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config.py
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config.py
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config = dict(is_train=True,
learning_rate_alpha=0.002, # as in paper
learning_rate=0.001,
learning_rate_beta=(0.9, 0.999), # as in paper
epsilon=1e-8, # as in paper
n_epochs=50, # NOTE unable to find in paper
n_models_for_ensemble=31, # as in paper
batchsize=32,
nerpos_dim=20, # in paper 20
tf_dim=1, # in paper 1
max_p_len=15,
max_q_len=14,
glove_dim=300, # in paper 300
cove_dim=600, # in paper 600
reading_rep_dim=50, # in paper 250
final_ques_under_dim=50, # in paper 250
fully_fused_para_dim=50, # in paper 250
sl_att_dim=13, # clarified as 250
sh_att_dim=12, # clarified as 250
su_att_dim=11, # clarified as 250
selfboost_att_dim=10, # clarified as 250
selfboost_rep_dim=8, # in paper 250
dropout_proba=0.4, # in paper 0.4
workspace_location='workspace'
)
if not config['is_train']:
config['dropout_proba'] = 1.