↓ 8 callersMethod__init__(self, num_features, apply_act=True, momentum=0.1, eps=1e-3, **_)
lib/models_timm/layers/evo_norm.py:100
↓ 7 callersFunctionpad_same(x, k: List[int], s: List[int], d: List[int] = (1, 1), value: float = 0)
lib/models_timm/layers/padding.py:28
↓ 5 callersMethod__init__(
self, channels, rd_ratio=1./16, rd_channels=None, rd_divisor=1,
spatial_kernel_size=
lib/models_timm/layers/cbam.py:83
↓ 4 callersMethod__init__(
self, num_channels, num_groups=32, eps=1e-5, affine=True, group_size=None,
apply_act
lib/models_timm/layers/norm_act.py:181
↓ 3 callersMethod__init__(
self, in_channel, out_channels, kernel_size, stride=1, padding=None,
dilation=1, gro
lib/models_timm/layers/std_conv.py:32
↓ 3 callersMethod__init__(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, bias=True, drop=0.)
lib/models_timm/layers/mlp.py:13
↓ 2 callersMethod__init__(self, in_channels, use_scale=True, rd_ratio=1/8, rd_channels=None, rd_divisor=8, **kwargs)
lib/models_timm/layers/non_local_attn.py:23
↓ 2 callersMethod__init__(
self, channels, rd_ratio=1. / 16, rd_channels=None, rd_divisor=8, add_maxpool=False,
lib/models_timm/layers/squeeze_excite.py:28
↓ 2 callersFunctionconv2d_same(
x, weight: torch.Tensor, bias: Optional[torch.Tensor] = None, stride: Tuple[int, int] = (1, 1),
lib/models_timm/layers/conv2d_same.py:13