Update baseline.sh
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		| @@ -113,7 +113,7 @@ class SuperAttention(SuperModule): | ||||
|             .permute(0, 2, 1, 3) | ||||
|         ) | ||||
|         attn_v1 = (q_v1 @ k_v1.transpose(-2, -1)) * math.sqrt(head_dim) | ||||
|         attn_v1 = attn_v1.softmax(dim=-1) | ||||
|         attn_v1 = attn_v1.softmax(dim=-1)  # B * #head * N * N | ||||
|         attn_v1 = self.attn_drop(attn_v1) | ||||
|         feats_v1 = (attn_v1 @ v_v1).permute(0, 2, 1, 3).reshape(B, N, -1) | ||||
|         if C == head_dim * num_head: | ||||
|   | ||||
| @@ -16,11 +16,10 @@ fi | ||||
| gpu=$1 | ||||
| market=$2 | ||||
|  | ||||
| algorithms="NAIVE-V1 NAIVE-V2 MLP GRU LSTM ALSTM XGBoost LightGBM SFM TabNet DoubleE" | ||||
| # algorithms="NAIVE-V1 NAIVE-V2 MLP GRU LSTM ALSTM XGBoost LightGBM SFM TabNet DoubleE" | ||||
| algorithms="MLP GRU LSTM ALSTM XGBoost LightGBM SFM TabNet DoubleE" | ||||
|  | ||||
| for alg in ${algorithms} | ||||
| do | ||||
|  | ||||
|   python exps/trading/baselines.py --alg ${alg} --gpu ${gpu} --market ${market} | ||||
|  | ||||
| done | ||||
|   | ||||
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