mirrors
/
mmcv
mirror of https://github.com/open-mmlab/mmcv.git
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

update docstring (#651)

pull/752/head
Jintao Lin 2020-11-15 18:48:03 +08:00 committed by GitHub
parent c390e327fa
commit 1290bdd181
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 26 additions and 13 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

21
mmcv/cnn/bricks/conv_module.py
View File

@ -26,13 +26,20 @@ class ConvModule(nn.Module):
supports zero and circular padding, and we add "reflect" padding mode.
Args:
in_channels (int): Same as nn.Conv2d.
out_channels (int): Same as nn.Conv2d.
kernel_size (int | tuple[int]): Same as nn.Conv2d.
stride (int | tuple[int]): Same as nn.Conv2d.
padding (int | tuple[int]): Same as nn.Conv2d.
dilation (int | tuple[int]): Same as nn.Conv2d.
groups (int): Same as nn.Conv2d.
in_channels (int): Number of channels in the input feature map.
Same as that in ``nn._ConvNd``.
out_channels (int): Number of channels produced by the convolution.
Same as that in ``nn._ConvNd``.
kernel_size (int | tuple[int]): Size of the convolving kernel.
Same as that in ``nn._ConvNd``.
stride (int | tuple[int]): Stride of the convolution.
Same as that in ``nn._ConvNd``.
padding (int | tuple[int]): Zero-padding added to both sides of
the input. Same as that in ``nn._ConvNd``.
dilation (int | tuple[int]): Spacing between kernel elements.
Same as that in ``nn._ConvNd``.
groups (int): Number of blocked connections from input channels to
output channels. Same as that in ``nn._ConvNd``.
bias (bool | str): If specified as `auto`, it will be decided by the
norm_cfg. Bias will be set as True if `norm_cfg` is None, otherwise
False. Default: "auto".

18
mmcv/cnn/bricks/depthwise_separable_conv_module.py
View File

@ -16,12 +16,18 @@ class DepthwiseSeparableConvModule(nn.Module):
if `norm_cfg` and `act_cfg` are specified.
Args:
in_channels (int): Same as nn.Conv2d.
out_channels (int): Same as nn.Conv2d.
kernel_size (int or tuple[int]): Same as nn.Conv2d.
stride (int or tuple[int]): Same as nn.Conv2d. Default: 1.
padding (int or tuple[int]): Same as nn.Conv2d. Default: 0.
dilation (int or tuple[int]): Same as nn.Conv2d. Default: 1.
in_channels (int): Number of channels in the input feature map.
Same as that in ``nn._ConvNd``.
out_channels (int): Number of channels produced by the convolution.
Same as that in ``nn._ConvNd``.
kernel_size (int | tuple[int]): Size of the convolving kernel.
Same as that in ``nn._ConvNd``.
stride (int | tuple[int]): Stride of the convolution.
Same as that in ``nn._ConvNd``. Default: 1.
padding (int | tuple[int]): Zero-padding added to both sides of
the input. Same as that in ``nn._ConvNd``. Default: 0.
dilation (int | tuple[int]): Spacing between kernel elements.
Same as that in ``nn._ConvNd``. Default: 1.
norm_cfg (dict): Default norm config for both depthwise ConvModule and
pointwise ConvModule. Default: None.
act_cfg (dict): Default activation config for both depthwise ConvModule