Condition on full signal
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@ -121,7 +121,8 @@ class DiffusionVocoderWithRef(nn.Module):
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self.conditioning_enabled = conditioning_inputs_provided
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if conditioning_inputs_provided:
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self.contextual_embedder = AudioMiniEncoder(conditioning_input_dim, time_embed_dim)
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self.contextual_embedder = AudioMiniEncoder(in_channels, time_embed_dim, base_channels=32, depth=6, resnet_blocks=1,
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attn_blocks=2, num_attn_heads=2, dropout=dropout, downsample_factor=4, kernel_size=5)
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self.input_blocks = nn.ModuleList(
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[
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@ -329,7 +330,7 @@ if __name__ == '__main__':
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clip = torch.randn(2, 1, 40960)
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#spec = torch.randint(8192, (2, 40,))
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spec = torch.randn(2,512,160)
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cond = torch.randn(2, 80, 173)
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cond = torch.randn(2, 1, 40960)
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ts = torch.LongTensor([555, 556])
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model = DiffusionVocoderWithRef(32, conditioning_inputs_provided=True, time_embed_dim_multiplier=8)
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print(model(clip, ts, spec, cond).shape)
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