Spaces:
Sleeping
Sleeping
File size: 1,320 Bytes
f643c3e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 |
#!/usr/bin/env python3
"""Initialize modules for espnet2 neural networks."""
import torch
from typeguard import check_argument_types
def initialize(model: torch.nn.Module, init: str):
"""Initialize weights of a neural network module.
Parameters are initialized using the given method or distribution.
Custom initialization routines can be implemented into submodules
as function `espnet_initialization_fn` within the custom module.
Args:
model: Target.
init: Method of initialization.
"""
assert check_argument_types()
print("init with", init)
# weight init
for p in model.parameters():
if p.dim() > 1:
if init == "xavier_uniform":
torch.nn.init.xavier_uniform_(p.data)
elif init == "xavier_normal":
torch.nn.init.xavier_normal_(p.data)
elif init == "kaiming_uniform":
torch.nn.init.kaiming_uniform_(p.data, nonlinearity="relu")
elif init == "kaiming_normal":
torch.nn.init.kaiming_normal_(p.data, nonlinearity="relu")
else:
raise ValueError("Unknown initialization: " + init)
# bias init
for name, p in model.named_parameters():
if ".bias" in name and p.dim() == 1:
p.data.zero_()
|