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⚗️ | Experimenting with very small model.

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NikkeDoy
2025-02-10 12:44:42 +02:00
parent 0790a0d3da
commit fb7b624c87
3 changed files with 9 additions and 10 deletions
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9
discriminator.py
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@ -13,7 +13,7 @@ def discriminator_block(in_channels, out_channels, kernel_size=3, stride=1, dila
class SISUDiscriminator(nn.Module):
def __init__(self):
super(SISUDiscriminator, self).__init__()
layers = 32 # Increased base layer count
layers = 4 # Increased base layer count
self.model = nn.Sequential(
# Initial Convolution
discriminator_block(1, layers, kernel_size=7, stride=2, dilation=1), # Downsample
@ -21,10 +21,9 @@ class SISUDiscriminator(nn.Module):
# Core Discriminator Blocks with varied kernels and dilations
discriminator_block(layers, layers * 2, kernel_size=5, stride=2, dilation=1), # Downsample
discriminator_block(layers * 2, layers * 4, kernel_size=5, dilation=4),
discriminator_block(layers * 4, layers * 8, kernel_size=5, dilation=16),
discriminator_block(layers * 8, layers * 4, kernel_size=3, dilation=8),
discriminator_block(layers * 4, layers * 2, kernel_size=3, dilation=2),
discriminator_block(layers * 2, layers, kernel_size=5, dilation=1),
discriminator_block(layers * 4, layers * 4, kernel_size=5, dilation=16),
discriminator_block(layers * 4, layers * 2, kernel_size=3, dilation=8),
discriminator_block(layers * 2, layers, kernel_size=3, dilation=1),
# Final Convolution
discriminator_block(layers, 1, kernel_size=3, stride=1),
)