mmcv.cnn.bricks.conv 源代码

# Copyright (c) OpenMMLab. All rights reserved.
from torch import nn

from .registry import CONV_LAYERS

CONV_LAYERS.register_module('Conv1d', module=nn.Conv1d)
CONV_LAYERS.register_module('Conv2d', module=nn.Conv2d)
CONV_LAYERS.register_module('Conv3d', module=nn.Conv3d)
CONV_LAYERS.register_module('Conv', module=nn.Conv2d)

[文档]def build_conv_layer(cfg, *args, **kwargs): """Build convolution layer. Args: cfg (None or dict): The conv layer config, which should contain: - type (str): Layer type. - layer args: Args needed to instantiate an conv layer. args (argument list): Arguments passed to the `__init__` method of the corresponding conv layer. kwargs (keyword arguments): Keyword arguments passed to the `__init__` method of the corresponding conv layer. Returns: nn.Module: Created conv layer. """ if cfg is None: cfg_ = dict(type='Conv2d') else: if not isinstance(cfg, dict): raise TypeError('cfg must be a dict') if 'type' not in cfg: raise KeyError('the cfg dict must contain the key "type"') cfg_ = cfg.copy() layer_type = cfg_.pop('type') if layer_type not in CONV_LAYERS: raise KeyError(f'Unrecognized norm type {layer_type}') else: conv_layer = CONV_LAYERS.get(layer_type) layer = conv_layer(*args, **kwargs, **cfg_) return layer