use registry to manage hooks (#199)

mmcv/runner/hooks/__init__.py

 # Copyright (c) Open-MMLab. All rights reserved.
 from .checkpoint import CheckpointHook
 from .closure import ClosureHook
-from .hook import Hook
+from .hook import HOOKS, Hook
 from .iter_timer import IterTimerHook
 from .logger import (LoggerHook, TensorboardLoggerHook, TextLoggerHook,
                      WandbLoggerHook)
@@ -11,7 +11,7 @@ from .optimizer import OptimizerHook
 from .sampler_seed import DistSamplerSeedHook
 
 __all__ = [
-    'Hook', 'CheckpointHook', 'ClosureHook', 'LrUpdaterHook', 'OptimizerHook',
-    'IterTimerHook', 'DistSamplerSeedHook', 'EmptyCacheHook', 'LoggerHook',
-    'TextLoggerHook', 'TensorboardLoggerHook', 'WandbLoggerHook'
+    'HOOKS', 'Hook', 'CheckpointHook', 'ClosureHook', 'LrUpdaterHook',
+    'OptimizerHook', 'IterTimerHook', 'DistSamplerSeedHook', 'EmptyCacheHook',
+    'LoggerHook', 'TextLoggerHook', 'TensorboardLoggerHook', 'WandbLoggerHook'
 ]

mmcv/runner/hooks/checkpoint.py

 # Copyright (c) Open-MMLab. All rights reserved.
 from ..dist_utils import master_only
-from .hook import Hook
+from .hook import HOOKS, Hook
 
 
+@HOOKS.register_module
 class CheckpointHook(Hook):
 
     def __init__(self,

mmcv/runner/hooks/closure.py

 # Copyright (c) Open-MMLab. All rights reserved.
-from .hook import Hook
+from .hook import HOOKS, Hook
 
 
+@HOOKS.register_module
 class ClosureHook(Hook):
 
     def __init__(self, fn_name, fn):

mmcv/runner/hooks/hook.py

 # Copyright (c) Open-MMLab. All rights reserved.
+from mmcv.utils import Registry
+
+HOOKS = Registry('hook')
+
+
 class Hook(object):
 
     def before_run(self, runner):

mmcv/runner/hooks/iter_timer.py

 # Copyright (c) Open-MMLab. All rights reserved.
 import time
 
-from .hook import Hook
+from .hook import HOOKS, Hook
 
 
+@HOOKS.register_module
 class IterTimerHook(Hook):
 
     def before_epoch(self, runner):

mmcv/runner/hooks/logger/tensorboard.py

@@ -3,10 +3,12 @@ import os.path as osp
 
 import torch
 
-from ...dist_utils import master_only
+from mmcv.runner import master_only
+from ..hook import HOOKS
 from .base import LoggerHook
 
 
+@HOOKS.register_module
 class TensorboardLoggerHook(LoggerHook):
 
     def __init__(self,

mmcv/runner/hooks/logger/text.py

@@ -7,9 +7,11 @@ import torch
 import torch.distributed as dist
 
 import mmcv
+from ..hook import HOOKS
 from .base import LoggerHook
 
 
+@HOOKS.register_module
 class TextLoggerHook(LoggerHook):
 
     def __init__(self, interval=10, ignore_last=True, reset_flag=False):

mmcv/runner/hooks/logger/wandb.py

 # Copyright (c) Open-MMLab. All rights reserved.
 import numbers
 
-from ...dist_utils import master_only
+from mmcv.runner import master_only
+from ..hook import HOOKS
 from .base import LoggerHook
 
 
+@HOOKS.register_module
 class WandbLoggerHook(LoggerHook):
 
     def __init__(self,

mmcv/runner/hooks/lr_updater.py

@@ -2,7 +2,7 @@
 from __future__ import division
 from math import cos, pi
 
-from .hook import Hook
+from .hook import HOOKS, Hook
 
 
 class LrUpdaterHook(Hook):
@@ -88,6 +88,7 @@ class LrUpdaterHook(Hook):
                 self._set_lr(runner, warmup_lr)
 
 
+@HOOKS.register_module
 class FixedLrUpdaterHook(LrUpdaterHook):
 
     def __init__(self, **kwargs):
@@ -97,6 +98,7 @@ class FixedLrUpdaterHook(LrUpdaterHook):
         return base_lr
 
 
+@HOOKS.register_module
 class StepLrUpdaterHook(LrUpdaterHook):
 
     def __init__(self, step, gamma=0.1, **kwargs):
@@ -126,6 +128,7 @@ class StepLrUpdaterHook(LrUpdaterHook):
         return base_lr * self.gamma**exp
 
 
+@HOOKS.register_module
 class ExpLrUpdaterHook(LrUpdaterHook):
 
     def __init__(self, gamma, **kwargs):
@@ -137,6 +140,7 @@ class ExpLrUpdaterHook(LrUpdaterHook):
         return base_lr * self.gamma**progress
 
 
+@HOOKS.register_module
 class PolyLrUpdaterHook(LrUpdaterHook):
 
     def __init__(self, power=1., min_lr=0., **kwargs):
@@ -155,6 +159,7 @@ class PolyLrUpdaterHook(LrUpdaterHook):
         return (base_lr - self.min_lr) * coeff + self.min_lr
 
 
+@HOOKS.register_module
 class InvLrUpdaterHook(LrUpdaterHook):
 
     def __init__(self, gamma, power=1., **kwargs):
@@ -167,6 +172,7 @@ class InvLrUpdaterHook(LrUpdaterHook):
         return base_lr * (1 + self.gamma * progress)**(-self.power)
 
