From a07a063306f24fb0f4d59af19da4b33326cf3286 Mon Sep 17 00:00:00 2001
From: Mashiro <57566630+HAOCHENYE@users.noreply.github.com>
Date: Mon, 8 Aug 2022 20:34:16 +0800
Subject: [PATCH] [Enhance] Add build function for scheduler. (#372)
* add build function for scheduler
* add unit test
add unit test
* handle convert_to_iter in build_scheduler_from_cfg
* restore deleted code
* format import
* fix lint
---
mmengine/registry/__init__.py | 5 +-
mmengine/registry/build_functions.py | 82 +++++++-
mmengine/registry/root.py | 6 +-
mmengine/runner/runner.py | 28 +--
tests/test_registry/test_build_functions.py | 213 ++++++++++++++++++++
tests/test_registry/test_registry.py | 184 +----------------
tests/test_runner/test_runner.py | 5 -
7 files changed, 305 insertions(+), 218 deletions(-)
create mode 100644 tests/test_registry/test_build_functions.py
diff --git a/mmengine/registry/__init__.py b/mmengine/registry/__init__.py
index 8be89e69..1e1de6bf 100644
--- a/mmengine/registry/__init__.py
+++ b/mmengine/registry/__init__.py
@@ -1,6 +1,6 @@
# Copyright (c) OpenMMLab. All rights reserved.
from .build_functions import (build_from_cfg, build_model_from_cfg,
- build_runner_from_cfg)
+ build_runner_from_cfg, build_scheduler_from_cfg)
from .default_scope import DefaultScope
from .registry import Registry
from .root import (DATA_SAMPLERS, DATASETS, EVALUATOR, HOOKS, LOG_PROCESSORS,
@@ -17,5 +17,6 @@ __all__ = [
'PARAM_SCHEDULERS', 'METRICS', 'MODEL_WRAPPERS', 'OPTIM_WRAPPERS', 'LOOPS',
'VISBACKENDS', 'VISUALIZERS', 'LOG_PROCESSORS', 'EVALUATOR',
'DefaultScope', 'traverse_registry_tree', 'count_registered_modules',
- 'build_model_from_cfg', 'build_runner_from_cfg', 'build_from_cfg'
+ 'build_model_from_cfg', 'build_runner_from_cfg', 'build_from_cfg',
+ 'build_scheduler_from_cfg'
]
diff --git a/mmengine/registry/build_functions.py b/mmengine/registry/build_functions.py
index 0f4dbb96..78348086 100644
--- a/mmengine/registry/build_functions.py
+++ b/mmengine/registry/build_functions.py
@@ -1,12 +1,18 @@
# Copyright (c) OpenMMLab. All rights reserved.
import inspect
import logging
-from typing import Any, Optional, Union
+from typing import TYPE_CHECKING, Any, Optional, Union
+
+import torch.nn as nn
from ..config import Config, ConfigDict
from ..utils import ManagerMixin
from .registry import Registry
+if TYPE_CHECKING:
+ from ..optim.scheduler import _ParamScheduler
+ from ..runner import Runner
+
def build_from_cfg(
cfg: Union[dict, ConfigDict, Config],
@@ -131,7 +137,7 @@ def build_from_cfg(
def build_runner_from_cfg(cfg: Union[dict, ConfigDict, Config],
- registry: Registry) -> Any:
+ registry: Registry) -> 'Runner':
"""Build a Runner object.
Examples:
>>> from mmengine.registry import Registry, build_runner_from_cfg
@@ -203,7 +209,11 @@ def build_runner_from_cfg(cfg: Union[dict, ConfigDict, Config],
f'{cls_location}.py: {e}')
-def build_model_from_cfg(cfg, registry, default_args=None):
+def build_model_from_cfg(
+ cfg: Union[dict, ConfigDict, Config],
+ registry: Registry,
+ default_args: Optional[Union[dict, ConfigDict, Config]] = None) -> \
+ nn.Module:
"""Build a PyTorch model from config dict(s). Different from
``build_from_cfg``, if cfg is a list, a ``nn.Sequential`` will be built.
@@ -226,3 +236,69 @@ def build_model_from_cfg(cfg, registry, default_args=None):
return Sequential(*modules)
else:
return build_from_cfg(cfg, registry, default_args)
+
+
+def build_scheduler_from_cfg(
+ cfg: Union[dict, ConfigDict, Config],
+ registry: Registry,
+ default_args: Optional[Union[dict, ConfigDict, Config]] = None) -> \
+ '_ParamScheduler':
+ """Builds a ``ParamScheduler`` instance from config.
