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INFO - 09/13/18 10:01:49 - 0:00:00 - ============ Initialized logger ============ | |
INFO - 09/13/18 10:01:49 - 0:00:00 - attention: True | |
attention_dropout: 0 | |
back_dataset: {} | |
back_directions: [] | |
batch_size: 32 | |
beam_size: 0 | |
clip_grad_norm: 5 | |
command: python ../main.py --exp_name 'endefr' --transformer 'True' --n_enc_layers '4' --n_dec_layers '4' --share_enc '3' --share_dec '3' --share_lang_emb 'True' --share_output_emb 'True' --langs 'de,en,fr' --n_mono '-1' --mono_dataset 'de:./data/mono/de.train.tok.bpe.pth,,;en:./data/mono/en.train.tok.bpe.pth,,;fr:./data/mono/fr.train.tok.bpe.pth,,' --para_dataset 'en-fr:,./data/para/dev/newstest2013-ref.XX.60000.pth,./data/para/dev/newstest2014-fren-src.XX.60000.pth;de-en:,./data/para/dev/newstest2013-ref.XX.60000.pth,. |
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INFO - 09/02/18 20:19:21 - 0:00:00 - ============ Initialized logger ============ | |
INFO - 09/02/18 20:19:21 - 0:00:00 - attention: True | |
attention_dropout: 0 | |
back_dataset: {} | |
back_directions: [] | |
batch_size: 32 | |
beam_size: 0 | |
clip_grad_norm: 5 | |
command: python main.py --exp_name 'test' --transformer 'True' --n_enc_layers '1' --n_dec_layers '1' --share_enc '1' --share_dec '1' --share_lang_emb 'True' --share_output_emb 'True' --langs 'en,fr' --n_mono '-1' --mono_dataset 'en:./data/mono/all.en.tok.60000.pth,,;fr:./data/mono/all.fr.tok.60000.pth,,' --para_dataset 'en-fr:,./data/para/dev/newstest2013-ref.XX.60000.pth,./data/para/dev/newstest2014-fren-src.XX.60000.pth' --mono_directions 'en,fr' --word_shuffle '3' --word_dropout '0.1' --word_blank '0.2' --pivo_directi |
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class MultistepAdamOptimizer(tf.train.AdamOptimizer): | |
"""Adam with SGD updates every n steps with accumulated gradients.""" | |
def __init__(self, learning_rate=0.001, beta1=0.9, beta2=0.999, epsilon=1e-8, | |
use_locking=False, name="Adam", n=1): | |
super(MultistepAdamOptimizer, self).__init__( | |
learning_rate=learning_rate, beta1=beta1, beta2=beta2, epsilon=epsilon, | |
use_locking=use_locking, name=name) | |
self._n = n # Call Adam optimizer every n batches with accumulated grads | |
self._n_t = None # n as tensor |
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m12:2037:2131 [0] INFO NET : Using interface eth2:172.23.233.77<0> | |
m12:2037:2131 [0] INFO NET/IB : Using interface eth2 for sideband communication | |
m12:2037:2131 [0] INFO NET/IB: [3] mlx5_0:1/IB | |
m12:2037:2131 [0] INFO Using internal Network IB | |
NCCL version 2.0.5 compiled with CUDA 8.0 | |
m12:2039:2134 [2] INFO NET : Using interface eth2:172.23.233.77<0> | |
m12:2039:2134 [2] INFO NET/IB : Using interface eth2 for sideband communication | |
m12:2041:2220 [4] INFO NET : Using interface eth2:172.23.233.77<0> | |
m12:2041:2220 [4] INFO NET/IB : Using interface eth2 for sideband communication | |
m13:42973:43395 [0] INFO NET : Using interface eth2:172.23.233.75<0> |