From 7e5ea0eee45299c40f8516f6c21798ca01aeb989 Mon Sep 17 00:00:00 2001
From: "anass.al-ammiri" <51008418+RandomAnass@users.noreply.github.com>
Date: Thu, 14 Aug 2025 01:27:15 +0200
Subject: [PATCH] Fix RationalHat layer UnboundLocalError

Fixes issue where RationalHat layer initialization used undefined variable LVinit
instead of LRinit, causing UnboundLocalError: local variable 'LVinit' referenced
before assignment.

- Changed line 161: LVinit([1]) -> LRinit([1])
- Verified fix works with test case
- Resolves GitHub issue #4
---
 perslay/perslay.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/perslay/perslay.py b/perslay/perslay.py
index 520164b3..acae4048 100644
--- a/perslay/perslay.py
+++ b/perslay/perslay.py
@@ -158,7 +158,7 @@ def __init__(self, name, diagdim, perslay_parameters, rho):
             elif layer == "RationalHat":
                 LMinit, LRinit = plp["lmean_init"], plp["lr_init"]
                 LMiv = LMinit if not callable(LMinit) else LMinit([self.diagdim, plp["lnum"]])
-                LRiv = LRinit if not callable(LRinit) else LVinit([1])
+                LRiv = LRinit if not callable(LRinit) else LRinit([1])  # Fixed: was LVinit([1]) causing UnboundLocalError
                 LM = tf.Variable(name=Lname+"-M", initial_value=LMiv, trainable=Ltrain)
                 LR = tf.Variable(name=Lname+"-R", initial_value=LRiv, trainable=Ltrain)
                 self.vars[nf].append([LM, LR])