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[Feature] Support Evaluation Hook of Translation Models #127

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merged 6 commits into from
Oct 15, 2021
Merged

[Feature] Support Evaluation Hook of Translation Models #127

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abf251a
support translation evaluation during training
Sep 28, 2021
432850b
fix lint
Sep 28, 2021
ce6e4eb
fix priority for eval hook
Sep 29, 2021
d069a05
solve conflict
Oct 14, 2021
d515286
fix pr and add evaluation to configs
Oct 14, 2021
bf86279
solve conflict
Oct 14, 2021
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18 changes: 16 additions & 2 deletions configs/cyclegan/cyclegan_lsgan_id0_resnet_in_1x1_250k_summer2winter.py
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Expand Up @@ -136,10 +136,24 @@
exp_name = 'cyclegan_summer2winter_id0'
work_dir = f'./work_dirs/experiments/{exp_name}'
# testA: 309, testB:238
num_images = 238
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When would you change the file name to follow the convention of MMGEN?

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I will rename them and reorganize configs in #118 .

metrics = dict(
FID=dict(type='FID', num_images=238, image_shape=(3, 256, 256)),
FID=dict(type='FID', num_images=num_images, image_shape=(3, 256, 256)),
IS=dict(
type='IS',
num_images=238,
num_images=num_images,
image_shape=(3, 256, 256),
inception_args=dict(type='pytorch')))

evaluation = dict(
type='TranslationEvalHook',
target_domain=domain_b,
interval=10000,
metrics=[
dict(type='FID', num_images=num_images, bgr2rgb=True),
dict(
type='IS',
num_images=num_images,
inception_args=dict(type='pytorch'))
],
best_metric=['fid', 'is'])
18 changes: 16 additions & 2 deletions configs/cyclegan/cyclegan_lsgan_id0_resnet_in_1x1_270k_horse2zebra.py
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Expand Up @@ -135,10 +135,24 @@
workflow = [('train', 1)]
exp_name = 'cyclegan_horse2zebra_id0'
work_dir = f'./work_dirs/experiments/{exp_name}'
num_images = 140
metrics = dict(
FID=dict(type='FID', num_images=140, image_shape=(3, 256, 256)),
FID=dict(type='FID', num_images=num_images, image_shape=(3, 256, 256)),
IS=dict(
type='IS',
num_images=140,
num_images=num_images,
image_shape=(3, 256, 256),
inception_args=dict(type='pytorch')))

evaluation = dict(
type='TranslationEvalHook',
target_domain=domain_b,
interval=10000,
metrics=[
dict(type='FID', num_images=num_images, bgr2rgb=True),
dict(
type='IS',
num_images=num_images,
inception_args=dict(type='pytorch'))
],
best_metric=['fid', 'is'])
18 changes: 16 additions & 2 deletions configs/cyclegan/cyclegan_lsgan_id0_resnet_in_1x1_80k_facades.py
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Expand Up @@ -138,10 +138,24 @@
workflow = [('train', 1)]
exp_name = 'cyclegan_facades_id0'
work_dir = f'./work_dirs/experiments/{exp_name}'
num_images = 106
metrics = dict(
FID=dict(type='FID', num_images=106, image_shape=(3, 256, 256)),
FID=dict(type='FID', num_images=num_images, image_shape=(3, 256, 256)),
IS=dict(
type='IS',
num_images=106,
num_images=num_images,
image_shape=(3, 256, 256),
inception_args=dict(type='pytorch')))

evaluation = dict(
type='TranslationEvalHook',
target_domain=domain_b,
interval=10000,
metrics=[
dict(type='FID', num_images=num_images, bgr2rgb=True),
dict(
type='IS',
num_images=num_images,
inception_args=dict(type='pytorch'))
],
best_metric=['fid', 'is'])
18 changes: 16 additions & 2 deletions configs/cyclegan/cyclegan_lsgan_resnet_in_1x1_250k_summer2winter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -151,10 +151,24 @@
exp_name = 'cyclegan_summer2winter'
work_dir = f'./work_dirs/experiments/{exp_name}'
# testA: 309, testB:238
num_images = 238
metrics = dict(
FID=dict(type='FID', num_images=238, image_shape=(3, 256, 256)),
FID=dict(type='FID', num_images=num_images, image_shape=(3, 256, 256)),
IS=dict(
type='IS',
num_images=238,
num_images=num_images,
image_shape=(3, 256, 256),
inception_args=dict(type='pytorch')))

evaluation = dict(
type='TranslationEvalHook',
target_domain=domain_b,
interval=10000,
metrics=[
dict(type='FID', num_images=num_images, bgr2rgb=True),
dict(
type='IS',
num_images=num_images,
inception_args=dict(type='pytorch'))
],
best_metric=['fid', 'is'])
20 changes: 16 additions & 4 deletions configs/cyclegan/cyclegan_lsgan_resnet_in_1x1_270k_horse2zebra.py
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Expand Up @@ -79,7 +79,6 @@
keys=[f'img_{domain_a}', f'img_{domain_b}'],
meta_keys=[f'img_{domain_a}_path', f'img_{domain_b}_path'])
]

