Canberk Baykal
app.py
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import numpy as np
from torch import nn
from torch.nn import Conv2d, Module
from models.stylegan2.model import EqualLinear
class GradualStyleBlock(Module):
def __init__(self, in_c, out_c, spatial):
super(GradualStyleBlock, self).__init__()
self.out_c = out_c
self.spatial = spatial
num_pools = int(np.log2(spatial))
modules = []
modules += [Conv2d(in_c, out_c, kernel_size=3, stride=2, padding=1),
nn.LeakyReLU()]
for i in range(num_pools - 1):
modules += [
Conv2d(out_c, out_c, kernel_size=3, stride=2, padding=1),
nn.LeakyReLU()
]
self.convs = nn.Sequential(*modules)
self.linear = EqualLinear(out_c, out_c, lr_mul=1)
def forward(self, x):
x = self.convs(x)
x = x.view(-1, self.out_c)
x = self.linear(x)
return x