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@ -24,19 +24,10 @@ class E2EVadModel(nn.Module):
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raise "unsupported encoder"
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def forward(self, feats: torch.Tensor,
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in_cache0: torch.Tensor,
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in_cache1: torch.Tensor,
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in_cache2: torch.Tensor,
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in_cache3: torch.Tensor,
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):
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def forward(self, feats: torch.Tensor, *args, ):
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scores, (cache0, cache1, cache2, cache3) = self.encoder(feats,
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in_cache0,
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in_cache1,
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in_cache2,
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in_cache3) # return B * T * D
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return scores, cache0, cache1, cache2, cache3
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scores, out_caches = self.encoder(feats, *args)
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return scores, out_caches
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def get_dummy_inputs(self, frame=30):
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speech = torch.randn(1, frame, self.feats_dim)
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