From a2caa736fc91958eba07fd6a4c1c4864bcca8ffc Mon Sep 17 00:00:00 2001
From: Slava <slava.medvedev@gmail.com>
Date: Thu, 2 Mar 2023 22:02:00 +0000
Subject: [PATCH] #8 Proper use of `lr` parameter

Use `lr` parameter provided to `train_simple_network(...)` when creating an optimizer
---
 idlmam.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/idlmam.py b/idlmam.py
index ed8685e..64cc772 100644
--- a/idlmam.py
+++ b/idlmam.py
@@ -120,7 +120,7 @@ def train_simple_network(model, loss_func, train_loader, test_loader=None, score
         results[item] = []
         
     #SGD is Stochastic Gradient Decent.
-    optimizer = torch.optim.SGD(model.parameters(), lr=0.001)
+    optimizer = torch.optim.SGD(model.parameters(), lr=lr)
     #Place the model on the correct compute resource (CPU or GPU)
     model.to(device)
     for epoch in tqdm(range(epochs), desc="Epoch"):