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authorAngelBottomless <35677394+aria1th@users.noreply.github.com>2022-10-27 14:44:53 +0900
committerGitHub <noreply@github.com>2022-10-27 14:44:53 +0900
commit029d7c75436558f1e884bb127caed73caaecb83a (patch)
treef4286ffe23f1b556fdb6f8fb20a95e174c9b65ec /modules/hypernetworks/hypernetwork.py
parentcc56df996e95c2c82295ab7b9928da2544791220 (diff)
Revert unresolved changes in Bias initialization
it should be zeros_ or parameterized in future properly.
Diffstat (limited to 'modules/hypernetworks/hypernetwork.py')
-rw-r--r--modules/hypernetworks/hypernetwork.py2
1 files changed, 1 insertions, 1 deletions
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index b17598fe..25427a37 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -75,7 +75,7 @@ class HypernetworkModule(torch.nn.Module):
w, b = layer.weight.data, layer.bias.data
if weight_init == "Normal" or type(layer) == torch.nn.LayerNorm:
normal_(w, mean=0.0, std=0.01)
- normal_(b, mean=0.0, std=0.005)
+ normal_(b, mean=0.0, std=0)
elif weight_init == 'XavierUniform':
xavier_uniform_(w)
zeros_(b)