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Another fix

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This commit is contained in:
James Betker 2022-07-18 17:09:13 -06:00
parent 83a4ef4149
commit cf57c352c8
1 changed files with 5 additions and 4 deletions
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9
codes/models/audio/music/transformer_diffusion13.py
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@ -190,7 +190,7 @@ class TransformerDiffusion(nn.Module):
s_prior = x_prior[:,:,start:start+self.max_window] s_prior = x_prior[:,:,start:start+self.max_window]
s_prior = F.interpolate(s_prior, scale_factor=.25, mode='linear', align_corners=True) s_prior = F.interpolate(s_prior, scale_factor=.25, mode='linear', align_corners=True)
s_prior = F.interpolate(s_prior, size=(s.shape[-1],), mode='linear', align_corners=True) s_prior = F.interpolate(s_prior, size=(s.shape[-1],), mode='linear', align_corners=True)
self.preprocessed = (s_prior, resolution) self.preprocessed = (s_prior, torch.tensor([resolution] * x.shape[0], dtype=torch.long, device=x.device))
return s return s
def forward(self, x, timesteps, x_prior=None, resolution=None, conditioning_input=None, conditioning_free=False): def forward(self, x, timesteps, x_prior=None, resolution=None, conditioning_input=None, conditioning_free=False):
@ -249,13 +249,14 @@ def register_transformer_diffusion13(opt_net, opt):
def test_tfd(): def test_tfd():
clip = torch.randn(2,256,2583) clip = torch.randn(2,256,10336)
cond = torch.randn(2,256,2583) cond = torch.randn(2,256,10336)
ts = torch.LongTensor([600, 600]) ts = torch.LongTensor([600, 600])
model = TransformerDiffusion(in_channels=256, model_channels=1024, contraction_dim=512, model = TransformerDiffusion(in_channels=256, model_channels=1024, contraction_dim=512,
num_heads=512//64, input_vec_dim=256, num_layers=12, dropout=.1) num_heads=512//64, input_vec_dim=256, num_layers=12, dropout=.1)
for k in range(100): for k in range(100):
model(clip, ts, clip, conditioning_input=cond) x = model.input_to_random_resolution_and_window(clip, x_prior=clip)
model(x, ts, clip)
if __name__ == '__main__': if __name__ == '__main__':