test_pipeline = [
dict(
type='LoadImageFromFile',
Expand Down Expand Up @@ -109,7 +108,6 @@
keys=[f'img_{domain_a}', f'img_{domain_b}'],
meta_keys=[f'img_{domain_a}_path', f'img_{domain_b}_path'])
]

data = dict(
train=dict(
dataroot=dataroot,
Expand Down Expand Up @@ -151,10 +149,24 @@
exp_name = 'cyclegan_horse2zebra'
work_dir = f'./work_dirs/experiments/{exp_name}'
# testA 120, testB 140
num_images = 140
metrics = dict(
FID=dict(type='FID', num_images=140, image_shape=(3, 256, 256)),
FID=dict(type='FID', num_images=num_images, image_shape=(3, 256, 256)),
IS=dict(
type='IS',
num_images=140,
num_images=num_images,
image_shape=(3, 256, 256),
inception_args=dict(type='pytorch')))

evaluation = dict(
type='TranslationEvalHook',
target_domain=domain_b,
interval=10000,
metrics=[
dict(type='FID', num_images=num_images, bgr2rgb=True),
dict(
type='IS',
num_images=num_images,
inception_args=dict(type='pytorch'))
],
best_metric=['fid', 'is'])
18 changes: 16 additions & 2 deletions configs/cyclegan/cyclegan_lsgan_resnet_in_1x1_80k_facades.py
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Original file line number Diff line number Diff line change
Expand Up @@ -153,10 +153,24 @@
workflow = [('train', 1)]
exp_name = 'cyclegan_facades'
work_dir = f'./work_dirs/experiments/{exp_name}'
num_images = 106
metrics = dict(
FID=dict(type='FID', num_images=106, image_shape=(3, 256, 256)),
FID=dict(type='FID', num_images=num_images, image_shape=(3, 256, 256)),
IS=dict(
type='IS',
num_images=106,
num_images=num_images,
image_shape=(3, 256, 256),
inception_args=dict(type='pytorch')))

evaluation = dict(
type='TranslationEvalHook',
target_domain=domain_b,
interval=10000,
metrics=[
dict(type='FID', num_images=num_images, bgr2rgb=True),
dict(
type='IS',
num_images=num_images,
inception_args=dict(type='pytorch'))
],
best_metric=['fid', 'is'])
20 changes: 17 additions & 3 deletions configs/pix2pix/pix2pix_vanilla_unet_bn_1x1_220k_aerial2maps.py
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Expand Up @@ -79,7 +79,7 @@
dataroot = 'data/paired/maps'
data = dict(
train=dict(dataroot=dataroot, pipeline=train_pipeline),
val=dict(dataroot=dataroot, pipeline=test_pipeline),
val=dict(dataroot=dataroot, pipeline=test_pipeline, testdir='val'),
test=dict(dataroot=dataroot, pipeline=test_pipeline, testdir='val'))

# optimizer
Expand Down Expand Up @@ -107,10 +107,24 @@
workflow = [('train', 1)]
exp_name = 'pix2pix_aerial2map'
work_dir = f'./work_dirs/experiments/{exp_name}'
num_images = 1098
metrics = dict(
FID=dict(type='FID', num_images=1098, image_shape=(3, 256, 256)),
FID=dict(type='FID', num_images=num_images, image_shape=(3, 256, 256)),
IS=dict(
type='IS',
num_images=1098,
num_images=num_images,
image_shape=(3, 256, 256),
inception_args=dict(type='pytorch')))

evaluation = dict(
type='TranslationEvalHook',
target_domain=domain_b,
interval=10000,
metrics=[
dict(type='FID', num_images=num_images, bgr2rgb=True),
dict(
type='IS',
num_images=num_images,
inception_args=dict(type='pytorch'))
],
best_metric=['fid', 'is'])
20 changes: 17 additions & 3 deletions configs/pix2pix/pix2pix_vanilla_unet_bn_1x1_220k_maps2aerial.py
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Expand Up @@ -79,7 +79,7 @@
dataroot = 'data/paired/maps'
data = dict(
train=dict(dataroot=dataroot, pipeline=train_pipeline),
val=dict(dataroot=dataroot, pipeline=test_pipeline),
val=dict(dataroot=dataroot, pipeline=test_pipeline, testdir='val'),
test=dict(dataroot=dataroot, pipeline=test_pipeline, testdir='val'))
# optimizer
optimizer = dict(
Expand All @@ -106,10 +106,24 @@
workflow = [('train', 1)]
exp_name = 'pix2pix_maps2aerial'
work_dir = f'./work_dirs/experiments/{exp_name}'
num_images = 1098
metrics = dict(
FID=dict(type='FID', num_images=1098, image_shape=(3, 256, 256)),
FID=dict(type='FID', num_images=num_images, image_shape=(3, 256, 256)),
IS=dict(
type='IS',
num_images=1098,
num_images=num_images,
image_shape=(3, 256, 256),
inception_args=dict(type='pytorch')))

