From 781ea8c9c11c2a0954bb2b80ddfdd1a018b33fe0 Mon Sep 17 00:00:00 2001
From: hzwer <598460606@163.com>
Date: Sun, 7 Mar 2021 01:00:24 +0800
Subject: [PATCH] Fix super parameters

---
 model/RIFE.py      | 2 +-
 model/RIFE15C.py   | 2 +-
 model/RIFE2F.py    | 2 +-
 model/RIFE2F15C.py | 2 +-
 train.py           | 2 +-
 5 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/model/RIFE.py b/model/RIFE.py
index 7dfa60f..0a9094f 100644
--- a/model/RIFE.py
+++ b/model/RIFE.py
@@ -110,7 +110,7 @@ class Model:
         self.optimG = AdamW(itertools.chain(
             self.flownet.parameters(),
             self.contextnet.parameters(),
-            self.fusionnet.parameters()), lr=1e-6, weight_decay=1e-5)
+            self.fusionnet.parameters()), lr=1e-6, weight_decay=1e-4)
         self.schedulerG = optim.lr_scheduler.CyclicLR(
             self.optimG, base_lr=1e-6, max_lr=1e-3, step_size_up=8000, cycle_momentum=False)
         self.epe = EPE()
diff --git a/model/RIFE15C.py b/model/RIFE15C.py
index 02ac33e..aaee0b4 100644
--- a/model/RIFE15C.py
+++ b/model/RIFE15C.py
@@ -110,7 +110,7 @@ class Model:
         self.optimG = AdamW(itertools.chain(
             self.flownet.parameters(),
             self.contextnet.parameters(),
-            self.fusionnet.parameters()), lr=1e-6, weight_decay=1e-5)
+            self.fusionnet.parameters()), lr=1e-6, weight_decay=1e-4)
         self.schedulerG = optim.lr_scheduler.CyclicLR(
             self.optimG, base_lr=1e-6, max_lr=1e-3, step_size_up=8000, cycle_momentum=False)
         self.epe = EPE()
diff --git a/model/RIFE2F.py b/model/RIFE2F.py
index 4a4b382..7e368bb 100644
--- a/model/RIFE2F.py
+++ b/model/RIFE2F.py
@@ -110,7 +110,7 @@ class Model:
         self.optimG = AdamW(itertools.chain(
             self.flownet.parameters(),
             self.contextnet.parameters(),
-            self.fusionnet.parameters()), lr=1e-6, weight_decay=1e-5)
+            self.fusionnet.parameters()), lr=1e-6, weight_decay=1e-4)
         self.schedulerG = optim.lr_scheduler.CyclicLR(
             self.optimG, base_lr=1e-6, max_lr=1e-3, step_size_up=8000, cycle_momentum=False)
         self.epe = EPE()
diff --git a/model/RIFE2F15C.py b/model/RIFE2F15C.py
index d59c557..d75a448 100644
--- a/model/RIFE2F15C.py
+++ b/model/RIFE2F15C.py
@@ -110,7 +110,7 @@ class Model:
         self.optimG = AdamW(itertools.chain(
             self.flownet.parameters(),
             self.contextnet.parameters(),
-            self.fusionnet.parameters()), lr=1e-6, weight_decay=1e-5)
+            self.fusionnet.parameters()), lr=1e-6, weight_decay=1e-4)
         self.schedulerG = optim.lr_scheduler.CyclicLR(
             self.optimG, base_lr=1e-6, max_lr=1e-3, step_size_up=8000, cycle_momentum=False)
         self.epe = EPE()
diff --git a/train.py b/train.py
index 00080b6..002dddd 100644
--- a/train.py
+++ b/train.py
@@ -19,7 +19,7 @@ def get_learning_rate(step):
         mul = step / 2000.
     else:
         mul = np.cos((step - 2000) / (args.epoch * args.step_per_epoch - 2000.) * math.pi) * 0.5 + 0.5
-    return  5e-4 * mul
+    return 3e-4 * mul
 
 def flow2rgb(flow_map_np):
     h, w, _ = flow_map_np.shape