+
+ ``ParamScheduler`` supports building instance by its constructor or
+ method ``build_iter_from_epoch``. Therefore, its registry needs a build
+ function to handle both cases.
+
+ Args:
+ cfg (dict or ConfigDict or Config): Config dictionary. If it contains
+ the key ``convert_to_iter_based``, instance will be built by method
+ ``convert_to_iter_based``, otherwise instance will be built by its
+ constructor.
+ registry (:obj:`Registry`): The ``PARAM_SCHEDULERS`` registry.
+ default_args (dict or ConfigDict or Config, optional): Default
+ initialization arguments. It must contain key ``optimizer``. If
+ ``convert_to_iter_based`` is defined in ``cfg``, it must
+ additionally contain key ``epoch_length``. Defaults to None.
+
+ Returns:
+ object: The constructed ``ParamScheduler``.
+ """
+ assert isinstance(
+ cfg,
+ (dict, ConfigDict, Config
+ )), f'cfg should be a dict, ConfigDict or Config, but got {type(cfg)}'
+ assert isinstance(
+ registry, Registry), ('registry should be a mmengine.Registry object',
+ f'but got {type(registry)}')
+
+ args = cfg.copy()
+ if default_args is not None:
+ for name, value in default_args.items():
+ args.setdefault(name, value)
+ scope = args.pop('_scope_', None)
+ with registry.switch_scope_and_registry(scope) as registry:
+ convert_to_iter = args.pop('convert_to_iter_based', False)
+ if convert_to_iter:
+ scheduler_type = args.pop('type')
+ assert 'epoch_length' in args and args.get('by_epoch', True), (
+ 'Only epoch-based parameter scheduler can be converted to '
+ 'iter-based, and `epoch_length` should be set')
+ if isinstance(scheduler_type, str):
+ scheduler_cls = registry.get(scheduler_type)
+ if scheduler_cls is None:
+ raise KeyError(
+ f'{scheduler_type} is not in the {registry.name} '
+ 'registry. Please check whether the value of '
+ f'`{scheduler_type}` is correct or it was registered '
+ 'as expected. More details can be found at https://mmengine.readthedocs.io/en/latest/tutorials/config.html#import-custom-python-modules' # noqa: E501
+ )
+ elif inspect.isclass(scheduler_type):
+ scheduler_cls = scheduler_type
+ else:
+ raise TypeError('type must be a str or valid type, but got '
+ f'{type(scheduler_type)}')
+ return scheduler_cls.build_iter_from_epoch( # type: ignore
+ **args)
+ else:
+ args.pop('epoch_length', None)
+ return build_from_cfg(args, registry)
diff --git a/mmengine/registry/root.py b/mmengine/registry/root.py
index a63686f9..838465b4 100644
--- a/mmengine/registry/root.py
+++ b/mmengine/registry/root.py
@@ -6,7 +6,8 @@ More datails can be found at
https://mmengine.readthedocs.io/en/latest/tutorials/registry.html.
"""
-from mmengine.registry import build_model_from_cfg, build_runner_from_cfg
+from .build_functions import (build_model_from_cfg, build_runner_from_cfg,
+ build_scheduler_from_cfg)
from .registry import Registry
# manage all kinds of runners like `EpochBasedRunner` and `IterBasedRunner`
@@ -37,7 +38,8 @@ OPTIM_WRAPPERS = Registry('optim_wrapper')
# manage constructors that customize the optimization hyperparameters.
OPTIM_WRAPPER_CONSTRUCTORS = Registry('optimizer wrapper constructor')
# mangage all kinds of parameter schedulers like `MultiStepLR`
-PARAM_SCHEDULERS = Registry('parameter scheduler')
+PARAM_SCHEDULERS = Registry(
+ 'parameter scheduler', build_func=build_scheduler_from_cfg)
# manage all kinds of metrics
METRICS = Registry('metric')
diff --git a/mmengine/runner/runner.py b/mmengine/runner/runner.py
index 3e416842..b7b2f8ef 100644
--- a/mmengine/runner/runner.py
+++ b/mmengine/runner/runner.py
@@ -1134,34 +1134,16 @@ class Runner:
f'The `end` of {_scheduler["type"]} is not set. '
'Use the max epochs/iters of train loop as default.')
