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Running
on
Zero
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"""
Ported from Paella
"""
import torch
from torch import nn
from diffusers.configuration_utils import ConfigMixin, register_to_config
from diffusers.models.modeling_utils import ModelMixin
# Discriminator model ported from Paella https://github.com/dome272/Paella/blob/main/src_distributed/vqgan.py
class Discriminator(ModelMixin, ConfigMixin):
@register_to_config
def __init__(self, in_channels=3, cond_channels=0, hidden_channels=512, depth=6):
super().__init__()
d = max(depth - 3, 3)
layers = [
nn.utils.spectral_norm(
nn.Conv2d(in_channels, hidden_channels // (2**d), kernel_size=3, stride=2, padding=1)
),
nn.LeakyReLU(0.2),
]
for i in range(depth - 1):
c_in = hidden_channels // (2 ** max((d - i), 0))
c_out = hidden_channels // (2 ** max((d - 1 - i), 0))
layers.append(nn.utils.spectral_norm(nn.Conv2d(c_in, c_out, kernel_size=3, stride=2, padding=1)))
layers.append(nn.InstanceNorm2d(c_out))
layers.append(nn.LeakyReLU(0.2))
self.encoder = nn.Sequential(*layers)
self.shuffle = nn.Conv2d(
(hidden_channels + cond_channels) if cond_channels > 0 else hidden_channels, 1, kernel_size=1
)
self.logits = nn.Sigmoid()
def forward(self, x, cond=None):
x = self.encoder(x)
if cond is not None:
cond = cond.view(
cond.size(0),
cond.size(1),
1,
1,
).expand(-1, -1, x.size(-2), x.size(-1))
x = torch.cat([x, cond], dim=1)
x = self.shuffle(x)
x = self.logits(x)
return x
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