start implementation

src/mLSTM.py

@@ -0,0 +1,33 @@
+import torch
+import torch.nn as nn
+
+torch.manual_seed(42)
+
+
+class mLSTM(nn.Module):
+    def __init__(self, n_embed):
+        super().__init__()
+        self.n_embeb = n_embed
+
+        # Query
+        self.W_q = nn.Linear(n_embed, n_embed)
+        # Key
+        self.W_k = nn.Linear(n_embed, n_embed)
+        # Value
+        self.W_v = nn.Linear(n_embed, n_embed)
+        # Forget
+        self.W_f = nn.Linear(n_embed, n_embed)
+        # Input
+        self.W_i = nn.Linear(n_embed, n_embed)
+        # Output projection
+        self.output_projection = nn.Linear(n_embed, n_embed)
+
+    def forward(self, x):
+        batch_size, seq_len, _ = x.size()
+
+        q = self.W_q(x)
+        k = self.W_k(x)
+        v = self.W_q(x)
+
+        f = torch.sigmoid(self.W_f(x))
+        i = torch.exp(self.W_i(x))