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checkpoitn save fix for ae norm

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luni
2023-07-02 14:59:31 +02:00
parent cd6d2bd1fb
commit ef73cd1a20
2 changed files with 3 additions and 4 deletions
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configs/iccvw/ae_norm_1.py
-1
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@@ -58,7 +58,6 @@ block_setting_reverse = [
CNBlockConfig(64, 32, 9),
CNBlockConfig(32, 16, 3),
CNBlockConfig(16, 3, 3),
# CNBlockConfig(3, 3, 3),
]
config['cond_ae']['encoder_block_settings'] = block_setting
scripts/ae_norm_train.py
+3 -3
View File
@@ -205,15 +205,15 @@ if __name__ == '__main__':
load_model(model.encoder, config['pretrained_model'] + '_enc')
load_model(model.decoder, config['pretrained_model'] + '_dec')
ckpt_saver_enc = CheckpointSaver('checkpoints/iccv/torch/' + config['name'] + '_enc', top_n=5)
ckpt_saver_dec = CheckpointSaver('checkpoints/iccv/torch/' + config['name'] + '_dec', top_n=5)
ckpt_saver_enc = CheckpointSaver('checkpoints/iccvw/' + config['name'] + '_enc', top_n=5)
ckpt_saver_dec = CheckpointSaver('checkpoints/iccvw/' + config['name'] + '_dec', top_n=5)
run_name = config['name']
print(f'started training: {run_name}')
if not args['debug']:
# model = torch.compile(model)
wandb.watch(model, log='all', log_freq=10000, log_graph=True)
wandb.watch(model, log='all', log_freq=20000, log_graph=True)
train()