From 711a16ba576319930ec59488c604f61afd532d5a Mon Sep 17 00:00:00 2001
From: AlexeyAB84 <alexeyab84@gmail.com>
Date: Tue, 9 Aug 2022 07:48:28 +0300
Subject: [PATCH] Added param loss_ota for hyp.yaml, to disable OTA for faster
training
---
data/hyp.scratch.custom.yaml | 3 ++-
data/hyp.scratch.p5.yaml | 3 ++-
data/hyp.scratch.p6.yaml | 3 ++-
data/hyp.scratch.tiny.yaml | 3 ++-
train.py | 5 ++++-
5 files changed, 12 insertions(+), 5 deletions(-)
diff --git a/data/hyp.scratch.custom.yaml b/data/hyp.scratch.custom.yaml
index 92b50d3..8570d73 100644
--- a/data/hyp.scratch.custom.yaml
+++ b/data/hyp.scratch.custom.yaml
@@ -27,4 +27,5 @@ fliplr: 0.5 # image flip left-right (probability)
mosaic: 1.0 # image mosaic (probability)
mixup: 0.0 # image mixup (probability)
copy_paste: 0.0 # image copy paste (probability)
-paste_in: 0.0 # image copy paste (probability)
+paste_in: 0.0 # image copy paste (probability), use 0 for faster training
+loss_ota: 1 # use ComputeLossOTA, use 0 for faster training
\ No newline at end of file
diff --git a/data/hyp.scratch.p5.yaml b/data/hyp.scratch.p5.yaml
index a64c404..a409bac 100644
--- a/data/hyp.scratch.p5.yaml
+++ b/data/hyp.scratch.p5.yaml
@@ -27,4 +27,5 @@ fliplr: 0.5 # image flip left-right (probability)
mosaic: 1.0 # image mosaic (probability)
mixup: 0.15 # image mixup (probability)
copy_paste: 0.0 # image copy paste (probability)
-paste_in: 0.15 # image copy paste (probability)
+paste_in: 0.15 # image copy paste (probability), use 0 for faster training
+loss_ota: 1 # use ComputeLossOTA, use 0 for faster training
\ No newline at end of file
diff --git a/data/hyp.scratch.p6.yaml b/data/hyp.scratch.p6.yaml
index 6ab7c01..192d0d5 100644
--- a/data/hyp.scratch.p6.yaml
+++ b/data/hyp.scratch.p6.yaml
@@ -27,4 +27,5 @@ fliplr: 0.5 # image flip left-right (probability)
mosaic: 1.0 # image mosaic (probability)
mixup: 0.15 # image mixup (probability)
copy_paste: 0.0 # image copy paste (probability)
-paste_in: 0.15 # image copy paste (probability)
+paste_in: 0.15 # image copy paste (probability), use 0 for faster training
+loss_ota: 1 # use ComputeLossOTA, use 0 for faster training
\ No newline at end of file
diff --git a/data/hyp.scratch.tiny.yaml b/data/hyp.scratch.tiny.yaml
index 01c6f49..b0dc14a 100644
--- a/data/hyp.scratch.tiny.yaml
+++ b/data/hyp.scratch.tiny.yaml
@@ -27,4 +27,5 @@ fliplr: 0.5 # image flip left-right (probability)
mosaic: 1.0 # image mosaic (probability)
mixup: 0.05 # image mixup (probability)
copy_paste: 0.0 # image copy paste (probability)
-paste_in: 0.05 # image copy paste (probability)
+paste_in: 0.05 # image copy paste (probability), use 0 for faster training
+loss_ota: 1 # use ComputeLossOTA, use 0 for faster training
diff --git a/train.py b/train.py
index c6db018..2864636 100644
--- a/train.py
+++ b/train.py
@@ -359,7 +359,10 @@ def train(hyp, opt, device, tb_writer=None):
# Forward
with amp.autocast(enabled=cuda):
pred = model(imgs) # forward
- loss, loss_items = compute_loss_ota(pred, targets.to(device), imgs) # loss scaled by batch_size
+ if hyp['loss_ota'] == 1:
+ loss, loss_items = compute_loss_ota(pred, targets.to(device), imgs) # loss scaled by batch_size
+ else:
+ loss, loss_items = compute_loss(pred, targets.to(device)) # loss scaled by batch_size
if rank != -1:
loss *= opt.world_size # gradient averaged between devices in DDP mode
if opt.quad: