Upload modeling_bilstm.py

model_folder/modeling_bilstm.py

@@ -0,0 +1,24 @@
+import torch.nn as nn
+import torch
+
+class BiLSTM(nn.Module):
+    def __init__(self, embedding_matrix, embed_size, num_labels, hidden_size=64, dropout=0.3):
+        super(BiLSTM, self).__init__()
+        self.embedding = nn.Embedding.from_pretrained(
+            torch.tensor(embedding_matrix, dtype=torch.float32), freeze=True)
+        self.lstm = nn.LSTM(embed_size, hidden_size, bidirectional=True, batch_first=True)
+        self.fc = nn.Sequential(
+            nn.Linear(hidden_size * 4, 128),
+            nn.ReLU(),
+            nn.Dropout(dropout),
+            nn.Linear(128, num_labels)
+        )
+
+    def forward(self, x):
+        x = self.embedding(x)
+        h_lstm, _ = self.lstm(x)
+        avg_pool = torch.mean(h_lstm, 1)
+        max_pool, _ = torch.max(h_lstm, 1)
+        x = torch.cat((avg_pool, max_pool), dim=1)
+        x = self.fc(x)
+        return x