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108ae46 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | import torch.nn as nn
from models.modules.utils import build_act_layer, build_norm_layer
class StemLayer(nn.Module):
r""" Stem layer of InternImage
Args:
in_channels (int): number of input channels
out_channels (int): number of output channels
act_layer (str): activation layer
norm_layer (str): normalization layer
"""
def __init__(self,
in_channels=3+1,
inter_channels=48,
out_channels=96,
act_layer='GELU',
norm_layer='BN'):
super().__init__()
self.conv1 = nn.Conv2d(in_channels,
inter_channels,
kernel_size=3,
stride=1,
padding=1)
self.norm1 = build_norm_layer(
inter_channels, norm_layer, 'channels_first', 'channels_first'
)
self.act = build_act_layer(act_layer)
self.conv2 = nn.Conv2d(inter_channels,
out_channels,
kernel_size=3,
stride=1,
padding=1)
self.norm2 = build_norm_layer(
out_channels, norm_layer, 'channels_first', 'channels_first'
)
def forward(self, x):
x = self.conv1(x)
x = self.norm1(x)
x = self.act(x)
x = self.conv2(x)
x = self.norm2(x)
return x
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