October 2024
Beginner to intermediate
340 pages
7h 38m
Korean
Content preview from 밑바닥부터 시작하는 딥러닝 5
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256
밑바닥부터 시작하는 딥러닝 5
self
.
time
_
embed
_
dim
=
time
_
embed
_
dim
self
.
down1
=
ConvBlock(in
_
ch, 64, time
_
embed
_
dim)
self
.
down2
=
ConvBlock(64, 128, time
_
embed
_
dim)
self
.
bot1
=
ConvBlock(128, 256, time
_
embed
_
dim)
self
.
up2
=
ConvBlock(128
+
256, 128, time
_
embed
_
dim)
self
.
up1
=
ConvBlock(128
+
64, 64, time
_
embed
_
dim)
self
.
out
=
nn
.
Conv2d(64, in
_
ch, 1)
self
.
maxpool
=
nn
.
MaxPool2d(2)
self
.
upsample
=
nn
.
Upsample(scale
_
factor
=
2, mode
=
'bilinear')
def forward(self, x, timesteps):
#
사인파
위치
인코딩
v
=
pos
_
encoding(timesteps, self
.
time
_
embed
_
dim, x
.
device)
x1
=
self
.
down1(x, v) #
신경망에
v
도
입력
x
=
self
.
maxpool(x1)
x2
=
self
.
down2(x, v)
x
=
self
.
maxpool(x2)
x
=
self
.