diff --git a/configs/fastscnn/fast_scnn_4x3_1000e_cityscapes.py b/configs/fastscnn/fast_scnn_4x3_1000e_cityscapes.py
index 6e6010e73..7583cb6f2 100644
--- a/configs/fastscnn/fast_scnn_4x3_1000e_cityscapes.py
+++ b/configs/fastscnn/fast_scnn_4x3_1000e_cityscapes.py
@@ -54,8 +54,9 @@ lr_config = dict(
     by_epoch=False,
 )
 # runtime settings
-# total_epochs = 1000
-total_iters = 247000
+total_epochs = 247000
 evaluation = dict(interval=1000, metric='mIoU')
 checkpoint_config = dict(interval=1000)
 
+# log config: log by iter.
+log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)])
diff --git a/configs/fastscnn/fast_scnn_4x3_450k_lr0.08_cityscapes.py b/configs/fastscnn/fast_scnn_4x3_450k_lr0.08_cityscapes.py
new file mode 100644
index 000000000..f562f0d76
--- /dev/null
+++ b/configs/fastscnn/fast_scnn_4x3_450k_lr0.08_cityscapes.py
@@ -0,0 +1,64 @@
+_base_ = [
+    '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py',
+    '../_base_/default_runtime.py'
+]
+crop_size = (512, 1024)
+cudnn_benchmark = True
+# model training and testing settings
+train_cfg = dict()
+test_cfg = dict(mode='whole')
+
+# Here: What is parameter 'with_seg'?
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+train_pipeline = [
+    dict(type='LoadImageFromFile', to_float32=True),
+    dict(type='LoadAnnotations'),   # with_seg=True
+    dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='PhotoMetricDistortion'),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='RandomCrop', crop_size=crop_size),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_semantic_seg']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(2048, 1024),
+        # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img']),
+        ])
+]
+data = dict(
+    samples_per_gpu=3,
+    workers_per_gpu=3,
+    train=dict(pipeline=train_pipeline),
+    val=dict(pipeline=test_pipeline),
+    test=dict(pipeline=test_pipeline))
+
+# optimizer
+optimizer = dict(type='SGD', lr=0.08, momentum=0.9, weight_decay=4e-5)
+optimizer_config = dict()
+# learning policy
+lr_config = dict(
+    policy='poly',
+    power=0.9,
+    by_epoch=False,
+)
+# runtime settings
+# total_epochs = 1000
+total_iters = 450000
+evaluation = dict(interval=2000, metric='mIoU')
+checkpoint_config = dict(interval=2000)
+
+# log config: log by iter.
+log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)])
+
diff --git a/configs/fastscnn/fast_scnn_4x8_100k_lr0.045_power1.2_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_100k_lr0.045_power1.2_cityscapes.py
new file mode 100644
index 000000000..078fa94c5
--- /dev/null
+++ b/configs/fastscnn/fast_scnn_4x8_100k_lr0.045_power1.2_cityscapes.py
@@ -0,0 +1,64 @@
+_base_ = [
+    '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py',
+    '../_base_/default_runtime.py'
+]
+crop_size = (512, 1024)
+cudnn_benchmark = True
+# model training and testing settings
+train_cfg = dict()
+test_cfg = dict(mode='whole')
+
+# Here: What is parameter 'with_seg'?
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+train_pipeline = [
+    dict(type='LoadImageFromFile', to_float32=True),
+    dict(type='LoadAnnotations'),   # with_seg=True
+    dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='PhotoMetricDistortion'),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='RandomCrop', crop_size=crop_size),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_semantic_seg']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(2048, 1024),
+        # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img']),
+        ])
+]
+data = dict(
+    samples_per_gpu=8,
+    workers_per_gpu=4,
+    train=dict(pipeline=train_pipeline),
+    val=dict(pipeline=test_pipeline),
+    test=dict(pipeline=test_pipeline))
+
+# optimizer
+optimizer = dict(type='SGD', lr=0.045, momentum=0.9, weight_decay=4e-5)
+optimizer_config = dict()
+# learning policy
+lr_config = dict(
+    policy='poly',
+    power=1.2,
+    by_epoch=False,
+)
+# runtime settings
+# total_epochs = 1000
+total_iters = 100000
+evaluation = dict(interval=2000, metric='mIoU')
+checkpoint_config = dict(interval=2000)
+
+# log config: log by iter.
