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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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8
generator.py
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@@ -10,7 +10,7 @@ def conv_block(in_channels, out_channels, kernel_size=3, dilation=1):
class SISUGenerator(nn.Module):
def __init__(self):
super(SISUGenerator, self).__init__()
layer = 32 # Increased base layer count
layer = 4 # Increased base layer count
self.conv1 = nn.Sequential(
nn.Conv1d(1, layer, kernel_size=7, padding=3),
nn.BatchNorm1d(layer),
@@ -18,9 +18,9 @@ class SISUGenerator(nn.Module):
)
self.conv_blocks = nn.Sequential(
conv_block(layer, layer, kernel_size=3, dilation=1), # Local details
conv_block(layer, layer*4, kernel_size=5, dilation=2), # Local Context
conv_block(layer*4, layer*4, kernel_size=3, dilation=16), # Longer range dependencies
conv_block(layer*4, layer*2, kernel_size=5, dilation=8), # Wider context
conv_block(layer, layer*2, kernel_size=5, dilation=2), # Local Context
conv_block(layer*2, layer*2, kernel_size=3, dilation=16), # Longer range dependencies
conv_block(layer*2, layer*2, kernel_size=5, dilation=8), # Wider context
conv_block(layer*2, layer, kernel_size=5, dilation=2), # Local Context
conv_block(layer, layer, kernel_size=3, dilation=1), # Local details
)