Update.

[mygptrnn.git] / fridge

diff --git a/fridge b/fridge
index d09e92d..143092c 100644 (file)
--- a/fridge
+++ b/fridge
@@ -292,3 +292,46 @@ class Calibrator:
         # A = har / (har + 1)
         # G = G / har
 
+
+######################################################################
+
+2024 Jan 18 08:46:18 (from mygpt.py)
+
+        # warnings.warn("softmax gating", RuntimeWarning)
+
+        # G = (
+        # torch.einsum("ntc,hrc->nhrt", X, self.w_G) + self.b_G[None, :, :, None]
+        # ).softmax(dim=2)
+
+######################################################################
+
+2024 Jan 21 16:55:24 (from main.py)
+
+        with open("test.dat", "a") as f:
+            for m filter(lambda m: isinstance(m,mygpt.Catenn.Linear),model.modules()):
+                for p in m.parameters() ]
+
+
+        for m in model.modules():
+            if isinstance(m, mygpt.Caterpillar):
+                
+
+
+######################################################################
+
+2024 Feb 13 22:53:52 (from mygpt.py)
+
+        ######################################################################
+        # Prepare the keys
+
+        k_star = self.k_star[:, None, :].expand(-1, t1 - t0, -1)
+
+        warnings.warn("rotating key barrel", RuntimeWarning)
+        k_star = self.k_star[:, None, :].expand(-1, x_q.size(1), -1)
+        t_barrel = torch.arange(t0, t1, device=k_star.device)
+        t_barrel = t_barrel[None, :].expand(k_star.size(0), t1 - t0)
+        l_barrel = (
+            torch.arange(k_star.size(0), device=k_star.device)[:, None] + t_barrel
+        ) % k_star.size(0)
+        k_star = k_star[l_barrel, t_barrel]
+