From fd8515641284b332a11f3f6f943aeab3f20887e1 Mon Sep 17 00:00:00 2001
From: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>
Date: Sat, 5 Mar 2022 17:44:31 +0800
Subject: [PATCH] fix type hint and format (#88)
---
mmengine/data/base_data_element.py | 2 +-
mmengine/data/base_data_sample.py | 2 +-
mmengine/evaluator/base.py | 11 ++++++-----
mmengine/evaluator/builder.py | 6 +++++-
mmengine/evaluator/composed_evaluator.py | 10 +++++-----
mmengine/hooks/checkpoint_hook.py | 2 ++
mmengine/hooks/empty_cache_hook.py | 2 ++
mmengine/hooks/hook.py | 2 ++
mmengine/hooks/iter_timer_hook.py | 2 ++
mmengine/hooks/optimizer_hook.py | 2 ++
mmengine/hooks/param_scheduler_hook.py | 2 ++
mmengine/hooks/sampler_seed_hook.py | 2 ++
mmengine/hooks/sync_buffer_hook.py | 2 ++
mmengine/model/wrappers/utils.py | 2 +-
14 files changed, 35 insertions(+), 14 deletions(-)
diff --git a/mmengine/data/base_data_element.py b/mmengine/data/base_data_element.py
index ac5870bc..609ce538 100644
--- a/mmengine/data/base_data_element.py
+++ b/mmengine/data/base_data_element.py
@@ -406,7 +406,7 @@ class BaseDataElement:
# Tensor-like methods
def numpy(self) -> 'BaseDataElement':
- """Convert all tensor　to np.narray in metainfo and data."""
+ """Convert all tensor to np.narray in metainfo and data."""
new_data = self.new()
for k, v in self.data_items():
if isinstance(v, torch.Tensor):
diff --git a/mmengine/data/base_data_sample.py b/mmengine/data/base_data_sample.py
index dd6fafd1..659a4a8b 100644
--- a/mmengine/data/base_data_sample.py
+++ b/mmengine/data/base_data_sample.py
@@ -500,7 +500,7 @@ class BaseDataSample:
# Tensor-like methods
def numpy(self) -> 'BaseDataSample':
- """Convert all tensor　to np.narray in metainfo and data."""
+ """Convert all tensor to np.narray in metainfo and data."""
new_data = self.new()
for k, v in self.data_items():
if isinstance(v, (torch.Tensor, BaseDataElement)):
diff --git a/mmengine/evaluator/base.py b/mmengine/evaluator/base.py
index 287c2fe2..51fbd17e 100644
--- a/mmengine/evaluator/base.py
+++ b/mmengine/evaluator/base.py
@@ -10,6 +10,7 @@ from typing import Any, List, Optional, Union
import torch
import torch.distributed as dist
+from mmengine.data import BaseDataSample
from mmengine.utils import mkdir_or_exist
@@ -45,13 +46,13 @@ class BaseEvaluator(metaclass=ABCMeta):
self._dataset_meta = dataset_meta
@abstractmethod
- def process(self, data_samples: dict, predictions: dict) -> None:
+ def process(self, data_samples: BaseDataSample, predictions: dict) -> None:
"""Process one batch of data samples and predictions. The processed
results should be stored in ``self.results``, which will be used to
compute the metrics when all batches have been processed.
Args:
- data_samples (dict): The data samples from the dataset.
+ data_samples (BaseDataSample): The data samples from the dataset.
predictions (dict): The output of the model.
"""
@@ -61,6 +62,7 @@ class BaseEvaluator(metaclass=ABCMeta):
Args:
results (list): The processed results of each batch.
+
Returns:
dict: The computed metrics. The keys are the names of the metrics,
and the values are corresponding results.
@@ -78,9 +80,8 @@ class BaseEvaluator(metaclass=ABCMeta):
this size.
Returns:
- metrics (dict): Evaluation metrics dict on the val dataset. The
- keys are the names of the metrics, and the values are
- corresponding results.
+ dict: Evaluation metrics dict on the val dataset. The keys are the
+ names of the metrics, and the values are corresponding results.
"""
if len(self.results) == 0:
warnings.warn(
diff --git a/mmengine/evaluator/builder.py b/mmengine/evaluator/builder.py
index 710c6554..2a8fb3d8 100644
--- a/mmengine/evaluator/builder.py
+++ b/mmengine/evaluator/builder.py
@@ -1,9 +1,13 @@
# Copyright (c) OpenMMLab. All rights reserved.
+from typing import Union
+
from ..registry import EVALUATORS
+from .base import BaseEvaluator
from .composed_evaluator import ComposedEvaluator
-def build_evaluator(cfg: dict) -> object:
+def build_evaluator(
+ cfg: Union[dict, list]) -> Union[BaseEvaluator, ComposedEvaluator]:
"""Build function of evaluator.
When the evaluator config is a list, it will automatically build composed
diff --git a/mmengine/evaluator/composed_evaluator.py b/mmengine/evaluator/composed_evaluator.py
index 225284e7..c0ba27f9 100644
--- a/mmengine/evaluator/composed_evaluator.py
+++ b/mmengine/evaluator/composed_evaluator.py
@@ -1,6 +1,7 @@
# Copyright (c) OpenMMLab. All rights reserved.
from typing import Optional, Sequence, Union
+from mmengine.data import BaseDataSample
from .base import BaseEvaluator
@@ -31,11 +32,11 @@ class ComposedEvaluator:
for evaluator in self.evaluators:
evaluator.dataset_meta = dataset_meta
- def process(self, data_samples: dict, predictions: dict):
+ def process(self, data_samples: BaseDataSample, predictions: dict):
"""Invoke process method of each wrapped evaluator.
