Jigyasas-MBP:nmt jigyasa$ python -m nmt.nmt --attention=scaled_luong --src=de --tgt=bo --vocab_prefix=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/vocab --train_prefix=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/train --dev_prefix=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/validate --test_prefix=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/test --out_dir=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/tmp/nmt_model --num_train_steps=10000 --steps_per_stats=100 --num_layers=2 --num_units=128 --dropout=0.2 --metrics=bleu --batch_size=28
/anaconda3/lib/python3.6/site-packages/h5py/init.py:36: FutureWarning: Conversion of the second argument of issubdtype from float to np.floating is deprecated. In future, it will be treated as np.float64 == np.dtype(float).type.
from ._conv import register_converters as _register_converters
Jigyasas-MBP:nmt jigyasa$ python -m nmt.nmt --attention=scaled_luong --src=de --tgt=bo --vocab_prefix=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/vocab --train_prefix=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/train --dev_prefix=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/validate --test_prefix=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/test --out_dir=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/tmp/nmt_model --num_train_steps=10000 --steps_per_stats=100 --num_layers=2 --num_units=128 --dropout=0.2 --metrics=bleu --batch_size=28 /anaconda3/lib/python3.6/site-packages/h5py/init.py:36: FutureWarning: Conversion of the second argument of issubdtype from
floattonp.floatingis deprecated. In future, it will be treated asnp.float64 == np.dtype(float).type. from ._conv import register_converters as _register_convertershparams: src=de tgt=bo train_prefix=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/train dev_prefix=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/validate test_prefix=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/test out_dir=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/tmp/nmt_model Vocab file /Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/vocab.de exists Vocab file /Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/vocab.bo exists saving hparams to /Users/jigyasa/Desktop/nmt_jigyasa/nmt/tmp/nmt_model/hparams saving hparams to /Users/jigyasa/Desktop/nmt_jigyasa/nmt/tmp/nmt_model/best_bleu/hparams attention=scaled_luong attention_architecture=standard avg_ckpts=False batch_size=28 beam_width=0 best_bleu=0 best_bleu_dir=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/tmp/nmt_model/best_bleu check_special_token=True colocate_gradients_with_ops=True decay_scheme= dev_prefix=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/nmt/scripts/iwslt15/validate dropout=0.2 embed_prefix=None encoder_type=uni eos= epoch_step=0 forget_bias=1.0 infer_batch_size=32 init_op=uniform init_weight=0.1 learning_rate=1.0 length_penalty_weight=0.0 log_device_placement=False max_gradient_norm=5.0 max_train=0 metrics=['bleu'] num_buckets=5 num_decoder_layers=2 num_decoder_residual_layers=0 num_embeddings_partitions=0 num_encoder_layers=2 num_encoder_residual_layers=0 num_gpus=1 num_inter_threads=0 num_intra_threads=0 num_keep_ckpts=5 num_layers=2 num_train_steps=10000 num_translations_per_input=1 num_units=128 optimizer=sgd out_dir=/Users/jigyasa/Desktop/nmt_jigyasa/nmt/tmp/nmt_model output_attention=True override_loaded_hparams=False pass_hidden_state=True random_seed=None residual=False sampling_temperature=0.0 share_vocab=False
segmentation fault :11
I am using a tensorflow version more that 1.4 and my operating system is MAC OS .
@kashif @ewilderj @bastings @jhseu @mrry