+log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)])
+
diff --git a/configs/fastscnn/fast_scnn_4x8_100k_lr0.08_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_100k_lr0.08_cityscapes.py
new file mode 100644
index 000000000..10f56e093
--- /dev/null
+++ b/configs/fastscnn/fast_scnn_4x8_100k_lr0.08_cityscapes.py
@@ -0,0 +1,64 @@
+_base_ = [
+    '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py',
+    '../_base_/default_runtime.py'
+]
+crop_size = (512, 1024)
+cudnn_benchmark = True
+# model training and testing settings
+train_cfg = dict()
+test_cfg = dict(mode='whole')
+
+# Here: What is parameter 'with_seg'?
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+train_pipeline = [
+    dict(type='LoadImageFromFile', to_float32=True),
+    dict(type='LoadAnnotations'),   # with_seg=True
+    dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='PhotoMetricDistortion'),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='RandomCrop', crop_size=crop_size),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_semantic_seg']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(2048, 1024),
+        # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img']),
+        ])
+]
+data = dict(
+    samples_per_gpu=8,
+    workers_per_gpu=4,
+    train=dict(pipeline=train_pipeline),
+    val=dict(pipeline=test_pipeline),
+    test=dict(pipeline=test_pipeline))
+
+# optimizer
+optimizer = dict(type='SGD', lr=0.08, momentum=0.9, weight_decay=4e-5)
+optimizer_config = dict()
+# learning policy
+lr_config = dict(
+    policy='poly',
+    power=0.9,
+    by_epoch=False,
+)
+# runtime settings
+# total_epochs = 1000
+total_iters = 100000
+evaluation = dict(interval=2000, metric='mIoU')
+checkpoint_config = dict(interval=2000)
+
+# log config: log by iter.
+log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)])
+
diff --git a/configs/fastscnn/fast_scnn_4x8_100k_lr0.12_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_100k_lr0.12_cityscapes.py
new file mode 100644
index 000000000..9ff49a9db
--- /dev/null
+++ b/configs/fastscnn/fast_scnn_4x8_100k_lr0.12_cityscapes.py
@@ -0,0 +1,64 @@
+_base_ = [
+    '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py',
+    '../_base_/default_runtime.py'
+]
+crop_size = (512, 1024)
+cudnn_benchmark = True
+# model training and testing settings
+train_cfg = dict()
+test_cfg = dict(mode='whole')
+
+# Here: What is parameter 'with_seg'?
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+train_pipeline = [
+    dict(type='LoadImageFromFile', to_float32=True),
+    dict(type='LoadAnnotations'),   # with_seg=True
+    dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='PhotoMetricDistortion'),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='RandomCrop', crop_size=crop_size),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_semantic_seg']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(2048, 1024),
+        # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img']),
+        ])
+]
+data = dict(
+    samples_per_gpu=8,
+    workers_per_gpu=4,
+    train=dict(pipeline=train_pipeline),
+    val=dict(pipeline=test_pipeline),
+    test=dict(pipeline=test_pipeline))
+
+# optimizer
+optimizer = dict(type='SGD', lr=0.12, momentum=0.9, weight_decay=4e-5)
+optimizer_config = dict()
+# learning policy
+lr_config = dict(
+    policy='poly',
+    power=0.9,
+    by_epoch=False,
+)
+# runtime settings
+# total_epochs = 1000
+total_iters = 100000
+evaluation = dict(interval=2000, metric='mIoU')
+checkpoint_config = dict(interval=2000)
+
+# log config: log by iter.
+log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)])
+
diff --git a/configs/fastscnn/fast_scnn_4x8_80k_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_80k_cityscapes.py
index 51d2d61eb..dd6ac7f15 100644
--- a/configs/fastscnn/fast_scnn_4x8_80k_cityscapes.py
+++ b/configs/fastscnn/fast_scnn_4x8_80k_cityscapes.py
@@ -55,7 +55,7 @@ lr_config = dict(
 )
 # runtime settings
 # total_epochs = 1000
-total_iters = 80000
-evaluation = dict(interval=8000, metric='mIoU')
-checkpoint_config = dict(interval=8000)
+total_iters = 100000
+evaluation = dict(interval=2000, metric='mIoU')
+checkpoint_config = dict(interval=2000)
 
diff --git a/configs/fastscnn/fast_scnn_4x8_80k_lr0.045_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_80k_lr0.045_cityscapes.py
new file mode 100644
index 000000000..f6fd1729e
--- /dev/null
+++ b/configs/fastscnn/fast_scnn_4x8_80k_lr0.045_cityscapes.py
@@ -0,0 +1,64 @@
+_base_ = [
+    '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py',
+    '../_base_/default_runtime.py'
+]
+crop_size = (512, 1024)
+cudnn_benchmark = True
+# model training and testing settings
+train_cfg = dict()
+test_cfg = dict(mode='whole')
+
+# Here: What is parameter 'with_seg'?