evaluation = dict(
type='TranslationEvalHook',
target_domain=domain_b,
interval=10000,
metrics=[
dict(type='FID', num_images=num_images, bgr2rgb=True),
dict(
type='IS',
num_images=num_images,
inception_args=dict(type='pytorch'))
],
best_metric=['fid', 'is'])
18 changes: 16 additions & 2 deletions configs/pix2pix/pix2pix_vanilla_unet_bn_1x1_80k_facades.py
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Original file line number Diff line number Diff line change
Expand Up @@ -107,10 +107,24 @@
workflow = [('train', 1)]
exp_name = 'pix2pix_facades'
work_dir = f'./work_dirs/experiments/{exp_name}'
num_images = 106
metrics = dict(
FID=dict(type='FID', num_images=106, image_shape=(3, 256, 256)),
FID=dict(type='FID', num_images=num_images, image_shape=(3, 256, 256)),
IS=dict(
type='IS',
num_images=106,
num_images=num_images,
image_shape=(3, 256, 256),
inception_args=dict(type='pytorch')))

evaluation = dict(
type='TranslationEvalHook',
target_domain=domain_b,
interval=10000,
metrics=[
dict(type='FID', num_images=num_images, bgr2rgb=True),
dict(
type='IS',
num_images=num_images,
inception_args=dict(type='pytorch'))
],
best_metric=['fid', 'is'])
21 changes: 17 additions & 4 deletions configs/pix2pix/pix2pix_vanilla_unet_bn_wo_jitter_flip_1x4_190k_edges2shoes.py
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Expand Up @@ -78,7 +78,7 @@
dataroot = 'data/paired/edges2shoes'
data = dict(
train=dict(dataroot=dataroot, pipeline=train_pipeline),
val=dict(dataroot=dataroot, pipeline=test_pipeline),
val=dict(dataroot=dataroot, pipeline=test_pipeline, testdir='val'),
test=dict(dataroot=dataroot, pipeline=test_pipeline, testdir='val'))

# optimizer
Expand Down Expand Up @@ -106,11 +106,24 @@
workflow = [('train', 1)]
exp_name = 'pix2pix_edges2shoes_wo_jitter_flip'
work_dir = f'./work_dirs/experiments/{exp_name}'
num_images = 200
metrics = dict(
FID=dict(
type='FID', num_images=200, image_shape=(3, 256, 256), bgr2rgb=True),
FID=dict(type='FID', num_images=num_images, image_shape=(3, 256, 256)),
IS=dict(
type='IS',
num_images=200,
num_images=num_images,
image_shape=(3, 256, 256),
inception_args=dict(type='pytorch')))

evaluation = dict(
type='TranslationEvalHook',
target_domain=domain_b,
interval=10000,
metrics=[
dict(type='FID', num_images=num_images, bgr2rgb=True),
dict(
type='IS',
num_images=num_images,
inception_args=dict(type='pytorch'))
],
best_metric=['fid', 'is'])
2 changes: 1 addition & 1 deletion mmgen/apis/train.py
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Expand Up @@ -172,9 +172,9 @@ def train_model(model,
val_dataloader = build_dataloader(
val_dataset, dist=distributed, **val_loader_cfg)
eval_cfg = deepcopy(cfg.get('evaluation'))
priority = eval_cfg.pop('priority', 'LOW')
eval_cfg.update(dict(dist=distributed, dataloader=val_dataloader))
eval_hook = build_from_cfg(eval_cfg, HOOKS)
priority = eval_cfg.pop('priority', 'NORMAL')
runner.register_hook(eval_hook, priority=priority)

# user-defined hooks
Expand Down
19 changes: 5 additions & 14 deletions mmgen/core/evaluation/__init__.py
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@@ -1,23 +1,14 @@
# Copyright (c) OpenMMLab. All rights reserved.
from .eval_hooks import GenerativeEvalHook
from .eval_hooks import GenerativeEvalHook, TranslationEvalHook
from .evaluation import (make_metrics_table, make_vanilla_dataloader,
single_gpu_evaluation, single_gpu_online_evaluation)
from .metric_utils import slerp
from .metrics import (IS, MS_SSIM, PR, SWD, GaussianKLD, ms_ssim,
sliced_wasserstein)

__all__ = [
'MS_SSIM',
'SWD',
'ms_ssim',
'sliced_wasserstein',
'single_gpu_evaluation',
'single_gpu_online_evaluation',
'PR',
'IS',
'slerp',
'GenerativeEvalHook',
'make_metrics_table',
'make_vanilla_dataloader',
'GaussianKLD',
'MS_SSIM', 'SWD', 'ms_ssim', 'sliced_wasserstein', 'single_gpu_evaluation',
'single_gpu_online_evaluation', 'PR', 'IS', 'slerp', 'GenerativeEvalHook',
'make_metrics_table', 'make_vanilla_dataloader', 'GaussianKLD',
'TranslationEvalHook'
]
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