build_activation_layer: Supported types are ReLU, LeakyReLU, PReLU, RReLU, ReLU6, ELU, Sigmoid, Tanh, GELU. build_upsample_layer: Supported types are nearest, bilinear, deconv, pixel_shuffle. build_padding_layer: Supported types are zero, reflect, replicate. Extension We also allow extending ...
Hi, The get_model_complexity_info method does not count the flops of build_upsample_layer('deconv'), but it works for nn.Conv2d, build_conv_layer('Conv2d'), nn.ConvTranspose2d. Could you help fix this bug? ===...
from mmcv.utils import Registry # 给每个层定义一个容器,相当于归类管理方便 CONV_LAYERS = Registry('conv layer') NORM_LAYERS = Registry('norm layer') ACTIVATION_LAYERS = Registry('activation layer') PADDING_LAYERS = Registry('padding layer') UPSAMPLE_LAYERS = Registry('upsample layer') ./mmc...
NORM_LAYERS = Registry('norm layer') ACTIVATION_LAYERS = Registry('activation layer') PADDING_LAYERS = Registry('padding layer') UPSAMPLE_LAYERS = Registry('upsample layer') ./mmcv.cnn.bricks.activation.py 以其中一个为代表举例说明: importtorch.nnasnnfrommmcv.utilsimportbuild_from_cfgfrom.regist...
之前自己实现了一遍mmcv这个库,现在把API文档翻译一遍。 英文官方文档地址:https://mmcv.readthedocs.io/en/latest/api.html 项目github地址:https://github.com/open-mmlab/mmcv 发现这个库的安装的时候常常很麻烦,因为太经常更新了,但其实核心部分也就下面这些功能嗷。
class MyUpsample: def __init__(self, scale_factor): pass def forward(self, x): pass ``` 2. Import `MyUpsample` somewhere (e.g., in `__init__.py`) and then use it. ```python cfg = dict(type='MyUpsample', scale_factor=2) layer = build_upsample_layer(cfg) ``` ### Modu...
cnn import ConvModule, build_upsample_layer, xavier_init from mmdet.ops import ConvModule, build_upsample_layer from mmdet.ops.carafe import CARAFEPack from ..builder import NECKS 3 changes: 1 addition & 2 deletions 3 mmdet/models/necks/hrfpn.py Original file line numberDiff line numberDiff...
build_upsample_layer: Supported types are nearest, bilinear, deconv, pixel_shuffle. build_padding_layer: Supported types are zero, reflect, replicate. Extension We also allow extending the building methods with custom layers and operators. Write and register your own module. from mmcv.cnn import ...
build_upsample_layer: Supported types are nearest, bilinear, deconv, pixel_shuffle. build_padding_layer: Supported types are zero, reflect, replicate. Extension We also allow extending the building methods with custom layers and operators. Write and register your own module. from mmcv.cnn import ...