| |
| import torch.nn as nn |
|
|
| from .registry import PADDING_LAYERS |
|
|
| PADDING_LAYERS.register_module('zero', module=nn.ZeroPad2d) |
| PADDING_LAYERS.register_module('reflect', module=nn.ReflectionPad2d) |
| PADDING_LAYERS.register_module('replicate', module=nn.ReplicationPad2d) |
|
|
|
|
| def build_padding_layer(cfg, *args, **kwargs): |
| """Build padding layer. |
| |
| Args: |
| cfg (None or dict): The padding layer config, which should contain: |
| - type (str): Layer type. |
| - layer args: Args needed to instantiate a padding layer. |
| |
| Returns: |
| nn.Module: Created padding layer. |
| """ |
| 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() |
| padding_type = cfg_.pop('type') |
| if padding_type not in PADDING_LAYERS: |
| raise KeyError(f'Unrecognized padding type {padding_type}.') |
| else: |
| padding_layer = PADDING_LAYERS.get(padding_type) |
|
|
| layer = padding_layer(*args, **kwargs, **cfg_) |
|
|
| return layer |
|
|
