Shortcuts

Source code for mmocr.models.textrecog.encoders.channel_reduction_encoder

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

from mmocr.models.builder import ENCODERS
from .base_encoder import BaseEncoder


[docs]@ENCODERS.register_module() class ChannelReductionEncoder(BaseEncoder): """Change the channel number with a one by one convoluational layer. Args: in_channels (int): Number of input channels. out_channels (int): Number of output channels. init_cfg (dict or list[dict], optional): Initialization configs. """ def __init__(self, in_channels, out_channels, init_cfg=dict(type='Xavier', layer='Conv2d')): super().__init__(init_cfg=init_cfg) self.layer = nn.Conv2d( in_channels, out_channels, kernel_size=1, stride=1, padding=0)
[docs] def forward(self, feat, img_metas=None): """ Args: feat (Tensor): Image features with the shape of :math:`(N, C_{in}, H, W)`. img_metas (None): Unused. Returns: Tensor: A tensor of shape :math:`(N, C_{out}, H, W)`. """ return self.layer(feat)
Read the Docs v: v0.4.0
Versions
latest
stable
v0.4.0
v0.3.0
v0.2.1
v0.2.0
v0.1.0
Downloads
On Read the Docs
Project Home
Builds

Free document hosting provided by Read the Docs.