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fix TRA when use single head

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Dong Zhou
2021-07-22 19:10:17 +08:00
committed by you-n-g
parent 319a2f38cc
commit 4f9f978909
1 changed files with 2 additions and 2 deletions
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4
qlib/contrib/model/pytorch_tra.py
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@@ -526,7 +526,7 @@ class RNN(nn.Module):
if self.use_attn: if self.use_attn:
laten = self.W(rnn_out).tanh() laten = self.W(rnn_out).tanh()
scores = self.u(laten).softmax(dim=1) scores = self.u(laten).softmax(dim=1)
att_out = (rnn_out * scores).sum(dim=1).squeeze() att_out = (rnn_out * scores).sum(dim=1)
last_out = torch.cat([last_out, att_out], dim=1) last_out = torch.cat([last_out, att_out], dim=1)
return last_out return last_out
@@ -648,7 +648,7 @@ class TRA(nn.Module):
preds = self.predictors(hidden) preds = self.predictors(hidden)
if self.num_states == 1: # no need for router when having only one prediction if self.num_states == 1: # no need for router when having only one prediction
return preds.squeeze(-1), preds, None return preds, None, None
if "TPE" in self.src_info: if "TPE" in self.src_info:
out = self.router(hist_loss)[0][:, -1] # TPE out = self.router(hist_loss)[0][:, -1] # TPE