From 7e53439b52dc3f0d930b1f2d641862820cb41bcc Mon Sep 17 00:00:00 2001
From: liyinhao <liyinhao@sensetime.com>
Date: Sat, 19 Sep 2020 23:19:40 +0800
Subject: [PATCH] Change cyclic_20e

---
 configs/_base_/schedules/cyclic_20e.py        |  2 +-
 ...1voxel_second_secfpn_4x8_cyclic_20e_nus.py | 25 -------------------
 ...pillar_second_secfpn_4x8_cyclic_20e_nus.py | 24 ------------------
 3 files changed, 1 insertion(+), 50 deletions(-)

diff --git a/configs/_base_/schedules/cyclic_20e.py b/configs/_base_/schedules/cyclic_20e.py
index aa5d83927b..c7df532525 100644
--- a/configs/_base_/schedules/cyclic_20e.py
+++ b/configs/_base_/schedules/cyclic_20e.py
@@ -1,6 +1,6 @@
 # For nuScenes dataset, we usually evaluate the model at the end of training.
 # Since the models are trained by 24 epochs by default, we set evaluation
-# interval to be 24. Please change the interval accordingly if you do not
+# interval to be 20. Please change the interval accordingly if you do not
 # use a default schedule.
 # optimizer
 # This schedule is mainly used by models on nuScenes dataset
diff --git a/configs/centerpoint/centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py b/configs/centerpoint/centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py
index 23af6ecdf2..8a714f2630 100644
--- a/configs/centerpoint/centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py
+++ b/configs/centerpoint/centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py
@@ -142,28 +142,3 @@
             box_type_3d='LiDAR')),
     val=dict(pipeline=test_pipeline, classes=class_names),
     test=dict(pipeline=test_pipeline, classes=class_names))
-
-# For nuScenes dataset, we usually evaluate the model at the end of training.
-# Since the models are trained by 24 epochs by default, we set evaluation
-# interval to be 24. Please change the interval accordingly if you do not
-# use a default schedule.
-# optimizer
-# This schedule is mainly used by models on nuScenes dataset
-optimizer = dict(type='AdamW', lr=1e-4, weight_decay=0.01)
-# max_norm=10 is better for SECOND
-optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2))
-lr_config = dict(
-    policy='cyclic',
-    target_ratio=(10, 1e-4),
-    cyclic_times=1,
-    step_ratio_up=0.4,
-)
-momentum_config = dict(
-    policy='cyclic',
-    target_ratio=(0.85 / 0.95, 1),
-    cyclic_times=1,
-    step_ratio_up=0.4,
-)
-
-# runtime settings
-total_epochs = 20
diff --git a/configs/centerpoint/centerpoint_02pillar_second_secfpn_4x8_cyclic_20e_nus.py b/configs/centerpoint/centerpoint_02pillar_second_secfpn_4x8_cyclic_20e_nus.py
index b62e35ac48..e71210906a 100644
--- a/configs/centerpoint/centerpoint_02pillar_second_secfpn_4x8_cyclic_20e_nus.py
+++ b/configs/centerpoint/centerpoint_02pillar_second_secfpn_4x8_cyclic_20e_nus.py
@@ -141,27 +141,3 @@
             box_type_3d='LiDAR')),
     val=dict(pipeline=test_pipeline, classes=class_names),
     test=dict(pipeline=test_pipeline, classes=class_names))
-
-# For nuScenes dataset, we usually evaluate the model at the end of training.
-# Since the models are trained by 24 epochs by default, we set evaluation
-# interval to be 24. Please change the interval accordingly if you do not
-# use a default schedule.
-
-optimizer = dict(type='AdamW', lr=1e-4, weight_decay=0.01)
-# max_norm=10 is better for SECOND
-optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2))
-lr_config = dict(
-    policy='cyclic',
-    target_ratio=(10, 1e-4),
-    cyclic_times=1,
-    step_ratio_up=0.4,
-)
-momentum_config = dict(
-    policy='cyclic',
-    target_ratio=(0.85 / 0.95, 1),
-    cyclic_times=1,
-    step_ratio_up=0.4,
-)
-
-# runtime settings
-total_epochs = 20