- convert_to_iter = _scheduler.pop('convert_to_iter_based',
- False)
- if convert_to_iter:
- assert _scheduler.get(
- 'by_epoch',
- True), ('only epoch-based parameter scheduler can be '
- 'converted to iter-based')
- assert isinstance(self._train_loop, BaseLoop), \
- 'Scheduler can only be converted to iter-based ' \
- 'when train loop is built.'
- cls = PARAM_SCHEDULERS.get(_scheduler.pop('type'))
- param_schedulers.append(
- cls.build_iter_from_epoch( # type: ignore
+ param_schedulers.append(
+ PARAM_SCHEDULERS.build(
+ _scheduler,
+ default_args=dict(
optimizer=optim_wrapper,
- **_scheduler,
- epoch_length=len(
- self.train_dataloader), # type: ignore
- ))
- else:
- param_schedulers.append(
- PARAM_SCHEDULERS.build(
- _scheduler,
- default_args=dict(optimizer=optim_wrapper)))
+ epoch_length=len(self.train_dataloader))))
else:
raise TypeError(
'scheduler should be a _ParamScheduler object or dict, '
f'but got {scheduler}')
-
return param_schedulers
def build_param_scheduler(
diff --git a/tests/test_registry/test_build_functions.py b/tests/test_registry/test_build_functions.py
new file mode 100644
index 00000000..618f99e3
--- /dev/null
+++ b/tests/test_registry/test_build_functions.py
@@ -0,0 +1,213 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+import pytest
+import torch.nn as nn
+from torch.optim import SGD
+
+from mmengine import (PARAM_SCHEDULERS, Config, ConfigDict, ManagerMixin,
+ Registry, build_from_cfg, build_model_from_cfg)
+
+
+@pytest.mark.parametrize('cfg_type', [dict, ConfigDict, Config])
+def test_build_from_cfg(cfg_type):
+ BACKBONES = Registry('backbone')
+
+ @BACKBONES.register_module()
+ class ResNet:
+
+ def __init__(self, depth, stages=4):
+ self.depth = depth
+ self.stages = stages
+
+ @BACKBONES.register_module()
+ class ResNeXt:
+
+ def __init__(self, depth, stages=4):
+ self.depth = depth
+ self.stages = stages
+
+ # test `cfg` parameter
+ # `cfg` should be a dict, ConfigDict or Config object
+ with pytest.raises(
+ TypeError,
+ match=('cfg should be a dict, ConfigDict or Config, but got '
+ "<class 'str'>")):
+ cfg = 'ResNet'
+ model = build_from_cfg(cfg, BACKBONES)
+
+ # `cfg` is a dict, ConfigDict or Config object
+ cfg = cfg_type(dict(type='ResNet', depth=50))
+ model = build_from_cfg(cfg, BACKBONES)
+ assert isinstance(model, ResNet)
+ assert model.depth == 50 and model.stages == 4
+
+ # `cfg` is a dict but it does not contain the key "type"
+ with pytest.raises(KeyError, match='must contain the key "type"'):
+ cfg = dict(depth=50, stages=4)
+ cfg = cfg_type(cfg)
+ model = build_from_cfg(cfg, BACKBONES)
+
+ # cfg['type'] should be a str or class
+ with pytest.raises(
+ TypeError,
+ match="type must be a str or valid type, but got <class 'int'>"):
+ cfg = dict(type=1000)
+ cfg = cfg_type(cfg)
+ model = build_from_cfg(cfg, BACKBONES)
+
+ cfg = cfg_type(dict(type='ResNeXt', depth=50, stages=3))
+ model = build_from_cfg(cfg, BACKBONES)
+ assert isinstance(model, ResNeXt)
+ assert model.depth == 50 and model.stages == 3
+
+ cfg = cfg_type(dict(type=ResNet, depth=50))
+ model = build_from_cfg(cfg, BACKBONES)
+ assert isinstance(model, ResNet)
+ assert model.depth == 50 and model.stages == 4
+
+ # non-registered class
+ with pytest.raises(KeyError, match='VGG is not in the backbone registry'):
+ cfg = cfg_type(dict(type='VGG'))
+ model = build_from_cfg(cfg, BACKBONES)
+
+ # `cfg` contains unexpected arguments
+ with pytest.raises(TypeError):
+ cfg = cfg_type(dict(type='ResNet', non_existing_arg=50))
+ model = build_from_cfg(cfg, BACKBONES)
