def __init__(self,
in_channels,
classes,
data_format="channels_last",
**kwargs):
super(Head, self).__init__(**kwargs)
self.conv1 = dwsconv3x3_block(
in_channels=in_channels,
out_channels=in_channels,
data_format=data_format,
name="conv1")
self.conv2 = dwsconv3x3_block(
in_channels=in_channels,
out_channels=in_channels,
data_format=data_format,
name="conv2")
self.dropout = nn.Dropout(
rate=0.1,
name="dropout")
self.conv3 = conv1x1(
in_channels=in_channels,
out_channels=classes,
use_bias=True,
data_format=data_format,
name="conv3")
def __init__(self,
in_channels,
channels,
data_format="channels_last",
**kwargs):
super(Stem, self).__init__(**kwargs)
assert (len(channels) == 3)
self.conv1 = conv3x3_block(
in_channels=in_channels,
out_channels=channels[0],
strides=2,
padding=0,
data_format=data_format,
name="conv1")
self.conv2 = dwsconv3x3_block(
in_channels=channels[0],
out_channels=channels[1],
strides=2,
data_format=data_format,
name="conv2")
self.conv3 = dwsconv3x3_block(
in_channels=channels[1],
out_channels=channels[2],
strides=2,
data_format=data_format,
name="conv3")
def __init__(self, in_channels, classes):
super(Head, self).__init__()
with self.name_scope():
self.dsconv1 = dwsconv3x3_block(in_channels=in_channels,
out_channels=in_channels)
self.dsconv2 = dwsconv3x3_block(in_channels=in_channels,
out_channels=in_channels)
self.dp = nn.Dropout(0.1)
self.conv = conv1x1(in_channels=in_channels,
out_channels=classes,
use_bias=True)
def __init__(self, in_channels, channels):
super(Steam, self).__init__()
assert (len(channels) == 3)
with self.name_scope():
self.conv = conv3x3_block(in_channels=in_channels,
out_channels=channels[0],
strides=2,
padding=0)
self.conv2 = dwsconv3x3_block(in_channels=channels[0],
out_channels=channels[1],
strides=2)
self.conv3 = dwsconv3x3_block(in_channels=channels[1],
out_channels=channels[2],
strides=2)