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@@ -486,7 +486,7 @@ function srcnn.upcunet(backend, ch)
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block2:add(unet_branch(backend, block1, backend, 128, 128, 4))
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block2:add(unet_conv(backend, 128, 64, 64, true))
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local model = nn.Sequential()
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- model:add(unet_conv(backend, ch, 32, 64, true))
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+ model:add(unet_conv(backend, ch, 32, 64, false))
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model:add(unet_branch(backend, block2, backend, 64, 64, 16))
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model:add(SpatialConvolution(backend, 64, 64, 3, 3, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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@@ -536,7 +536,7 @@ function srcnn.cunet(backend, ch)
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block2:add(unet_conv(backend, 128, 64, 64, true))
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local model = nn.Sequential()
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- model:add(unet_conv(backend, ch, 32, 64, true))
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+ model:add(unet_conv(backend, ch, 32, 64, false))
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model:add(unet_branch(backend, block2, backend, 64, 64, 16))
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model:add(SpatialConvolution(backend, 64, 64, 3, 3, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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@@ -583,7 +583,7 @@ function srcnn.upcunet_s(backend, ch)
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block2:add(unet_branch(backend, block1, backend, 128, 128, 4))
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block2:add(unet_conv(backend, 128, 64, 32, true))
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local model = nn.Sequential()
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- model:add(unet_conv(backend, ch, 32, 32, true))
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+ model:add(unet_conv(backend, ch, 32, 32, false))
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model:add(unet_branch(backend, block2, backend, 32, 32, 16))
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model:add(SpatialConvolution(backend, 32, 64, 3, 3, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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@@ -631,7 +631,7 @@ function srcnn.cunet_s(backend, ch)
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block2:add(unet_conv(backend, 128, 64, 32, true))
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local model = nn.Sequential()
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- model:add(unet_conv(backend, ch, 32, 32, true))
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+ model:add(unet_conv(backend, ch, 32, 32, false))
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model:add(unet_branch(backend, block2, backend, 32, 32, 16))
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model:add(SpatialConvolution(backend, 32, 64, 3, 3, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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nagadomi