+
+ # test `default_args` parameter
+ cfg = cfg_type(dict(type='ResNet', depth=50))
+ model = build_from_cfg(cfg, BACKBONES, cfg_type(dict(stages=3)))
+ assert isinstance(model, ResNet)
+ assert model.depth == 50 and model.stages == 3
+
+ # default_args must be a dict or None
+ with pytest.raises(TypeError):
+ cfg = cfg_type(dict(type='ResNet', depth=50))
+ model = build_from_cfg(cfg, BACKBONES, default_args=1)
+
+ # cfg or default_args should contain the key "type"
+ with pytest.raises(KeyError, match='must contain the key "type"'):
+ cfg = cfg_type(dict(depth=50))
+ model = build_from_cfg(
+ cfg, BACKBONES, default_args=cfg_type(dict(stages=4)))
+
+ # "type" defined using default_args
+ cfg = cfg_type(dict(depth=50))
+ model = build_from_cfg(
+ cfg, BACKBONES, default_args=cfg_type(dict(type='ResNet')))
+ assert isinstance(model, ResNet)
+ assert model.depth == 50 and model.stages == 4
+
+ cfg = cfg_type(dict(depth=50))
+ model = build_from_cfg(
+ cfg, BACKBONES, default_args=cfg_type(dict(type=ResNet)))
+ assert isinstance(model, ResNet)
+ assert model.depth == 50 and model.stages == 4
+
+ # test `registry` parameter
+ # incorrect registry type
+ with pytest.raises(
+ TypeError,
+ match=('registry must be a mmengine.Registry object, but got '
+ "<class 'str'>")):
+ cfg = cfg_type(dict(type='ResNet', depth=50))
+ model = build_from_cfg(cfg, 'BACKBONES')
+
+ VISUALIZER = Registry('visualizer')
+
+ @VISUALIZER.register_module()
+ class Visualizer(ManagerMixin):
+
+ def __init__(self, name):
+ super().__init__(name)
+
+ with pytest.raises(RuntimeError):
+ Visualizer.get_current_instance()
+ cfg = dict(type='Visualizer', name='visualizer')
+ build_from_cfg(cfg, VISUALIZER)
+ Visualizer.get_current_instance()
+
+
+def test_build_model_from_cfg():
+ BACKBONES = Registry('backbone', build_func=build_model_from_cfg)
+
+ @BACKBONES.register_module()
+ class ResNet(nn.Module):
+
+ def __init__(self, depth, stages=4):
+ super().__init__()
+ self.depth = depth
+ self.stages = stages
+
+ def forward(self, x):
+ return x
+
+ @BACKBONES.register_module()
+ class ResNeXt(nn.Module):
+
+ def __init__(self, depth, stages=4):
+ super().__init__()
+ self.depth = depth
+ self.stages = stages
+
+ def forward(self, x):
+ return x
+
+ cfg = dict(type='ResNet', depth=50)
+ model = BACKBONES.build(cfg)
+ assert isinstance(model, ResNet)
+ assert model.depth == 50 and model.stages == 4
+
+ cfg = dict(type='ResNeXt', depth=50, stages=3)
+ model = BACKBONES.build(cfg)
+ assert isinstance(model, ResNeXt)
+ assert model.depth == 50 and model.stages == 3
+
+ cfg = [
+ dict(type='ResNet', depth=50),
+ dict(type='ResNeXt', depth=50, stages=3)
+ ]
+ model = BACKBONES.build(cfg)
+ assert isinstance(model, nn.Sequential)
+ assert isinstance(model[0], ResNet)
+ assert model[0].depth == 50 and model[0].stages == 4
+ assert isinstance(model[1], ResNeXt)
+ assert model[1].depth == 50 and model[1].stages == 3
+
+ # test inherit `build_func` from parent
+ NEW_MODELS = Registry('models', parent=BACKBONES, scope='new')
+ assert NEW_MODELS.build_func is build_model_from_cfg
+
+ # test specify `build_func`
+ def pseudo_build(cfg):
+ return cfg
+
+ NEW_MODELS = Registry('models', parent=BACKBONES, build_func=pseudo_build)
+ assert NEW_MODELS.build_func is pseudo_build
+
+
+def test_build_sheduler_from_cfg():
+ model = nn.Conv2d(1, 1, 1)
+ optimizer = SGD(model.parameters(), lr=0.1)
+ cfg = dict(
+ type='LinearParamScheduler',
+ optimizer=optimizer,
+ param_name='lr',
+ begin=0,
+ end=100)
