From b75b004fe62826455f1aa77e849e7da13902cb17 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 16 Jul 2023 23:13:55 +0300
Subject: lora extension rework to include other types of networks

---
 extensions-builtin/Lora/lyco_helpers.py | 15 +++++++++++++++
 1 file changed, 15 insertions(+)
 create mode 100644 extensions-builtin/Lora/lyco_helpers.py

(limited to 'extensions-builtin/Lora/lyco_helpers.py')

diff --git a/extensions-builtin/Lora/lyco_helpers.py b/extensions-builtin/Lora/lyco_helpers.py
new file mode 100644
index 00000000..9ea499fb
--- /dev/null
+++ b/extensions-builtin/Lora/lyco_helpers.py
@@ -0,0 +1,15 @@
+import torch
+
+
+def make_weight_cp(t, wa, wb):
+    temp = torch.einsum('i j k l, j r -> i r k l', t, wb)
+    return torch.einsum('i j k l, i r -> r j k l', temp, wa)
+
+
+def rebuild_conventional(up, down, shape, dyn_dim=None):
+    up = up.reshape(up.size(0), -1)
+    down = down.reshape(down.size(0), -1)
+    if dyn_dim is not None:
+        up = up[:, :dyn_dim]
+        down = down[:dyn_dim, :]
+    return (up @ down).reshape(shape)
-- 
cgit v1.2.3


From 238adeaffb037dedbcefe41e7fd4814a1f17baa2 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Mon, 17 Jul 2023 09:00:47 +0300
Subject: support specifying te and unet weights separately update lora code
 support full module

---
 extensions-builtin/Lora/lyco_helpers.py | 6 ++++++
 1 file changed, 6 insertions(+)

(limited to 'extensions-builtin/Lora/lyco_helpers.py')

diff --git a/extensions-builtin/Lora/lyco_helpers.py b/extensions-builtin/Lora/lyco_helpers.py
index 9ea499fb..279b34bc 100644
--- a/extensions-builtin/Lora/lyco_helpers.py
+++ b/extensions-builtin/Lora/lyco_helpers.py
@@ -13,3 +13,9 @@ def rebuild_conventional(up, down, shape, dyn_dim=None):
         up = up[:, :dyn_dim]
         down = down[:dyn_dim, :]
     return (up @ down).reshape(shape)
+
+
+def rebuild_cp_decomposition(up, down, mid):
+    up = up.reshape(up.size(0), -1)
+    down = down.reshape(down.size(0), -1)
+    return torch.einsum('n m k l, i n, m j -> i j k l', mid, up, down)
-- 
cgit v1.2.3