From 6ee675430f603e764a37946c329956984846eb18 Mon Sep 17 00:00:00 2001
From: Mashiro <57566630+HAOCHENYE@users.noreply.github.com>
Date: Wed, 8 Jun 2022 13:28:00 +0800
Subject: [PATCH] [Refactor]: change order of BaseModel arguments (#282)
---
mmengine/model/base_model/base_model.py | 10 +++++-----
tests/test_model/test_base_model/test_base_model.py | 2 +-
2 files changed, 6 insertions(+), 6 deletions(-)
diff --git a/mmengine/model/base_model/base_model.py b/mmengine/model/base_model/base_model.py
index ede27b7a..1155d999 100644
--- a/mmengine/model/base_model/base_model.py
+++ b/mmengine/model/base_model/base_model.py
@@ -57,21 +57,21 @@ class BaseModel(BaseModule):
>>> return dict(loss=loss)
Args:
- init_cfg (dict, optional): The weight initialized config for
- :class:`BaseModule`.
data_preprocessor (dict, optional): The pre-process config of
:class:`BaseDataPreprocessor`.
+ init_cfg (dict, optional): The weight initialized config for
+ :class:`BaseModule`.
Attributes:
- init_cfg (dict, optional): Initialization config dict.
data_preprocessor (:obj:`BaseDataPreprocessor`): Used for
pre-processing data sampled by dataloader to the format accepted by
:meth:`forward`.
+ init_cfg (dict, optional): Initialization config dict.
"""
def __init__(self,
- init_cfg: Optional[dict] = None,
- data_preprocessor: Optional[Union[dict, nn.Module]] = None):
+ data_preprocessor: Optional[Union[dict, nn.Module]] = None,
+ init_cfg: Optional[dict] = None):
super().__init__(init_cfg)
if data_preprocessor is None:
data_preprocessor = dict(type='BaseDataPreprocessor')
diff --git a/tests/test_model/test_base_model/test_base_model.py b/tests/test_model/test_base_model/test_base_model.py
index 280fcead..222e703d 100644
--- a/tests/test_model/test_base_model/test_base_model.py
+++ b/tests/test_model/test_base_model/test_base_model.py
@@ -25,7 +25,7 @@ class CustomDataPreprocessor(BaseDataPreprocessor):
class ToyModel(BaseModel):
def __init__(self, data_preprocessor=None):
- super().__init__(None, data_preprocessor=data_preprocessor)
+ super().__init__(data_preprocessor=data_preprocessor, init_cfg=None)
self.conv = nn.Conv2d(3, 1, 1)
def forward(self, batch_inputs, data_samples=None, mode='tensor'):
--
GitLab