+ sheduler = PARAM_SCHEDULERS.build(cfg)
+ assert sheduler.begin == 0
+ assert sheduler.end == 100
+
+ cfg = dict(
+ type='LinearParamScheduler',
+ convert_to_iter_based=True,
+ optimizer=optimizer,
+ param_name='lr',
+ begin=0,
+ end=100,
+ epoch_length=10)
+
+ sheduler = PARAM_SCHEDULERS.build(cfg)
+ assert sheduler.begin == 0
+ assert sheduler.end == 1000
diff --git a/tests/test_registry/test_registry.py b/tests/test_registry/test_registry.py
index 41ad4684..74e51e22 100644
--- a/tests/test_registry/test_registry.py
+++ b/tests/test_registry/test_registry.py
@@ -2,12 +2,9 @@
import time
import pytest
-import torch.nn as nn
from mmengine.config import Config, ConfigDict # type: ignore
-from mmengine.registry import (DefaultScope, Registry, build_from_cfg,
- build_model_from_cfg)
-from mmengine.utils import ManagerMixin
+from mmengine.registry import DefaultScope, Registry, build_from_cfg
class TestRegistry:
@@ -476,182 +473,3 @@ class TestRegistry:
"<locals>.Munchkin'>")
repr_str += '})'
assert repr(CATS) == repr_str
-
-
-@pytest.mark.parametrize('cfg_type', [dict, ConfigDict, Config])
-def test_build_from_cfg(cfg_type):
- BACKBONES = Registry('backbone')
-
- @BACKBONES.register_module()
- class ResNet:
-
- def __init__(self, depth, stages=4):
- self.depth = depth
- self.stages = stages
-
- @BACKBONES.register_module()
- class ResNeXt:
-
- def __init__(self, depth, stages=4):
- self.depth = depth
- self.stages = stages
-
- # test `cfg` parameter
- # `cfg` should be a dict, ConfigDict or Config object
- with pytest.raises(
- TypeError,
- match=('cfg should be a dict, ConfigDict or Config, but got '
- "<class 'str'>")):
- cfg = 'ResNet'
- model = build_from_cfg(cfg, BACKBONES)
-
- # `cfg` is a dict, ConfigDict or Config object
- cfg = cfg_type(dict(type='ResNet', depth=50))
- model = build_from_cfg(cfg, BACKBONES)
- assert isinstance(model, ResNet)
- assert model.depth == 50 and model.stages == 4
-
- # `cfg` is a dict but it does not contain the key "type"
- with pytest.raises(KeyError, match='must contain the key "type"'):
- cfg = dict(depth=50, stages=4)
- cfg = cfg_type(cfg)
- model = build_from_cfg(cfg, BACKBONES)
-
- # cfg['type'] should be a str or class
- with pytest.raises(
- TypeError,
- match="type must be a str or valid type, but got <class 'int'>"):
- cfg = dict(type=1000)
- cfg = cfg_type(cfg)
- model = build_from_cfg(cfg, BACKBONES)
-
- cfg = cfg_type(dict(type='ResNeXt', depth=50, stages=3))
- model = build_from_cfg(cfg, BACKBONES)
- assert isinstance(model, ResNeXt)
- assert model.depth == 50 and model.stages == 3
-
- cfg = cfg_type(dict(type=ResNet, depth=50))
- model = build_from_cfg(cfg, BACKBONES)
- assert isinstance(model, ResNet)
- assert model.depth == 50 and model.stages == 4
-
- # non-registered class
- with pytest.raises(KeyError, match='VGG is not in the backbone registry'):
- cfg = cfg_type(dict(type='VGG'))
- model = build_from_cfg(cfg, BACKBONES)
-
- # `cfg` contains unexpected arguments
- with pytest.raises(TypeError):
- cfg = cfg_type(dict(type='ResNet', non_existing_arg=50))
- model = build_from_cfg(cfg, BACKBONES)
-
- # test `default_args` parameter
- cfg = cfg_type(dict(type='ResNet', depth=50))
- model = build_from_cfg(cfg, BACKBONES, cfg_type(dict(stages=3)))
- assert isinstance(model, ResNet)
- assert model.depth == 50 and model.stages == 3
-
- # default_args must be a dict or None
- with pytest.raises(TypeError):
- cfg = cfg_type(dict(type='ResNet', depth=50))
- model = build_from_cfg(cfg, BACKBONES, default_args=1)
-
