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Scale anorm by transform count

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James Betker 2020-07-13 08:49:09 -06:00
parent dd0bbd9a7c
commit a2285ff2ee
1 changed files with 1 additions and 1 deletions
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codes/models/archs/SwitchedResidualGenerator_arch.py
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@ -123,7 +123,7 @@ class ConfigurableSwitchComputer(nn.Module):
self.noise_scale = nn.Parameter(torch.full((1,), float(1e-3)))
# And the switch itself, including learned scalars
self.switch = BareConvSwitch(initial_temperature=init_temp, attention_norm=AttentionNorm(transform_count, accumulator_size=128))
self.switch = BareConvSwitch(initial_temperature=init_temp, attention_norm=AttentionNorm(transform_count, accumulator_size=16 * transform_count))
self.switch_scale = nn.Parameter(torch.full((1,), float(1)))
self.post_switch_conv = ConvBnLelu(base_filters, base_filters, norm=False, bias=True)
# The post_switch_conv gets a low scale initially. The network can decide to magnify it (or not)