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Source code for mmedit.models.backbones.encoder_decoders.encoders.gl_encoder

# Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from mmcv.cnn import ConvModule

from mmedit.models.registry import COMPONENTS


[docs]@COMPONENTS.register_module() class GLEncoder(nn.Module): """Encoder used in Global&Local model. This implementation follows: Globally and locally Consistent Image Completion Args: norm_cfg (dict): Config dict to build norm layer. act_cfg (dict): Config dict for activation layer, "relu" by default. """ def __init__(self, norm_cfg=None, act_cfg=dict(type='ReLU')): super().__init__() channel_list = [64, 128, 128, 256, 256, 256] kernel_size_list = [5, 3, 3, 3, 3, 3] stride_list = [1, 2, 1, 2, 1, 1] in_channels = 4 for i in range(6): ks = kernel_size_list[i] padding = (ks - 1) // 2 self.add_module( f'enc{i + 1}', ConvModule( in_channels, channel_list[i], kernel_size=ks, stride=stride_list[i], padding=padding, norm_cfg=norm_cfg, act_cfg=act_cfg)) in_channels = channel_list[i]
[docs] def forward(self, x): """Forward Function. Args: x (torch.Tensor): Input tensor with shape of (n, c, h, w). Returns: torch.Tensor: Output tensor with shape of (n, c, h', w'). """ for i in range(6): x = getattr(self, f'enc{i + 1}')(x) return x
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