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Migrate backtest logic from NT (#1263)

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* Backtest migration

* Minor bug fix in test

* Reorganize file to avoid loop import

* Fix test SAOE bug

* Remove unnecessary names

* Resolve PR comments; remove private classes;

* Fix CI error

* Resolve PR comments

* Refactor data interfaces

* Remove convert_instance_config and change config

* Pylint issue

* Pylint issue

* Fix tempfile warning

* Resolve PR comments

* Add more comments
This commit is contained in:
Huoran Li
2022-09-19 14:54:26 +08:00
committed by GitHub
parent e762548295
commit bee05f56ef
19 changed files with 794 additions and 118 deletions
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21
qlib/rl/order_execution/network.py
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@@ -117,3 +117,24 @@ class Recurrent(nn.Module):
out = torch.cat(sources, -1)
return self.fc(out)
class Attention(nn.Module):
def __init__(self, in_dim, out_dim):
super().__init__()
self.q_net = nn.Linear(in_dim, out_dim)
self.k_net = nn.Linear(in_dim, out_dim)
self.v_net = nn.Linear(in_dim, out_dim)
def forward(self, Q, K, V):
q = self.q_net(Q)
k = self.k_net(K)
v = self.v_net(V)
attn = torch.einsum("ijk,ilk->ijl", q, k)
attn = attn.to(Q.device)
attn_prob = torch.softmax(attn, dim=-1)
attn_vec = torch.einsum("ijk,ikl->ijl", attn_prob, v)
return attn_vec