 
+@HOOKS.register_module
 class CosineLrUpdaterHook(LrUpdaterHook):
 
     def __init__(self, target_lr=0, **kwargs):

mmcv/runner/hooks/memory.py

 # Copyright (c) Open-MMLab. All rights reserved.
 import torch
 
-from .hook import Hook
+from .hook import HOOKS, Hook
 
 
+@HOOKS.register_module
 class EmptyCacheHook(Hook):
 
     def __init__(self, before_epoch=False, after_epoch=True, after_iter=False):

mmcv/runner/hooks/optimizer.py

 # Copyright (c) Open-MMLab. All rights reserved.
 from torch.nn.utils import clip_grad
 
-from .hook import Hook
+from .hook import HOOKS, Hook
 
 
+@HOOKS.register_module
 class OptimizerHook(Hook):
 
     def __init__(self, grad_clip=None):

mmcv/runner/hooks/sampler_seed.py

 # Copyright (c) Open-MMLab. All rights reserved.
-from .hook import Hook
+from .hook import HOOKS, Hook
 
 
+@HOOKS.register_module
 class DistSamplerSeedHook(Hook):
 
     def before_epoch(self, runner):

mmcv/runner/runner.py

@@ -6,11 +6,9 @@ import time
 import torch
 
 import mmcv
-from . import hooks
 from .checkpoint import load_checkpoint, save_checkpoint
 from .dist_utils import get_dist_info
-from .hooks import (CheckpointHook, Hook, IterTimerHook, LrUpdaterHook,
-                    OptimizerHook, lr_updater)
+from .hooks import HOOKS, Hook, IterTimerHook
 from .log_buffer import LogBuffer
 from .priority import get_priority
 from .utils import get_host_info, get_time_str, obj_from_dict
@@ -223,16 +221,6 @@ class Runner(object):
         if not inserted:
             self._hooks.insert(0, hook)
 
-    def build_hook(self, args, hook_type=None):
-        if isinstance(args, Hook):
-            return args
-        elif isinstance(args, dict):
-            assert issubclass(hook_type, Hook)
-            return hook_type(**args)
-        else:
-            raise TypeError('"args" must be either a Hook object'
-                            ' or dict, not {}'.format(type(args)))
-
     def call_hook(self, fn_name):
         for hook in self._hooks:
             getattr(hook, fn_name)(self)
@@ -373,26 +361,41 @@ class Runner(object):
         time.sleep(1)  # wait for some hooks like loggers to finish
         self.call_hook('after_run')
 
-    def register_lr_hooks(self, lr_config):
-        if isinstance(lr_config, LrUpdaterHook):
-            self.register_hook(lr_config)
-        elif isinstance(lr_config, dict):
+    def register_lr_hook(self, lr_config):
+        if isinstance(lr_config, dict):
             assert 'policy' in lr_config
-            # from .hooks import lr_updater
-            hook_name = lr_config['policy'].title() + 'LrUpdaterHook'
-            if not hasattr(lr_updater, hook_name):
-                raise ValueError('"{}" does not exist'.format(hook_name))
-            hook_cls = getattr(lr_updater, hook_name)
-            self.register_hook(hook_cls(**lr_config))
+            hook_type = lr_config.pop('policy').title() + 'LrUpdaterHook'
+            lr_config['type'] = hook_type
+            hook = mmcv.build_from_cfg(lr_config, HOOKS)
+        else:
+            hook = lr_config
+        self.register_hook(hook)
+
+    def register_optimizer_hook(self, optimizer_config):
+        if optimizer_config is None:
+            return
+        if isinstance(optimizer_config, dict):
+            optimizer_config.setdefault('type', 'OptimizerHook')
+            hook = mmcv.build_from_cfg(optimizer_config, HOOKS)
         else:
-            raise TypeError('"lr_config" must be either a LrUpdaterHook object'
-                            ' or dict, not {}'.format(type(lr_config)))
+            hook = optimizer_config
+        self.register_hook(hook)
+
+    def register_checkpoint_hook(self, checkpoint_config):
+        if checkpoint_config is None:
+            return
+        if isinstance(checkpoint_config, dict):
+            checkpoint_config.setdefault('type', 'CheckpointHook')
+            hook = mmcv.build_from_cfg(checkpoint_config, HOOKS)
+        else:
+            hook = checkpoint_config
+        self.register_hook(hook)
 
     def register_logger_hooks(self, log_config):
         log_interval = log_config['interval']
         for info in log_config['hooks']:
-            logger_hook = obj_from_dict(
-                info, hooks, default_args=dict(interval=log_interval))
+            logger_hook = mmcv.build_from_cfg(
+                info, HOOKS, default_args=dict(interval=log_interval))
             self.register_hook(logger_hook, priority='VERY_LOW')
 
     def register_training_hooks(self,
@@ -410,13 +413,8 @@ class Runner(object):
         - IterTimerHook
         - LoggerHook(s)
         """
-        if optimizer_config is None:
-            optimizer_config = {}
-        if checkpoint_config is None:
-            checkpoint_config = {}
-        self.register_lr_hooks(lr_config)
-        self.register_hook(self.build_hook(optimizer_config, OptimizerHook))
-        self.register_hook(self.build_hook(checkpoint_config, CheckpointHook))
+        self.register_lr_hook(lr_config)
+        self.register_optimizer_hook(optimizer_config)
+        self.register_checkpoint_hook(checkpoint_config)
         self.register_hook(IterTimerHook())
-        if log_config is not None:
         self.register_logger_hooks(log_config)