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D-X-Y
2021-05-24 02:35:32 +00:00
parent da4b61f3ab
commit c5788ba19c
1 changed files with 4 additions and 3 deletions
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7
exps/LFNA/lfna_meta_model.py
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@@ -1,7 +1,6 @@
##################################################### #####################################################
# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2021.04 # # Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2021.04 #
##################################################### #####################################################
import copy
import torch import torch
import torch.nn.functional as F import torch.nn.functional as F
@@ -294,7 +293,9 @@ class LFNA_Meta(super_core.SuperModule):
best_loss = init_info["loss"] best_loss = init_info["loss"]
new_param.data.copy_(init_info["param"].data) new_param.data.copy_(init_info["param"].data)
else: else:
best_new_param, best_loss = None, 1e9 best_loss = 1e9
with torch.no_grad():
best_new_param = new_param.detach().clone()
for iepoch in range(epochs): for iepoch in range(epochs):
optimizer.zero_grad() optimizer.zero_grad()
_, [_], time_embed = self(timestamp.view(1, 1), None, True) _, [_], time_embed = self(timestamp.view(1, 1), None, True)
@@ -310,7 +311,7 @@ class LFNA_Meta(super_core.SuperModule):
if meta_loss.item() < best_loss: if meta_loss.item() < best_loss:
with torch.no_grad(): with torch.no_grad():
best_loss = meta_loss.item() best_loss = meta_loss.item()
best_new_param = new_param.detach() best_new_param = new_param.detach().clone()
with torch.no_grad(): with torch.no_grad():
self.replace_append_learnt(None, None) self.replace_append_learnt(None, None)
self.append_fixed(timestamp, best_new_param) self.append_fixed(timestamp, best_new_param)