Args:
- data_samples (dict): The data samples from the dataset.
+ data_samples (BaseDataSample): The data samples from the dataset.
predictions (dict): The output of the model.
"""
@@ -54,9 +55,8 @@ class ComposedEvaluator:
this size.
Returns:
- metrics (dict): Evaluation metrics of all wrapped evaluators. The
- keys are the names of the metrics, and the values are
- corresponding results.
+ dict: Evaluation metrics of all wrapped evaluators. The keys are
+ the names of the metrics, and the values are corresponding results.
"""
metrics = {}
for evaluator in self.evaluators:
diff --git a/mmengine/hooks/checkpoint_hook.py b/mmengine/hooks/checkpoint_hook.py
index 7baa99ed..14a7ab7b 100644
--- a/mmengine/hooks/checkpoint_hook.py
+++ b/mmengine/hooks/checkpoint_hook.py
@@ -43,6 +43,8 @@ class CheckpointHook(Hook):
Default: None.
"""
+ priority = 'VERY_LOW'
+
def __init__(self,
interval: int = -1,
by_epoch: bool = True,
diff --git a/mmengine/hooks/empty_cache_hook.py b/mmengine/hooks/empty_cache_hook.py
index b457f2c0..44bf53ec 100644
--- a/mmengine/hooks/empty_cache_hook.py
+++ b/mmengine/hooks/empty_cache_hook.py
@@ -22,6 +22,8 @@ class EmptyCacheHook(Hook):
Defaults to False.
"""
+ priority = 'NORMAL'
+
def __init__(self,
before_epoch: bool = False,
after_epoch: bool = True,
diff --git a/mmengine/hooks/hook.py b/mmengine/hooks/hook.py
index 8321af83..f0ccb1f7 100644
--- a/mmengine/hooks/hook.py
+++ b/mmengine/hooks/hook.py
@@ -10,6 +10,8 @@ class Hook:
All hooks should inherit from this class.
"""
+ priority = 'NORMAL'
+
def before_run(self, runner: object) -> None:
"""All subclasses should override this method, if they need any
operations before the training process.
diff --git a/mmengine/hooks/iter_timer_hook.py b/mmengine/hooks/iter_timer_hook.py
index ecc84465..3c637056 100644
--- a/mmengine/hooks/iter_timer_hook.py
+++ b/mmengine/hooks/iter_timer_hook.py
@@ -14,6 +14,8 @@ class IterTimerHook(Hook):
Eg. ``data_time`` for loading data and ``time`` for a model train step.
"""
+ priority = 'NORMAL'
+
def before_epoch(self, runner: object) -> None:
"""Record time flag before start a epoch.
diff --git a/mmengine/hooks/optimizer_hook.py b/mmengine/hooks/optimizer_hook.py
index 8689b9fa..99f010ab 100644
--- a/mmengine/hooks/optimizer_hook.py
+++ b/mmengine/hooks/optimizer_hook.py
@@ -30,6 +30,8 @@ class OptimizerHook(Hook):
Defaults to False.
"""
+ priority = 'HIGH'
+
def __init__(self,
grad_clip: Optional[dict] = None,
detect_anomalous_params: bool = False) -> None:
diff --git a/mmengine/hooks/param_scheduler_hook.py b/mmengine/hooks/param_scheduler_hook.py
index 1bbf610f..425ab123 100644
--- a/mmengine/hooks/param_scheduler_hook.py
+++ b/mmengine/hooks/param_scheduler_hook.py
@@ -11,6 +11,8 @@ class ParamSchedulerHook(Hook):
"""A hook to update some hyper-parameters in optimizer, e.g learning rate
and momentum."""
+ priority = 'LOW'
+
def after_iter(self,
runner: object,
data_batch: Optional[Sequence[BaseDataSample]] = None,
diff --git a/mmengine/hooks/sampler_seed_hook.py b/mmengine/hooks/sampler_seed_hook.py
index d2c991a9..6d665172 100644
--- a/mmengine/hooks/sampler_seed_hook.py
+++ b/mmengine/hooks/sampler_seed_hook.py
@@ -12,6 +12,8 @@ class DistSamplerSeedHook(Hook):
purpose with :obj:`IterLoader`.
"""
+ priority = 'NORMAL'
+
def before_epoch(self, runner: object) -> None:
"""Set the seed for sampler and batch_sampler.
diff --git a/mmengine/hooks/sync_buffer_hook.py b/mmengine/hooks/sync_buffer_hook.py
index 89edb55d..f62910e8 100644
--- a/mmengine/hooks/sync_buffer_hook.py
+++ b/mmengine/hooks/sync_buffer_hook.py
@@ -84,6 +84,8 @@ class SyncBuffersHook(Hook):
"""Synchronize model buffers such as running_mean and running_var in BN at
the end of each epoch."""
+ priority = 'NORMAL'
+
def __init__(self) -> None:
self.distributed = dist.IS_DIST
diff --git a/mmengine/model/wrappers/utils.py b/mmengine/model/wrappers/utils.py
index f888f49c..f952e9b1 100644
--- a/mmengine/model/wrappers/utils.py
+++ b/mmengine/model/wrappers/utils.py
@@ -8,7 +8,7 @@ def is_model_wrapper(model):
The following 4 model in MMEngine (and their subclasses) are regarded as
model wrappers: DataParallel, DistributedDataParallel,
MMDataParallel, MMDistributedDataParallel. You may add you own
- model wrapper by registering it to mmengine.registry.MODEL_WRAPPERS.
+ model wrapper by registering it to ``mmengine.registry.MODEL_WRAPPERS``.
Args:
model (nn.Module): The model to be checked.
--
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