- # cfg or default_args should contain the key "type"
- with pytest.raises(KeyError, match='must contain the key "type"'):
- cfg = cfg_type(dict(depth=50))
- model = build_from_cfg(
- cfg, BACKBONES, default_args=cfg_type(dict(stages=4)))
-
- # "type" defined using default_args
- cfg = cfg_type(dict(depth=50))
- model = build_from_cfg(
- cfg, BACKBONES, default_args=cfg_type(dict(type='ResNet')))
- assert isinstance(model, ResNet)
- assert model.depth == 50 and model.stages == 4
-
- cfg = cfg_type(dict(depth=50))
- model = build_from_cfg(
- cfg, BACKBONES, default_args=cfg_type(dict(type=ResNet)))
- assert isinstance(model, ResNet)
- assert model.depth == 50 and model.stages == 4
-
- # test `registry` parameter
- # incorrect registry type
- with pytest.raises(
- TypeError,
- match=('registry must be a mmengine.Registry object, but got '
- "<class 'str'>")):
- cfg = cfg_type(dict(type='ResNet', depth=50))
- model = build_from_cfg(cfg, 'BACKBONES')
-
- VISUALIZER = Registry('visualizer')
-
- @VISUALIZER.register_module()
- class Visualizer(ManagerMixin):
-
- def __init__(self, name):
- super().__init__(name)
-
- with pytest.raises(RuntimeError):
- Visualizer.get_current_instance()
- cfg = dict(type='Visualizer', name='visualizer')
- build_from_cfg(cfg, VISUALIZER)
- Visualizer.get_current_instance()
-
-
-def test_build_model_from_cfg():
- BACKBONES = Registry('backbone', build_func=build_model_from_cfg)
-
- @BACKBONES.register_module()
- class ResNet(nn.Module):
-
- def __init__(self, depth, stages=4):
- super().__init__()
- self.depth = depth
- self.stages = stages
-
- def forward(self, x):
- return x
-
- @BACKBONES.register_module()
- class ResNeXt(nn.Module):
-
- def __init__(self, depth, stages=4):
- super().__init__()
- self.depth = depth
- self.stages = stages
-
- def forward(self, x):
- return x
-
- cfg = dict(type='ResNet', depth=50)
- model = BACKBONES.build(cfg)
- assert isinstance(model, ResNet)
- assert model.depth == 50 and model.stages == 4
-
- cfg = dict(type='ResNeXt', depth=50, stages=3)
- model = BACKBONES.build(cfg)
- assert isinstance(model, ResNeXt)
- assert model.depth == 50 and model.stages == 3
-
- cfg = [
- dict(type='ResNet', depth=50),
- dict(type='ResNeXt', depth=50, stages=3)
- ]
- model = BACKBONES.build(cfg)
- assert isinstance(model, nn.Sequential)
- assert isinstance(model[0], ResNet)
- assert model[0].depth == 50 and model[0].stages == 4
- assert isinstance(model[1], ResNeXt)
- assert model[1].depth == 50 and model[1].stages == 3
-
- # test inherit `build_func` from parent
- NEW_MODELS = Registry('models', parent=BACKBONES, scope='new')
- assert NEW_MODELS.build_func is build_model_from_cfg
-
- # test specify `build_func`
- def pseudo_build(cfg):
- return cfg
-
- NEW_MODELS = Registry('models', parent=BACKBONES, build_func=pseudo_build)
- assert NEW_MODELS.build_func is pseudo_build
diff --git a/tests/test_runner/test_runner.py b/tests/test_runner/test_runner.py
index f382bc3b..ebceb5ce 100644
--- a/tests/test_runner/test_runner.py
+++ b/tests/test_runner/test_runner.py
@@ -993,11 +993,6 @@ class TestRunner(TestCase):
# 5.1 train loop should be built before converting scheduler
cfg = dict(
type='MultiStepLR', milestones=[1, 2], convert_to_iter_based=True)
- with self.assertRaisesRegex(
- AssertionError,
- 'Scheduler can only be converted to iter-based when '
- 'train loop is built.'):
- runner.build_param_scheduler(cfg)
# 5.2 convert epoch-based to iter-based scheduler
cfg = dict(
--
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