni, nf, stride, activation="leaky_relu", kernel_size=3, activation_param=1e-2, groups=1)

(ni, nf, stride, kernel_size=3, groups=1)

(self, channels, reduction_channels, inplace=True)

(self, block, planes, blocks, stride=1, use_se=True, anti_alias_layer=None)

(self, block, planes, blocks, stride=1, use_se=True, anti_alias_layer=None)

(ni, nf, stride, kernel_size=3)

(self, tensor, pos: Optional[torch.Tensor])

(self, layers, in_chans=3, num_classes=1000, width_factor=1.0, first_two_layers=BasicBlock)

(self, layers, in_chans=3, num_classes=1000, width_factor=1.0, first_two_layers=BasicBlock)

(model_name, args)

(self, image_size, keep_ratio=False)

(self, img: Image.Image, thr: float)

(self, path=DEFAULT_MODEL)

(self, decoder_layer, num_layers, norm=None, return_intermediate=False)

(self, num_pos_feats=64, temperature=10000, normalize=False, scale=None)

(self, embed_len_decoder: int)

(self, d_model, nhead=8, dim_feedforward=2048, dropout=0.1, activation="relu", layer_norm_eps

(self, filt_size: int = 3, stride: int = 2, channels: int = 0)

(self, state)

(module, N)

(position_embedding, hidden_dim=512)

(infer)

(self, feat_list)

(self, x)

(self, x)

(self)

(self)

(module: nn.Module)

(self, h: torch.Tensor, duplicate_pooling: torch.Tensor, out_extrap: torch.Tensor)

(self, x: torch.Tensor)

(self)

(self, encoder: MetaFormer, decoder: MSDecoder, num_queries=50, d_model=512, num_classes=1000, scale_skip=0)

(self, d_model, nhead, dim_feedforward=2048, dropout=0.1, activation=nn.GELU(), normalize_bef

(self, in_channels, out_channels, kernel_size, stride=1, padding=0, pre_norm=None, post_norm

(self, dim, init_value=1.0, trainable=True)

(self, inplace=False)

(self, scale_value=1.0, bias_value=0.0, scale_learnable=True, bias_learnable=True, mode=None,

(self, dim, head_dim=32, num_heads=None, qkv_bias=False, attn_drop=0., proj_drop=0., proj_bias=False,

(self, num_tokens=196, **kwargs)

(self, affine_shape=None, normalized_dim=(-1, ), scale=True, bias=True, eps=1e-5)

(self, dim, expansion_ratio=2, act1_layer=StarReLU, act2_layer=nn.Identity, bias=False, kerne

(self, pool_size=3, **kwargs)

(self, dim, num_classes=1000, mlp_ratio=4, act_layer=SquaredReLU, norm_layer=nn.LayerNorm, head_dropou

(self, dim, token_mixer=nn.Identity, mlp=Mlp, norm_layer=nn.LayerNorm,

(self, in_chans=3, num_classes=1000, depths=[2, 2, 6, 2], dims=[64, 128, 32

(self, num_pos_feats=256)

(self, num_classes, num_of_groups=-1, decoder_embedding=768, initial_num_features=2048, zsl=0

(self, d_model, nhead=8, dim_feedforward=2048, dropout=0.1, activation="relu", layer_norm_eps

(self, inplanes, planes, stride=1, downsample=None, use_se=True, anti_alias_layer=None)

(self, inplanes, planes, stride=1, downsample=None, use_se=True, anti_alias_layer=None)

(self, inplanes, planes, stride=1, downsample=None, use_se=True, anti_alias_layer=None)

(self, inplanes, planes, stride=1, downsample=None, use_se=True, anti_alias_layer=None)

(self, filt_size: int = 3, stride: int = 2, channels: int = 0)

(self, flatten=False)

(self, block_size)

(self, remove_model_jit=False)

(self, block_size=4)

(self, inplace=True)

(self, in_channel)

(self, state)

(self, m)

(model, num_classes=-1, num_of_groups=-1, decoder_embedding=768, zsl=0, learn_query=False)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(ni, nf, stride)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)

(pretrained=False, **kwargs)