25 lines
1020 B
Python
25 lines
1020 B
Python
import torch.nn as nn
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class SISUGenerator(nn.Module):
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def __init__(self): # No noise_dim parameter
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super(SISUGenerator, self).__init__()
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self.model = nn.Sequential(
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nn.Conv1d(2, 64, kernel_size=7, stride=1, padding=3), # Input 2 channels (low-quality audio)
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nn.LeakyReLU(0.2),
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nn.Conv1d(64, 64, kernel_size=7, stride=1, padding=3),
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nn.LeakyReLU(0.2),
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nn.Conv1d(64, 128, kernel_size=5, stride=2, padding=2),
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nn.LeakyReLU(0.2),
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nn.Conv1d(128, 128, kernel_size=5, stride=1, padding=2),
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nn.LeakyReLU(0.2),
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nn.ConvTranspose1d(128, 64, kernel_size=4, stride=2, padding=1),
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nn.LeakyReLU(0.2),
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nn.Conv1d(64, 64, kernel_size=3, stride=1, padding=1),
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nn.LeakyReLU(0.2),
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nn.Conv1d(64, 2, kernel_size=3, stride=1, padding=1), # Output 2 channels (high-quality audio)
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nn.Tanh()
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)
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def forward(self, x):
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return self.model(x)
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