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+train_pipeline = [
+    dict(type='LoadImageFromFile', to_float32=True),
+    dict(type='LoadAnnotations'),   # with_seg=True
+    dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='PhotoMetricDistortion'),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='RandomCrop', crop_size=crop_size),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_semantic_seg']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(2048, 1024),
+        # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img']),
+        ])
+]
+data = dict(
+    samples_per_gpu=8,
+    workers_per_gpu=4,
+    train=dict(pipeline=train_pipeline),
+    val=dict(pipeline=test_pipeline),
+    test=dict(pipeline=test_pipeline))
+
+# optimizer
+optimizer = dict(type='SGD', lr=0.045, momentum=0.9, weight_decay=4e-5)
+optimizer_config = dict()
+# learning policy
+lr_config = dict(
+    policy='poly',
+    power=0.9,
+    by_epoch=False,
+)
+# runtime settings
+# total_epochs = 1000
+total_iters = 100000
+evaluation = dict(interval=2000, metric='mIoU')
+checkpoint_config = dict(interval=2000)
+
+# log config: log by iter.
+log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)])
+
diff --git a/configs/fastscnn/fast_scnn_4x8_80k_lr0.08_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_80k_lr0.08_cityscapes.py
new file mode 100644
index 000000000..aec2ea0a2
--- /dev/null
+++ b/configs/fastscnn/fast_scnn_4x8_80k_lr0.08_cityscapes.py
@@ -0,0 +1,64 @@
+_base_ = [
+    '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py',
+    '../_base_/default_runtime.py'
+]
+crop_size = (512, 1024)
+cudnn_benchmark = True
+# model training and testing settings
+train_cfg = dict()
+test_cfg = dict(mode='whole')
+
+# Here: What is parameter 'with_seg'?
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+train_pipeline = [
+    dict(type='LoadImageFromFile', to_float32=True),
+    dict(type='LoadAnnotations'),   # with_seg=True
+    dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='PhotoMetricDistortion'),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='RandomCrop', crop_size=crop_size),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_semantic_seg']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(2048, 1024),
+        # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img']),
+        ])
+]
+data = dict(
+    samples_per_gpu=8,
+    workers_per_gpu=4,
+    train=dict(pipeline=train_pipeline),
+    val=dict(pipeline=test_pipeline),
+    test=dict(pipeline=test_pipeline))
+
+# optimizer
+optimizer = dict(type='SGD', lr=0.08, momentum=0.9, weight_decay=4e-5)
+optimizer_config = dict()
+# learning policy
+lr_config = dict(
+    policy='poly',
+    power=0.9,
+    by_epoch=False,
+)
+# runtime settings
+# total_epochs = 1000
+total_iters = 80000
+evaluation = dict(interval=2000, metric='mIoU')
+checkpoint_config = dict(interval=2000)
+
+# log config: log by iter.
+log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)])
+
diff --git a/configs/fastscnn/fast_scnn_4x8_80k_lr0.12_cityscapes.py b/configs/fastscnn/fast_scnn_4x8_80k_lr0.12_cityscapes.py
new file mode 100644
index 000000000..cf6075f12
--- /dev/null
+++ b/configs/fastscnn/fast_scnn_4x8_80k_lr0.12_cityscapes.py
@@ -0,0 +1,64 @@
+_base_ = [
+    '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py',
+    '../_base_/default_runtime.py'
+]
+crop_size = (512, 1024)
+cudnn_benchmark = True
+# model training and testing settings
+train_cfg = dict()
+test_cfg = dict(mode='whole')
+
+# Here: What is parameter 'with_seg'?
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+train_pipeline = [
+    dict(type='LoadImageFromFile', to_float32=True),
+    dict(type='LoadAnnotations'),   # with_seg=True
+    dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='PhotoMetricDistortion'),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='RandomCrop', crop_size=crop_size),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_semantic_seg']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(2048, 1024),
+        # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img']),
+        ])
+]
+data = dict(
+    samples_per_gpu=8,
+    workers_per_gpu=4,
+    train=dict(pipeline=train_pipeline),
+    val=dict(pipeline=test_pipeline),
+    test=dict(pipeline=test_pipeline))
+
+# optimizer
+optimizer = dict(type='SGD', lr=0.12, momentum=0.9, weight_decay=4e-5)
+optimizer_config = dict()
+# learning policy
+lr_config = dict(
+    policy='poly',
+    power=0.9,
+    by_epoch=False,
+)
+# runtime settings
+# total_epochs = 1000
+total_iters = 80000
+evaluation = dict(interval=2000, metric='mIoU')
+checkpoint_config = dict(interval=2000)
+
+# log config: log by iter.
+log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)])
+