def test_rnnslu():
s = {'fold': 3,
# 5 folds 0,1,2,3,4
'data': 'atis',
'lr': 0.0970806646812754,
'verbose': 1,
'decay': True,
# decay on the learning rate if improvement stops
'win': 7,
# number of words in the context window
'nhidden': 200,
# number of hidden units
'seed': 345,
'emb_dimension': 50,
# dimension of word embedding
'nepochs': 1, # CHANGED
'savemodel': False}
rnnslu.main(s)
def test_rnnslu():
s = {'fold': 3,
# 5 folds 0,1,2,3,4
'data': 'atis',
'lr': 0.0970806646812754,
'verbose': 1,
'decay': True,
# decay on the learning rate if improvement stops
'win': 7,
# number of words in the context window
'nhidden': 200,
# number of hidden units
'seed': 345,
'emb_dimension': 50,
# dimension of word embedding
'nepochs': 1, # CHANGED
'savemodel': False}
rnnslu.main(s)
def test_rnnslu():
s = {
"fold": 3,
# 5 folds 0,1,2,3,4
"data": "atis",
"lr": 0.0970806646812754,
"verbose": 1,
"decay": True,
# decay on the learning rate if improvement stops
"win": 7,
# number of words in the context window
"nhidden": 200,
# number of hidden units
"seed": 345,
"emb_dimension": 50,
# dimension of word embedding
"nepochs": 1, # CHANGED
"savemodel": False,
}
rnnslu.main(s)
def test_rnnslu():
rnnslu.main()
def test_rnnslu():
rnnslu.main()
