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Difference between revisions of "ESRGAN old-arch"

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(Created page with "ESRGAN old-arch or old-architecture models are the original architecture for ESRGAN models trained with BasicSR. These models still allow scales other than 4, and therefore ar...")
 
(removed code)
 
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ESRGAN old-arch or old-architecture models are the original architecture for ESRGAN models trained with BasicSR. These models still allow scales other than 4, and therefore are still heavily used by the community.
 
ESRGAN old-arch or old-architecture models are the original architecture for ESRGAN models trained with BasicSR. These models still allow scales other than 4, and therefore are still heavily used by the community.
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<pre>
 
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import math
 
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import torch
 
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import torch.nn as nn
 
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import block as B
 
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class RRDB_Net(nn.Module):
 
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    def __init__(self, in_nc, out_nc, nf, nb, gc=32, upscale=4, norm_type=None, act_type='leakyrelu', \
 
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            mode='CNA', res_scale=1, upsample_mode='upconv'):
 
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        super(RRDB_Net, self).__init__()
 
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        n_upscale = int(math.log(upscale, 2))
 
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        if upscale == 3:
 
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            n_upscale = 1
 
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        fea_conv = B.conv_block(in_nc, nf, kernel_size=3, norm_type=None, act_type=None)
 
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        rb_blocks = [B.RRDB(nf, kernel_size=3, gc=32, stride=1, bias=True, pad_type='zero', \
 
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            norm_type=norm_type, act_type=act_type, mode='CNA') for _ in range(nb)]
 
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        LR_conv = B.conv_block(nf, nf, kernel_size=3, norm_type=norm_type, act_type=None, mode=mode)
 
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        if upsample_mode == 'upconv':
 
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            upsample_block = B.upconv_blcok
 
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        elif upsample_mode == 'pixelshuffle':
 
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            upsample_block = B.pixelshuffle_block
 
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        else:
 
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            raise NotImplementedError('upsample mode [%s] is not found' % upsample_mode)
 
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        if upscale == 3:
 
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            upsampler = upsample_block(nf, nf, 3, act_type=act_type)
 
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        else:
 
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            upsampler = [upsample_block(nf, nf, act_type=act_type) for _ in range(n_upscale)]
 
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        HR_conv0 = B.conv_block(nf, nf, kernel_size=3, norm_type=None, act_type=act_type)
 
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        HR_conv1 = B.conv_block(nf, out_nc, kernel_size=3, norm_type=None, act_type=None)
 
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        self.model = B.sequential(fea_conv, B.ShortcutBlock(B.sequential(*rb_blocks, LR_conv)),\
 
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            *upsampler, HR_conv0, HR_conv1)
 
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    def forward(self, x):
 
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        x = self.model(x)
 
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        return x
 
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</pre>
 

Latest revision as of 03:08, 1 September 2020

ESRGAN old-arch or old-architecture models are the original architecture for ESRGAN models trained with BasicSR. These models still allow scales other than 4, and therefore are still heavily used by the community.

Retrieved from "https://upscale.wiki/w/index.php?title=ESRGAN_old-arch&oldid=1003"