mirror of
https://github.com/storytold/torchscript-models.git
synced 2026-10-18 07:33:20 +00:00
Brandon Thomas
72dd12b460
I copied this from my old and messy `tacotron-melgan` repo, where I had previously experimented with running the two models in a pipeline. I'll be moving over all the JIT pieces here and cleaning up when I can.
30 lines
800 B
Python
30 lines
800 B
Python
import torch
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import torch.nn as nn
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import torch.nn.functional as F
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from .discriminator import Discriminator
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from .identity import Identity
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class MultiScaleDiscriminator(nn.Module):
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def __init__(self):
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super(MultiScaleDiscriminator, self).__init__()
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self.discriminators = nn.ModuleList(
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[Discriminator() for _ in range(3)]
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)
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self.pooling = nn.ModuleList(
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[Identity()] +
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[nn.AvgPool1d(kernel_size=4, stride=2, padding=1, count_include_pad=False) for _ in range(1, 3)]
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)
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def forward(self, x):
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ret = list()
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for pool, disc in zip(self.pooling, self.discriminators):
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x = pool(x)
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ret.append(disc(x))
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return ret # [(feat, score), (feat, score), (feat, score)]
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